Mercurial > hg > map
changeset 31:c54a34161e4a
MT update
| author | Ray Meddis <rmeddis@essex.ac.uk> |
|---|---|
| date | Mon, 11 Jul 2011 14:43:23 +0100 |
| parents | 1a502830d462 |
| children | 82fb37eb430e |
| files | Help and reference data/MAPlog.doc Help and reference data/Test files readme.doc Help and reference data/replication.xlsx multithreshold 1.46/MAPmodel.m multithreshold 1.46/UTIL_testPhysiology.m multithreshold 1.46/paradigms/paradigmList.mat multithreshold 1.46/paradigms/paradigm_IFMC_16ms.m multithreshold 1.46/paradigms/paradigm_TMC_16ms.m multithreshold 1.46/paradigms/paradigm_TMCmodel.m multithreshold 1.46/paradigms/paradigm_absThreshold_8.m multithreshold 1.46/paradigms/paradigm_thr_IFMC.m multithreshold 1.46/paradigms/paradigm_thr_TMC.m multithreshold 1.46/paradigms/reserve team/OHIOthresholds.m multithreshold 1.46/paradigms/reserve team/paradigm_OHIOabs.m multithreshold 1.46/paradigms/reserve team/paradigm_OHIOrand.m multithreshold 1.46/paradigms/reserve team/paradigm_OHIOspect.m multithreshold 1.46/paradigms/reserve team/paradigm_OHIOspectemp.m multithreshold 1.46/paradigms/reserve team/paradigm_OHIOtemp.m multithreshold 1.46/paradigms/stimulus.wav multithreshold 1.46/savedData/nemo_06-Jun-2011 17_25_10_training.mat multithreshold 1.46/savedData/nemo_06-Jun-2011 17_26_02_training.mat multithreshold 1.46/testAN.m multithreshold 1.46/testBM.m multithreshold 1.46/testFM.m multithreshold 1.46/testOME.m multithreshold 1.46/testPeriphery.m multithreshold 1.46/testPhaseLocking.m multithreshold 1.46/testRF.m multithreshold 1.46/testRP.m multithreshold 1.46/testSynapse.m parameterStore/MAPparamsEndo.m parameterStore/MAPparamsJE.m parameterStore/MAPparamsNormalHold.m parameterStore/MAPparamsNormalTest.m parameterStore/MAPparamsOHC.m parameterStore/MAPparamsStd.m |
| diffstat | 36 files changed, 0 insertions(+), 4159 deletions(-) [+] |
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--- a/multithreshold 1.46/MAPmodel.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,136 +0,0 @@ -function [modelResponse, MacGregorResponse]=MAPmodel( MAPplot, method) - -global experiment stimulusParameters audio withinRuns -global outerMiddleEarParams DRNLParams AN_IHCsynapseParams - -savePath=path; -addpath(['..' filesep 'MAP'], ['..' filesep 'utilities']) -modelResponse=[]; -MacGregorResponse=[]; - -% mono only (column vector) -audio=audio(:,1)'; - -% if stop button pressed earlier -if experiment.stop, return, end - -% -------------------------------------------------------------- run Model -MAPparamsName=experiment.name; -showPlotsAndDetails=experiment.MAPplot; -AN_spikesOrProbability='spikes'; - -% [response, method]=MAPsequenceSeg(audio, method, 1:8); -global ICoutput ANdt - MAP1_14(audio, 1/method.dt, method.nonlinCF,... - MAPparamsName, AN_spikesOrProbability); - -if showPlotsAndDetails - options.printModelParameters=0; - options.showModelOutput=1; - options.printFiringRates=1; - options.showACF=0; - options.showEfferent=1; - UTIL_showMAP(options) -end - -% No response, probably caused by hitting 'stop' button -if isempty(ICoutput), return, end - -% MacGregor response is the sum total of all final stage spiking -MacGregorResponse= sum(ICoutput,1); % use IC - -% ---------------------------------------------------------- end model run - -dt=ANdt; -time=dt:dt:dt*length(MacGregorResponse); - -% group delay on unit response -MacGonsetDelay= 0.004; -MacGoffsetDelay= 0.022; - -% now find the response of the MacGregor model during the target presentation + group delay -switch experiment.threshEstMethod - case {'2I2AFC++', '2I2AFC+++'} - idx= time>stimulusParameters.testTargetBegins+MacGonsetDelay ... - & time<stimulusParameters.testTargetEnds+MacGoffsetDelay; - nSpikesTrueWindow=sum(MacGregorResponse(:,idx)); - idx=find(time>stimulusParameters.testNonTargetBegins+MacGonsetDelay ... - & time<stimulusParameters.testNonTargetEnds+MacGoffsetDelay); - nSpikesFalseWindow=sum(MacGregorResponse(:,idx)); - % nSpikesDuringTarget is +ve when more spikes are found - % in the target window - difference= nSpikesTrueWindow-nSpikesFalseWindow; - - if difference>0 - % hit - nSpikesDuringTarget=experiment.MacGThreshold+1; - elseif difference<0 - % miss (wrong choice) - nSpikesDuringTarget=experiment.MacGThreshold-1; - else - if rand>0.5 - % hit (random choice) - nSpikesDuringTarget=experiment.MacGThreshold+1; - else - % miss (random choice) - nSpikesDuringTarget=experiment.MacGThreshold-1; - end - end - disp(['level target dummy decision: ' ... - num2str([withinRuns.variableValue nSpikesTrueWindow ... - nSpikesFalseWindow nSpikesDuringTarget], '%4.0f') ] ) - - otherwise - % idx=find(time>stimulusParameters.testTargetBegins+MacGonsetDelay ... - % & time<stimulusParameters.testTargetEnds+MacGoffsetDelay); - % no delay at onset - idx=find(time>stimulusParameters.testTargetBegins +MacGonsetDelay... - & time<stimulusParameters.testTargetEnds+MacGoffsetDelay); - nSpikesDuringTarget=sum(MacGregorResponse(:,idx)); - - % find(MacGregorResponse)*dt-stimulusParameters.stimulusDelay - timeX=time(idx); -end - -% now find the response of the MacGregor model at the end of the masker -idx2=find(time>stimulusParameters.testTargetBegins-0.02 ... - & time<stimulusParameters.testTargetBegins); -if ~isempty(idx2) - maskerRate=mean(mean(MacGregorResponse(idx2))); -else - %e.g. no masker - maskerRate=0; -end - -if experiment.MAPplot - % add vertical lines to indicate target region - figure(99), subplot(6,1,6) - hold on - yL=get(gca,'YLim'); - plot([stimulusParameters.testTargetBegins + MacGonsetDelay ... - stimulusParameters.testTargetBegins + MacGonsetDelay],yL,'r') - plot([stimulusParameters.testTargetEnds + MacGoffsetDelay ... - stimulusParameters.testTargetEnds + MacGoffsetDelay],yL,'r') -end - -% specify unambiguous response -switch experiment.paradigm - case 'gapDetection' - gapResponse=(maskerRate-nSpikesDuringTarget)/maskerRate; - if gapResponse>0.2 - modelResponse=2; % gap detected - else - modelResponse=1; % gap not detected - end - [nSpikesDuringTarget maskerRate gapResponse modelResponse] - figure(22), plot(timeX,earObject(idx)) - otherwise - if nSpikesDuringTarget>experiment.MacGThreshold - modelResponse=2; % stimulus detected - else - modelResponse=1; % nothing heard (default) - end -end - - -path(savePath)
--- a/multithreshold 1.46/UTIL_testPhysiology.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,11 +0,0 @@ -function UTIL_testPhysiology(BF) -testOME('Normal') -relativeFrequencies=[0.25 .5 .75 1 1.25 1.5 2]; -testBM (BF, 'Normal',relativeFrequencies) -testRP(BF,'Normal') -testSynapse(BF,'Normal') -testFM(BF,'Normal',1) -testPhaseLocking -testAN(BF,BF, 10:10:80); -figure(14) -figure(15)
--- a/multithreshold 1.46/paradigms/paradigm_IFMC_16ms.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,41 +0,0 @@ -function paradigm_IFMC_8ms(handles) -global stimulusParameters experiment betweenRuns - -paradigm_training(handles) % default - -stimulusParameters.WRVname='maskerLevel'; -stimulusParameters.WRVstartValues=50; -stimulusParameters.WRVsteps= [-10 -2]; -stimulusParameters.WRVlimits=[-30 110]; - -experiment.psyFunSlope = -1; -withinRuns.direction='up'; - -betweenRuns.variableName1='maskerRelativeFrequency'; -betweenRuns.variableList1=[1 0.5 1.6 .9 .7 1.1 1.3 ]; -betweenRuns.variableName2='targetFrequency'; -% keep old list of target frequencies -betweenRuns.variableList2=str2num(get(handles.edittargetFrequency,'string')); -betweenRuns.randomizeSequence=1; % 'random sequence' - -stimulusParameters.maskerDuration=0.108; -stimulusParameters.maskerLevel=stimulusParameters.WRVstartValues(1); -stimulusParameters.maskerRelativeFrequency=betweenRuns.variableList1; - -stimulusParameters.gapDuration=0.01; - -stimulusParameters.targetType='tone'; -stimulusParameters.targetPhase='sin'; -stimulusParameters.targetFrequency=betweenRuns.variableList2(1); -stimulusParameters.targetDuration=0.016; -stimulusParameters.targetLevel=NaN; - -stimulusParameters.rampDuration=0.004; - -% instructions to user -% single interval up/down no cue -stimulusParameters.instructions{1}=[{'YES if you hear the added click'}, { }, { 'NO if not (or you are uncertain'}]; -% single interval up/down with cue -stimulusParameters.instructions{2}=[{'count how many distinct clicks you hear'},{'ignore the tones'},{' '},... - {'The clicks must be **clearly distinct** to count'}]; -
--- a/multithreshold 1.46/paradigms/paradigm_TMC_16ms.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,46 +0,0 @@ -function paradigm_TMC_16ms(handles) -global stimulusParameters experiment betweenRuns - -paradigm_training(handles) % default - -experiment.singleIntervalMaxTrials=20; - -stimulusParameters.WRVname='maskerLevel'; -stimulusParameters.WRVstartValues=50; -stimulusParameters.WRVsteps= [-10 -4]; -stimulusParameters.WRVlimits=[-30 110]; - -stimulusParameters.cueTestDifference = 10; -experiment.psyFunSlope = -1; -withinRuns.direction='up'; - -betweenRuns.variableName1='gapDuration'; -betweenRuns.variableList1=[.01 .09 .03 .05 .07]; -betweenRuns.variableName2='targetFrequency'; -% retain existing targetFrequencies -betweenRuns.variableList2=str2num(get(handles.edittargetFrequency,'string')); -betweenRuns.randomizeSequence=1; % 'random sequence' - -stimulusParameters.maskerType='tone'; -stimulusParameters.maskerPhase='sin'; -stimulusParameters.maskerDuration=0.108; -stimulusParameters.maskerLevel=stimulusParameters.WRVstartValues(1); -stimulusParameters.maskerRelativeFrequency=1; - -stimulusParameters.gapDuration=betweenRuns.variableList1; - -stimulusParameters.targetType='tone'; -stimulusParameters.targetPhase='sin'; -stimulusParameters.targetFrequency=betweenRuns.variableList2(1); -stimulusParameters.targetDuration=0.016; -stimulusParameters.targetLevel=NaN; - -stimulusParameters.rampDuration=0.004; - -% instructions to user -% single interval up/down no cue -stimulusParameters.instructions{1}=[{'YES if you hear the added click'}, { }, { 'NO if not (or you are uncertain'}]; -% single interval up/down with cue -stimulusParameters.instructions{2}=[{'count how many distinct clicks you hear'},{'ignore the tones'},{' '},... - {'The clicks must be **clearly distinct** to count'}]; -
--- a/multithreshold 1.46/paradigms/paradigm_TMCmodel.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,45 +0,0 @@ -function paradigm_TMCmodel(handles) -global stimulusParameters experiment betweenRuns - -paradigm_training(handles) % default - -stimulusParameters.WRVname='maskerLevel'; -stimulusParameters.WRVstartValues=30; -stimulusParameters.WRVsteps= [-10 -4]; -stimulusParameters.WRVlimits=[-30 110]; - -stimulusParameters.cueTestDifference = 10; -experiment.psyFunSlope = -1; -withinRuns.direction='up'; - -betweenRuns.variableName1='gapDuration'; -betweenRuns.variableList1=[ 0.09 0.01:0.02:0.07 0.02:0.02:.08 0.005]; -betweenRuns.variableName2='targetFrequency'; -% retain existing targetFrequencies -betweenRuns.variableList2=str2num(get(handles.edittargetFrequency,'string')); -betweenRuns.randomizeSequence=1; % 'random sequence' - -stimulusParameters.maskerType='tone'; -stimulusParameters.maskerPhase='sin'; -stimulusParameters.maskerDuration=0.108; -stimulusParameters.maskerLevel=stimulusParameters.WRVstartValues(1); -stimulusParameters.maskerRelativeFrequency=1; -experiment.singleIntervalMaxTrials=10; - -stimulusParameters.gapDuration=betweenRuns.variableList1; - -stimulusParameters.targetType='tone'; -stimulusParameters.targetPhase='sin'; -stimulusParameters.targetFrequency=betweenRuns.variableList2(1); -stimulusParameters.targetDuration=0.016; -stimulusParameters.targetLevel=NaN; - -stimulusParameters.rampDuration=0.004; - -% instructions to user -% single interval up/down no cue -stimulusParameters.instructions{1}=[{'YES if you hear the added click'}, { }, { 'NO if not (or you are uncertain'}]; -% single interval up/down with cue -stimulusParameters.instructions{2}=[{'count how many distinct clicks you hear'},{'ignore the tones'},{' '},... - {'The clicks must be **clearly distinct** to count'}]; -
--- a/multithreshold 1.46/paradigms/paradigm_absThreshold_8.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,32 +0,0 @@ -function paradigm_absThreshold_8(handles) -global stimulusParameters experiment betweenRuns - -paradigm_training(handles) % default - -betweenRuns.variableName1='targetFrequency'; -betweenRuns.variableList1=1000; -betweenRuns.variableList1=str2num(get(handles.edittargetFrequency,'string')); -betweenRuns.variableName2='targetDuration'; -betweenRuns.variableList2=0.008 ; -betweenRuns.randomizeSequence=1; % 'random sequence' - -% delay > masker > gap > target - - -stimulusParameters.targetType='tone'; -stimulusParameters.targetPhase='sin'; -stimulusParameters.targetFrequency=1000; -stimulusParameters.targetDuration=0.008; -stimulusParameters.targetLevel=stimulusParameters.WRVstartValues(1); - -stimulusParameters.rampDuration=0.004; - -% forced choice window interval -stimulusParameters.AFCsilenceDuration=0.5; - -% instructions to user -% single interval up/down no cue -stimulusParameters.instructions{1}= [{'YES if you hear the tone clearly'}, { }, { 'NO if not (or you are uncertain'}]; -% single interval up/down with cue -stimulusParameters.instructions{2}= [{'count the tones you hear clearly'}, { }, { 'ignore indistinct tones'}]; -
--- a/multithreshold 1.46/paradigms/paradigm_thr_IFMC.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,36 +0,0 @@ -function paradigm_thr_IFMC(handles) -global stimulusParameters experiment betweenRuns - -paradigm_training(handles) % default - -betweenRuns.variableName1='targetFrequency'; -betweenRuns.variableList1=1000; -betweenRuns.variableList1=str2num(get(handles.edittargetFrequency,'string')); -betweenRuns.variableName2='targetDuration'; -betweenRuns.variableList2=0.016; -betweenRuns.randomizeSequence=1; % 'random sequence' - -% delay > masker > gap > target - - -stimulusParameters.targetType='tone'; -stimulusParameters.targetPhase='sin'; -stimulusParameters.targetFrequency=1000; -stimulusParameters.targetDuration=0.016; -stimulusParameters.targetLevel=stimulusParameters.WRVstartValues(1); - -stimulusParameters.rampDuration=0.004; - -experiment.stopCriteria2IFC=[75 3 5]; -experiment.singleIntervalMaxTrials=[20]; - - -% forced choice window interval -stimulusParameters.AFCsilenceDuration=0.5; - -% instructions to user -% single interval up/down no cue -stimulusParameters.instructions{1}= [{'YES if you hear the tone clearly'}, { }, { 'NO if not (or you are uncertain'}]; -% single interval up/down with cue -stimulusParameters.instructions{2}= [{'count the tones you hear clearly'}, { }, { 'ignore indistinct tones'}]; -
--- a/multithreshold 1.46/paradigms/paradigm_thr_TMC.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,36 +0,0 @@ -function paradigm_thr_TMC(handles) -global stimulusParameters experiment betweenRuns - -paradigm_training(handles) % default - -betweenRuns.variableName1='targetFrequency'; -betweenRuns.variableList1=1000; -betweenRuns.variableList1=str2num(get(handles.edittargetFrequency,'string')); -betweenRuns.variableName2='targetDuration'; -betweenRuns.variableList2=0.016; -betweenRuns.randomizeSequence=1; % 'random sequence' - -% delay > masker > gap > target - - -stimulusParameters.targetType='tone'; -stimulusParameters.targetPhase='sin'; -stimulusParameters.targetFrequency=1000; -stimulusParameters.targetDuration=0.016; -stimulusParameters.targetLevel=stimulusParameters.WRVstartValues(1); - -stimulusParameters.rampDuration=0.004; - -experiment.stopCriteria2IFC=[75 3 5]; -experiment.singleIntervalMaxTrials=[20]; - - -% forced choice window interval -stimulusParameters.AFCsilenceDuration=0.5; - -% instructions to user -% single interval up/down no cue -stimulusParameters.instructions{1}= [{'YES if you hear the tone clearly'}, { }, { 'NO if not (or you are uncertain'}]; -% single interval up/down with cue -stimulusParameters.instructions{2}= [{'count the tones you hear clearly'}, { }, { 'ignore indistinct tones'}]; -
--- a/multithreshold 1.46/paradigms/reserve team/OHIOthresholds.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,7 +0,0 @@ -function experiment=OHIOthresholds(experiment) - -experiment.OHIOfrequencies=[494, 663, 870, 1125, 1442, 1838, 2338, 2957, 3725, 4680, 5866, 7334]; %Hz. -% User must specify abs thresholds (dB SPL) of each tone frequency -experiment.OHIOthresholds= [ - 9.1 8.6 8.1 7.9 9.8 10.5 13.5 15.0 17.4 19.4 22.6 25.2 -]; \ No newline at end of file
--- a/multithreshold 1.46/paradigms/reserve team/paradigm_OHIOabs.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,47 +0,0 @@ -function paradigm_OHIOabs(handles) -global stimulusParameters experiment betweenRuns - -paradigm_training(handles) % default - -% find the threshold for a tonecomplex consisting of a sequence of 10-ms tones -% whose frequencies are chosen at random from a list (OHIOfrequencies) -% All tones are presented at the same level (SL) computed using absolute -% threshols specified in OHIOthresholds; -% The duration of the complex is increased across runs and the number of tones is -% controlled by OHIOdurations, (for each 20 ms a further tone is added. -% The frequency of the tones is changed on each trial - -experiment.OHIOfrequencies=[494, 663, 870, 1125, 1442, 1838, 2338, 2957, 3725, 4680, 5866, 7334]; %Hz. -% User must specify abs thresholds (dB SPL) of each tone frequency -% experiment.OHIOthresholds= [18 16 16 19 20 22 24 26 27 30 32 35]; - -% assessment method -% {'oneIntervalUpDown', 'MaxLikelihood', '2I2AFC++', '2I2AFC+++'} -experiment.threshEstMethod='oneIntervalUpDown'; -% {'cued', 'noCue'}; - -stimulusParameters.WRVname='targetLevel'; -stimulusParameters.WRVstartValues=20 ; -stimulusParameters.WRVsteps=[10 2]; -stimulusParameters.WRVlimits=[-30 110]; - -betweenRuns.variableName1='numOHIOtones'; -betweenRuns.variableList1= 1:12; % i.e. the frequency to be used -betweenRuns.variableName2='stimulusDelay'; -betweenRuns.variableList2=0.05; -betweenRuns.randomizeSequence=2; % not random sequence - -stimulusParameters.targetType='OHIO'; -stimulusParameters.targetPhase='sin'; -stimulusParameters.targetFrequency=experiment.OHIOfrequencies; -stimulusParameters.targetDuration=0.01; % overruled by OHIO program -stimulusParameters.targetLevel=stimulusParameters.WRVstartValues(1); - -stimulusParameters.rampDuration=0.005; - -% instructions to user -% single interval up/down no cue -stimulusParameters.instructions{1}= [{'YES if you hear the tone clearly'}, { }, { 'NO if not (or you are uncertain'}]; -% single interval up/down with cue -stimulusParameters.instructions{2}= [{'count the tones you hear clearly'}, { }, { 'ignore indistinct tones'}]; -
--- a/multithreshold 1.46/paradigms/reserve team/paradigm_OHIOrand.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,41 +0,0 @@ -function paradigm_OHIOrand(handles) -global stimulusParameters experiment betweenRuns - -paradigm_training(handles) % default - -% find the threshold for a tonecomplex consisting of a sequence of 10-ms tones -% whose frequencies are chosen at random from a list (OHIOfrequencies) -% All tones are presented at the same level (SL) computed using absolute -% threshols specified in OHIOthresholds; -% The duration of the complex is increased across runs and the number of tones is -% controlled by OHIOdurations, (for each 20 ms a further tone is added. -% The frequency of the tones is changed on each trial - -% fetch thresholds and frequencies -experiment=OHIOthresholds(experiment); - -stimulusParameters.WRVname='targetLevel'; -stimulusParameters.WRVstartValues=0 ; -stimulusParameters.WRVsteps=[10 2]; -stimulusParameters.WRVlimits=[-30 110]; - -betweenRuns.variableName1='numOHIOtones'; -betweenRuns.variableList1= [1 2 4 8 12]; -betweenRuns.variableName2='stimulusDelay'; -betweenRuns.variableList2=0.1; -betweenRuns.randomizeSequence=2; % not random sequence - -stimulusParameters.targetType='OHIO'; -stimulusParameters.targetPhase='sin'; -stimulusParameters.targetFrequency=experiment.OHIOfrequencies; -stimulusParameters.targetDuration=betweenRuns.variableList2; -stimulusParameters.targetLevel=stimulusParameters.WRVstartValues(1); - -stimulusParameters.rampDuration=0.005; - -% instructions to user -% single interval up/down no cue -stimulusParameters.instructions{1}= [{'YES if you hear the tone clearly'}, { }, { 'NO if not (or you are uncertain'}]; -% single interval up/down with cue -stimulusParameters.instructions{2}= [{'count the tones you hear clearly'}, { }, { 'ignore indistinct tones'}]; -
--- a/multithreshold 1.46/paradigms/reserve team/paradigm_OHIOspect.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,41 +0,0 @@ -function paradigm_OHIOspect(handles) -global stimulusParameters experiment betweenRuns - -paradigm_training(handles) % default - -% find the threshold for a tonecomplex consisting of a sequence of 10-ms tones -% whose frequencies are chosen at random from a list (OHIOfrequencies) -% All tones are presented at the same level (SL) computed using absolute -% threshols specified in OHIOthresholds; -% The duration of the complex is increased across runs and the number of tones is -% controlled by OHIOdurations, (for each 20 ms a further tone is added. -% The frequency of the tones is changed on each trial - -% fetch thresholds and frequencies -experiment=OHIOthresholds(experiment); - -stimulusParameters.WRVname='targetLevel'; -stimulusParameters.WRVstartValues=0 ; -stimulusParameters.WRVsteps=[10 2]; -stimulusParameters.WRVlimits=[-30 110]; - -betweenRuns.variableName1='numOHIOtones'; -betweenRuns.variableList1= [1 2 4 8 12]; -betweenRuns.variableName2='stimulusDelay'; -betweenRuns.variableList2=0.1; -betweenRuns.randomizeSequence=2; % not random sequence - -stimulusParameters.targetType='OHIO'; -stimulusParameters.targetPhase='sin'; -stimulusParameters.targetFrequency=experiment.OHIOfrequencies; -stimulusParameters.targetDuration=betweenRuns.variableList2; -stimulusParameters.targetLevel=stimulusParameters.WRVstartValues(1); - -stimulusParameters.rampDuration=0.005; - -% instructions to user -% single interval up/down no cue -stimulusParameters.instructions{1}= [{'YES if you hear the tone clearly'}, { }, { 'NO if not (or you are uncertain'}]; -% single interval up/down with cue -stimulusParameters.instructions{2}= [{'count the tones you hear clearly'}, { }, { 'ignore indistinct tones'}]; -
--- a/multithreshold 1.46/paradigms/reserve team/paradigm_OHIOspectemp.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,40 +0,0 @@ -function paradigm_OHIOspectemp(handles) -global stimulusParameters experiment betweenRuns - -paradigm_training(handles) % default - -% find the threshold for a tonecomplex consisting of a sequence of 10-ms tones -% whose frequencies are chosen at random from a list (OHIOfrequencies) -% All tones are presented at the same level (SL) computed using absolute -% threshols specified in OHIOthresholds; -% The duration of the complex is increased across runs and the number of tones is -% controlled by OHIOdurations, (for each 20 ms a further tone is added. -% The frequency of the tones is changed on each trial - -% fetch thresholds and frequencies -experiment=OHIOthresholds(experiment); - -stimulusParameters.WRVname='targetLevel'; -stimulusParameters.WRVstartValues=0 ; -stimulusParameters.WRVsteps=[10 2]; -stimulusParameters.WRVlimits=[-30 110]; - -betweenRuns.variableName1='numOHIOtones'; -betweenRuns.variableList1= [1 2 4 8 12]; -betweenRuns.variableName2='stimulusDelay'; -betweenRuns.variableList2=0.1; -betweenRuns.randomizeSequence=2; % not random sequence - -stimulusParameters.targetType='OHIO'; -stimulusParameters.targetPhase='sin'; -stimulusParameters.targetFrequency=experiment.OHIOfrequencies; -stimulusParameters.targetDuration=betweenRuns.variableList2; -stimulusParameters.targetLevel=stimulusParameters.WRVstartValues(1); - -stimulusParameters.rampDuration=0.005; - -% instructions to user -% single interval up/down no cue -stimulusParameters.instructions{1}= [{'YES if you hear the tone clearly'}, { }, { 'NO if not (or you are uncertain'}]; -% single interval up/down with cue -stimulusParameters.instructions{2}= [{'count the tones you hear clearly'}, { }, { 'ignore indistinct tones'}];
--- a/multithreshold 1.46/paradigms/reserve team/paradigm_OHIOtemp.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,44 +0,0 @@ -function paradigm_OHIOtemp(handles) -global stimulusParameters experiment betweenRuns - -paradigm_training(handles) % default - -% find the threshold for a tonecomplex consisting of a sequence of 10-ms tones -% whose frequencies are chosen at random from a list (OHIOfrequencies) -% All tones are presented at the same level (SL) computed using absolute -% threshols specified in OHIOthresholds; -% The duration of the complex is increased across runs and the number of tones is -% controlled by OHIOdurations, (for each 20 ms a further tone is added. -% The frequency of the tones is changed on each trial - -% fetch thresholds and frequencies -experiment=OHIOthresholds(experiment); - -stimulusParameters.WRVname='targetLevel'; -stimulusParameters.WRVstartValues=0 ; -stimulusParameters.WRVsteps=[10 2]; -stimulusParameters.WRVlimits=[-30 110]; -% target variable: slope=1, start going down. -stimulusParameters.cueTestDifference=10; -experiment.psyFunSlope= 1; -withinRuns.direction='down'; - -betweenRuns.variableName1='numOHIOtones'; -betweenRuns.variableList1= [1 2 4 8 12]; -betweenRuns.variableName2='stimulusDelay'; -betweenRuns.variableList2=0.1; -betweenRuns.randomizeSequence=2; % not random sequence - -stimulusParameters.targetType='OHIO'; -stimulusParameters.targetPhase='sin'; -stimulusParameters.targetFrequency=experiment.OHIOfrequencies; -stimulusParameters.targetDuration=betweenRuns.variableList2; -stimulusParameters.targetLevel=stimulusParameters.WRVstartValues(1); - -stimulusParameters.rampDuration=0.005; - -% instructions to user -% single interval up/down no cue -stimulusParameters.instructions{1}= [{'YES if you hear the tone clearly'}, { }, { 'NO if not (or you are uncertain'}]; -% single interval up/down with cue -stimulusParameters.instructions{2}= [{'count the tones you hear clearly'}, { }, { 'ignore indistinct tones'}];
--- a/multithreshold 1.46/testAN.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,324 +0,0 @@ -function vectorStrength=testAN(targetFrequency,BFlist, levels) -% testIHC used either for IHC I/O function ... -% or receptive field (doReceptiveFields=1) - -global experiment method stimulusParameters -global IHC_VResp_VivoParams IHC_cilia_RPParams IHCpreSynapseParams -global AN_IHCsynapseParams - - global ANoutput ANdt CNoutput ICoutput ICmembraneOutput tauCas - global ARattenuation MOCattenuation - -dbstop if error - -addpath (['..' filesep 'MAP'], ['..' filesep 'utilities'], ... - ['..' filesep 'parameterStore'], ['..' filesep 'wavFileStore'],... - ['..' filesep 'testPrograms']) - -if nargin<3 - levels=-10:10:80; - % levels=80:10:90; -end - -nLevels=length(levels); - -toneDuration=.2; -rampDuration=0.002; -silenceDuration=.02; -localPSTHbinwidth=0.001; - -% Use only the first frequency in the GUI targetFrequency box to defineBF -% targetFrequency=stimulusParameters.targetFrequency(1); -% BFlist=targetFrequency; - -AN_HSRonset=zeros(nLevels,1); -AN_HSRsaturated=zeros(nLevels,1); -AN_LSRonset=zeros(nLevels,1); -AN_LSRsaturated=zeros(nLevels,1); -CNLSRrate=zeros(nLevels,1); -CNHSRsaturated=zeros(nLevels,1); -ICHSRsaturated=zeros(nLevels,1); -ICLSRsaturated=zeros(nLevels,1); -vectorStrength=zeros(nLevels,1); - -AR=zeros(nLevels,1); -MOC=zeros(nLevels,1); - -% ANoutput=zeros(200,200); - -figure(15), clf -set(gcf,'position',[980 356 401 321]) -figure(5), clf -set(gcf,'position', [980 34 400 295]) -drawnow - -%% guarantee that the sample rate is at least 10 times the frequency -sampleRate=50000; -while sampleRate< 10* targetFrequency - sampleRate=sampleRate+10000; -end - -%% adjust sample rate so that the pure tone stimulus has an integer -%% numver of epochs in a period -dt=1/sampleRate; -period=1/targetFrequency; -ANspeedUpFactor=5; %anticipating MAP (needs clearing up) -ANdt=dt*ANspeedUpFactor; -ANdt=period/round(period/ANdt); -dt=ANdt/ANspeedUpFactor; -sampleRate=1/dt; -epochsPerPeriod=sampleRate*period; - -%% main computational loop (vary level) -levelNo=0; -for leveldB=levels - levelNo=levelNo+1; - - fprintf('%4.0f\t', leveldB) - amp=28e-6*10^(leveldB/20); - - time=dt:dt:toneDuration; - rampTime=dt:dt:rampDuration; - ramp=[0.5*(1+cos(2*pi*rampTime/(2*rampDuration)+pi)) ... - ones(1,length(time)-length(rampTime))]; - ramp=ramp.*fliplr(ramp); - - silence=zeros(1,round(silenceDuration/dt)); - - % create signal (leveldB/ targetFrequency) - inputSignal=amp*sin(2*pi*targetFrequency'*time); - inputSignal= ramp.*inputSignal; - inputSignal=[silence inputSignal]; - - %% run the model - AN_spikesOrProbability='spikes'; - MAPparamsName=experiment.name; - showPlotsAndDetails=0; - - - MAP1_14(inputSignal, 1/dt, BFlist, ... - MAPparamsName, AN_spikesOrProbability); - - nTaus=length(tauCas); - - %LSR (same as HSR if no LSR fibers present) - [nANFibers nTimePoints]=size(ANoutput); - - numLSRfibers=nANFibers/nTaus; - numHSRfibers=numLSRfibers; - - LSRspikes=ANoutput(1:numLSRfibers,:); - PSTH=UTIL_PSTHmaker(LSRspikes, ANdt, localPSTHbinwidth); - PSTHLSR=mean(PSTH,1)/localPSTHbinwidth; % across fibers rates - PSTHtime=localPSTHbinwidth:localPSTHbinwidth:... - localPSTHbinwidth*length(PSTH); - AN_LSRonset(levelNo)= max(PSTHLSR); % peak in 5 ms window - AN_LSRsaturated(levelNo)= mean(PSTHLSR(round(length(PSTH)/2):end)); - - % HSR - HSRspikes= ANoutput(end- numHSRfibers+1:end, :); - PSTH=UTIL_PSTHmaker(HSRspikes, ANdt, localPSTHbinwidth); - PSTH=mean(PSTH,1)/localPSTHbinwidth; % sum across fibers (HSR only) - AN_HSRonset(levelNo)= max(PSTH); - AN_HSRsaturated(levelNo)= mean(PSTH(round(length(PSTH)/2): end)); - - figure(5), subplot(2,2,2) - hold off, bar(PSTHtime,PSTH, 'b') - hold on, bar(PSTHtime,PSTHLSR,'r') - ylim([0 1000]) - xlim([0 length(PSTH)*localPSTHbinwidth]) - set(gcf,'name',[num2str(BFlist), ' Hz: ' num2str(leveldB) ' dB']); - - % AN - CV - % CV is computed 5 times. Use the middle one (3) as most typical - cvANHSR= UTIL_CV(HSRspikes, ANdt); - - % AN - vector strength - PSTH=sum(HSRspikes); - [PH, binTimes]=UTIL_periodHistogram... - (PSTH, ANdt, targetFrequency); - VS=UTIL_vectorStrength(PH); - vectorStrength(levelNo)=VS; - disp(['sat rate= ' num2str(AN_HSRsaturated(levelNo)) ... - '; phase-locking VS = ' num2str(VS)]) - title(['AN HSR: CV=' num2str(cvANHSR(3),'%5.2f') ... - 'VS=' num2str(VS,'%5.2f')]) - - % CN - first-order neurons - - % CN LSR - [nCNneurons c]=size(CNoutput); - nLSRneurons=round(nCNneurons/nTaus); - CNLSRspikes=CNoutput(1:nLSRneurons,:); - PSTH=UTIL_PSTHmaker(CNLSRspikes, ANdt, localPSTHbinwidth); - PSTH=sum(PSTH)/nLSRneurons; - CNLSRrate(levelNo)=mean(PSTH(round(length(PSTH)/2):end))/localPSTHbinwidth; - - %CN HSR - MacGregorMultiHSRspikes=... - CNoutput(end-nLSRneurons:end,:); - PSTH=UTIL_PSTHmaker(MacGregorMultiHSRspikes, ANdt, localPSTHbinwidth); - PSTH=sum(PSTH)/nLSRneurons; - PSTH=mean(PSTH,1)/localPSTHbinwidth; % sum across fibers (HSR only) - - CNHSRsaturated(levelNo)=mean(PSTH(length(PSTH)/2:end)); - - figure(5), subplot(2,2,3) - bar(PSTHtime,PSTH) - ylim([0 1000]) - xlim([0 length(PSTH)*localPSTHbinwidth]) - cvMMHSR= UTIL_CV(MacGregorMultiHSRspikes, ANdt); - title(['CN CV= ' num2str(cvMMHSR(3),'%5.2f')]) - - % IC LSR - [nICneurons c]=size(ICoutput); - nLSRneurons=round(nICneurons/nTaus); - ICLSRspikes=ICoutput(1:nLSRneurons,:); - PSTH=UTIL_PSTHmaker(ICLSRspikes, ANdt, localPSTHbinwidth); - ICLSRsaturated(levelNo)=mean(PSTH(round(length(PSTH)/2):end))/localPSTHbinwidth; - - %IC HSR - MacGregorMultiHSRspikes=... - ICoutput(end-nLSRneurons:end,:); - PSTH=UTIL_PSTHmaker(MacGregorMultiHSRspikes, ANdt, localPSTHbinwidth); - PSTH=sum(PSTH)/nLSRneurons; - PSTH=mean(PSTH,1)/localPSTHbinwidth; % sum across fibers (HSR only) - - ICHSRsaturated(levelNo)=mean(PSTH(length(PSTH)/2:end)); - - AR(levelNo)=min(ARattenuation); - MOC(levelNo)=min(MOCattenuation(length(MOCattenuation)/2:end)); - - time=dt:dt:dt*size(ICmembraneOutput,2); - figure(5), subplot(2,2,4) - plot(time,ICmembraneOutput(2, 1:end),'k') - ylim([-0.07 0]) - xlim([0 max(time)]) - title(['IC ' num2str(leveldB,'%4.0f') 'dB']) - drawnow - - figure(5), subplot(2,2,1) - plot(20*log10(MOC), 'k'), - title(' MOC'), ylabel('dB attenuation') - ylim([-30 0]) - - -end % level -figure(5), subplot(2,2,1) -plot(levels,20*log10(MOC), 'k'), -title(' MOC'), ylabel('dB attenuation') -ylim([-30 0]) -xlim([0 max(levels)]) - -fprintf('\n') -toneDuration=2; -rampDuration=0.004; -silenceDuration=.02; -nRepeats=200; % no. of AN fibers -fprintf('toneDuration %6.3f\n', toneDuration) -fprintf(' %6.0f AN fibers (repeats)\n', nRepeats) -fprintf('levels') -fprintf('%6.2f\t', levels) -fprintf('\n') - - -% ---------------------------------------------------- display parameters - -figure(15), clf -nRows=2; nCols=2; - -% AN rate - level ONSET functions -subplot(nRows,nCols,1) -plot(levels,AN_LSRonset,'ro'), hold on -plot(levels,AN_HSRonset,'ko'), hold off -ylim([0 1000]), xlim([min(levels) max(levels)]) -ttl=['tauCa= ' num2str(IHCpreSynapseParams.tauCa)]; -title( ttl) -xlabel('level dB SPL'), ylabel('peak rate (sp/s)'), grid on -text(0, 800, 'AN onset', 'fontsize', 16) - -% AN rate - level ADAPTED function -subplot(nRows,nCols,2) -plot(levels,AN_LSRsaturated, 'ro'), hold on -plot(levels,AN_HSRsaturated, 'ko'), hold off -ylim([0 400]) -set(gca,'ytick',0:50:300) -xlim([min(levels) max(levels)]) -set(gca,'xtick',[levels(1):20:levels(end)]) -% grid on -ttl=[ 'spont=' num2str(mean(AN_HSRsaturated(1,:)),'%4.0f')... - ' sat=' num2str(mean(AN_HSRsaturated(end,1)),'%4.0f')]; -title( ttl) -xlabel('level dB SPL'), ylabel ('adapted rate (sp/s)') -text(0, 340, 'AN adapted', 'fontsize', 16), grid on - -% CN rate - level ADAPTED function -subplot(nRows,nCols,3) -plot(levels,CNLSRrate, 'ro'), hold on -plot(levels,CNHSRsaturated, 'ko'), hold off -ylim([0 400]) -set(gca,'ytick',0:50:300) -xlim([min(levels) max(levels)]) -set(gca,'xtick',[levels(1):20:levels(end)]) -% grid on -ttl=[ 'spont=' num2str(mean(CNHSRsaturated(1,:)),'%4.0f') ' sat=' ... - num2str(mean(CNHSRsaturated(end,1)),'%4.0f')]; -title( ttl) -xlabel('level dB SPL'), ylabel ('adapted rate (sp/s)') -text(0, 350, 'CN', 'fontsize', 16), grid on - -% IC rate - level ADAPTED function -subplot(nRows,nCols,4) -plot(levels,ICLSRsaturated, 'ro'), hold on -plot(levels,ICHSRsaturated, 'ko'), hold off -ylim([0 400]) -set(gca,'ytick',0:50:300) -xlim([min(levels) max(levels)]) -set(gca,'xtick',[levels(1):20:levels(end)]), grid on - - -ttl=['spont=' num2str(mean(ICHSRsaturated(1,:)),'%4.0f') ... - ' sat=' num2str(mean(ICHSRsaturated(end,1)),'%4.0f')]; -title( ttl) -xlabel('level dB SPL'), ylabel ('adapted rate (sp/s)') -text(0, 350, 'IC', 'fontsize', 16) -set(gcf,'name',' AN CN IC rate/level') - -peakVectorStrength=max(vectorStrength); - -fprintf('\n') -disp('levels vectorStrength') -fprintf('%3.0f \t %6.4f \n', [levels; vectorStrength']) -fprintf('\n') -fprintf('Phase locking, max vector strength=\t %6.4f\n\n',... - max(vectorStrength)) - -allData=[ levels' AN_HSRonset AN_HSRsaturated... - AN_LSRonset AN_LSRsaturated ... - CNHSRsaturated CNLSRrate... - ICHSRsaturated ICLSRsaturated]; -fprintf('\n levels \tANHSR Onset \tANHSR adapted\tANLSR Onset \tANLSR adapted\tCNHSR\tCNLSR\tICHSR \tICLSR \n'); -UTIL_printTabTable(round(allData)) -fprintf('VS (phase locking)= \t%6.4f\n\n',... - max(vectorStrength)) - -UTIL_showStruct(IHC_cilia_RPParams, 'IHC_cilia_RPParams') -UTIL_showStruct(IHCpreSynapseParams, 'IHCpreSynapseParams') -UTIL_showStruct(AN_IHCsynapseParams, 'AN_IHCsynapseParams') - -fprintf('\n') -disp('levels vectorStrength') -fprintf('%3.0f \t %6.4f \n', [levels; vectorStrength']) -fprintf('\n') -fprintf('Phase locking, max vector strength= \t%6.4f\n\n',... - max(vectorStrength)) - -allData=[ levels' AN_HSRonset AN_HSRsaturated... - AN_LSRonset AN_LSRsaturated ... - CNHSRsaturated CNLSRrate... - ICHSRsaturated ICLSRsaturated]; -fprintf('\n levels \tANHSR Onset \tANHSR adapted\tANLSR Onset \tANLSR adapted\tCNHSR\tCNLSR\tICHSR \tICLSR \n'); -UTIL_printTabTable(round(allData)) -fprintf('VS (phase locking)= \t%6.4f\n\n',... - max(vectorStrength)) -
--- a/multithreshold 1.46/testBM.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,157 +0,0 @@ -function testBM (BMlocations, paramsName,relativeFrequencies) -% testBM generates input output functions for DRNL model for any number -% of locations. -% Computations are bast on a single channel model (channelBFs=BF) -% peak displacement (peakAmp) is measured. -% if DRNLParams.useMOC is chosen, the full model is run (slow) -% otherwise only DRNL is computed. -% Tuning curves are generated based on a range of frequencies reletove to -% the BF of the location. -% - -global DRNLParams - -savePath=path; - -addpath (['..' filesep 'utilities'],['..' filesep 'MAP']) - -levels=-10:10:90; nLevels=length(levels); -% levels= 50; nLevels=length(levels); - -% refBMdisplacement is the displacement of the BM at threshold -% 1 nm disp at threshold (9 kHz, Ruggero) -refBMdisplacement= 1e-8; % adjusted for 10 nm at 1 kHz - -toneDuration=.200; -rampDuration=0.01; -silenceDuration=0.01; - -sampleRate=30000; - -dbstop if error -figure(3), clf -set(gcf,'position',[280 350 327 326]) -set(gcf,'name','DRNL - BM') -pause(0.1) - -finalSummary=[]; -nBFs=length(BMlocations); -BFno=0; plotCount=0; -for BF=BMlocations - BFno=BFno+1; - plotCount=plotCount+nBFs; - stimulusFrequencies=BF* relativeFrequencies; - nFrequencies=length(stimulusFrequencies); - - peakAmpBM=zeros(nLevels,nFrequencies); - peakAmpBMdB=NaN(nLevels,nFrequencies); - peakEfferent=NaN(nLevels,nFrequencies); - peakAREfferent=NaN(nLevels,nFrequencies); - - - levelNo=0; - for leveldB=levels - disp(['level= ' num2str(leveldB)]) - levelNo=levelNo+1; - - freqNo=0; - for frequency=stimulusFrequencies - freqNo=freqNo+1; - - % Generate stimuli - globalStimParams.FS=sampleRate; - globalStimParams.overallDuration=... - toneDuration+silenceDuration; % s - stim.phases='sin'; - stim.type='tone'; - stim.toneDuration=toneDuration; - stim.frequencies=frequency; - stim.amplitudesdB=leveldB; - stim.beginSilence=silenceDuration; - stim.rampOnDur=rampDuration; - % no offset ramp - stim.rampOffDur=rampDuration; - doPlot=0; - inputSignal=stimulusCreate(globalStimParams, stim, doPlot); - inputSignal=inputSignal(:,1)'; - - %% run the model - MAPparamsName=paramsName; - AN_spikesOrProbability='probability'; -% AN_spikesOrProbability='spikes'; - - global DRNLoutput MOCattenuation ARattenuation - MAP1_14(inputSignal, sampleRate, BF, ... - MAPparamsName, AN_spikesOrProbability); - - DRNLresponse=DRNLoutput; - peakAmp=max(max(... - DRNLresponse(:, end-round(length(DRNLresponse)/2):end))); - peakAmpBM(levelNo,freqNo)=peakAmp; - peakAmpBMdB(levelNo,freqNo)=... - 20*log10(peakAmp/refBMdisplacement); - peakEfferent(levelNo,freqNo)=min(min(MOCattenuation)); - peakAREfferent(levelNo,freqNo)=min(min(ARattenuation)); - - end % tone frequency - end % level - - %% analyses results and plot - - % BM I/O plot (top panel) - figure(3) - subplot(3,nBFs,BFno), cla - plot(levels,peakAmpBMdB, 'linewidth',2) - hold on, plot(levels, repmat(refBMdisplacement,1,length(levels))) - hold off - title(['BF=' num2str(BF,'%5.0f') ' - ' paramsName]) - xlabel('level') - % set(gca,'xtick',levels), grid on - if length(levels)>1,xlim([min(levels) max(levels)]), end - ylabel(['dB re:' num2str(refBMdisplacement,'%6.1e') 'm']) - ylim([-20 50]) - set(gca,'ytick',[-10 0 10 20 40]) - grid on - % legend({num2str(stimulusFrequencies')}, 'location', 'EastOutside') - UTIL_printTabTable([levels' peakAmpBMdB], ... - num2str([0 stimulusFrequencies]','%5.0f'), '%5.0f') - finalSummary=[finalSummary peakAmpBMdB]; - - % Tuning curve - if length(relativeFrequencies)>2 - figure(3), subplot(3,nBFs, 2*nBFs+BFno) - % contour(stimulusFrequencies,levels,peakAmpBM,... - % [refBMdisplacement refBMdisplacement],'r') - contour(stimulusFrequencies,levels,peakAmpBM,... - refBMdisplacement.*[1 5 10 50 100]) - title(['tuning curve at ' num2str(refBMdisplacement) 'm']); - ylabel('level (dB) at reference') - xlim([100 10000]) - grid on - hold on - set(gca,'xscale','log') - end - - - % MOC contribution - figure(3) - subplot(3,nBFs,nBFs+BFno), cla - plot(levels,20*log10(peakEfferent), 'linewidth',2) - ylabel('MOC (dB attenuation)'), xlabel('level') - title(['peak MOC: model= ' AN_spikesOrProbability]) - grid on - if length(levels)>1, xlim([min(levels) max(levels)]), end - - % AR contribution - hold on - plot(levels,20*log10(peakAREfferent), 'r') - hold off - -end % best frequency - -UTIL_showStructureSummary(DRNLParams, 'DRNLParams', 10) - - UTIL_printTabTable([levels' finalSummary], ... - num2str([0 stimulusFrequencies]','%5.0f'), '%5.0f') - -path(savePath);
--- a/multithreshold 1.46/testFM.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,244 +0,0 @@ -function testFM(BFlist,paramsName,showPSTHs) -% specify whether you want AN 'probability' or 'spikes' -% spikes is more realistic but takes longer -% refractory effect is included only for spikes -% - -% specify the AN ANresponse bin width (normally 1 ms). -% This can influence the measure of the AN onset rate based on the -% largest bin in the ANresponse -% -% Demonstration is based on Harris and Dallos - -global inputStimulusParams outerMiddleEarParams DRNLParams -global IHC_VResp_VivoParams IHCpreSynapseParams AN_IHCsynapseParams - -dbstop if error -% masker and probe levels are relative to this threshold -thresholdAtCF=10; % dB SPL -thresholdAtCF=5; % dB SPL - -if nargin<1, showPSTHs=1;end - -sampleRate=50000; - -% fetch BF from GUI: use only the first target frequency -maskerFrequency=BFlist; -maskerDuration=.1; - -targetFrequency=maskerFrequency; -probeLeveldB=20+thresholdAtCF; % H&D use 20 dB SL/ TMC uses 10 dB SL -probeDuration=0.008; % HD use 15 ms probe (fig 3). -probeDuration=0.015; % HD use 15 ms probe (fig 3). - -rampDuration=.001; % HD use 1 ms linear ramp -initialSilenceDuration=0.02; -finalSilenceDuration=0.05; % useful for showing recovery - -maskerLevels=[-80 10 20 30 40 60 ] + thresholdAtCF; -% maskerLevels=[-80 40 60 ] + thresholdAtCF; - -dt=1/sampleRate; - -figure(7), clf -set(gcf,'position',[613 36 360 247]) -set(gcf,'name', ['forward masking: thresholdAtCF=' num2str(thresholdAtCF)]) - -if showPSTHs - figure(8), clf - set(gcf,'name', 'Harris and Dallos simulation') - set(gcf,'position',[980 36 380 249]) -end - -% Plot Harris and Dallos result for comparison -gapDurations=[0.001 0.002 0.005 0.01 0.02 0.05 0.1 0.3]; -HDmaskerLevels=[+10 +20 +30 +40 +60]; -HDresponse=[ - 1 1 1 1 1 1 1 1; - 0.8 0.82 0.81 0.83 0.87 0.95 1 1; - 0.48 0.5 0.54 0.58 0.7 0.85 0.95 1; - 0.3 0.31 0.35 0.4 0.5 0.68 0.82 0.94; - 0.2 0.27 0.27 0.29 0.42 0.64 0.75 0.92; - 0.15 0.17 0.18 0.23 0.3 0.5 0.6 0.82]; - -figure(7) -semilogx(gapDurations,HDresponse,'o'), hold on -legend(strvcat(num2str(maskerLevels')),'location','southeast') -title([ 'masker dB: ' num2str(HDmaskerLevels)]) - -%% Run the trials -maxProbeResponse=0; -levelNo=0; -resultsMatrix=zeros(length(maskerLevels), length(gapDurations)); -summaryFiringRates=[]; - -% initial silence -time=dt: dt: initialSilenceDuration; -initialSilence=zeros(1,length(time)); - -% probe -time=dt: dt: probeDuration; -amp=28e-6*10^(probeLeveldB/20); -probe=amp*sin(2*pi.*targetFrequency*time); -% ramps -% catch rampTime error -if rampDuration>0.5*probeDuration, rampDuration=probeDuration/2; end -rampTime=dt:dt:rampDuration; -% raised cosine ramp -ramp=[0.5*(1+cos(2*pi*rampTime/(2*rampDuration)+pi)) ... - ones(1,length(time)-length(rampTime))]; -% onset ramp -probe=probe.*ramp; -% offset ramp makes complete ramp for probe -ramp=fliplr(ramp); -% apply ramp mask to probe. Probe does not change below -probe=probe.*ramp; - -% final silence -time=dt: dt: finalSilenceDuration; -finalSilence=zeros(1,length(time)); - -PSTHplotCount=0; -longestSignalDuration=initialSilenceDuration + maskerDuration +... - max(gapDurations) + probeDuration + finalSilenceDuration ; -for maskerLeveldB=maskerLevels - levelNo=levelNo+1; - allDurations=[]; - allFiringRates=[]; - - %masker - time=dt: dt: maskerDuration; - masker=sin(2*pi.*maskerFrequency*time); - % masker ramps - if rampDuration>0.5*maskerDuration - % catch ramp duration error - rampDuration=maskerDuration/2; - end - % NB masker ramp (not probe ramp) - rampTime=dt:dt:rampDuration; - % raised cosine ramp - ramp=[0.5*(1+cos(2*pi*rampTime/(2*rampDuration)+pi))... - ones(1,length(time)-length(rampTime))]; - % onset ramp - masker=masker.*ramp; - % offset ramp - ramp=fliplr(ramp); - % apply ramp - masker=masker.*ramp; - amp=28e-6*10^(maskerLeveldB/20); - maskerPa=amp*masker; - - for gapDuration=gapDurations - time=dt: dt: gapDuration; - gap=zeros(1,length(time)); - - inputSignal=... - [initialSilence maskerPa gap probe finalSilence]; - - % ********************************** run MAP model - - global ANprobRateOutput tauCas ... - - showPlotsAndDetails=0; - -AN_spikesOrProbability='probability'; - -MAP1_14(inputSignal, 1/dt, targetFrequency, ... - paramsName, AN_spikesOrProbability); - - [nFibers c]=size(ANprobRateOutput); - nLSRfibers=nFibers/length(tauCas); - ANresponse=ANprobRateOutput(end-nLSRfibers:end,:); - ANresponse=sum(ANresponse)/nLSRfibers; - - % analyse results - probeStart=initialSilenceDuration+maskerDuration+gapDuration; - PSTHbinWidth=dt; - responseDelay=0.005; - probeTimes=probeStart+responseDelay:... - PSTHbinWidth:probeStart+probeDuration+responseDelay; - probeIDX=round(probeTimes/PSTHbinWidth); - probePSTH=ANresponse(probeIDX); - firingRate=mean(probePSTH); - % NB this only works if you start with the lowest level masker - maxProbeResponse=max([maxProbeResponse firingRate]); - allDurations=[allDurations gapDuration]; - allFiringRates=[allFiringRates firingRate]; - - %% show PSTHs - if showPSTHs - nLevels=length(maskerLevels); - nDurations=length(gapDurations); - figure(8) - PSTHbinWidth=1e-3; - PSTH=UTIL_PSTHmaker(ANresponse, dt, PSTHbinWidth); - PSTH=PSTH*dt/PSTHbinWidth; - PSTHplotCount=PSTHplotCount+1; - subplot(nLevels,nDurations,PSTHplotCount) - probeTime=PSTHbinWidth:PSTHbinWidth:... - PSTHbinWidth*length(PSTH); - bar(probeTime, PSTH) - if strcmp(AN_spikesOrProbability, 'spikes') - ylim([0 500]) - else - ylim([0 500]) - end - xlim([0 longestSignalDuration]) - grid on - - if PSTHplotCount< (nLevels-1) * nDurations+1 - set(gca,'xticklabel',[]) - end - - if ~isequal(mod(PSTHplotCount,nDurations),1) - set(gca,'yticklabel',[]) - else - ylabel([num2str(maskerLevels... - (round(PSTHplotCount/nDurations) +1))]) - end - - if PSTHplotCount<=nDurations - title([num2str(1000*gapDurations(PSTHplotCount)) 'ms']) - end - end % showPSTHs - - end % gapDurations duration - summaryFiringRates=[summaryFiringRates allFiringRates']; - - figure(7), hold on - semilogx(allDurations, allFiringRates/maxProbeResponse) - ylim([0 1]), hold on - ylim([0 inf]), xlim([min(gapDurations) max(gapDurations)]) - xlim([0.001 1]) - pause(0.1) % to allow for CTRL/C interrupts - resultsMatrix(levelNo,:)=allFiringRates; -end % maskerLevel - -disp('delay/ rates') -disp(num2str(round( [1000*allDurations' summaryFiringRates]))) - -% replot with best adjustment -% figure(34), clf% use for separate plot -figure(7), clf -peakProbe=max(max(resultsMatrix)); -resultsMatrix=resultsMatrix/peakProbe; -semilogx(gapDurations,HDresponse,'o'), hold on -title(['FrMsk: probe ' num2str(probeLeveldB)... - 'dB SL: peakProbe=' num2str(peakProbe,'%5.0f') ' sp/s']) -xlabel('gap duration (s)'), ylabel ('probe response') -semilogx(allDurations, resultsMatrix'), ylim([0 1]) -ylim([0 inf]), -xlim([0.001 1]) -legend(strvcat(num2str(maskerLevels'-thresholdAtCF)), -1) - -% ------------------------------------------------- display parameters -disp(['parameter file was: ' paramsName]) -fprintf('\n') -% UTIL_showStruct(inputStimulusParams, 'inputStimulusParams') -% UTIL_showStruct(outerMiddleEarParams, 'outerMiddleEarParams') -% UTIL_showStruct(DRNLParams, 'DRNLParams') -% UTIL_showStruct(IHC_VResp_VivoParams, 'IHC_VResp_VivoParams') -UTIL_showStruct(IHCpreSynapseParams, 'IHCpreSynapseParams') -UTIL_showStruct(AN_IHCsynapseParams, 'AN_IHCsynapseParams') - -
--- a/multithreshold 1.46/testOME.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,86 +0,0 @@ -function testOME(paramsName) - -savePath=path; -addpath (['..' filesep 'utilities'],['..' filesep 'MAP']) - -sampleRate=50000; - -dt=1/sampleRate; -leveldBSPL=80; % dB SPL as used by Huber (may trigger AR) -amp=10^(leveldBSPL/20)*28e-6; -duration=.05; -time=dt: dt: duration; - -%% Comparison data (human) -% These data are taken directly from Huber 2001 (Fig. 4) -HuberFrequencies=[600 800 1000 2000 3000 4000 6000 8000]; -HuberDisplacementAt80dBSPL=[1.5E-9 1.5E-09 1.5E-09 1.0E-09 7.0E-10 ... - 3.0E-10 2.0E-10 1.0E-10]; % m; -% HuberVelocityAt80dBSPL= 2*pi*HuberFrequencies.*HuberDisplacementAt80dBSPL; - -figure(2), clf, subplot(2,1,1) -set(2,'position',[5 349 268 327]) -semilogx(HuberFrequencies, 20*log10(HuberDisplacementAt80dBSPL/1e-10),... - 'ko', 'MarkerFaceColor','k', 'Marker','o', 'markerSize',6) -hold on - -%% Generate test stimulus ................................................................. - -% independent test using discrete frequencies -peakResponses=[]; -peakTMpressure=[]; -frequencies=[200 400 HuberFrequencies 10000]; -for toneFrequency=frequencies - inputSignal=amp*sin(2*pi*toneFrequency*time); - - showPlotsAndDetails=0; - AN_spikesOrProbability='probability'; - % switch off AR & MOC (Huber's patients were deaf) - paramChanges{1}='OMEParams.rateToAttenuationFactorProb=0;'; - paramChanges{2}='DRNLParams.rateToAttenuationFactorProb = 0;'; - - global OMEoutput OMEextEarPressure TMoutput ARattenuation - % BF is irrelevant - MAP1_14(inputSignal, sampleRate, -1, ... - paramsName, AN_spikesOrProbability, paramChanges); - - peakDisplacement=max(OMEoutput(floor(end/2):end)); - peakResponses=[peakResponses peakDisplacement]; - - peakTMpressure=[peakTMpressure max(OMEextEarPressure)]; - disp([' AR attenuation (dB): ' num2str(20*log10(min(ARattenuation)))]) -end - -%% Report -disp('frequency displacement(m)') -% disp(num2str([frequencies' peakResponses'])) -fprintf('%6.0f \t%10.3e\n',[frequencies' peakResponses']') - -% stapes peak displacement -figure(2), subplot(2,1,1), hold on -semilogx(frequencies, 20*log10(peakResponses/1e-10), 'r', 'linewidth',4) -set(gca,'xScale','log') -% ylim([1e-11 1e-8]) -xlim([100 10000]), ylim([0 30]) -grid on -title(['stapes at ' num2str(leveldBSPL) ' (NB deaf)']) -ylabel('disp: dB re 1e-10m') -xlabel('stimulus frequency (Hz)') -legend({'Huber et al','model'},'location','southWest') -set(gcf,'name','OME') - -% external ear resonance -figure(2), subplot(2,1,2),hold off -semilogx(frequencies, 20*log10(peakTMpressure/28e-6)-leveldBSPL,... - 'k', 'linewidth',2) -xlim([100 10000]) %, ylim([-10 30]) -grid on -title(['External ear resonances' ]) -ylabel('dB') -xlabel('frequency') -set(gcf,'name','OME: external resonances') -% ---------------------------------------------------------- display parameters -disp(['parameter file was: ' paramsName]) -fprintf('\n') - -path(savePath);
--- a/multithreshold 1.46/testPeriphery.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,161 +0,0 @@ -function testPeriphery (BMlocations, paramsName) -% testBM generates input output functions for DRNL model for any number -% of locations. -% Computations are bast on a single channel model (channelBFs=BF) -% peak displacement (peakAmp) is measured. -% if DRNLParams.useMOC is chosen, the full model is run (slow) -% otherwise only DRNL is computed. -% Tuning curves are generated based on a range of frequencies reletove to -% the BF of the location. -% - -global DRNLParams - -savePath=path; - -addpath (['..' filesep 'utilities'],['..' filesep 'MAP']) - -levels=-10:10:90; nLevels=length(levels); -% levels= 50; nLevels=length(levels); - -% relativeFrequencies=[0.25 .5 .75 1 1.25 1.5 2]; -relativeFrequencies=1; - -% refBMdisplacement is the displacement of the BM at threshold -% 1 nm disp at threshold (9 kHz, Ruggero) -refBMdisplacement= 1e-8; % adjusted for 10 nm at 1 kHz - -toneDuration=.200; -rampDuration=0.01; -silenceDuration=0.01; - -sampleRate=30000; - -dbstop if error -figure(3), clf -% set(gcf,'position',[276 33 331 645]) -set(gcf,'name','DRNL - BM') - -finalSummary=[]; -nBFs=length(BMlocations); -BFno=0; plotCount=0; -for BF=BMlocations - BFno=BFno+1; - plotCount=plotCount+nBFs; - stimulusFrequencies=BF* relativeFrequencies; - nFrequencies=length(stimulusFrequencies); - - peakAmpBM=zeros(nLevels,nFrequencies); - peakAmpBMdB=NaN(nLevels,nFrequencies); - peakEfferent=NaN(nLevels,nFrequencies); - peakAREfferent=NaN(nLevels,nFrequencies); - - - levelNo=0; - for leveldB=levels - disp(['level= ' num2str(leveldB)]) - levelNo=levelNo+1; - - freqNo=0; - for frequency=stimulusFrequencies - freqNo=freqNo+1; - - % Generate stimuli - globalStimParams.FS=sampleRate; - globalStimParams.overallDuration=... - toneDuration+silenceDuration; % s - stim.type='tone'; - stim.phases='sin'; - stim.toneDuration=toneDuration; - stim.frequencies=frequency; - stim.amplitudesdB=leveldB; - stim.beginSilence=silenceDuration; - stim.rampOnDur=rampDuration; - stim.rampOffDur=rampDuration; - doPlot=0; - inputSignal=stimulusCreate(globalStimParams, stim, doPlot); - inputSignal=inputSignal(:,1)'; - - %% run the model - MAPparamsName=paramsName; - AN_spikesOrProbability='probability'; - % spikes are slow but can be used to study MOC using IC units - % AN_spikesOrProbability='spikes'; - - global DRNLoutput MOCattenuation ARattenuation IHCoutput - MAP1_14(inputSignal, sampleRate, BF, ... - MAPparamsName, AN_spikesOrProbability); - - DRNLresponse=IHCoutput; - peakAmp=max(max(... - DRNLresponse(:, end-round(length(DRNLresponse)/2):end))); - peakAmpBM(levelNo,freqNo)=peakAmp; - if peakAmp>0 - peakAmpBMdB(levelNo,freqNo)=... - 20*log10(peakAmp/refBMdisplacement); - else - peakAmpBMdB(levelNo,freqNo)=peakAmp; - end - peakEfferent(levelNo,freqNo)=min(min(MOCattenuation)); - peakAREfferent(levelNo,freqNo)=min(min(ARattenuation)); - - end % tone frequency - end % level - - %% analyses results and plot - - % BM I/O plot (top panel) - figure(3) - subplot(3,nBFs,BFno), cla - plot(levels,peakAmpBMdB, 'linewidth',2) - hold on, plot(levels, repmat(refBMdisplacement,1,length(levels))) - hold off - title(['BF=' num2str(BF,'%5.0f') ' - ' paramsName]) - xlabel('level') - % set(gca,'xtick',levels), grid on - if length(levels)>1,xlim([min(levels) max(levels)]), end - ylabel(['dB re:' num2str(refBMdisplacement,'%6.1e') 'm']) - ylim([-20 50]) - set(gca,'ytick',[-10 0 10 20 40]) - % legend({num2str(stimulusFrequencies')}, 'location', 'EastOutside') - UTIL_printTabTable([levels' peakAmpBMdB], ... - num2str([0 stimulusFrequencies]','%5.0f'), '%5.0f') - finalSummary=[finalSummary peakAmpBMdB]; - - % Tuning curve - if length(relativeFrequencies)>2 - figure(3), subplot(3,nBFs, nBFs+BFno) - % contour(stimulusFrequencies,levels,peakAmpBM,... - % [refBMdisplacement refBMdisplacement],'r') - contour(stimulusFrequencies,levels,peakAmpBM,... - refBMdisplacement.*[1 5 10 50 100]) - title(['tuning curve at ' num2str(refBMdisplacement) 'm']); - ylabel('level (dB) at reference') - xlim([100 10000]) - hold on - set(gca,'xscale','log') - end - - - % MOC contribution - figure(3) - subplot(3,nBFs,2*nBFs+BFno), cla - plot(levels,20*log10(peakEfferent), 'linewidth',2) - ylabel('MOC (dB attenuation)'), xlabel('level') - title(['peak MOC: model= ' AN_spikesOrProbability]) - grid on - if length(levels)>1, xlim([min(levels) max(levels)]), end - - % AR contribution - hold on - plot(levels,20*log10(peakAREfferent), 'r') - hold off - -end % best frequency - -UTIL_showStructureSummary(DRNLParams, 'DRNLParams', 10) - - UTIL_printTabTable([levels' finalSummary], ... - num2str([0 stimulusFrequencies]','%5.0f'), '%5.0f') - -path(savePath); \ No newline at end of file
--- a/multithreshold 1.46/testPhaseLocking.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,45 +0,0 @@ -function testPhaseLocking - -testFrequencies=[250 500 1000 2000 4000 8000]; -levels=50:10:80; -figure(14), clf -set(gcf,'position', [980 36 383 321]) -set(gcf,'name', 'phase locking') -allStrengths=zeros(length(testFrequencies), length(levels)); -peakVectorStrength=zeros(1,length(testFrequencies)); -freqCount=0; -for targetFrequency=testFrequencies; - %single test - freqCount=freqCount+1; - vectorStrength=testAN(targetFrequency,targetFrequency, levels); - allStrengths(freqCount,:)=vectorStrength'; - peakVectorStrength(freqCount)=max(vectorStrength'); -end -%% plot results -figure(14) -subplot(2,1,2) -plot(levels,allStrengths) -xlabel('levels') -ylabel('vector strength') -legend (num2str(testFrequencies'),'location','eastOutside') - -subplot(2,1,1) -semilogx(testFrequencies,peakVectorStrength) -grid on -title ('peak vector strength') -xlabel('frequency') -ylabel('vector strength') - -johnson=[250 0.79 -500 0.82 -1000 0.8 -2000 0.7 -4000 0.25 -5500 0.05 -]; -hold on -plot(johnson(:,1),johnson(:,2),'o') -legend({'model','Johnson 80'},'location','eastOutside') -hold off - -
--- a/multithreshold 1.46/testRF.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,295 +0,0 @@ -function testRF -% testIHC used either for IHC I/O function or receptive field (doReceptiveFields=1) - -global experiment method stimulusParameters expGUIhandles -global inputStimulusParams IHC_ciliaParams -global IHC_VResp_VivoParams IHCpreSynapseParams AN_IHCsynapseParams -dbstop if error -% set(expGUIhandles.pushbuttonStop, 'backgroundColor', [.941 .941 .941]) - -addpath (['..' filesep 'MAP'], ['..' filesep 'utilities'], ... - ['..' filesep 'parameterStore'], ['..' filesep 'wavFileStore'],... - ['..' filesep 'testPrograms']) - -targetFrequency=stimulusParameters.targetFrequency(1); - -sampleRate=50000; -doReceptiveFields=1; - -toneDuration=.05; -rampDuration=0.004; -silenceDuration=.02; - -nRepeats=100; % no. of AN fibers - -plotGraphsForIHC=1; -% number of MacGregor units is set in the parameter file. - -if doReceptiveFields - % show all receptive field - frequencies=targetFrequency* [ 0.5 0.7 0.9 1 1.1 1.3 1.6]; - levels=0:20:80; nLevels=length(levels); - figure(14), clf - figure(15), clf -else - % show only I/O function at BF - frequencies=targetFrequency; - levels=-20:10:90; - % levels=10:.25:13; - % levels=-20:1:-15 - nLevels=length(levels); -% figure(13), clf, -% set (gcf, 'name', ['IHC/AN input/output' num2str(AN_IHCsynapseParams.numFibers) ' repeats']) -% drawnow -end -nFrequencies=length(frequencies); - -IHC_RP_peak=zeros(nLevels,nFrequencies); -IHC_RP_min=zeros(nLevels,nFrequencies); -IHC_RP_dc=zeros(nLevels,nFrequencies); -AN_HSRonset=zeros(nLevels,nFrequencies); -AN_HSRsaturated=zeros(nLevels,nFrequencies); -AN_LSRonset=zeros(nLevels,nFrequencies); -AN_LSRsaturated=zeros(nLevels,nFrequencies); -CNLSRsaturated=zeros(nLevels,nFrequencies); -CNHSRsaturated=zeros(nLevels,nFrequencies); -ICHSRsaturated=zeros(nLevels,nFrequencies); -ICLSRsaturated=zeros(nLevels,nFrequencies); - - -levelNo=0; PSTHplotCount=0; -for leveldB=levels - fprintf('%4.0f\t', leveldB) - levelNo=levelNo+1; - amp=28e-6*10^(leveldB/20); - - freqNo=0; - for frequency=frequencies - - paramFunctionName=['method=MAPparams' experiment.name ... - '(' num2str(targetFrequency) ');' ]; - eval(paramFunctionName); % read parameters afresh each pass - - dt=method.dt; - time=dt:dt:toneDuration; - rampTime=dt:dt:rampDuration; - ramp=[0.5*(1+cos(2*pi*rampTime/(2*rampDuration)+pi)) ones(1,length(time)-length(rampTime))]; - ramp=ramp.*fliplr(ramp); - - silence=zeros(1,round(silenceDuration/dt)); - - toneStartptr=length(silence)+1; - toneMidptr=toneStartptr+round(toneDuration/(2*dt)) -1; - toneEndptr=toneStartptr+round(toneDuration/dt) -1; - - % create signal (leveldB/ frequency) - freqNo=freqNo+1; - inputSignal=amp*sin(2*pi*frequency'*time); - inputSignal= ramp.*inputSignal; - inputSignal=[silence inputSignal silence]; - - if doReceptiveFields % receptive field - method.plotGraphs= 0; % plot only PSTHs - else - method.plotGraphs= plotGraphsForIHC; % show progress - end - - targetChannelNo=1; - - % force parameters - % the number of AN fibers at each BF - AN_IHCsynapseParams.numFibers= nRepeats; - AN_IHCsynapseParams. mode= 'spikes'; - AN_IHCsynapseParams.plotSynapseContents=0; - AN_IHCsynapseParams.PSTHbinWidth=.001; - - method.DRNLSave=1; - method.IHC_cilia_RPSave=1; - method.PSTHbinWidth=1e-3; % useful 1-ms default for all PSTHs - method.AN_IHCsynapseSave=1; - method.MacGregorMultiSave=1; - method.MacGregorSave=1; - method.dt=dt; - - moduleSequence=[1:8]; - - global ANdt ARAttenuation TMoutput OMEoutput ... - DRNLoutput IHC_cilia_output IHCrestingCiliaCond IHCrestingV... - IHCoutput ANprobRateOutput ANoutput savePavailable tauCas ... - CNoutput ICoutput ICmembraneOutput ICfiberTypeRates MOCattenuation - -AN_spikesOrProbability='spikes'; -AN_spikesOrProbability='probability'; -MAPparamsName='Normal'; - -MAP1_14(inputSignal, 1/dt, targetFrequency, ... - MAPparamsName, AN_spikesOrProbability); - - % RP - IHC_RPData=IHC_cilia_output; - IHC_RPData=IHCoutput(targetChannelNo,:); - IHC_RP_peak(levelNo,freqNo)=max(IHC_RPData(toneStartptr:toneEndptr)); - IHC_RP_min(levelNo,freqNo)=min(IHC_RPData(toneStartptr:toneEndptr)); - IHC_RP_dc(levelNo,freqNo)=mean(IHC_RPData(toneStartptr:toneEndptr)); - - % AN next - AN_IHCsynapseAllData=ANoutput; - method.PSTHbinWidth=0.001; - - nTaus=length(tauCas); - numANfibers=size(ANoutput,1); - numLSRfibers=numANfibers/nTaus; - - %LSR (same as HSR if no LSR fibers present) - channelPtr1=(targetChannelNo-1)*numANfibers+1; - channelPtr2=channelPtr1+numANfibers-1; - LSRspikes=AN_IHCsynapseAllData(channelPtr1:channelPtr2,:); - method.dt=method.AN_IHCsynapsedt; - PSTH=UTIL_PSTHmaker(LSRspikes, method); - PSTH=sum(PSTH,1); % sum across fibers (HSR only) - PSTHStartptr=round(silenceDuration/method.PSTHbinWidth)+1; - PSTHMidptr=PSTHStartptr+round(toneDuration/(2*method.PSTHbinWidth)) -1; - PSTHEndptr=PSTHStartptr+round(toneDuration/method.PSTHbinWidth) -1; - AN_LSRonset(levelNo,freqNo)=max(max(PSTH))/(method.PSTHbinWidth*method.numANfibers); - AN_LSRsaturated(levelNo,freqNo)=sum(PSTH(PSTHMidptr:PSTHEndptr))/(method.numANfibers*toneDuration/2); - - % HSR - channelPtr1=numLSRfibers+(targetChannelNo-1)*method.numANfibers+1; - channelPtr2=channelPtr1+method.numANfibers-1; - HSRspikes=AN_IHCsynapseAllData(channelPtr1:channelPtr2,:); - method.dt=method.AN_IHCsynapsedt; - PSTH=UTIL_PSTHmaker(HSRspikes, method); - PSTH=sum(PSTH,1); % sum across fibers (HSR only) - PSTHStartptr=round(silenceDuration/method.PSTHbinWidth)+1; - PSTHMidptr=PSTHStartptr+round(toneDuration/(2*method.PSTHbinWidth)) -1; - PSTHEndptr=PSTHStartptr+round(toneDuration/method.PSTHbinWidth) -1; - AN_HSRonset(levelNo,freqNo)=max(max(PSTH))/(method.PSTHbinWidth*method.numANfibers); - AN_HSRsaturated(levelNo,freqNo)=sum(PSTH(PSTHMidptr:PSTHEndptr))/(method.numANfibers*toneDuration/2); - [cvANHSR, cvTimes, allTimeStamps, allISIs]= UTIL_CV(HSRspikes, method.AN_IHCsynapsedt); - - PSTHplotCount=PSTHplotCount+1; - if doReceptiveFields % receptive field for HSR only - figure(14), set(gcf,'name','AN') - plotReceptiveFields(method, PSTH, PSTHplotCount, levels, frequencies) - ylim([0 method.numANfibers]) - xlabel(['CV= ' num2str(max(cvANHSR),'%4.2f')],'fontsize',8) - end % doReceptiveFields - - % CN - MacGregorMultiAllData=method.MacGregorMultiData; - numLSRfibers=method.McGMultinNeuronsPerBF*length(method.nonlinCF)* (nTaus-1); - - %LSR (same as HSR if no LSR fibers present) - channelPtr1=(targetChannelNo-1)*method.McGMultinNeuronsPerBF+1; - channelPtr2=channelPtr1+method.McGMultinNeuronsPerBF-1; - MacGregorMultiLSRspikes=MacGregorMultiAllData(channelPtr1:channelPtr2,:); - method.dt=method.MacGregorMultidt; - PSTH=UTIL_PSTHmaker(MacGregorMultiLSRspikes, method); - PSTH=sum(PSTH,1); % sum across fibers (HSR only) - PSTHStartptr=round(silenceDuration/method.PSTHbinWidth)+1; - PSTHMidptr=PSTHStartptr+round(toneDuration/(2*method.PSTHbinWidth)) -1; - PSTHEndptr=PSTHStartptr+round(toneDuration/method.PSTHbinWidth) -1; - CNLSRsaturated(levelNo,freqNo)=sum(PSTH(PSTHMidptr:PSTHEndptr)); - CNLSRsaturated(levelNo,freqNo)=CNLSRsaturated(levelNo,freqNo)... - /((toneDuration/2)*method.McGMultinNeuronsPerBF); - - %HSR - channelPtr1=numLSRfibers+(targetChannelNo-1)*method.McGMultinNeuronsPerBF+1; - channelPtr2=channelPtr1+method.McGMultinNeuronsPerBF-1; - MacGregorMultiHSRspikes=MacGregorMultiAllData(channelPtr1:channelPtr2,:); - method.dt=method.MacGregorMultidt; - PSTH=UTIL_PSTHmaker(MacGregorMultiHSRspikes, method); - PSTH=sum(PSTH,1); % sum across fibers (HSR only) - PSTHStartptr=round(silenceDuration/method.PSTHbinWidth)+1; - PSTHMidptr=PSTHStartptr+round(toneDuration/(2*method.PSTHbinWidth)) -1; - PSTHEndptr=PSTHStartptr+round(toneDuration/method.PSTHbinWidth) -1; - CNHSRsaturated(levelNo,freqNo)=sum(PSTH(PSTHMidptr:PSTHEndptr)); - CNHSRsaturated(levelNo,freqNo)=CNHSRsaturated(levelNo,freqNo)... - /((toneDuration/2)*method.McGMultinNeuronsPerBF); - [cvMMHSR, cvTimes, allTimeStamps, allISIs]= UTIL_CV(MacGregorMultiHSRspikes, method.MacGregorMultidt); - - if doReceptiveFields % receptive field - figure(15), set(gcf,'name','CN HSR input') - plotReceptiveFields(method, PSTH, PSTHplotCount, levels, frequencies) - ylim([0 method.McGMultinNeuronsPerBF]) - xlabel(['CV= ' num2str(max(cvMMHSR),'%4.2f')],'fontsize',8) - end - - MacGregorAllData=method.MacGregorData; - numLSRfibers=length(method.nonlinCF)* (nTaus-1); - - %LSR (same as HSR if no LSR fibers present) - channelPtr1=targetChannelNo; - MacGregorLSR=MacGregorAllData(channelPtr1,:); - method.dt=method.MacGregordt; - PSTH=UTIL_PSTHmaker(MacGregorLSR, method); - PSTHStartptr=round(silenceDuration/method.PSTHbinWidth)+1; - PSTHMidptr=PSTHStartptr+round(toneDuration/(2*method.PSTHbinWidth)) -1; - PSTHEndptr=PSTHStartptr+round(toneDuration/method.PSTHbinWidth) -1; - ICLSRsaturated(levelNo,freqNo)=sum(PSTH(PSTHMidptr:PSTHEndptr)); - ICLSRsaturated(levelNo,freqNo)=ICLSRsaturated(levelNo,freqNo)/(toneDuration/2); - - %LSR (same as HSR if no LSR fibers present) - channelPtr1=numLSRfibers+targetChannelNo; - MacGregorHSR=MacGregorAllData(channelPtr1,:); - method.dt=method.MacGregordt; - PSTH=UTIL_PSTHmaker(MacGregorHSR, method); - PSTHStartptr=round(silenceDuration/method.PSTHbinWidth)+1; - PSTHMidptr=PSTHStartptr+round(toneDuration/(2*method.PSTHbinWidth)) -1; - PSTHEndptr=PSTHStartptr+round(toneDuration/method.PSTHbinWidth) -1; - ICHSRsaturated(levelNo,freqNo)=sum(PSTH(PSTHMidptr:PSTHEndptr)); - ICHSRsaturated(levelNo,freqNo)=ICHSRsaturated(levelNo,freqNo)/(toneDuration/2); - [cvICHSR, cvTimes, allTimeStamps, allISIs]= UTIL_CV(MacGregorHSR, method.MacGregordt); - -% if doReceptiveFields % receptive field -% figure(16), set(gcf,'name','IC HSR input') -% plotReceptiveFields(method, PSTH, PSTHplotCount, levels, frequencies) -% ylim([0 method.McGMultinNeuronsPerBF]) -% xlabel(['CV= ' num2str(max(cvICHSR),'%4.2f')],'fontsize',8) -% end - end % frequency -end % level -fprintf('\n') -toneDuration=2; -rampDuration=0.004; -silenceDuration=.02; -nRepeats=200; % no. of AN fibers -fprintf('toneDuration %6.3f\n', toneDuration) -fprintf(' %6.0f AN fibers (repeats)\n', nRepeats) -fprintf('levels') -fprintf('%6.2f\t', levels) -fprintf('\n') - - -% ---------------------------------------------------------- display parameters -disp(['parameter file was: ' experiment.name]) -fprintf('\n') -UTIL_showStruct(IHC_VResp_VivoParams, 'IHC_cilia_RPParams') -UTIL_showStruct(IHCpreSynapseParams, 'IHCpreSynapseParams') -UTIL_showStruct(AN_IHCsynapseParams, 'AN_IHCsynapseParams') - - - -function plotReceptiveFields(method, PSTH, PSTHplotCount, levels, frequencies) - -% show PSTH for each level/frequency combination -nLevels=length(levels); -nFrequencies=length(frequencies); - -PSTHtime=method.PSTHbinWidth:method.PSTHbinWidth:method.PSTHbinWidth*length(PSTH); -subplot(nLevels,nFrequencies,PSTHplotCount) -bar(PSTHtime, PSTH) -xlim([0 max(PSTHtime)]) -% write axis labels only at left and bottom -if PSTHplotCount< (nLevels-1) * nFrequencies+1 - set(gca,'xticklabel',[]) -end -if ~isequal(mod(PSTHplotCount,nFrequencies),1) - set(gca,'yticklabel',[]) -else - ylabel([num2str(levels(round(PSTHplotCount/nFrequencies) +1)) ' dB']) -end -% add titles only on top row -if PSTHplotCount<=nFrequencies - title([num2str(frequencies(PSTHplotCount)) ' Hz']) -end
--- a/multithreshold 1.46/testRP.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,212 +0,0 @@ -function testRP(BFs,MAPparamsName,paramChanges) -% testIHC used for IHC I/O function - -global experiment method inputStimulusParams -global stimulusParameters IHC_VResp_VivoParams IHC_cilia_RPParams -savePath=path; -addpath (['..' filesep 'utilities'],['..' filesep 'MAP']) -dbstop if error - -figure(4), clf, -set (gcf, 'name', ['IHC']) -set(gcf,'position',[613 354 360 322]) -drawColors='rgbkmcy'; -drawnow - -if nargin<3, paramChanges=[]; end - -levels=-20:10:100; -nLevels=length(levels); -toneDuration=.05; -silenceDuration=.01; -sampleRate=50000; -dt=1/sampleRate; - -allIHC_RP_peak=[]; -allIHC_RP_dc=[]; - -changes{1}=[]; -% changes{1}='IHC_cilia_RPParams.Et= 0.100;'; -% changes{2}='IHC_cilia_RPParams.Et= 0.070;'; - -for changeNo=1:length(changes) - if isempty(changes{1}) - paramChanges=[]; - else - paramChanges{1}=changes{changeNo}; - end -for BFno=1:length(BFs) - BF=BFs(BFno); - targetFrequency=BF; - % OR - %Patuzzi and Sellick test (see ELP & AEM, 2006) - % targetFrequency=100; - - IHC_RP_peak=zeros(nLevels,1); - IHC_RP_min=zeros(nLevels,1); - IHC_RP_dc=zeros(nLevels,1); - - time=dt:dt:toneDuration; - - rampDuration=0.004; - rampTime=dt:dt:rampDuration; - ramp=[0.5*(1+cos(2*pi*rampTime/(2*rampDuration)+pi)) ... - ones(1,length(time)-length(rampTime))]; - ramp=ramp.*fliplr(ramp); - - silence=zeros(1,round(silenceDuration/dt)); - - toneStartptr=length(silence)+1; - toneMidptr=toneStartptr+round(toneDuration/(2*dt)) -1; - toneEndptr=toneStartptr+round(toneDuration/dt) -1; - - levelNo=0; - for leveldB=levels - levelNo=levelNo+1; - % replicate at all levels - amp=28e-6*10^(leveldB/20); - - %% create signal (leveldB/ frequency) - inputSignal=amp*sin(2*pi*targetFrequency'*time); - inputSignal= ramp.*inputSignal; - inputSignal=[silence inputSignal silence]; - inputStimulusParams.sampleRate=1/dt; -% global IHC_ciliaParams - - %% disable efferent for fast processing - method.DRNLSave=1; - method.IHC_cilia_RPSave=1; - method.IHCpreSynapseSave=1; - method.IHC_cilia_RPSave=1; - method.segmentDuration=-1; - moduleSequence=1:4; - - %% run the model - global DRNLoutput IHC_cilia_output IHCrestingCiliaCond IHCrestingV... - IHCoutput - AN_spikesOrProbability='probability'; - - MAP1_14(inputSignal, sampleRate, BF, ... - MAPparamsName, AN_spikesOrProbability, paramChanges); - - % DRNL - DRNLoutput=DRNLoutput; - DRNL_peak(levelNo,1)=max(DRNLoutput(toneMidptr:toneEndptr)); - DRNL_min(levelNo,1)=min(DRNLoutput(toneMidptr:toneEndptr)); - DRNL_dc(levelNo,1)=mean(DRNLoutput(toneMidptr:toneEndptr)); - - % cilia - IHC_ciliaData=IHC_cilia_output; - IHC_ciliaData=IHC_ciliaData; - IHC_cilia_peak(levelNo,1)=... - max(IHC_ciliaData(toneMidptr:toneEndptr)); - IHC_cilia_min(levelNo,1)=... - min(IHC_ciliaData(toneMidptr:toneEndptr)); - IHC_cilia_dc(levelNo,1)=... - mean(IHC_ciliaData(toneMidptr:toneEndptr)); - - % RP - IHC_RPData=IHCoutput; - IHC_RPData=IHC_RPData; - IHC_RP_peak(levelNo,1)=... - max(IHC_RPData(toneMidptr:toneEndptr)); - IHC_RP_min(levelNo,1)=... - min(IHC_RPData(toneMidptr:toneEndptr)); - IHC_RP_dc(levelNo,1)=... - mean(IHC_RPData(toneMidptr:toneEndptr)); - - end % level - - - disp(['parameter file was: ' MAPparamsName]) - fprintf('\n') - - %% plot DRNL - subplot(2,2,1) -% referenceDisp= 9e-9*1000/targetFrequency; -% plot(levels,20*log10(DRNL_peak/referenceDisp), drawColors(BFno), ... -% 'linewidth',2), hold on - referenceDisp=10e-9; - plot(levels,20*log10(DRNL_peak/referenceDisp), drawColors(BFno), ... - 'linewidth',2), hold on - title([' DRNL peak: ' num2str(BFs) ' Hz']) - ylabel ('log10DRNL(m)'), xlabel('dB SPL') - xlim([min(levels) max(levels)]), ylim([-10 50]) - grid on - - %% plot cilia displacement - figure(4) - subplot(2,2,2) - restingIHC_cilia=IHCrestingCiliaCond; - plot(levels, IHC_cilia_peak,'k', 'linewidth',2), hold on - plot(levels, IHC_cilia_min,'r', 'linewidth',2) - hold on, - plot([min(levels) max(levels)], ... - [restingIHC_cilia restingIHC_cilia], 'g') - title(' IHC apical cond.') - ylabel ('IHCcilia(conductance)'), xlabel('dB SPL') - xlim([min(levels) max(levels)]) - grid on - - %% plot receptor potentials - figure(4) - subplot(2,2,3) - % RP I/O function min and max - restingRP=IHC_RP_peak(1); - toPlot= [fliplr(IHC_RP_min(:,1)') IHC_RP_peak(:,1)']; - microPa= 28e-6*10.^(levels/20); - microPa=[-fliplr(microPa) microPa]; - plot(microPa,toPlot, drawColors(BFno), 'linewidth',2) - % ylim([0 300]) - - %% Dallos and Harris data - dallosx=[-0.9 -0.1 -0.001 0.001 0.01 0.9]; - dallosy=[-8 -7.8 -6.5 11 16.5 22]/1000 + restingRP; - hold on, plot(dallosx,dallosy, 'o') - plot([-1 1], [restingRP restingRP], 'r') - title(' Dallos(86) data at 800 Hz') - ylabel ('receptor potential(V)'), xlabel('Pa') - ylim([-0.08 -0.02]), xlim([-1 1]) - grid on - - %% RP I/O function min and max - figure(4) - subplot(2,2,4) - restingRP=IHC_RP_peak(1); - peakRP=max(IHC_RP_peak); - plot(levels, IHC_RP_peak,drawColors(BFno), 'linewidth',2) - hold on - plot(levels, IHC_RP_dc, [drawColors(BFno) ':'], 'linewidth',2) - hold on, - plot([min(levels) max(levels)], [restingRP restingRP], 'r') - xlim([min(levels) max(levels)]) - % animal data - sndLevel=[5 15 25 35 45 55 65 75]; -RPanimal=restingRP+[0.5 2 4.6 5.8 6.4 7.2 8 10.2]/1000; -hold on, plot(sndLevel,RPanimal,'o') - - grid on - title(['Et= ' num2str(IHC_cilia_RPParams.Et) ': RP data 7 kHz Patuzzi']) - ylabel ('RP(V)'), xlabel('dB SPL') - ylim([-0.08 -0.04]) - allIHC_RP_peak=[allIHC_RP_peak IHC_RP_peak]; - allIHC_RP_dc=[allIHC_RP_dc IHC_RP_dc]; - - fprintf('level\t peak\t DC\n') - UTIL_printTabTable([levels' IHC_RP_peak IHC_RP_dc]) - % disp(['restingIHC_cilia= ' num2str(restingIHC_cilia)]) - fprintf('peakRP= \t%6.3f', peakRP) - fprintf('\nrestingRP= \t%6.3f', restingRP) - fprintf('\ndifference= \t%6.3f\n', (peakRP-restingRP)) - drawnow -end -end -% UTIL_showStruct(IHC_VResp_VivoParams, 'IHC_VResp_VivoParams') -UTIL_showStruct(IHC_cilia_RPParams, 'IHC_cilia_RPParams') - fprintf('level\t peak\n') - UTIL_printTabTable([levels' allIHC_RP_peak]) - fprintf('level\t DC\n') - UTIL_printTabTable([levels' allIHC_RP_dc]) - -path(savePath); -disp(paramChanges)
--- a/multithreshold 1.46/testSynapse.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,87 +0,0 @@ -function testSynapse(BFlist,paramsName) -% testSynapse tracks the quantity of available transmitter vesicles -% the computations are single channel using the first frequency -% in the targetFrequency box of the expGUI. -% For, speed this function uses only probability and HSR fibers. -% This cannot be changed because of the way AN_IHCsynapse is coded.This). - -global experiment method IHCpreSynapseParams -global AN_IHCsynapseParams stimulusParameters -savePath=path; -addpath (['..' filesep 'utilities'],['..' filesep 'MAP']) - -figure(6),clf -plotColors='rbgkrbgkrbgkrbgkrbgkrbgk'; -set(gcf,'position',[5 32 264 243]) - -sampleRate=5e4; dt=1/sampleRate; - -maskerLevels=-0:10:100; - -targetFrequency=stimulusParameters.targetFrequency; -targetFrequency=targetFrequency(1); % only one frequency used - -showParams=0; -useEfferent=0; % no efferent - -silenceDuration=0.005; -silenceDuration=0.015; -maskerDuration=0.1; -recoveryDuration=0.15; -rampDuration=0.004; - -maskerTime=dt:dt:maskerDuration; - -rampTime=dt:dt:rampDuration; -ramp=[0.5*(1+cos(2*pi*rampTime/(2*rampDuration)+pi)) ... - ones(1,length(maskerTime)-length(rampTime))]; -ramp=ramp.*fliplr(ramp); - -initialSilence=zeros(1,round(silenceDuration/dt)); -recoverySilence=zeros(1,round(recoveryDuration/dt)); - -signal=sin(2*pi*targetFrequency'*maskerTime); -signal= ramp.*signal; -signal=[initialSilence signal recoverySilence]; - -levelCount=0; -qtMatrix=[]; -for leveldB=maskerLevels - levelCount=levelCount+1; - - amp=28e-6*10^(leveldB/20); - inputSignal=amp*signal; - - AN_spikesOrProbability='probability'; - showPlotsAndDetails=0; - - global savePavailable - - MAP1_14(inputSignal, 1/dt, targetFrequency, ... - paramsName, AN_spikesOrProbability); - - % ignore LSR channels (if any) at the top of the matrix - qt=savePavailable(end, :); - - synapsedt=dt; - time=synapsedt:synapsedt:synapsedt*length(qt); - - figure(6) - qtMatrix=[qtMatrix; qt]; - plot(time,qt, plotColors(levelCount)) - hold on - xlim([0 max(time)]) - ylim([0 AN_IHCsynapseParams.M]) -end - -set(gcf,'name','pre-synaptic available transmitter') -title(['q - available vesicles:' num2str(BFlist) ' Hz']) -legend(strvcat(num2str(maskerLevels')),'location','southeast') -legend boxoff -grid on - -figure(88), [c,H]=contour(time, maskerLevels,qtMatrix); clabel(c, H); -set(gcf,'position',[ 276 31 328 246]) -xlabel('time'), ylabel('maskerLevels') - -path(savePath);
--- a/parameterStore/MAPparamsEndo.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,302 +0,0 @@ -function method=MAPparamsEndo ... - (BFlist, sampleRate, showParams, paramChanges) -% MAPparams<> establishes a complete set of MAP parameters -% Parameter file names must be of the form <MAPparams> <name> -% -% input arguments -% BFlist (optional) specifies the desired list of channel BFs -% otherwise defaults set below -% sampleRate (optional), default is 50000. -% showParams (optional) =1 prints out the complete set of parameters -% output argument -% method passes a miscelleny of values - -global inputStimulusParams OMEParams DRNLParams IHC_cilia_RPParams -global IHC_VResp_VivoParams IHCpreSynapseParams AN_IHCsynapseParams -global MacGregorParams MacGregorMultiParams filteredSACFParams -global experiment % used by calls from multiThreshold only - - -currentFile=mfilename; % i.e. the name of this mfile -method.parameterSource=currentFile(10:end); % for the record - -efferentDelay=0.010; -method.segmentDuration=efferentDelay; - -if nargin<3, showParams=0; end -if nargin<2, sampleRate=50000; end -if nargin<1 || BFlist(1)<0 % if BFlist= -1, set BFlist to default - lowestBF=250; highestBF= 8000; numChannels=21; - % 21 chs (250-8k)includes BFs at 250 500 1000 2000 4000 8000 - BFlist=round(logspace(log10(lowestBF),log10(highestBF),numChannels)); -end -% BFlist=1000; - -% preserve for backward campatibility -method.nonlinCF=BFlist; -method.dt=1/sampleRate; - -%%%%%%%%%%%%%%%%%%%%%%%%%%%% -% set model parameters -%%%%%%%%%%%%%%%%%%%%%%%%%%%% - -%% #1 inputStimulus -inputStimulusParams=[]; -inputStimulusParams.sampleRate= sampleRate; - -%% #2 outerMiddleEar -OMEParams=[]; % clear the structure first -% outer ear resonances band pass filter [gain lp order hp] -OMEParams.externalResonanceFilters= [ 10 1 1000 4000]; - -% highpass stapes filter -% Huber gives 2e-9 m at 80 dB and 1 kHz (2e-13 at 0 dB SPL) -OMEParams.OMEstapesLPcutoff= 1000; -OMEParams.stapesScalar= 45e-9; - -% Acoustic reflex: maximum attenuation should be around 25 dB Price (1966) -% i.e. a minimum ratio of 0.056. -% 'spikes' model: AR based on brainstem spiking activity (LSR) -OMEParams.rateToAttenuationFactor=0.006; % * N(all ICspikes) -% OMEParams.rateToAttenuationFactor=0; % * N(all ICspikes) - -% 'probability model': Ar based on AN firing probabilities (LSR) -OMEParams.rateToAttenuationFactorProb=0.01;% * N(all ANrates) -% OMEParams.rateToAttenuationFactorProb=0;% * N(all ANrates) - -% asymptote should be around 100-200 ms -OMEParams.ARtau=.05; % AR smoothing function -% delay must be longer than the segment length -OMEParams.ARdelay=efferentDelay; %Moss gives 8.5 ms latency -OMEParams.ARrateThreshold=0; - -%% #3 DRNL -DRNLParams=[]; % clear the structure first -DRNLParams.BFlist=BFlist; - -% DRNL nonlinear path -DRNLParams.a=5e4; % DRNL.a=0 means no OHCs (no nonlinear path) -DRNLParams.a=2e4; % DRNL.a=0 means no OHCs (no nonlinear path) - -DRNLParams.b=8e-6; % *compression threshold raised compression -% DRNLParams.b=1; % b=1 means no compression - -DRNLParams.c=0.2; % compression exponent -% nonlinear filters -DRNLParams.nonlinCFs=BFlist; -DRNLParams.nonlinOrder= 3; % order of nonlinear gammatone filters -p=0.2895; q=170; % human (% p=0.14; q=366; % cat) -DRNLParams.nlBWs= p * BFlist + q; -DRNLParams.p=p; DRNLParams.q=q; % save p and q for printing only - -% DRNL linear path: -DRNLParams.g=100; % linear path gain factor -% linCF is not necessarily the same as nonlinCF -minLinCF=153.13; coeffLinCF=0.7341; % linCF>nonlinBF for BF < 1 kHz -DRNLParams.linCFs=minLinCF+coeffLinCF*BFlist; -DRNLParams.linOrder= 3; % order of linear gammatone filters -minLinBW=100; coeffLinBW=0.6531; -DRNLParams.linBWs=minLinBW + coeffLinBW*BFlist; % bandwidths of linear filters - -% DRNL MOC efferents -DRNLParams.MOCdelay = efferentDelay; % must be < segment length! - -% 'spikes' model: MOC based on brainstem spiking activity (HSR) -DRNLParams.rateToAttenuationFactor = .01; % strength of MOC -% DRNLParams.rateToAttenuationFactor = 0; % strength of MOC -% 'probability' model: MOC based on AN spiking activity (HSR) -DRNLParams.rateToAttenuationFactorProb = .0055; % strength of MOC -% DRNLParams.rateToAttenuationFactorProb = .0; % strength of MOC -DRNLParams.MOCrateThresholdProb =70; % spikes/s probability only - -DRNLParams.MOCtau =.1; % smoothing for MOC - - -%% #4 IHC_cilia_RPParams - -IHC_cilia_RPParams.tc= 0.0003; % 0.0003 filter time simulates viscocity -% IHC_cilia_RPParams.tc= 0.0005; % 0.0003 filter time simulates viscocity -IHC_cilia_RPParams.C= 0.03; % 0.1 scalar (C_cilia ) -IHC_cilia_RPParams.u0= 5e-9; -IHC_cilia_RPParams.s0= 30e-9; -IHC_cilia_RPParams.u1= 1e-9; -IHC_cilia_RPParams.s1= 1e-9; - -IHC_cilia_RPParams.Gmax= 6e-9; % 2.5e-9 maximum conductance (Siemens) -IHC_cilia_RPParams.Ga= 1e-9; % 4.3e-9 fixed apical membrane conductance -IHC_cilia_RPParams.Ga= .8e-9; % 4.3e-9 fixed apical membrane conductance - -% #5 IHC_RP -IHC_cilia_RPParams.Cab= 4e-012; % IHC capacitance (F) -% IHC_cilia_RPParams.Cab= 1e-012; % IHC capacitance (F) -IHC_cilia_RPParams.Et= 0.05; % endocochlear potential (V) - -IHC_cilia_RPParams.Gk= 2e-008; % 1e-8 potassium conductance (S) -IHC_cilia_RPParams.Ek= -0.08; % -0.084 K equilibrium potential -IHC_cilia_RPParams.Rpc= 0.04; % combined resistances - - -%% #5 IHCpreSynapse -IHCpreSynapseParams=[]; -IHCpreSynapseParams.GmaxCa= 14e-9;% maximum calcium conductance -IHCpreSynapseParams.GmaxCa= 12e-9;% maximum calcium conductance -IHCpreSynapseParams.ECa= 0.066; % calcium equilibrium potential -IHCpreSynapseParams.beta= 400; % determine Ca channel opening -IHCpreSynapseParams.gamma= 100; % determine Ca channel opening -IHCpreSynapseParams.tauM= 0.00005; % membrane time constant ?0.1ms -IHCpreSynapseParams.power= 3; -% reminder: changing z has a strong effect on HF thresholds (like Et) -IHCpreSynapseParams.z= 2e42; % scalar Ca -> vesicle release rate - -LSRtauCa=35e-6; HSRtauCa=85e-6; % seconds -% LSRtauCa=35e-6; HSRtauCa=70e-6; % seconds -IHCpreSynapseParams.tauCa= [LSRtauCa HSRtauCa]; %LSR and HSR fiber - -%% #6 AN_IHCsynapse -% c=kym/(y(l+r)+kl) (spontaneous rate) -% c=(approx) ym/l (saturated rate) -AN_IHCsynapseParams=[]; % clear the structure first -AN_IHCsynapseParams.M= 12; % maximum vesicles at synapse -AN_IHCsynapseParams.y= 4; % depleted vesicle replacement rate -AN_IHCsynapseParams.y= 6; % depleted vesicle replacement rate - -AN_IHCsynapseParams.x= 30; % replenishment from re-uptake store -AN_IHCsynapseParams.x= 60; % replenishment from re-uptake store - -% reduce l to increase saturated rate -AN_IHCsynapseParams.l= 100; % *loss rate of vesicles from the cleft -AN_IHCsynapseParams.l= 250; % *loss rate of vesicles from the cleft - -AN_IHCsynapseParams.r= 500; % *reuptake rate from cleft into cell -% AN_IHCsynapseParams.r= 300; % *reuptake rate from cleft into cell - -AN_IHCsynapseParams.refractory_period= 0.00075; -% number of AN fibers at each BF (used only for spike generation) -AN_IHCsynapseParams.numFibers= 100; -AN_IHCsynapseParams.TWdelay=0.004; % ?delay before stimulus first spike - -AN_IHCsynapseParams.ANspeedUpFactor=5; % longer epochs for computing spikes. - -%% #7 MacGregorMulti (first order brainstem neurons) -MacGregorMultiParams=[]; -MacGregorMultiType='chopper'; % MacGregorMultiType='primary-like'; %choose -switch MacGregorMultiType - case 'primary-like' - MacGregorMultiParams.nNeuronsPerBF= 10; % N neurons per BF - MacGregorMultiParams.type = 'primary-like cell'; - MacGregorMultiParams.fibersPerNeuron=4; % N input fibers - MacGregorMultiParams.dendriteLPfreq=200; % dendritic filter - MacGregorMultiParams.currentPerSpike=0.11e-6; % (A) per spike - MacGregorMultiParams.Cap=4.55e-9; % cell capacitance (Siemens) - MacGregorMultiParams.tauM=5e-4; % membrane time constant (s) - MacGregorMultiParams.Ek=-0.01; % K+ eq. potential (V) - MacGregorMultiParams.dGkSpike=3.64e-5; % K+ cond.shift on spike,S - MacGregorMultiParams.tauGk= 0.0012; % K+ conductance tau (s) - MacGregorMultiParams.Th0= 0.01; % equilibrium threshold (V) - MacGregorMultiParams.c= 0.01; % threshold shift on spike, (V) - MacGregorMultiParams.tauTh= 0.015; % variable threshold tau - MacGregorMultiParams.Er=-0.06; % resting potential (V) - MacGregorMultiParams.Eb=0.06; % spike height (V) - - case 'chopper' - MacGregorMultiParams.nNeuronsPerBF= 10; % N neurons per BF - MacGregorMultiParams.type = 'chopper cell'; - MacGregorMultiParams.fibersPerNeuron=10; % N input fibers -% MacGregorMultiParams.fibersPerNeuron=6; % N input fibers - - MacGregorMultiParams.dendriteLPfreq=50; % dendritic filter - MacGregorMultiParams.currentPerSpike=35e-9; % *per spike -% MacGregorMultiParams.currentPerSpike=30e-9; % *per spike - - MacGregorMultiParams.Cap=1.67e-8; % ??cell capacitance (Siemens) - MacGregorMultiParams.tauM=0.002; % membrane time constant (s) - MacGregorMultiParams.Ek=-0.01; % K+ eq. potential (V) - MacGregorMultiParams.dGkSpike=1.33e-4; % K+ cond.shift on spike,S - MacGregorMultiParams.tauGk= 0.0005;% K+ conductance tau (s) - MacGregorMultiParams.Th0= 0.01; % equilibrium threshold (V) - MacGregorMultiParams.c= 0; % threshold shift on spike, (V) - MacGregorMultiParams.tauTh= 0.02; % variable threshold tau - MacGregorMultiParams.Er=-0.06; % resting potential (V) - MacGregorMultiParams.Eb=0.06; % spike height (V) - MacGregorMultiParams.PSTHbinWidth= 1e-4; -end - -%% #8 MacGregor (second-order neuron). Only one per channel -MacGregorParams=[]; % clear the structure first -MacGregorParams.type = 'chopper cell'; -MacGregorParams.fibersPerNeuron=10; % N input fibers -MacGregorParams.dendriteLPfreq=100; % dendritic filter -MacGregorParams.currentPerSpike=120e-9;% *(A) per spike -MacGregorParams.currentPerSpike=40e-9;% *(A) per spike - -MacGregorParams.Cap=16.7e-9; % cell capacitance (Siemens) -MacGregorParams.tauM=0.002; % membrane time constant (s) -MacGregorParams.Ek=-0.01; % K+ eq. potential (V) -MacGregorParams.dGkSpike=1.33e-4; % K+ cond.shift on spike,S -MacGregorParams.tauGk= 0.0005; % K+ conductance tau (s) -MacGregorParams.Th0= 0.01; % equilibrium threshold (V) -MacGregorParams.c= 0; % threshold shift on spike, (V) -MacGregorParams.tauTh= 0.02; % variable threshold tau -MacGregorParams.Er=-0.06; % resting potential (V) -MacGregorParams.Eb=0.06; % spike height (V) -MacGregorParams.debugging=0; % (special) -% wideband accepts input from all channels (of same fiber type) -% use wideband to create inhibitory units -MacGregorParams.wideband=0; % special for wideband units -% MacGregorParams.saveAllData=0; - -%% #9 filteredSACF -minPitch= 300; maxPitch= 3000; numPitches=60; % specify lags -pitches=100*log10(logspace(minPitch/100, maxPitch/100, numPitches)); -filteredSACFParams.lags=1./pitches; % autocorrelation lags vector -filteredSACFParams.acfTau= .003; % time constant of running ACF -filteredSACFParams.lambda= 0.12; % slower filter to smooth ACF -filteredSACFParams.plotFilteredSACF=1; % 0 plots unfiltered ACFs -filteredSACFParams.plotACFs=0; % special plot (see code) -% filteredSACFParams.usePressnitzer=0; % attenuates ACF at long lags -filteredSACFParams.lagsProcedure= 'useAllLags'; -% filteredSACFParams.lagsProcedure= 'useBernsteinLagWeights'; -% filteredSACFParams.lagsProcedure= 'omitShortLags'; -filteredSACFParams.criterionForOmittingLags=3; - -% checks -if AN_IHCsynapseParams.numFibers<MacGregorMultiParams.fibersPerNeuron - error('MacGregorMulti: too few input fibers for input to MacG unit') -end - - -%% now accept last minute parameter changes required by the calling program -% paramChanges -if nargin>3 && ~isempty(paramChanges) - nChanges=length(paramChanges); - for idx=1:nChanges - eval(paramChanges{idx}) - end -end - - -%% write all parameters to the command window -% showParams is currently set at the top of htis function -if showParams - fprintf('\n %%%%%%%%\n') - fprintf('\n%s\n', method.parameterSource) - fprintf('\n') - nm=UTIL_paramsList(whos); - for i=1:length(nm) - % eval(['UTIL_showStruct(' nm{i} ', ''' nm{i} ''')']) - if ~strcmp(nm(i), 'method') - eval(['UTIL_showStructureSummary(' nm{i} ', ''' nm{i} ''', 10)']) - end - end - - % highlight parameter changes made locally - if nargin>3 && ~isempty(paramChanges) - fprintf('\n Local parameter changes:\n') - for i=1:length(paramChanges) - disp(paramChanges{i}) - end - end -end - -% for backward compatibility -experiment.comparisonData=[];
--- a/parameterStore/MAPparamsJE.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,302 +0,0 @@ -function method=MAPparamsJE ... - (BFlist, sampleRate, showParams, paramChanges) -% MAPparams<> establishes a complete set of MAP parameters -% Parameter file names must be of the form <MAPparams> <name> -% -% input arguments -% BFlist (optional) specifies the desired list of channel BFs -% otherwise defaults set below -% sampleRate (optional), default is 50000. -% showParams (optional) =1 prints out the complete set of parameters -% output argument -% method passes a miscelleny of values - -global inputStimulusParams OMEParams DRNLParams IHC_cilia_RPParams -global IHC_VResp_VivoParams IHCpreSynapseParams AN_IHCsynapseParams -global MacGregorParams MacGregorMultiParams filteredSACFParams -global experiment % used by calls from multiThreshold only - - -currentFile=mfilename; % i.e. the name of this mfile -method.parameterSource=currentFile(10:end); % for the record - -efferentDelay=0.010; -method.segmentDuration=efferentDelay; - -if nargin<3, showParams=0; end -if nargin<2, sampleRate=50000; end -if nargin<1 || BFlist(1)<0 % if BFlist= -1, set BFlist to default - lowestBF=250; highestBF= 8000; numChannels=21; - % 21 chs (250-8k)includes BFs at 250 500 1000 2000 4000 8000 - BFlist=round(logspace(log10(lowestBF),log10(highestBF),numChannels)); -end -% BFlist=1000; - -% preserve for backward campatibility -method.nonlinCF=BFlist; -method.dt=1/sampleRate; - -%%%%%%%%%%%%%%%%%%%%%%%%%%%% -% set model parameters -%%%%%%%%%%%%%%%%%%%%%%%%%%%% - -%% #1 inputStimulus -inputStimulusParams=[]; -inputStimulusParams.sampleRate= sampleRate; - -%% #2 outerMiddleEar -OMEParams=[]; % clear the structure first -% outer ear resonances band pass filter [gain lp order hp] -OMEParams.externalResonanceFilters= [ 10 1 1000 4000]; - -% highpass stapes filter -% Huber gives 2e-9 m at 80 dB and 1 kHz (2e-13 at 0 dB SPL) -OMEParams.OMEstapesLPcutoff= 1000; -OMEParams.stapesScalar= 45e-9; - -% Acoustic reflex: maximum attenuation should be around 25 dB Price (1966) -% i.e. a minimum ratio of 0.056. -% 'spikes' model: AR based on brainstem spiking activity (LSR) -OMEParams.rateToAttenuationFactor=0.006; % * N(all ICspikes) -% OMEParams.rateToAttenuationFactor=0; % * N(all ICspikes) - -% 'probability model': Ar based on AN firing probabilities (LSR) -OMEParams.rateToAttenuationFactorProb=0.01;% * N(all ANrates) -% OMEParams.rateToAttenuationFactorProb=0;% * N(all ANrates) - -% asymptote should be around 100-200 ms -OMEParams.ARtau=.05; % AR smoothing function -% delay must be longer than the segment length -OMEParams.ARdelay=efferentDelay; %Moss gives 8.5 ms latency -OMEParams.ARrateThreshold=0; - -%% #3 DRNL -DRNLParams=[]; % clear the structure first -DRNLParams.BFlist=BFlist; - -% DRNL nonlinear path -DRNLParams.a=5e4; % DRNL.a=0 means no OHCs (no nonlinear path) -DRNLParams.a=2e4; % DRNL.a=0 means no OHCs (no nonlinear path) - -DRNLParams.b=8e-6; % *compression threshold raised compression -% DRNLParams.b=1; % b=1 means no compression - -DRNLParams.c=0.2; % compression exponent -% nonlinear filters -DRNLParams.nonlinCFs=BFlist; -DRNLParams.nonlinOrder= 3; % order of nonlinear gammatone filters -p=0.2895; q=170; % human (% p=0.14; q=366; % cat) -DRNLParams.nlBWs= p * BFlist + q; -DRNLParams.p=p; DRNLParams.q=q; % save p and q for printing only - -% DRNL linear path: -DRNLParams.g=1000; % linear path gain factor -% linCF is not necessarily the same as nonlinCF -minLinCF=153.13; coeffLinCF=0.7341; % linCF>nonlinBF for BF < 1 kHz -DRNLParams.linCFs=minLinCF+coeffLinCF*BFlist; -DRNLParams.linOrder= 3; % order of linear gammatone filters -minLinBW=100; coeffLinBW=0.6531; -DRNLParams.linBWs=minLinBW + coeffLinBW*BFlist; % bandwidths of linear filters - -% DRNL MOC efferents -DRNLParams.MOCdelay = efferentDelay; % must be < segment length! - -% 'spikes' model: MOC based on brainstem spiking activity (HSR) -DRNLParams.rateToAttenuationFactor = .01; % strength of MOC -% DRNLParams.rateToAttenuationFactor = 0; % strength of MOC -% 'probability' model: MOC based on AN spiking activity (HSR) -DRNLParams.rateToAttenuationFactorProb = .0055; % strength of MOC -% DRNLParams.rateToAttenuationFactorProb = .0; % strength of MOC -DRNLParams.MOCrateThresholdProb =70; % spikes/s probability only - -DRNLParams.MOCtau =.1; % smoothing for MOC - - -%% #4 IHC_cilia_RPParams - -IHC_cilia_RPParams.tc= 0.0003; % 0.0003 filter time simulates viscocity -% IHC_cilia_RPParams.tc= 0.0005; % 0.0003 filter time simulates viscocity -IHC_cilia_RPParams.C= 0.03; % 0.1 scalar (C_cilia ) -IHC_cilia_RPParams.u0= 5e-9; -IHC_cilia_RPParams.s0= 30e-9; -IHC_cilia_RPParams.u1= 1e-9; -IHC_cilia_RPParams.s1= 1e-9; - -IHC_cilia_RPParams.Gmax= 6e-9; % 2.5e-9 maximum conductance (Siemens) -IHC_cilia_RPParams.Ga= 1e-9; % 4.3e-9 fixed apical membrane conductance -IHC_cilia_RPParams.Ga= .8e-9; % 4.3e-9 fixed apical membrane conductance - -% #5 IHC_RP -IHC_cilia_RPParams.Cab= 4e-012; % IHC capacitance (F) -% IHC_cilia_RPParams.Cab= 1e-012; % IHC capacitance (F) -IHC_cilia_RPParams.Et= 0.05; % endocochlear potential (V) - -IHC_cilia_RPParams.Gk= 2e-008; % 1e-8 potassium conductance (S) -IHC_cilia_RPParams.Ek= -0.08; % -0.084 K equilibrium potential -IHC_cilia_RPParams.Rpc= 0.04; % combined resistances - - -%% #5 IHCpreSynapse -IHCpreSynapseParams=[]; -IHCpreSynapseParams.GmaxCa= 14e-9;% maximum calcium conductance -IHCpreSynapseParams.GmaxCa= 12e-9;% maximum calcium conductance -IHCpreSynapseParams.ECa= 0.066; % calcium equilibrium potential -IHCpreSynapseParams.beta= 400; % determine Ca channel opening -IHCpreSynapseParams.gamma= 100; % determine Ca channel opening -IHCpreSynapseParams.tauM= 0.00005; % membrane time constant ?0.1ms -IHCpreSynapseParams.power= 3; -% reminder: changing z has a strong effect on HF thresholds (like Et) -IHCpreSynapseParams.z= 2e42; % scalar Ca -> vesicle release rate - -LSRtauCa=35e-6; HSRtauCa=85e-6; % seconds -% LSRtauCa=35e-6; HSRtauCa=70e-6; % seconds -IHCpreSynapseParams.tauCa= [LSRtauCa HSRtauCa]; %LSR and HSR fiber - -%% #6 AN_IHCsynapse -% c=kym/(y(l+r)+kl) (spontaneous rate) -% c=(approx) ym/l (saturated rate) -AN_IHCsynapseParams=[]; % clear the structure first -AN_IHCsynapseParams.M= 12; % maximum vesicles at synapse -AN_IHCsynapseParams.y= 4; % depleted vesicle replacement rate -AN_IHCsynapseParams.y= 6; % depleted vesicle replacement rate - -AN_IHCsynapseParams.x= 30; % replenishment from re-uptake store -AN_IHCsynapseParams.x= 60; % replenishment from re-uptake store - -% reduce l to increase saturated rate -AN_IHCsynapseParams.l= 100; % *loss rate of vesicles from the cleft -AN_IHCsynapseParams.l= 250; % *loss rate of vesicles from the cleft - -AN_IHCsynapseParams.r= 500; % *reuptake rate from cleft into cell -% AN_IHCsynapseParams.r= 300; % *reuptake rate from cleft into cell - -AN_IHCsynapseParams.refractory_period= 0.00075; -% number of AN fibers at each BF (used only for spike generation) -AN_IHCsynapseParams.numFibers= 100; -AN_IHCsynapseParams.TWdelay=0.004; % ?delay before stimulus first spike - -AN_IHCsynapseParams.ANspeedUpFactor=5; % longer epochs for computing spikes. - -%% #7 MacGregorMulti (first order brainstem neurons) -MacGregorMultiParams=[]; -MacGregorMultiType='chopper'; % MacGregorMultiType='primary-like'; %choose -switch MacGregorMultiType - case 'primary-like' - MacGregorMultiParams.nNeuronsPerBF= 10; % N neurons per BF - MacGregorMultiParams.type = 'primary-like cell'; - MacGregorMultiParams.fibersPerNeuron=4; % N input fibers - MacGregorMultiParams.dendriteLPfreq=200; % dendritic filter - MacGregorMultiParams.currentPerSpike=0.11e-6; % (A) per spike - MacGregorMultiParams.Cap=4.55e-9; % cell capacitance (Siemens) - MacGregorMultiParams.tauM=5e-4; % membrane time constant (s) - MacGregorMultiParams.Ek=-0.01; % K+ eq. potential (V) - MacGregorMultiParams.dGkSpike=3.64e-5; % K+ cond.shift on spike,S - MacGregorMultiParams.tauGk= 0.0012; % K+ conductance tau (s) - MacGregorMultiParams.Th0= 0.01; % equilibrium threshold (V) - MacGregorMultiParams.c= 0.01; % threshold shift on spike, (V) - MacGregorMultiParams.tauTh= 0.015; % variable threshold tau - MacGregorMultiParams.Er=-0.06; % resting potential (V) - MacGregorMultiParams.Eb=0.06; % spike height (V) - - case 'chopper' - MacGregorMultiParams.nNeuronsPerBF= 10; % N neurons per BF - MacGregorMultiParams.type = 'chopper cell'; - MacGregorMultiParams.fibersPerNeuron=10; % N input fibers -% MacGregorMultiParams.fibersPerNeuron=6; % N input fibers - - MacGregorMultiParams.dendriteLPfreq=50; % dendritic filter - MacGregorMultiParams.currentPerSpike=35e-9; % *per spike -% MacGregorMultiParams.currentPerSpike=30e-9; % *per spike - - MacGregorMultiParams.Cap=1.67e-8; % ??cell capacitance (Siemens) - MacGregorMultiParams.tauM=0.002; % membrane time constant (s) - MacGregorMultiParams.Ek=-0.01; % K+ eq. potential (V) - MacGregorMultiParams.dGkSpike=1.33e-4; % K+ cond.shift on spike,S - MacGregorMultiParams.tauGk= 0.0005;% K+ conductance tau (s) - MacGregorMultiParams.Th0= 0.01; % equilibrium threshold (V) - MacGregorMultiParams.c= 0; % threshold shift on spike, (V) - MacGregorMultiParams.tauTh= 0.02; % variable threshold tau - MacGregorMultiParams.Er=-0.06; % resting potential (V) - MacGregorMultiParams.Eb=0.06; % spike height (V) - MacGregorMultiParams.PSTHbinWidth= 1e-4; -end - -%% #8 MacGregor (second-order neuron). Only one per channel -MacGregorParams=[]; % clear the structure first -MacGregorParams.type = 'chopper cell'; -MacGregorParams.fibersPerNeuron=10; % N input fibers -MacGregorParams.dendriteLPfreq=100; % dendritic filter -MacGregorParams.currentPerSpike=120e-9;% *(A) per spike -MacGregorParams.currentPerSpike=40e-9;% *(A) per spike - -MacGregorParams.Cap=16.7e-9; % cell capacitance (Siemens) -MacGregorParams.tauM=0.002; % membrane time constant (s) -MacGregorParams.Ek=-0.01; % K+ eq. potential (V) -MacGregorParams.dGkSpike=1.33e-4; % K+ cond.shift on spike,S -MacGregorParams.tauGk= 0.0005; % K+ conductance tau (s) -MacGregorParams.Th0= 0.01; % equilibrium threshold (V) -MacGregorParams.c= 0; % threshold shift on spike, (V) -MacGregorParams.tauTh= 0.02; % variable threshold tau -MacGregorParams.Er=-0.06; % resting potential (V) -MacGregorParams.Eb=0.06; % spike height (V) -MacGregorParams.debugging=0; % (special) -% wideband accepts input from all channels (of same fiber type) -% use wideband to create inhibitory units -MacGregorParams.wideband=0; % special for wideband units -% MacGregorParams.saveAllData=0; - -%% #9 filteredSACF -minPitch= 300; maxPitch= 3000; numPitches=60; % specify lags -pitches=100*log10(logspace(minPitch/100, maxPitch/100, numPitches)); -filteredSACFParams.lags=1./pitches; % autocorrelation lags vector -filteredSACFParams.acfTau= .003; % time constant of running ACF -filteredSACFParams.lambda= 0.12; % slower filter to smooth ACF -filteredSACFParams.plotFilteredSACF=1; % 0 plots unfiltered ACFs -filteredSACFParams.plotACFs=0; % special plot (see code) -% filteredSACFParams.usePressnitzer=0; % attenuates ACF at long lags -filteredSACFParams.lagsProcedure= 'useAllLags'; -% filteredSACFParams.lagsProcedure= 'useBernsteinLagWeights'; -% filteredSACFParams.lagsProcedure= 'omitShortLags'; -filteredSACFParams.criterionForOmittingLags=3; - -% checks -if AN_IHCsynapseParams.numFibers<MacGregorMultiParams.fibersPerNeuron - error('MacGregorMulti: too few input fibers for input to MacG unit') -end - - -%% now accept last minute parameter changes required by the calling program -% paramChanges -if nargin>3 && ~isempty(paramChanges) - nChanges=length(paramChanges); - for idx=1:nChanges - eval(paramChanges{idx}) - end -end - - -%% write all parameters to the command window -% showParams is currently set at the top of htis function -if showParams - fprintf('\n %%%%%%%%\n') - fprintf('\n%s\n', method.parameterSource) - fprintf('\n') - nm=UTIL_paramsList(whos); - for i=1:length(nm) - % eval(['UTIL_showStruct(' nm{i} ', ''' nm{i} ''')']) - if ~strcmp(nm(i), 'method') - eval(['UTIL_showStructureSummary(' nm{i} ', ''' nm{i} ''', 10)']) - end - end - - % highlight parameter changes made locally - if nargin>3 && ~isempty(paramChanges) - fprintf('\n Local parameter changes:\n') - for i=1:length(paramChanges) - disp(paramChanges{i}) - end - end -end - -% for backward compatibility -experiment.comparisonData=[];
--- a/parameterStore/MAPparamsNormalHold.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,300 +0,0 @@ -function method=MAPparamsNormal ... - (BFlist, sampleRate, showParams, paramChanges) -% MAPparams<> establishes a complete set of MAP parameters -% Parameter file names must be of the form <MAPparams> <name> -% -% input arguments -% BFlist (optional) specifies the desired list of channel BFs -% otherwise defaults set below -% sampleRate (optional), default is 50000. -% showParams (optional) =1 prints out the complete set of parameters -% output argument -% method passes a miscelleny of values - -global inputStimulusParams OMEParams DRNLParams IHC_cilia_RPParams -global IHC_VResp_VivoParams IHCpreSynapseParams AN_IHCsynapseParams -global MacGregorParams MacGregorMultiParams filteredSACFParams -global experiment % used by calls from multiThreshold only - - -currentFile=mfilename; % i.e. the name of this mfile -method.parameterSource=currentFile(10:end); % for the record - -efferentDelay=0.010; -method.segmentDuration=efferentDelay; - -if nargin<3, showParams=0; end -if nargin<2, sampleRate=50000; end -if nargin<1 || BFlist(1)<0 % if BFlist= -1, set BFlist to default - lowestBF=250; highestBF= 8000; numChannels=21; - % 21 chs (250-8k)includes BFs at 250 500 1000 2000 4000 8000 - BFlist=round(logspace(log10(lowestBF),log10(highestBF),numChannels)); -end -% BFlist=1000; - -% preserve for backward campatibility -method.nonlinCF=BFlist; -method.dt=1/sampleRate; - -%%%%%%%%%%%%%%%%%%%%%%%%%%%% -% set model parameters -%%%%%%%%%%%%%%%%%%%%%%%%%%%% - -%% #1 inputStimulus -inputStimulusParams=[]; -inputStimulusParams.sampleRate= sampleRate; - -%% #2 outerMiddleEar -OMEParams=[]; % clear the structure first -% outer ear resonances band pass filter [gain lp order hp] -OMEParams.externalResonanceFilters= [ 10 1 1000 4000]; - -% highpass stapes filter -% Huber gives 2e-9 m at 80 dB and 1 kHz (2e-13 at 0 dB SPL) -OMEParams.OMEstapesLPcutoff= 1000; -OMEParams.stapesScalar= 45e-9; - -% Acoustic reflex: maximum attenuation should be around 25 dB Price (1966) -% i.e. a minimum ratio of 0.056. -% 'spikes' model: AR based on brainstem spiking activity (LSR) -OMEParams.rateToAttenuationFactor=0.006; % * N(all ICspikes) -% OMEParams.rateToAttenuationFactor=0; % * N(all ICspikes) - -% 'probability model': Ar based on AN firing probabilities (LSR) -OMEParams.rateToAttenuationFactorProb=0.01;% * N(all ANrates) -% OMEParams.rateToAttenuationFactorProb=0;% * N(all ANrates) - -% asymptote should be around 100-200 ms -OMEParams.ARtau=.05; % AR smoothing function -% delay must be longer than the segment length -OMEParams.ARdelay=efferentDelay; %Moss gives 8.5 ms latency -OMEParams.ARrateThreshold=0; - -%% #3 DRNL -DRNLParams=[]; % clear the structure first -DRNLParams.BFlist=BFlist; - -% DRNL nonlinear path -DRNLParams.a=5e4; % DRNL.a=0 means no OHCs (no nonlinear path) - -DRNLParams.b=8e-6; % *compression threshold raised compression -% DRNLParams.b=1; % b=1 means no compression - -DRNLParams.c=0.2; % compression exponent -% nonlinear filters -DRNLParams.nonlinCFs=BFlist; -DRNLParams.nonlinOrder= 3; % order of nonlinear gammatone filters -p=0.2895; q=170; % human (% p=0.14; q=366; % cat) -DRNLParams.nlBWs= p * BFlist + q; -DRNLParams.p=p; DRNLParams.q=q; % save p and q for printing only - -% DRNL linear path: -DRNLParams.g=100; % linear path gain factor -% linCF is not necessarily the same as nonlinCF -minLinCF=153.13; coeffLinCF=0.7341; % linCF>nonlinBF for BF < 1 kHz -DRNLParams.linCFs=minLinCF+coeffLinCF*BFlist; -DRNLParams.linOrder= 3; % order of linear gammatone filters -minLinBW=100; coeffLinBW=0.6531; -DRNLParams.linBWs=minLinBW + coeffLinBW*BFlist; % bandwidths of linear filters - -% DRNL MOC efferents -DRNLParams.MOCdelay = efferentDelay; % must be < segment length! - -% 'spikes' model: MOC based on brainstem spiking activity (HSR) -DRNLParams.rateToAttenuationFactor = .01; % strength of MOC -% DRNLParams.rateToAttenuationFactor = 0; % strength of MOC -% 'probability' model: MOC based on AN spiking activity (HSR) -DRNLParams.rateToAttenuationFactorProb = .0055; % strength of MOC -% DRNLParams.rateToAttenuationFactorProb = .0; % strength of MOC -DRNLParams.MOCrateThresholdProb =70; % spikes/s probability only - -DRNLParams.MOCtau =.1; % smoothing for MOC - - -%% #4 IHC_cilia_RPParams - -IHC_cilia_RPParams.tc= 0.0003; % 0.0003 filter time simulates viscocity -% IHC_cilia_RPParams.tc= 0.0005; % 0.0003 filter time simulates viscocity -IHC_cilia_RPParams.C= 0.05; % 0.1 scalar (C_cilia ) -IHC_cilia_RPParams.u0= 5e-9; -IHC_cilia_RPParams.s0= 30e-9; -IHC_cilia_RPParams.u1= 1e-9; -IHC_cilia_RPParams.s1= 1e-9; - -IHC_cilia_RPParams.Gmax= 5e-9; % 2.5e-9 maximum conductance (Siemens) -IHC_cilia_RPParams.Ga= 1e-9; % 4.3e-9 fixed apical membrane conductance - -% #5 IHC_RP -IHC_cilia_RPParams.Cab= 4e-012; % IHC capacitance (F) -IHC_cilia_RPParams.Cab= 1e-012; % IHC capacitance (F) -IHC_cilia_RPParams.Et= 0.100; % endocochlear potential (V) - -IHC_cilia_RPParams.Gk= 2e-008; % 1e-8 potassium conductance (S) -IHC_cilia_RPParams.Ek= -0.08; % -0.084 K equilibrium potential -IHC_cilia_RPParams.Rpc= 0.04; % combined resistances - - -%% #5 IHCpreSynapse -IHCpreSynapseParams=[]; -IHCpreSynapseParams.GmaxCa= 14e-9;% maximum calcium conductance -IHCpreSynapseParams.GmaxCa= 12e-9;% maximum calcium conductance -IHCpreSynapseParams.ECa= 0.066; % calcium equilibrium potential -IHCpreSynapseParams.beta= 400; % determine Ca channel opening -IHCpreSynapseParams.gamma= 100; % determine Ca channel opening -IHCpreSynapseParams.tauM= 0.00005; % membrane time constant ?0.1ms -IHCpreSynapseParams.power= 3; -% reminder: changing z has a strong effect on HF thresholds (like Et) -IHCpreSynapseParams.z= 2e42; % scalar Ca -> vesicle release rate - -LSRtauCa=35e-6; HSRtauCa=85e-6; % seconds -% LSRtauCa=35e-6; HSRtauCa=70e-6; % seconds -IHCpreSynapseParams.tauCa= [LSRtauCa HSRtauCa]; %LSR and HSR fiber - -%% #6 AN_IHCsynapse -% c=kym/(y(l+r)+kl) (spontaneous rate) -% c=(approx) ym/l (saturated rate) -AN_IHCsynapseParams=[]; % clear the structure first -AN_IHCsynapseParams.M= 12; % maximum vesicles at synapse -AN_IHCsynapseParams.y= 4; % depleted vesicle replacement rate -AN_IHCsynapseParams.y= 6; % depleted vesicle replacement rate - -AN_IHCsynapseParams.x= 30; % replenishment from re-uptake store -AN_IHCsynapseParams.x= 60; % replenishment from re-uptake store - -% reduce l to increase saturated rate -AN_IHCsynapseParams.l= 100; % *loss rate of vesicles from the cleft -AN_IHCsynapseParams.l= 250; % *loss rate of vesicles from the cleft - -AN_IHCsynapseParams.r= 500; % *reuptake rate from cleft into cell -% AN_IHCsynapseParams.r= 300; % *reuptake rate from cleft into cell - -AN_IHCsynapseParams.refractory_period= 0.00075; -% number of AN fibers at each BF (used only for spike generation) -AN_IHCsynapseParams.numFibers= 100; -AN_IHCsynapseParams.TWdelay=0.004; % ?delay before stimulus first spike - -AN_IHCsynapseParams.ANspeedUpFactor=5; % longer epochs for computing spikes. - -%% #7 MacGregorMulti (first order brainstem neurons) -MacGregorMultiParams=[]; -MacGregorMultiType='chopper'; % MacGregorMultiType='primary-like'; %choose -switch MacGregorMultiType - case 'primary-like' - MacGregorMultiParams.nNeuronsPerBF= 10; % N neurons per BF - MacGregorMultiParams.type = 'primary-like cell'; - MacGregorMultiParams.fibersPerNeuron=4; % N input fibers - MacGregorMultiParams.dendriteLPfreq=200; % dendritic filter - MacGregorMultiParams.currentPerSpike=0.11e-6; % (A) per spike - MacGregorMultiParams.Cap=4.55e-9; % cell capacitance (Siemens) - MacGregorMultiParams.tauM=5e-4; % membrane time constant (s) - MacGregorMultiParams.Ek=-0.01; % K+ eq. potential (V) - MacGregorMultiParams.dGkSpike=3.64e-5; % K+ cond.shift on spike,S - MacGregorMultiParams.tauGk= 0.0012; % K+ conductance tau (s) - MacGregorMultiParams.Th0= 0.01; % equilibrium threshold (V) - MacGregorMultiParams.c= 0.01; % threshold shift on spike, (V) - MacGregorMultiParams.tauTh= 0.015; % variable threshold tau - MacGregorMultiParams.Er=-0.06; % resting potential (V) - MacGregorMultiParams.Eb=0.06; % spike height (V) - - case 'chopper' - MacGregorMultiParams.nNeuronsPerBF= 10; % N neurons per BF - MacGregorMultiParams.type = 'chopper cell'; - MacGregorMultiParams.fibersPerNeuron=10; % N input fibers -% MacGregorMultiParams.fibersPerNeuron=6; % N input fibers - - MacGregorMultiParams.dendriteLPfreq=50; % dendritic filter - MacGregorMultiParams.currentPerSpike=35e-9; % *per spike - MacGregorMultiParams.currentPerSpike=30e-9; % *per spike - - MacGregorMultiParams.Cap=1.67e-8; % ??cell capacitance (Siemens) - MacGregorMultiParams.tauM=0.002; % membrane time constant (s) - MacGregorMultiParams.Ek=-0.01; % K+ eq. potential (V) - MacGregorMultiParams.dGkSpike=1.33e-4; % K+ cond.shift on spike,S - MacGregorMultiParams.tauGk= 0.0005;% K+ conductance tau (s) - MacGregorMultiParams.Th0= 0.01; % equilibrium threshold (V) - MacGregorMultiParams.c= 0; % threshold shift on spike, (V) - MacGregorMultiParams.tauTh= 0.02; % variable threshold tau - MacGregorMultiParams.Er=-0.06; % resting potential (V) - MacGregorMultiParams.Eb=0.06; % spike height (V) - MacGregorMultiParams.PSTHbinWidth= 1e-4; -end - -%% #8 MacGregor (second-order neuron). Only one per channel -MacGregorParams=[]; % clear the structure first -MacGregorParams.type = 'chopper cell'; -MacGregorParams.fibersPerNeuron=10; % N input fibers -MacGregorParams.dendriteLPfreq=100; % dendritic filter -MacGregorParams.currentPerSpike=120e-9;% *(A) per spike -MacGregorParams.currentPerSpike=30e-9;% *(A) per spike - -MacGregorParams.Cap=16.7e-9; % cell capacitance (Siemens) -MacGregorParams.tauM=0.002; % membrane time constant (s) -MacGregorParams.Ek=-0.01; % K+ eq. potential (V) -MacGregorParams.dGkSpike=1.33e-4; % K+ cond.shift on spike,S -MacGregorParams.tauGk= 0.0005; % K+ conductance tau (s) -MacGregorParams.Th0= 0.01; % equilibrium threshold (V) -MacGregorParams.c= 0; % threshold shift on spike, (V) -MacGregorParams.tauTh= 0.02; % variable threshold tau -MacGregorParams.Er=-0.06; % resting potential (V) -MacGregorParams.Eb=0.06; % spike height (V) -MacGregorParams.debugging=0; % (special) -% wideband accepts input from all channels (of same fiber type) -% use wideband to create inhibitory units -MacGregorParams.wideband=0; % special for wideband units -% MacGregorParams.saveAllData=0; - -%% #9 filteredSACF -minPitch= 300; maxPitch= 3000; numPitches=60; % specify lags -pitches=100*log10(logspace(minPitch/100, maxPitch/100, numPitches)); -filteredSACFParams.lags=1./pitches; % autocorrelation lags vector -filteredSACFParams.acfTau= .003; % time constant of running ACF -filteredSACFParams.lambda= 0.12; % slower filter to smooth ACF -filteredSACFParams.plotFilteredSACF=1; % 0 plots unfiltered ACFs -filteredSACFParams.plotACFs=0; % special plot (see code) -% filteredSACFParams.usePressnitzer=0; % attenuates ACF at long lags -filteredSACFParams.lagsProcedure= 'useAllLags'; -% filteredSACFParams.lagsProcedure= 'useBernsteinLagWeights'; -% filteredSACFParams.lagsProcedure= 'omitShortLags'; -filteredSACFParams.criterionForOmittingLags=3; - -% checks -if AN_IHCsynapseParams.numFibers<MacGregorMultiParams.fibersPerNeuron - error('MacGregorMulti: too few input fibers for input to MacG unit') -end - - -%% now accept last minute parameter changes required by the calling program -% paramChanges -if nargin>3 && ~isempty(paramChanges) - nChanges=length(paramChanges); - for idx=1:nChanges - eval(paramChanges{idx}) - end -end - - -%% write all parameters to the command window -% showParams is currently set at the top of htis function -if showParams - fprintf('\n %%%%%%%%\n') - fprintf('\n%s\n', method.parameterSource) - fprintf('\n') - nm=UTIL_paramsList(whos); - for i=1:length(nm) - % eval(['UTIL_showStruct(' nm{i} ', ''' nm{i} ''')']) - if ~strcmp(nm(i), 'method') - eval(['UTIL_showStructureSummary(' nm{i} ', ''' nm{i} ''', 10)']) - end - end - - % highlight parameter changes made locally - if nargin>3 && ~isempty(paramChanges) - fprintf('\n Local parameter changes:\n') - for i=1:length(paramChanges) - disp(paramChanges{i}) - end - end -end - -% for backward compatibility -experiment.comparisonData=[];
--- a/parameterStore/MAPparamsNormalTest.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,340 +0,0 @@ -function method=MAPparamsNormalTest ... - (BFlist, sampleRate, showParams) -% MAPparams<> establishes a complete set of MAP parameters -% Parameter file names must be of the form <MAPparams> <name> -% -% input arguments -% BFlist (optional) specifies the desired list of channel BFs -% otherwise defaults set below -% sampleRate (optional), default is 50000. -% showParams (optional) =1 prints out the complete set of parameters -% output argument -% method passes a miscelleny of values - -global inputStimulusParams OMEParams DRNLParams -global IHC_VResp_VivoParams IHCpreSynapseParams AN_IHCsynapseParams -global MacGregorParams MacGregorMultiParams filteredSACFParams -global experiment % used by calls from multiThreshold only -global IHC_cilia_RPParams - -currentFile=mfilename; % i.e. the name of this mfile -method.parameterSource=currentFile(10:end); % for the record - -efferentDelay=0.010; -method.segmentDuration=efferentDelay; - -if nargin<3, showParams=0; end -if nargin<2, sampleRate=50000; end -if nargin<1 || BFlist(1)<0 % if BFlist= -1, set BFlist to default - lowestBF=250; highestBF= 8000; numChannels=21; - % 21 chs (250-8k)includes BFs at 250 500 1000 2000 4000 8000 - BFlist=round(logspace(log10(lowestBF),log10(highestBF),numChannels)); -end -% BFlist=1000; - -% preserve for backward campatibility -method.nonlinCF=BFlist; -method.dt=1/sampleRate; - -%%%%%%%%%%%%%%%%%%%%%%%%%%%% -% set model parameters -%%%%%%%%%%%%%%%%%%%%%%%%%%%% - -%% #1 inputStimulus -inputStimulusParams=[]; -inputStimulusParams.sampleRate= sampleRate; - -%% #2 outerMiddleEar -OMEParams=[]; % clear the structure first -% outer ear resonances band pass filter [gain lp order hp] -OMEParams.externalResonanceFilters= [ 10 1 1000 4000]; - -% highpass stapes filter -% Huber gives 2e-9 m at 80 dB and 1 kHz (2e-13 at 0 dB SPL) -OMEParams.OMEstapesLPcutoff= 1000; -OMEParams.stapesScalar= 45e-9; - -% Acoustic reflex: maximum attenuation should be around 25 dB Price (1966) -% i.e. a minimum ratio of 0.056. -% 'spikes' model: AR based on brainstem spiking activity (LSR) -OMEParams.rateToAttenuationFactor=0.006; % * N(all ICspikes) -% OMEParams.rateToAttenuationFactor=0; % * N(all ICspikes) - -% 'probability model': Ar based on AN firing probabilities (LSR) -OMEParams.rateToAttenuationFactorProb=0.01;% * N(all ANrates) -% OMEParams.rateToAttenuationFactorProb=0;% * N(all ANrates) - -% asymptote should be around 100-200 ms -OMEParams.ARtau=.05; % AR smoothing function -% delay must be longer than the segment length -OMEParams.ARdelay=efferentDelay; %Moss gives 8.5 ms latency -OMEParams.ARrateThreshold=0; - -%% #3 DRNL -DRNLParams=[]; % clear the structure first -DRNLParams.BFlist=BFlist; - -% DRNL nonlinear path -DRNLParams.a=5e4; % DRNL.a=0 means no OHCs (no nonlinear path) -DRNLParams.a=0e4; % DRNL.a=0 means no OHCs (no nonlinear path) - -DRNLParams.b=8e-6; % *compression threshold raised compression -% DRNLParams.b=12e-6; % *compression threshold raised compression -% DRNLParams.b=1; % b=1 means no compression - -DRNLParams.c=0.2; % compression exponent -% nonlinear filters -DRNLParams.nonlinCFs=BFlist; -DRNLParams.nonlinOrder= 3; % order of nonlinear gammatone filters -p=0.2895; q=170; % human (% p=0.14; q=366; % cat) -DRNLParams.nlBWs= p * BFlist + q; -DRNLParams.p=p; DRNLParams.q=q; % save p and q for printing only - -% DRNL linear path: -DRNLParams.g=1000; % linear path gain factor -% linCF is not necessarily the same as nonlinCF -minLinCF=153.13; coeffLinCF=0.7341; % linCF>nonlinBF for BF < 1 kHz -DRNLParams.linCFs=minLinCF+coeffLinCF*BFlist; -DRNLParams.linOrder= 3; % order of linear gammatone filters -minLinBW=100; coeffLinBW=0.6531; -DRNLParams.linBWs=minLinBW + coeffLinBW*BFlist; % bandwidths of linear filters - -% DRNL MOC efferents -DRNLParams.MOCdelay = efferentDelay; % must be < segment length! - -% 'spikes' model: MOC based on brainstem spiking activity (HSR) -DRNLParams.rateToAttenuationFactor = .01; % strength of MOC -% DRNLParams.rateToAttenuationFactor = 0; % strength of MOC -% 'probability' model: MOC based on AN spiking activity (HSR) -DRNLParams.rateToAttenuationFactorProb = .005; % strength of MOC -% DRNLParams.rateToAttenuationFactorProb = .0; % strength of MOC -DRNLParams.MOCrateThresholdProb =70; % spikes/s probability only - -DRNLParams.MOCtau =.1; % smoothing for MOC - - -%% #4 IHC_cilia_RPParams - -IHC_cilia_RPParams.tc= 0.0003; % 0.0003 filter time simulates viscocity -% IHC_cilia_RPParams.tc= 0.0005; % 0.0003 filter time simulates viscocity -IHC_cilia_RPParams.C= 0.01; % 0.1 scalar (C_cilia ) -IHC_cilia_RPParams.u0= 5e-10; -IHC_cilia_RPParams.s0= 10e-10; -IHC_cilia_RPParams.u1= 5e-10; -IHC_cilia_RPParams.s1= 5e-10; - -IHC_cilia_RPParams.Gmax= 4e-9; % 2.5e-9 maximum conductance (Siemens) -IHC_cilia_RPParams.Ga= 1.5e-9; % 4.3e-9 fixed apical membrane conductance - -% #5 IHC_RP -IHC_cilia_RPParams.Cab= 4e-012; % IHC capacitance (F) -IHC_cilia_RPParams.Cab= 2e-012; % IHC capacitance (F) -IHC_cilia_RPParams.Et= 0.100; % endocochlear potential (V) - -IHC_cilia_RPParams.Gk= 2e-008; % 1e-8 potassium conductance (S) -IHC_cilia_RPParams.Ek= -0.08; % -0.084 K equilibrium potential -IHC_cilia_RPParams.Rpc= 0.04; % combined resistances - - -%% #5 IHCpreSynapse -IHCpreSynapseParams=[]; -IHCpreSynapseParams.GmaxCa= 14e-9;% maximum calcium conductance -IHCpreSynapseParams.GmaxCa= 12e-9;% maximum calcium conductance -IHCpreSynapseParams.ECa= 0.066; % calcium equilibrium potential -IHCpreSynapseParams.beta= 400; % determine Ca channel opening -IHCpreSynapseParams.gamma= 100; % determine Ca channel opening -IHCpreSynapseParams.tauM= 0.00005; % membrane time constant ?0.1ms -IHCpreSynapseParams.power= 3; -% reminder: changing z has a strong effect on HF thresholds (like Et) -IHCpreSynapseParams.z= 1e42; % scalar Ca -> vesicle release rate - -LSRtauCa=35e-6; HSRtauCa=85e-6; % seconds -% LSRtauCa=35e-6; HSRtauCa=70e-6; % seconds -IHCpreSynapseParams.tauCa= [LSRtauCa HSRtauCa]; %LSR and HSR fiber - -%% #6 AN_IHCsynapse -% c=kym/(y(l+r)+kl) (spontaneous rate) -% c=(approx) ym/l (saturated rate) -AN_IHCsynapseParams=[]; % clear the structure first -AN_IHCsynapseParams.M= 12; % maximum vesicles at synapse -AN_IHCsynapseParams.y= 4; % depleted vesicle replacement rate -% AN_IHCsynapseParams.y= 6; % depleted vesicle replacement rate - -AN_IHCsynapseParams.x= 10; % replenishment from re-uptake store -AN_IHCsynapseParams.x= 60; % replenishment from re-uptake store - -% reduce l to increase saturated rate -AN_IHCsynapseParams.l= 150; % *loss rate of vesicles from the cleft -% AN_IHCsynapseParams.l= 250; % *loss rate of vesicles from the cleft - -AN_IHCsynapseParams.r= 500; % *reuptake rate from cleft into cell -% AN_IHCsynapseParams.r= 300; % *reuptake rate from cleft into cell - -AN_IHCsynapseParams.refractory_period= 0.00075; -% number of AN fibers at each BF (used only for spike generation) -AN_IHCsynapseParams.numFibers= 100; -AN_IHCsynapseParams.TWdelay=0.004; % ?delay before stimulus first spike - -AN_IHCsynapseParams.ANspeedUpFactor=5; % longer epochs for computing spikes. - -%% #7 MacGregorMulti (first order brainstem neurons) -MacGregorMultiParams=[]; -MacGregorMultiType='chopper'; % MacGregorMultiType='primary-like'; %choose -switch MacGregorMultiType - case 'primary-like' - MacGregorMultiParams.nNeuronsPerBF= 10; % N neurons per BF - MacGregorMultiParams.type = 'primary-like cell'; - MacGregorMultiParams.fibersPerNeuron=4; % N input fibers - MacGregorMultiParams.dendriteLPfreq=200; % dendritic filter - MacGregorMultiParams.currentPerSpike=0.11e-6; % (A) per spike - MacGregorMultiParams.Cap=4.55e-9; % cell capacitance (Siemens) - MacGregorMultiParams.tauM=5e-4; % membrane time constant (s) - MacGregorMultiParams.Ek=-0.01; % K+ eq. potential (V) - MacGregorMultiParams.dGkSpike=3.64e-5; % K+ cond.shift on spike,S - MacGregorMultiParams.tauGk= 0.0012; % K+ conductance tau (s) - MacGregorMultiParams.Th0= 0.01; % equilibrium threshold (V) - MacGregorMultiParams.c= 0.01; % threshold shift on spike, (V) - MacGregorMultiParams.tauTh= 0.015; % variable threshold tau - MacGregorMultiParams.Er=-0.06; % resting potential (V) - MacGregorMultiParams.Eb=0.06; % spike height (V) - - case 'chopper' - MacGregorMultiParams.nNeuronsPerBF= 10; % N neurons per BF - MacGregorMultiParams.type = 'chopper cell'; - MacGregorMultiParams.fibersPerNeuron=10; % N input fibers -% MacGregorMultiParams.fibersPerNeuron=6; % N input fibers - - MacGregorMultiParams.dendriteLPfreq=50; % dendritic filter - MacGregorMultiParams.currentPerSpike=35e-9; % *per spike - MacGregorMultiParams.currentPerSpike=30e-9; % *per spike - - MacGregorMultiParams.Cap=1.67e-8; % ??cell capacitance (Siemens) - MacGregorMultiParams.tauM=0.002; % membrane time constant (s) - MacGregorMultiParams.Ek=-0.01; % K+ eq. potential (V) - MacGregorMultiParams.dGkSpike=1.33e-4; % K+ cond.shift on spike,S - MacGregorMultiParams.tauGk= 0.0005;% K+ conductance tau (s) - MacGregorMultiParams.Th0= 0.01; % equilibrium threshold (V) - MacGregorMultiParams.c= 0; % threshold shift on spike, (V) - MacGregorMultiParams.tauTh= 0.02; % variable threshold tau - MacGregorMultiParams.Er=-0.06; % resting potential (V) - MacGregorMultiParams.Eb=0.06; % spike height (V) - MacGregorMultiParams.PSTHbinWidth= 1e-4; -end - -%% #8 MacGregor (second-order neuron). Only one per channel -MacGregorParams=[]; % clear the structure first -MacGregorParams.type = 'chopper cell'; -MacGregorParams.fibersPerNeuron=10; % N input fibers -MacGregorParams.dendriteLPfreq=100; % dendritic filter -MacGregorParams.currentPerSpike=120e-9;% *(A) per spike -MacGregorParams.currentPerSpike=30e-9;% *(A) per spike - -MacGregorParams.Cap=16.7e-9; % cell capacitance (Siemens) -MacGregorParams.tauM=0.002; % membrane time constant (s) -MacGregorParams.Ek=-0.01; % K+ eq. potential (V) -MacGregorParams.dGkSpike=1.33e-4; % K+ cond.shift on spike,S -MacGregorParams.tauGk= 0.0005; % K+ conductance tau (s) -MacGregorParams.Th0= 0.01; % equilibrium threshold (V) -MacGregorParams.c= 0; % threshold shift on spike, (V) -MacGregorParams.tauTh= 0.02; % variable threshold tau -MacGregorParams.Er=-0.06; % resting potential (V) -MacGregorParams.Eb=0.06; % spike height (V) -MacGregorParams.debugging=0; % (special) -% wideband accepts input from all channels (of same fiber type) -% use wideband to create inhibitory units -MacGregorParams.wideband=0; % special for wideband units -% MacGregorParams.saveAllData=0; - -%% #9 filteredSACF -minPitch= 300; maxPitch= 3000; numPitches=60; % specify lags -pitches=100*log10(logspace(minPitch/100, maxPitch/100, numPitches)); -filteredSACFParams.lags=1./pitches; % autocorrelation lags vector -filteredSACFParams.acfTau= .003; % time constant of running ACF -filteredSACFParams.lambda= 0.12; % slower filter to smooth ACF -filteredSACFParams.plotFilteredSACF=1; % 0 plots unfiltered ACFs -filteredSACFParams.plotACFs=0; % special plot (see code) -% filteredSACFParams.usePressnitzer=0; % attenuates ACF at long lags -filteredSACFParams.lagsProcedure= 'useAllLags'; -% filteredSACFParams.lagsProcedure= 'useBernsteinLagWeights'; -% filteredSACFParams.lagsProcedure= 'omitShortLags'; -filteredSACFParams.criterionForOmittingLags=3; - -% checks -if AN_IHCsynapseParams.numFibers<MacGregorMultiParams.fibersPerNeuron - error('MacGregorMulti: too few input fibers for input to MacG unit') -end - - -%% write all parameters to the command window -% showParams is currently set at the top of htis function -if showParams - fprintf('\n %%%%%%%%\n') - fprintf('\n%s\n', method.parameterSource) - fprintf('\n') - nm=UTIL_paramsList(whos); - for i=1:length(nm) - % eval(['UTIL_showStruct(' nm{i} ', ''' nm{i} ''')']) - if ~strcmp(nm(i), 'method') - eval(['UTIL_showStructureSummary(' nm{i} ', ''' nm{i} ''', 10)']) - end - end -end - - - -% ********************************************************************** comparison data -% store individual data here for display on the multiThreshold GUI (if used) -% the final value in each vector is an identifier (BF or duration)) -if isstruct(experiment) - switch experiment.paradigm - case {'IFMC','IFMC_8ms'} - % based on MPa - comparisonData=[ - 66 51 49 48 46 45 54 250; - 60 54 46 42 39 49 65 500; - 64 51 38 32 33 59 75 1000; - 59 51 36 30 41 81 93 2000; - 71 63 53 44 36 76 95 4000; - 70 64 43 35 35 66 88 6000; - 110 110 110 110 110 110 110 8000; - ]; - if length(BFlist)==1 && ~isempty(comparisonData) - availableFrequencies=comparisonData(:,end)'; - findRow= find(BFlist==availableFrequencies); - if ~isempty (findRow) - experiment.comparisonData=comparisonData(findRow,:); - end - end - - case {'TMC','TMC_8ms'} - % based on MPa - comparisonData=[ - 48 58 63 68 75 80 85 92 99 250; - 33 39 40 49 52 61 64 77 79 500; - 39 42 50 81 83 92 96 97 110 1000; - 24 26 32 37 46 51 59 71 78 2000; - 65 68 77 85 91 93 110 110 110 4000; - 20 19 26 44 80 95 96 110 110 6000; - ]; - if length(BFlist)==1 && ~isempty(comparisonData) - availableFrequencies=comparisonData(:,end)'; - findRow= find(BFlist==availableFrequencies); - if ~isempty (findRow) - experiment.comparisonData=comparisonData(findRow,:); - end - end - - case { 'absThreshold', 'absThreshold_8'} - % MPa thresholds - experiment.comparisonData=[ - 32 26 16 18 22 22 0.008; - 16 13 6 9 15 11 0.500 - ]; - - - otherwise - experiment.comparisonData=[]; - end -end - -
--- a/parameterStore/MAPparamsOHC.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,356 +0,0 @@ -function method=MAPparamsOHC ... - (BFlist, sampleRate, showParams, paramChanges) -% MAPparams<> establishes a complete set of MAP parameters -% Parameter file names must be of the form <MAPparams> <name> -% -% input arguments -% BFlist (optional) specifies the desired list of channel BFs -% otherwise defaults set below -% sampleRate (optional), default is 50000. -% showParams (optional) =1 prints out the complete set of parameters -% output argument -% method passes a miscelleny of values - -global inputStimulusParams OMEParams DRNLParams -global IHC_VResp_VivoParams IHCpreSynapseParams AN_IHCsynapseParams -global MacGregorParams MacGregorMultiParams filteredSACFParams -global experiment % used by calls from multiThreshold only -global IHC_cilia_RPParams - -currentFile=mfilename; % i.e. the name of this mfile -method.parameterSource=currentFile(10:end); % for the record - -efferentDelay=0.010; -method.segmentDuration=efferentDelay; - -if nargin<3, showParams=0; end -if nargin<2, sampleRate=50000; end -if nargin<1 || BFlist(1)<0 % if BFlist= -1, set BFlist to default - lowestBF=250; highestBF= 8000; numChannels=21; - % 21 chs (250-8k)includes BFs at 250 500 1000 2000 4000 8000 - BFlist=round(logspace(log10(lowestBF),log10(highestBF),numChannels)); -end -% BFlist=1000; - -% preserve for backward campatibility -method.nonlinCF=BFlist; -method.dt=1/sampleRate; - -%%%%%%%%%%%%%%%%%%%%%%%%%%%% -% set model parameters -%%%%%%%%%%%%%%%%%%%%%%%%%%%% - -%% #1 inputStimulus -inputStimulusParams=[]; -inputStimulusParams.sampleRate= sampleRate; - -%% #2 outerMiddleEar -OMEParams=[]; % clear the structure first -% outer ear resonances band pass filter [gain lp order hp] -OMEParams.externalResonanceFilters= [ 10 1 1000 4000]; - -% highpass stapes filter -% Huber gives 2e-9 m at 80 dB and 1 kHz (2e-13 at 0 dB SPL) -OMEParams.OMEstapesLPcutoff= 1000; -OMEParams.stapesScalar= 45e-9; - -% Acoustic reflex: maximum attenuation should be around 25 dB Price (1966) -% i.e. a minimum ratio of 0.056. -% 'spikes' model: AR based on brainstem spiking activity (LSR) -OMEParams.rateToAttenuationFactor=0.006; % * N(all ICspikes) -% OMEParams.rateToAttenuationFactor=0; % * N(all ICspikes) - -% 'probability model': Ar based on AN firing probabilities (LSR) -OMEParams.rateToAttenuationFactorProb=0.01;% * N(all ANrates) -% OMEParams.rateToAttenuationFactorProb=0;% * N(all ANrates) - -% asymptote should be around 100-200 ms -OMEParams.ARtau=.05; % AR smoothing function -% delay must be longer than the segment length -OMEParams.ARdelay=efferentDelay; %Moss gives 8.5 ms latency -OMEParams.ARrateThreshold=0; - -%% #3 DRNL -DRNLParams=[]; % clear the structure first -DRNLParams.BFlist=BFlist; - -% DRNL nonlinear path -DRNLParams.a=0; % DRNL.a=0 means no OHCs (no nonlinear path) - -DRNLParams.b=8e-6; % *compression threshold raised compression -% DRNLParams.b=1; % b=1 means no compression - -DRNLParams.c=0.2; % compression exponent -% nonlinear filters -DRNLParams.nonlinCFs=BFlist; -DRNLParams.nonlinOrder= 3; % order of nonlinear gammatone filters -p=0.2895; q=170; % human (% p=0.14; q=366; % cat) -DRNLParams.nlBWs= p * BFlist + q; -DRNLParams.p=p; DRNLParams.q=q; % save p and q for printing only - -% DRNL linear path: -DRNLParams.g=100; % linear path gain factor -% linCF is not necessarily the same as nonlinCF -minLinCF=153.13; coeffLinCF=0.7341; % linCF>nonlinBF for BF < 1 kHz -DRNLParams.linCFs=minLinCF+coeffLinCF*BFlist; -DRNLParams.linOrder= 3; % order of linear gammatone filters -minLinBW=100; coeffLinBW=0.6531; -DRNLParams.linBWs=minLinBW + coeffLinBW*BFlist; % bandwidths of linear filters - -% DRNL MOC efferents -DRNLParams.MOCdelay = efferentDelay; % must be < segment length! - -% 'spikes' model: MOC based on brainstem spiking activity (HSR) -DRNLParams.rateToAttenuationFactor = .01; % strength of MOC -% DRNLParams.rateToAttenuationFactor = 0; % strength of MOC -% 'probability' model: MOC based on AN spiking activity (HSR) -DRNLParams.rateToAttenuationFactorProb = .0055; % strength of MOC -% DRNLParams.rateToAttenuationFactorProb = .0; % strength of MOC -DRNLParams.MOCrateThresholdProb =70; % spikes/s probability only - -DRNLParams.MOCtau =.1; % smoothing for MOC - - -%% #4 IHC_cilia_RPParams - -IHC_cilia_RPParams.tc= 0.0003; % 0.0003 filter time simulates viscocity -% IHC_cilia_RPParams.tc= 0.0005; % 0.0003 filter time simulates viscocity -IHC_cilia_RPParams.C= 0.05; % 0.1 scalar (C_cilia ) -IHC_cilia_RPParams.u0= 5e-9; -IHC_cilia_RPParams.s0= 30e-9; -IHC_cilia_RPParams.u1= 1e-9; -IHC_cilia_RPParams.s1= 1e-9; - -IHC_cilia_RPParams.Gmax= 5e-9; % 2.5e-9 maximum conductance (Siemens) -IHC_cilia_RPParams.Ga= 1e-9; % 4.3e-9 fixed apical membrane conductance - -% #5 IHC_RP -IHC_cilia_RPParams.Cab= 4e-012; % IHC capacitance (F) -IHC_cilia_RPParams.Cab= 1e-012; % IHC capacitance (F) -IHC_cilia_RPParams.Et= 0.1; % endocochlear potential (V) - -IHC_cilia_RPParams.Gk= 2e-008; % 1e-8 potassium conductance (S) -IHC_cilia_RPParams.Ek= -0.08; % -0.084 K equilibrium potential -IHC_cilia_RPParams.Rpc= 0.04; % combined resistances - - -%% #5 IHCpreSynapse -IHCpreSynapseParams=[]; -IHCpreSynapseParams.GmaxCa= 14e-9;% maximum calcium conductance -IHCpreSynapseParams.GmaxCa= 12e-9;% maximum calcium conductance -IHCpreSynapseParams.ECa= 0.066; % calcium equilibrium potential -IHCpreSynapseParams.beta= 400; % determine Ca channel opening -IHCpreSynapseParams.gamma= 100; % determine Ca channel opening -IHCpreSynapseParams.tauM= 0.00005; % membrane time constant ?0.1ms -IHCpreSynapseParams.power= 3; -% reminder: changing z has a strong effect on HF thresholds (like Et) -IHCpreSynapseParams.z= 2e42; % scalar Ca -> vesicle release rate - -LSRtauCa=35e-6; HSRtauCa=85e-6; % seconds -% LSRtauCa=35e-6; HSRtauCa=70e-6; % seconds -IHCpreSynapseParams.tauCa= [LSRtauCa HSRtauCa]; %LSR and HSR fiber - -%% #6 AN_IHCsynapse -% c=kym/(y(l+r)+kl) (spontaneous rate) -% c=(approx) ym/l (saturated rate) -AN_IHCsynapseParams=[]; % clear the structure first -AN_IHCsynapseParams.M= 12; % maximum vesicles at synapse -AN_IHCsynapseParams.y= 4; % depleted vesicle replacement rate -AN_IHCsynapseParams.y= 6; % depleted vesicle replacement rate - -AN_IHCsynapseParams.x= 30; % replenishment from re-uptake store -AN_IHCsynapseParams.x= 60; % replenishment from re-uptake store - -% reduce l to increase saturated rate -AN_IHCsynapseParams.l= 100; % *loss rate of vesicles from the cleft -AN_IHCsynapseParams.l= 250; % *loss rate of vesicles from the cleft - -AN_IHCsynapseParams.r= 500; % *reuptake rate from cleft into cell -% AN_IHCsynapseParams.r= 300; % *reuptake rate from cleft into cell - -AN_IHCsynapseParams.refractory_period= 0.00075; -% number of AN fibers at each BF (used only for spike generation) -AN_IHCsynapseParams.numFibers= 100; -AN_IHCsynapseParams.TWdelay=0.004; % ?delay before stimulus first spike - -AN_IHCsynapseParams.ANspeedUpFactor=5; % longer epochs for computing spikes. - -%% #7 MacGregorMulti (first order brainstem neurons) -MacGregorMultiParams=[]; -MacGregorMultiType='chopper'; % MacGregorMultiType='primary-like'; %choose -switch MacGregorMultiType - case 'primary-like' - MacGregorMultiParams.nNeuronsPerBF= 10; % N neurons per BF - MacGregorMultiParams.type = 'primary-like cell'; - MacGregorMultiParams.fibersPerNeuron=4; % N input fibers - MacGregorMultiParams.dendriteLPfreq=200; % dendritic filter - MacGregorMultiParams.currentPerSpike=0.11e-6; % (A) per spike - MacGregorMultiParams.Cap=4.55e-9; % cell capacitance (Siemens) - MacGregorMultiParams.tauM=5e-4; % membrane time constant (s) - MacGregorMultiParams.Ek=-0.01; % K+ eq. potential (V) - MacGregorMultiParams.dGkSpike=3.64e-5; % K+ cond.shift on spike,S - MacGregorMultiParams.tauGk= 0.0012; % K+ conductance tau (s) - MacGregorMultiParams.Th0= 0.01; % equilibrium threshold (V) - MacGregorMultiParams.c= 0.01; % threshold shift on spike, (V) - MacGregorMultiParams.tauTh= 0.015; % variable threshold tau - MacGregorMultiParams.Er=-0.06; % resting potential (V) - MacGregorMultiParams.Eb=0.06; % spike height (V) - - case 'chopper' - MacGregorMultiParams.nNeuronsPerBF= 10; % N neurons per BF - MacGregorMultiParams.type = 'chopper cell'; - MacGregorMultiParams.fibersPerNeuron=10; % N input fibers -% MacGregorMultiParams.fibersPerNeuron=6; % N input fibers - - MacGregorMultiParams.dendriteLPfreq=50; % dendritic filter - MacGregorMultiParams.currentPerSpike=35e-9; % *per spike - MacGregorMultiParams.currentPerSpike=30e-9; % *per spike - - MacGregorMultiParams.Cap=1.67e-8; % ??cell capacitance (Siemens) - MacGregorMultiParams.tauM=0.002; % membrane time constant (s) - MacGregorMultiParams.Ek=-0.01; % K+ eq. potential (V) - MacGregorMultiParams.dGkSpike=1.33e-4; % K+ cond.shift on spike,S - MacGregorMultiParams.tauGk= 0.0005;% K+ conductance tau (s) - MacGregorMultiParams.Th0= 0.01; % equilibrium threshold (V) - MacGregorMultiParams.c= 0; % threshold shift on spike, (V) - MacGregorMultiParams.tauTh= 0.02; % variable threshold tau - MacGregorMultiParams.Er=-0.06; % resting potential (V) - MacGregorMultiParams.Eb=0.06; % spike height (V) - MacGregorMultiParams.PSTHbinWidth= 1e-4; -end - -%% #8 MacGregor (second-order neuron). Only one per channel -MacGregorParams=[]; % clear the structure first -MacGregorParams.type = 'chopper cell'; -MacGregorParams.fibersPerNeuron=10; % N input fibers -MacGregorParams.dendriteLPfreq=100; % dendritic filter -MacGregorParams.currentPerSpike=120e-9;% *(A) per spike -MacGregorParams.currentPerSpike=30e-9;% *(A) per spike - -MacGregorParams.Cap=16.7e-9; % cell capacitance (Siemens) -MacGregorParams.tauM=0.002; % membrane time constant (s) -MacGregorParams.Ek=-0.01; % K+ eq. potential (V) -MacGregorParams.dGkSpike=1.33e-4; % K+ cond.shift on spike,S -MacGregorParams.tauGk= 0.0005; % K+ conductance tau (s) -MacGregorParams.Th0= 0.01; % equilibrium threshold (V) -MacGregorParams.c= 0; % threshold shift on spike, (V) -MacGregorParams.tauTh= 0.02; % variable threshold tau -MacGregorParams.Er=-0.06; % resting potential (V) -MacGregorParams.Eb=0.06; % spike height (V) -MacGregorParams.debugging=0; % (special) -% wideband accepts input from all channels (of same fiber type) -% use wideband to create inhibitory units -MacGregorParams.wideband=0; % special for wideband units -% MacGregorParams.saveAllData=0; - -%% #9 filteredSACF -minPitch= 300; maxPitch= 3000; numPitches=60; % specify lags -pitches=100*log10(logspace(minPitch/100, maxPitch/100, numPitches)); -filteredSACFParams.lags=1./pitches; % autocorrelation lags vector -filteredSACFParams.acfTau= .003; % time constant of running ACF -filteredSACFParams.lambda= 0.12; % slower filter to smooth ACF -filteredSACFParams.plotFilteredSACF=1; % 0 plots unfiltered ACFs -filteredSACFParams.plotACFs=0; % special plot (see code) -% filteredSACFParams.usePressnitzer=0; % attenuates ACF at long lags -filteredSACFParams.lagsProcedure= 'useAllLags'; -% filteredSACFParams.lagsProcedure= 'useBernsteinLagWeights'; -% filteredSACFParams.lagsProcedure= 'omitShortLags'; -filteredSACFParams.criterionForOmittingLags=3; - -% checks -if AN_IHCsynapseParams.numFibers<MacGregorMultiParams.fibersPerNeuron - error('MacGregorMulti: too few input fibers for input to MacG unit') -end - - -%% now accept last minute parameter changes required by the calling program -% paramChanges -if nargin>3 && ~isempty(paramChanges) - nChanges=length(paramChanges); - for idx=1:nChanges - eval(paramChanges{idx}) - end -end - - -%% write all parameters to the command window -% showParams is currently set at the top of htis function -if showParams - fprintf('\n %%%%%%%%\n') - fprintf('\n%s\n', method.parameterSource) - fprintf('\n') - nm=UTIL_paramsList(whos); - for i=1:length(nm) - % eval(['UTIL_showStruct(' nm{i} ', ''' nm{i} ''')']) - if ~strcmp(nm(i), 'method') - eval(['UTIL_showStructureSummary(' nm{i} ', ''' nm{i} ''', 10)']) - end - end - - % highlight parameter changes made locally - if nargin>3 && ~isempty(paramChanges) - fprintf('\n Local parameter changes:\n') - for i=1:length(paramChanges) - disp(paramChanges{i}) - end - end -end - - - -% ********************************************************************** comparison data -% store individual data here for display on the multiThreshold GUI (if used) -% the final value in each vector is an identifier (BF or duration)) -if isstruct(experiment) - switch experiment.paradigm - case {'IFMC','IFMC_8ms'} - % based on MPa - comparisonData=[ - 66 51 49 48 46 45 54 250; - 60 54 46 42 39 49 65 500; - 64 51 38 32 33 59 75 1000; - 59 51 36 30 41 81 93 2000; - 71 63 53 44 36 76 95 4000; - 70 64 43 35 35 66 88 6000; - 110 110 110 110 110 110 110 8000; - ]; - if length(BFlist)==1 && ~isempty(comparisonData) - availableFrequencies=comparisonData(:,end)'; - findRow= find(BFlist==availableFrequencies); - if ~isempty (findRow) - experiment.comparisonData=comparisonData(findRow,:); - end - end - - case {'TMC','TMC_8ms'} - % based on MPa - comparisonData=[ - 48 58 63 68 75 80 85 92 99 250; - 33 39 40 49 52 61 64 77 79 500; - 39 42 50 81 83 92 96 97 110 1000; - 24 26 32 37 46 51 59 71 78 2000; - 65 68 77 85 91 93 110 110 110 4000; - 20 19 26 44 80 95 96 110 110 6000; - ]; - if length(BFlist)==1 && ~isempty(comparisonData) - availableFrequencies=comparisonData(:,end)'; - findRow= find(BFlist==availableFrequencies); - if ~isempty (findRow) - experiment.comparisonData=comparisonData(findRow,:); - end - end - - case { 'absThreshold', 'absThreshold_8'} - % MPa thresholds - experiment.comparisonData=[ - 32 26 16 18 22 22 0.008; - 16 13 6 9 15 11 0.500 - ]; - - - otherwise - experiment.comparisonData=[]; - end -end - -
--- a/parameterStore/MAPparamsStd.m Mon Jul 11 14:31:29 2011 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,345 +0,0 @@ -function method=MAPparamsStd ... - (BFlist, sampleRate, showParams) -% MAPparams<> establishes a complete set of MAP parameters -% Parameter file names must be of the form <MAPparams> <name> -% -% input arguments -% BFlist (optional) specifies the desired list of channel BFs -% otherwise defaults set below -% sampleRate (optional), default is 50000. -% showParams (optional) =1 prints out the complete set of parameters -% output argument -% method passes a miscelleny of values - -global inputStimulusParams OMEParams DRNLParams -global IHC_VResp_VivoParams IHCpreSynapseParams AN_IHCsynapseParams -global MacGregorParams MacGregorMultiParams filteredSACFParams -global experiment % used by calls from multiThreshold only -global IHC_cilia_RPParams - -currentFile=mfilename; % i.e. the name of this mfile -method.parameterSource=currentFile(10:end); % for the record - -switchOffEfferent=0; -efferentDelay=0.010; -method.segmentDuration=efferentDelay; - -if nargin<3, showParams=0; end -if nargin<2, sampleRate=50000; end -if nargin<1 || BFlist(1)<0 % if BFlist= -1, set BFlist to default - lowestBF=250; highestBF= 8000; numChannels=21; - % 21 chs (250-8k)includes BFs at 250 500 1000 2000 4000 8000 - BFlist=round(logspace(log10(lowestBF),log10(highestBF),numChannels)); -end -% BFlist=1000; - -% preserve for backward campatibility -method.nonlinCF=BFlist; -method.dt=1/sampleRate; - -%%%%%%%%%%%%%%%%%%%%%%%%%%%% -% set model parameters -%%%%%%%%%%%%%%%%%%%%%%%%%%%% - -%% #1 inputStimulus -inputStimulusParams=[]; -inputStimulusParams.sampleRate= sampleRate; - -%% #2 outerMiddleEar -OMEParams=[]; % clear the structure first -% outer ear resonances band pass filter [gain lp order hp] -OMEParams.externalResonanceFilters= [ 10 1 1000 4000]; - -% highpass stapes filter -% Huber gives 2e-9 m at 80 dB and 1 kHz (2e-13 at 0 dB SPL) -OMEParams.OMEstapesLPcutoff= 1000; -OMEParams.stapesScalar= 45e-9; - -% Acoustic reflex: maximum attenuation should be around 25 dB Price (1966) -% i.e. a minimum ratio of 0.056. -if ~switchOffEfferent - % 'spikes' model: AR based on brainstem spiking activity (LSR) - OMEParams.rateToAttenuationFactor=0.003; % * N(all ICspikes) -% OMEParams.rateToAttenuationFactor=0; % * N(all ICspikes) - % 'probability model': Ar based on An firing probabilities (LSR) - OMEParams.rateToAttenuationFactorProb=0.005;% * N(all ANrates) -% OMEParams.rateToAttenuationFactorProb=0;% * N(all ANrates) -else - OMEParams.rateToAttenuationFactor=0; % 0= off - OMEParams.rateToAttenuationFactorProb=0; % 0= off -end -% asymptote should be around 100-200 ms -OMEParams.ARtau=.05; % AR smoothing function -% delay must be longer than the segment length -OMEParams.ARdelay=efferentDelay; %Moss gives 8.5 ms latency -OMEParams.ARrateThreshold=0; - -%% #3 DRNL -DRNLParams=[]; % clear the structure first -DRNLParams.BFlist=BFlist; - -% DRNL nonlinear path -DRNLParams.a=3e4; % nonlinear path gain (below compression threshold) -% DRNLParams.a=3e2; % DRNL.a=0 means no OHCs (no nonlinear path) - -DRNLParams.b=8e-6; % *compression threshold raised compression -% DRNLParams.b=1; % b=1 means no compression - -DRNLParams.c=0.2; % compression exponent -% nonlinear filters -DRNLParams.nonlinCFs=BFlist; -DRNLParams.nonlinOrder= 3; % order of nonlinear gammatone filters -p=0.2895; q=170; % human (% p=0.14; q=366; % cat) -DRNLParams.nlBWs= p * BFlist + q; -DRNLParams.p=p; DRNLParams.q=q; % save p and q for printing only - -% DRNL linear path: -DRNLParams.g=100; % linear path gain factor -% linCF is not necessarily the same as nonlinCF -minLinCF=153.13; coeffLinCF=0.7341; % linCF>nonlinBF for BF < 1 kHz -DRNLParams.linCFs=minLinCF+coeffLinCF*BFlist; -DRNLParams.linOrder= 3; % order of linear gammatone filters -minLinBW=100; coeffLinBW=0.6531; -DRNLParams.linBWs=minLinBW + coeffLinBW*BFlist; % bandwidths of linear filters - -% DRNL MOC efferents -DRNLParams.MOCdelay = efferentDelay; % must be < segment length! -if ~switchOffEfferent - % 'spikes' model: MOC based on brainstem spiking activity (HSR) - DRNLParams.rateToAttenuationFactor = .009; % strength of MOC - DRNLParams.rateToAttenuationFactor = .009; % strength of MOC -% DRNLParams.rateToAttenuationFactor = 0; % strength of MOC - - % 'spikes' model: MOC based on brainstem spiking activity (HSR) - DRNLParams.rateToAttenuationFactorProb = .002; % strength of MOC -else - DRNLParams.rateToAttenuationFactor = 0; % 0 = MOC off (probability) - DRNLParams.rateToAttenuationFactorProb = 0; % 0 = MOC off (spikes) -end -DRNLParams.MOCtau =.03; % smoothing for MOC -DRNLParams.MOCrateThresholdProb =50; % set to AN rate threshold - - -%% #4 IHC_cilia_RPParams - -IHC_cilia_RPParams.tc= 0.0003; % 0.0003 filter time simulates viscocity -% IHC_cilia_RPParams.tc= 0.0005; % 0.0003 filter time simulates viscocity -IHC_cilia_RPParams.C= 0.05; % 0.1 scalar (C_cilia ) -IHC_cilia_RPParams.u0= 5e-9; -IHC_cilia_RPParams.s0= 30e-9; -IHC_cilia_RPParams.u1= 1e-9; -IHC_cilia_RPParams.s1= 1e-9; - -IHC_cilia_RPParams.Gmax= 5e-9; % 2.5e-9 maximum conductance (Siemens) -IHC_cilia_RPParams.Ga= 1e-9; % 4.3e-9 fixed apical membrane conductance - -% #5 IHC_RP -IHC_cilia_RPParams.Cab= 4e-012; % IHC capacitance (F) -IHC_cilia_RPParams.Cab= 1e-012; % IHC capacitance (F) -IHC_cilia_RPParams.Et= 0.100; % endocochlear potential (V) -% IHC_cilia_RPParams.Et= 0.07; % endocochlear potential (V) - -IHC_cilia_RPParams.Gk= 2e-008; % 1e-8 potassium conductance (S) -IHC_cilia_RPParams.Ek= -0.08; % -0.084 K equilibrium potential -IHC_cilia_RPParams.Rpc= 0.04; % combined resistances - - -%% #5 IHCpreSynapse -IHCpreSynapseParams=[]; -IHCpreSynapseParams.GmaxCa= 14e-9;% maximum calcium conductance -IHCpreSynapseParams.GmaxCa= 12e-9;% maximum calcium conductance -IHCpreSynapseParams.ECa= 0.066; % calcium equilibrium potential -IHCpreSynapseParams.beta= 400; % determine Ca channel opening -IHCpreSynapseParams.gamma= 100; % determine Ca channel opening -IHCpreSynapseParams.tauM= 0.00005; % membrane time constant ?0.1ms -IHCpreSynapseParams.power= 3; -% reminder: changing z has a strong effect on HF thresholds (like Et) -IHCpreSynapseParams.z= 2e42; % scalar Ca -> vesicle release rate - -LSRtauCa=50e-6; HSRtauCa=85e-6; % seconds -% LSRtauCa=35e-6; HSRtauCa=70e-6; % seconds -IHCpreSynapseParams.tauCa= [LSRtauCa HSRtauCa]; %LSR and HSR fiber - -%% #6 AN_IHCsynapse -% c=kym/(y(l+r)+kl) (spontaneous rate) -% c=(approx) ym/l (saturated rate) -AN_IHCsynapseParams=[]; % clear the structure first -AN_IHCsynapseParams.M= 12; % maximum vesicles at synapse -AN_IHCsynapseParams.y= 4; % depleted vesicle replacement rate -AN_IHCsynapseParams.y= 6; % depleted vesicle replacement rate - -AN_IHCsynapseParams.x= 30; % replenishment from re-uptake store -AN_IHCsynapseParams.x= 60; % replenishment from re-uptake store - -% reduce l to increase saturated rate -AN_IHCsynapseParams.l= 100; % *loss rate of vesicles from the cleft -AN_IHCsynapseParams.l= 250; % *loss rate of vesicles from the cleft - -AN_IHCsynapseParams.r= 500; % *reuptake rate from cleft into cell -% AN_IHCsynapseParams.r= 300; % *reuptake rate from cleft into cell - -AN_IHCsynapseParams.refractory_period= 0.00075; -% number of AN fibers at each BF (used only for spike generation) -AN_IHCsynapseParams.numFibers= 100; -AN_IHCsynapseParams.TWdelay=0.004; % ?delay before stimulus first spike - -%% #7 MacGregorMulti (first order brainstem neurons) -MacGregorMultiParams=[]; -MacGregorMultiType='chopper'; % MacGregorMultiType='primary-like'; %choose -switch MacGregorMultiType - case 'primary-like' - MacGregorMultiParams.nNeuronsPerBF= 10; % N neurons per BF - MacGregorMultiParams.type = 'primary-like cell'; - MacGregorMultiParams.fibersPerNeuron=4; % N input fibers - MacGregorMultiParams.dendriteLPfreq=200; % dendritic filter - MacGregorMultiParams.currentPerSpike=0.11e-6; % (A) per spike - MacGregorMultiParams.Cap=4.55e-9; % cell capacitance (Siemens) - MacGregorMultiParams.tauM=5e-4; % membrane time constant (s) - MacGregorMultiParams.Ek=-0.01; % K+ eq. potential (V) - MacGregorMultiParams.dGkSpike=3.64e-5; % K+ cond.shift on spike,S - MacGregorMultiParams.tauGk= 0.0012; % K+ conductance tau (s) - MacGregorMultiParams.Th0= 0.01; % equilibrium threshold (V) - MacGregorMultiParams.c= 0.01; % threshold shift on spike, (V) - MacGregorMultiParams.tauTh= 0.015; % variable threshold tau - MacGregorMultiParams.Er=-0.06; % resting potential (V) - MacGregorMultiParams.Eb=0.06; % spike height (V) - - case 'chopper' - MacGregorMultiParams.nNeuronsPerBF= 10; % N neurons per BF - MacGregorMultiParams.type = 'chopper cell'; - MacGregorMultiParams.fibersPerNeuron=10; % N input fibers -% MacGregorMultiParams.fibersPerNeuron=6; % N input fibers - - MacGregorMultiParams.dendriteLPfreq=50; % dendritic filter - MacGregorMultiParams.currentPerSpike=35e-9; % *per spike -% MacGregorMultiParams.currentPerSpike=45e-9; % *per spike - - MacGregorMultiParams.Cap=1.67e-8; % ??cell capacitance (Siemens) - MacGregorMultiParams.tauM=0.002; % membrane time constant (s) - MacGregorMultiParams.Ek=-0.01; % K+ eq. potential (V) - MacGregorMultiParams.dGkSpike=1.33e-4; % K+ cond.shift on spike,S - MacGregorMultiParams.tauGk= 0.0001;% K+ conductance tau (s) - MacGregorMultiParams.Th0= 0.01; % equilibrium threshold (V) - MacGregorMultiParams.c= 0; % threshold shift on spike, (V) - MacGregorMultiParams.tauTh= 0.02; % variable threshold tau - MacGregorMultiParams.Er=-0.06; % resting potential (V) - MacGregorMultiParams.Eb=0.06; % spike height (V) - MacGregorMultiParams.PSTHbinWidth= 1e-4; -end - -%% #8 MacGregor (second-order neuron). Only one per channel -MacGregorParams=[]; % clear the structure first -MacGregorParams.type = 'chopper cell'; -MacGregorParams.fibersPerNeuron=10; % N input fibers -MacGregorParams.dendriteLPfreq=100; % dendritic filter -MacGregorParams.currentPerSpike=120e-9;% *(A) per spike - -MacGregorParams.Cap=16.7e-9; % cell capacitance (Siemens) -MacGregorParams.tauM=0.002; % membrane time constant (s) -MacGregorParams.Ek=-0.01; % K+ eq. potential (V) -MacGregorParams.dGkSpike=1.33e-4; % K+ cond.shift on spike,S -MacGregorParams.tauGk= 0.0003; % K+ conductance tau (s) -MacGregorParams.Th0= 0.01; % equilibrium threshold (V) -MacGregorParams.c= 0; % threshold shift on spike, (V) -MacGregorParams.tauTh= 0.02; % variable threshold tau -MacGregorParams.Er=-0.06; % resting potential (V) -MacGregorParams.Eb=0.06; % spike height (V) -MacGregorParams.debugging=0; % (special) -% wideband accepts input from all channels (of same fiber type) -% use wideband to create inhibitory units -MacGregorParams.wideband=0; % special for wideband units -% MacGregorParams.saveAllData=0; - -%% #9 filteredSACF -minPitch= 300; maxPitch= 3000; numPitches=60; % specify lags -pitches=100*log10(logspace(minPitch/100, maxPitch/100, numPitches)); -filteredSACFParams.lags=1./pitches; % autocorrelation lags vector -filteredSACFParams.acfTau= .003; % time constant of running ACF -filteredSACFParams.lambda= 0.12; % slower filter to smooth ACF -filteredSACFParams.plotFilteredSACF=1; % 0 plots unfiltered ACFs -filteredSACFParams.plotACFs=0; % special plot (see code) -% filteredSACFParams.usePressnitzer=0; % attenuates ACF at long lags -filteredSACFParams.lagsProcedure= 'useAllLags'; -% filteredSACFParams.lagsProcedure= 'useBernsteinLagWeights'; -% filteredSACFParams.lagsProcedure= 'omitShortLags'; -filteredSACFParams.criterionForOmittingLags=3; - -% checks -if AN_IHCsynapseParams.numFibers<MacGregorMultiParams.fibersPerNeuron - error('MacGregorMulti: too few input fibers for input to MacG unit') -end - - -%% write all parameters to the command window -% showParams is currently set at the top of htis function -if showParams - fprintf('\n %%%%%%%%\n') - fprintf('\n%s\n', method.parameterSource) - fprintf('\n') - nm=UTIL_paramsList(whos); - for i=1:length(nm) - % eval(['UTIL_showStruct(' nm{i} ', ''' nm{i} ''')']) - if ~strcmp(nm(i), 'method') - eval(['UTIL_showStructureSummary(' nm{i} ', ''' nm{i} ''', 10)']) - end - end -end - - - -% ********************************************************************** comparison data -% store individual data here for display on the multiThreshold GUI (if used) -% the final value in each vector is an identifier (BF or duration)) -if isstruct(experiment) - switch experiment.paradigm - case {'IFMC','IFMC_8ms'} - % based on MPa - comparisonData=[ - 66 51 49 48 46 45 54 250; - 60 54 46 42 39 49 65 500; - 64 51 38 32 33 59 75 1000; - 59 51 36 30 41 81 93 2000; - 71 63 53 44 36 76 95 4000; - 70 64 43 35 35 66 88 6000; - 110 110 110 110 110 110 110 8000; - ]; - if length(BFlist)==1 && ~isempty(comparisonData) - availableFrequencies=comparisonData(:,end)'; - findRow= find(BFlist==availableFrequencies); - if ~isempty (findRow) - experiment.comparisonData=comparisonData(findRow,:); - end - end - - case {'TMC','TMC_8ms'} - % based on MPa - comparisonData=[ - 48 58 63 68 75 80 85 92 99 250; - 33 39 40 49 52 61 64 77 79 500; - 39 42 50 81 83 92 96 97 110 1000; - 24 26 32 37 46 51 59 71 78 2000; - 65 68 77 85 91 93 110 110 110 4000; - 20 19 26 44 80 95 96 110 110 6000; - ]; - if length(BFlist)==1 && ~isempty(comparisonData) - availableFrequencies=comparisonData(:,end)'; - findRow= find(BFlist==availableFrequencies); - if ~isempty (findRow) - experiment.comparisonData=comparisonData(findRow,:); - end - end - - case { 'absThreshold', 'absThreshold_8'} - % MPa thresholds - experiment.comparisonData=[ - 32 26 16 18 22 22 0.008; - 16 13 6 9 15 11 0.500 - ]; - - - otherwise - experiment.comparisonData=[]; - end -end - -