diff -r b51bf546ca3f -r 1a502830d462 Help and reference data/MAP 1_14 DEVELOPMENT log.doc Binary file Help and reference data/MAP 1_14 DEVELOPMENT log.doc has changed diff -r b51bf546ca3f -r 1a502830d462 MAP/MAP1_14.m --- a/MAP/MAP1_14.m +++ b/MAP/MAP1_14.m @@ -313,15 +313,15 @@ % Fiber types are specified in terms of tauCa nANfiberTypes= length(IHCpreSynapseParams.tauCa); tauCas= IHCpreSynapseParams.tauCa; -nChannels= nANfiberTypes*nBFs; -synapticCa= zeros(nChannels,segmentLength); +nANchannels= nANfiberTypes*nBFs; +synapticCa= zeros(nANchannels,segmentLength); % Calcium control (more calcium, greater release rate) ECa=IHCpreSynapseParams.ECa; gamma=IHCpreSynapseParams.gamma; beta=IHCpreSynapseParams.beta; tauM=IHCpreSynapseParams.tauM; -mICa=zeros(nChannels,segmentLength); +mICa=zeros(nANchannels,segmentLength); GmaxCa=IHCpreSynapseParams.GmaxCa; synapse_z= IHCpreSynapseParams.z; synapse_power=IHCpreSynapseParams.power; @@ -329,9 +329,9 @@ % tauCa vector is established across channels to allow vectorization % (one tauCa per channel). Do not confuse with tauCas (one pre fiber type) tauCa=repmat(tauCas, nBFs,1); -tauCa=reshape(tauCa, nChannels, 1); +tauCa=reshape(tauCa, nANchannels, 1); -% presynapse startup values (vectors, length:nChannels) +% presynapse startup values (vectors, length:nANchannels) % proportion (0 - 1) of Ca channels open at IHCrestingV mICaCurrent=((1+beta^-1 * exp(-gamma*IHCrestingV))^-1)... *ones(nBFs*nANfiberTypes,1); @@ -349,7 +349,7 @@ % The results computed either for probabiities *or* for spikes (not both) % Spikes are necessary if CN and IC are to be computed nFibersPerChannel= AN_IHCsynapseParams.numFibers; -nANfibers= nChannels*nFibersPerChannel; +nANfibers= nANchannels*nFibersPerChannel; AN_refractory_period= AN_IHCsynapseParams.refractory_period; y=AN_IHCsynapseParams.y; @@ -359,10 +359,10 @@ M=round(AN_IHCsynapseParams.M); % probability (NB initial 'P' on everything) -PAN_ydt = repmat(AN_IHCsynapseParams.y*dt, nChannels,1); -PAN_ldt = repmat(AN_IHCsynapseParams.l*dt, nChannels,1); -PAN_xdt = repmat(AN_IHCsynapseParams.x*dt, nChannels,1); -PAN_rdt = repmat(AN_IHCsynapseParams.r*dt, nChannels,1); +PAN_ydt = repmat(AN_IHCsynapseParams.y*dt, nANchannels,1); +PAN_ldt = repmat(AN_IHCsynapseParams.l*dt, nANchannels,1); +PAN_xdt = repmat(AN_IHCsynapseParams.x*dt, nANchannels,1); +PAN_rdt = repmat(AN_IHCsynapseParams.r*dt, nANchannels,1); PAN_rdt_plus_ldt = PAN_rdt + PAN_ldt; PAN_M=round(AN_IHCsynapseParams.M); @@ -371,12 +371,12 @@ Pavailable = Pcleft*(l+r)./kt0; Preprocess = Pcleft*r/x; % canbe fractional -ANprobability=zeros(nChannels,segmentLength); -ANprobRateOutput=zeros(nChannels,signalLength); +ANprobability=zeros(nANchannels,segmentLength); +ANprobRateOutput=zeros(nANchannels,signalLength); lengthAbsRefractoryP= round(AN_refractory_period/dt); % special variables for monitoring synaptic cleft (specialists only) -savePavailableSeg=zeros(nChannels,segmentLength); -savePavailable=zeros(nChannels,signalLength); +savePavailableSeg=zeros(nANchannels,segmentLength); +savePavailable=zeros(nANchannels,signalLength); % spikes % ! ! ! ! ! ! ! ! lengthAbsRefractory= round(AN_refractory_period/ANdt); @@ -406,27 +406,39 @@ %% CN (first brain stem nucleus - could be any subdivision of CN) % Input to a CN neuorn is a random selection of AN fibers within a channel % The number of AN fibers used is ANfibersFanInToCN -ANfibersFanInToCN=MacGregorMultiParams.fibersPerNeuron; -nCNneuronsPerChannel=MacGregorMultiParams.nNeuronsPerBF; % CNtauGk (Potassium time constant) determines the rate of firing of % the unit when driven hard by a DC input (not normally >350 sp/s) -CNtauGk=MacGregorMultiParams.tauGk; +% If there is more than one value, everything is replicated accordingly + ANavailableFibersPerChan=AN_IHCsynapseParams.numFibers; -nCNneurons=nCNneuronsPerChannel*nChannels; -% nCNneuronsPerFiberType= nCNneurons/nANfiberTypes; +ANfibersFanInToCN=MacGregorMultiParams.fibersPerNeuron; +CNtauGk=MacGregorMultiParams.tauGk; % row vector of CN types (by tauGk) +nCNtauGk=length(CNtauGk); + +% the total number of 'channels' is now greater +nCNchannels=nANchannels*nCNtauGk; + +nCNneuronsPerChannel=MacGregorMultiParams.nNeuronsPerBF; +tauGk=repmat(CNtauGk, nCNneuronsPerChannel,1); +tauGk=reshape(tauGk,nCNneuronsPerChannel*nCNtauGk,1); + +% Now the number of neurons has been increased +nCNneurons=nCNneuronsPerChannel*nCNchannels; CNmembranePotential=zeros(nCNneurons,reducedSegmentLength); % establish which ANfibers (by name) feed into which CN nuerons -CNinputfiberLists=zeros(nChannels*nCNneuronsPerChannel, ANfibersFanInToCN); +CNinputfiberLists=zeros(nANchannels*nCNneuronsPerChannel, ANfibersFanInToCN); unitNo=1; -for ch=1:nChannels +for ch=1:nANchannels % Each channel contains a number of units =length(listOfFanInValues) for idx=1:nCNneuronsPerChannel - fibersUsed=(ch-1)*ANavailableFibersPerChan + ... - ceil(rand(1,ANfibersFanInToCN)* ANavailableFibersPerChan); - CNinputfiberLists(unitNo,:)=fibersUsed; - unitNo=unitNo+1; + for idx2=1:nCNtauGk + fibersUsed=(ch-1)*ANavailableFibersPerChan + ... + ceil(rand(1,ANfibersFanInToCN)* ANavailableFibersPerChan); + CNinputfiberLists(unitNo,:)=fibersUsed; + unitNo=unitNo+1; + end end end @@ -468,14 +480,14 @@ CNtimeSinceLastSpike=zeros(nCNneurons,1); % tauGk is the main distinction between neurons % in fact they are all the same in the standard model -tauGk=repmat(CNtauGk,nChannels*nCNneuronsPerChannel,1); +tauGk=repmat(tauGk,nANchannels,1); -CN_PSTH=zeros(nChannels,reducedSegmentLength); CNoutput=false(nCNneurons,reducedSignalLength); %% MacGregor (IC - second nucleus) -------- -nICcells=nChannels; % one cell per channel +nICcells=nANchannels*nCNtauGk; % one cell per channel +CN_PSTH=zeros(nICcells ,reducedSegmentLength); ICspikeWidth=0.00015; % this may need revisiting epochsPerSpike=round(ICspikeWidth/ANdt); @@ -515,7 +527,7 @@ ICtrailingAlphas=zeros(nICcells, length(IC_CNalphaFunction)); ICfiberTypeRates=zeros(nANfiberTypes,reducedSignalLength); -ICoutput=false(nChannels,reducedSignalLength); +ICoutput=false(nICcells,reducedSignalLength); ICmembranePotential=zeros(nICcells,reducedSegmentLength); ICmembraneOutput=zeros(nICcells,signalLength); @@ -799,7 +811,7 @@ % releaseProb is the release probability per channel % but each channel has many synapses releaseProb=repmat(releaseProb',nFibersPerChannel,1); - releaseProb=reshape(releaseProb, nFibersPerChannel*nChannels,1); + releaseProb=reshape(releaseProb, nFibersPerChannel*nANchannels,1); % AN_available=round(AN_available); % vesicles must be integer, (?needed) M_q=AN_M- AN_available; % number of missing vesicles @@ -883,7 +895,7 @@ % Create the dendritic current for that neuron % First get input spikes to this neuron synapseNo=1; - for ch=1:nChannels + for ch=1:nCNchannels for idx=1:nCNneuronsPerChannel % determine candidate fibers for this unit fibersUsed=CNinputfiberLists(synapseNo,:); @@ -992,7 +1004,8 @@ %% IC ---------------------------------------------- % MacGregor or some other second order neurons - % combine CN neurons in same channel, i.e. same BF & same tauCa + % combine CN neurons in same channel, + % i.e. same BF & same tauCa % to generate inputs to single IC unit channelNo=0; for idx=1:nCNneuronsPerChannel:nCNneurons-nCNneuronsPerChannel+1; diff -r b51bf546ca3f -r 1a502830d462 multithreshold 1.46/expGUI_MT.m --- a/multithreshold 1.46/expGUI_MT.m +++ b/multithreshold 1.46/expGUI_MT.m @@ -85,38 +85,37 @@ % Get default command line output from handles structure initializeGUI(handles) varargout{1} = handles.output; -setLocationOfGUIs(handles) -function setLocationOfGUIs(handles) -global checkForPreviousGUI % holds screen positioning across repeated calls -scrnsize=get(0,'screensize'); -checkForPreviousGUI=[]; -% if isstruct(checkForPreviousGUI)... -% && checkForPreviousGUI.GUIalreadyStarted==1 ... -% && isfield(checkForPreviousGUI,'GUIposition') -% set(handles.figure1,'position',checkForPreviousGUI.GUIposition) -% else -% % relocate the GUI only if this is the first time of use -% set(0, 'units','pixels') -% % occupies top to bottom of screen but only 60% width -% % [left bottom width height] -% firstPos=[0.01*scrnsize(4) 0.03*scrnsize(3) 0.6*scrnsize(3) 0.92*scrnsize(4)]; -% firstPos=[4 0.045*scrnsize(4) 0.6*scrnsize(3) 0.93*scrnsize(4)]; -% set(handles.figure1, 'units','pixels') -% set(handles.figure1,'position',firstPos) -% checkForPreviousGUI.GUIalreadyStarted=1; -% checkForPreviousGUI.GUIposition=firstPos; -% end -set(handles.figure1,'color',[.871 .961 .996]) -set(handles.figure1,'name', pwd) - -% MAP model figure; sits alongside GUI if requested -figure(99) -% [left bottom width height] -MAPpos=[0.615*scrnsize(3) 0.05*scrnsize(4) 0.15*scrnsize(3) 0.85*scrnsize(4)]; -% visible only on request. -set(gcf,'position',MAPpos , 'visible','off') - +% function setLocationOfGUIs(handles) +% global checkForPreviousGUI % holds screen positioning across repeated calls +% scrnsize=get(0,'screensize'); +% checkForPreviousGUI=[]; +% % if isstruct(checkForPreviousGUI)... +% % && checkForPreviousGUI.GUIalreadyStarted==1 ... +% % && isfield(checkForPreviousGUI,'GUIposition') +% % set(handles.figure1,'position',checkForPreviousGUI.GUIposition) +% % else +% % % relocate the GUI only if this is the first time of use +% % set(0, 'units','pixels') +% % % occupies top to bottom of screen but only 60% width +% % % [left bottom width height] +% % firstPos=[0.01*scrnsize(4) 0.03*scrnsize(3) 0.6*scrnsize(3) 0.92*scrnsize(4)]; +% % firstPos=[4 0.045*scrnsize(4) 0.6*scrnsize(3) 0.93*scrnsize(4)]; +% % set(handles.figure1, 'units','pixels') +% % set(handles.figure1,'position',firstPos) +% % checkForPreviousGUI.GUIalreadyStarted=1; +% % checkForPreviousGUI.GUIposition=firstPos; +% % end +% set(handles.figure1,'color',[.871 .961 .996]) +% set(handles.figure1,'name', pwd) +% +% % MAP model figure; sits alongside GUI if requested +% figure(99) +% % [left bottom width height] +% MAPpos=[0.615*scrnsize(3) 0.05*scrnsize(4) 0.15*scrnsize(3) 0.85*scrnsize(4)]; +% % visible only on request. +% set(gcf,'position',MAPpos , 'visible','off') +% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% @@ -128,19 +127,12 @@ global targetTypes maskerTypes backgroundTypes global variableNames paradigmNames threshEstNames cueNames -% dbstop if error % allow for debugging and user error reporting -% dbstop if warning - -% specify structure fields for pretty automatic printing -% It also initialises some simple variables +% Specify order of fields in main structures +% identify as empty values or empty strings only orderGlobals -addpath ('paradigms') % preset paradigm informations is stored here -% filesep is usd to be compatible with other operating systems -% addpath (['..' filesep 'modules'], ['..' filesep 'utilities'], ... -% ['..' filesep 'parameterStore'], ['..' filesep 'wavFileStore'],... -% ['..' filesep 'testPrograms']) -addpath (['..' filesep 'testPrograms']) +addpath ('paradigms') %paradigm informations is stored here +addpath (['..' filesep 'testPrograms']) % model physiology tests % specify all variables that need to be set on the GUI variableNames={'stimulusDelay','maskerDuration','maskerLevel',... @@ -149,20 +141,14 @@ 'cueTestDifference', 'WRVstartValues', 'WRVsteps', 'WRVlimits'}; % Variable variables -% (specifies paradigm paramaters that can changed on a 'between runs' basis) -% make them options in the two between runs variable menus -% NB 'numOHIOtones' is used only to solve a problem; it should not be -% selected manually +% (names of variable that can changed between runs) betweenRunsVariables={'stimulusDelay','maskerDuration','maskerLevel',... 'maskerRelativeFrequency','targetFrequency', 'gapDuration',... 'targetDuration','targetLevel','numOHIOtones'}; +% populate the 'between runs variable' menus set(handles.popupmenuVaryParameter1,'string',betweenRunsVariables) set(handles.popupmenuVaryParameter2,'string',betweenRunsVariables) -% NB 'Warning: popupmenu control requires a scalar Value' -% indicates that an inappropriate 'value' is being set. -% when testing for this, always clear the GUI before running - % Trial presentation order - randomize at startup presentationOrderNames={'randomize within blocks', 'fixed sequence', ... 'randomize across blocks'}; @@ -184,13 +170,14 @@ '16TalkerBabble','8TalkerBabble','4TalkerBabble',... '4TalkerReversedBabble','2TalkerBabble','1TalkerBabble'}; set(handles.popupmenuBackgroundType, 'string', backgroundTypes); -set(handles.editBackgroundLevel,'string',... - num2str(stimulusParameters.backgroundLevel)) +set(handles.editBackgroundLevel,'string', '0') % Establish available paradigms by scanning paradigms folder paradigmNames= what('paradigms'); -paradigmNames=paradigmNames.m; % m files only -for i=1:length(paradigmNames), paradigmNames{i}=paradigmNames{i}(10:end-2); end +paradigmNames= paradigmNames.m; % select m files only +for i=1:length(paradigmNames) % strip off file extension + paradigmNames{i}=paradigmNames{i}(10:end-2); +end set(handles.popupmenuParadigm,'string', paradigmNames) % startup paradigm, 'training' (could be anywhere on the list) @@ -199,7 +186,7 @@ if ~isempty(idx) set(handles.popupmenuParadigm,'value', idx) else - % training paradigm is always the startup paradigm + % training paradigm must exist error(['expGUI_MT\initializeGUI: No ' startupParadigm... ' paradigm found in paradigms folder']) end @@ -213,13 +200,15 @@ set(handles.popupmenuEar,'value', defaultOption) % 'left' is deafult set(handles.pushbuttonSingleShot, 'visible', 'off') % use only for MAP -% masker phase box- value must be set in paradigm +% phase phaseOptions={'sin','cos','alt','rand'}; set(handles.popupmenuPhase,'string', phaseOptions) +set(handles.popupmenuPhase,'value', 1) % Cue cueNames={'cued', 'noCue'}; set(handles.popupmenuCueNoCue, 'string', cueNames); +set(handles.popupmenuCueNoCue, 'value', 1); % threshold assessment method - value must be set in paradigm threshEstNames={'oneIntervalUpDown', 'MaxLikelihood', ... @@ -265,7 +254,7 @@ % message box set(handles.textMSG,'backgroundcolor', 'w', 'ForegroundColor', 'b', 'string', '') -set(handles.editMsgFont,'string','7') +set(handles.editMsgFont,'string','10') set(handles.editSubjectFont,'string','14') % default psychometric bin size and logistic slopes @@ -328,14 +317,17 @@ end rmpath ('paradigms') -switch experiment.paradigm - % identify masker free paradigms - case {'training', 'discomfort','absThreshold', 'absThreshold_8',... - 'absThreshold_16','TENtest', 'threshold_duration','SRT'... - 'paradigm_thr_IFMC'} - experiment.maskerInUse=0; - otherwise - experiment.maskerInUse=1; +if ~isfield(experiment,'maskerInUse') + error('selected paradigm does not specify if masker is used') +end + + +if ~experiment.maskerInUse + stimulusParameters.maskerType='tone'; + stimulusParameters.maskerPhase='sin'; + stimulusParameters.maskerDuration=0.0; + stimulusParameters.maskerLevel= -50; + stimulusParameters.maskerRelativeFrequency= 1 ; end % if a variable is subject to change, specify list of values here @@ -348,8 +340,15 @@ eval (cmd); % establish popup menus on the basis of the paradigm file -set(handles.popupmenuRandomize,'value', betweenRuns.randomizeSequence) -set(handles.popupmenuPhase,'string', stimulusParameters.maskerPhase) +% set(handles.popupmenuRandomize,'value', betweenRuns.randomizeSequence) +sequenceOptions=get(handles.popupmenuRandomize,'string'); +idx=find(strcmp(betweenRuns.randomizeSequence, sequenceOptions)==1); +set(handles.popupmenuRandomize,'value', idx) + +phaseOptions=get(handles.popupmenuPhase,'string'); +idx=find(strcmp(stimulusParameters.maskerPhase, phaseOptions)==1); +set(handles.popupmenuPhase,'value', idx) + if stimulusParameters.includeCue set(handles.popupmenuCueNoCue,'value', 1) else @@ -614,6 +613,8 @@ global experiment betweenRuns paradigmNames errormsg checkForPreviousGUI.GUIposition=get(handles.figure1,'position'); experiment.singleShot=0; +experiment.stop=0; + switch experiment.paradigm case 'profile' %% special option for two successive and linked measurements @@ -784,6 +785,8 @@ 'MAPmodelSingleCh', 'MAPmodelListen'} % MAPmodel writes forced parameter settings to the screen % so that they can be read from there + % {'randomize within blocks', 'fixed sequence',... + % 'randomize across blocks'} set(handles.popupmenuRandomize,'value',2) % fixed sequence set(handles.editstimulusDelay,'string','0.01') % no stimulus delay stimulusParameters.includeCue=0; % no cue for MAP @@ -1301,8 +1304,8 @@ experiment.threshEstMethod= ''; experiment.functionEstMethod= ''; experiment.psyBinWidth= []; -experiment.maxLogisticK=2; -experiment.numPossLogisticK=100; +experiment.maxLogisticK=[]; +experiment.numPossLogisticK=[]; experiment.possLogSlopes= []; experiment.meanSearchStep= []; experiment.psyFunSlope= []; @@ -1311,7 +1314,7 @@ experiment.buttonBoxType= ''; experiment.buttonBoxStatus= ''; experiment.status= ''; -experiment.stop= 0; +experiment.stop= []; experiment.pleaseRepeat= []; experiment.justInitialized=[]; @@ -1334,8 +1337,6 @@ betweenRuns.randomizeSequence=[]; betweenRuns.timeNow= []; betweenRuns.runNumber= []; -% betweenRuns.variableCount1= []; -% betweenRuns.variableCount2= []; betweenRuns.thresholds= []; betweenRuns.forceThresholds= []; betweenRuns.observationCount= []; @@ -1357,8 +1358,8 @@ withinRuns=[]; withinRuns.trialNumber=[]; -withinRuns.nowInPhase2=0; -withinRuns.beginningOfPhase2=0; +withinRuns.nowInPhase2=[]; +withinRuns.beginningOfPhase2=[]; withinRuns.variableValue=[]; withinRuns.direction=''; withinRuns.peaks=[]; @@ -1375,7 +1376,7 @@ withinRuns.caughtOut=[]; withinRuns.catchTrialCount=[]; withinRuns.wrongButton= []; -withinRuns.babblePlaying=0; +withinRuns.babblePlaying=[]; % --- Executes on selection change in popupmenuBackgroundType. function popupmenuBackgroundType_Callback(hObject, eventdata, handles) diff -r b51bf546ca3f -r 1a502830d462 multithreshold 1.46/nextStimulus.m --- a/multithreshold 1.46/nextStimulus.m +++ b/multithreshold 1.46/nextStimulus.m @@ -560,7 +560,7 @@ duration(3)=precedingSilence+maskerDuration+ terminalSilence; globalStimParams.overallDuration=max(duration); globalStimParams.nSignalPoints=... - round(globalStimParams.overallDuration/globalStimParams.dt); + round(globalStimParams.overallDuration*globalStimParams.FS); % ----------------------------------------------cue stimulus % cue masker diff -r b51bf546ca3f -r 1a502830d462 multithreshold 1.46/paradigms/paradigm_GOM.m --- a/multithreshold 1.46/paradigms/paradigm_GOM.m +++ b/multithreshold 1.46/paradigms/paradigm_GOM.m @@ -16,8 +16,8 @@ betweenRuns.variableList1=25: 5: 70; betweenRuns.variableName2='maskerRelativeFrequency'; betweenRuns.variableList2=[1 0.5]; -betweenRuns.randomizeSequence=1; % 'random sequence' +experiment.maskerInUse=1; stimulusParameters.maskerType='tone'; stimulusParameters.maskerPhase='sin'; stimulusParameters.maskerDuration=0.104; diff -r b51bf546ca3f -r 1a502830d462 multithreshold 1.46/paradigms/paradigm_IFMC.m --- a/multithreshold 1.46/paradigms/paradigm_IFMC.m +++ b/multithreshold 1.46/paradigms/paradigm_IFMC.m @@ -16,8 +16,10 @@ betweenRuns.variableName2='targetFrequency'; % keep old list of target frequencies betweenRuns.variableList2=str2num(get(handles.edittargetFrequency,'string')); -betweenRuns.randomizeSequence=1; % 'random sequence' +experiment.maskerInUse=1; +stimulusParameters.maskerType='tone'; +stimulusParameters.maskerPhase='sin'; stimulusParameters.maskerDuration=0.108; stimulusParameters.maskerLevel=stimulusParameters.WRVstartValues(1); stimulusParameters.maskerRelativeFrequency=betweenRuns.variableList1; diff -r b51bf546ca3f -r 1a502830d462 multithreshold 1.46/paradigms/paradigm_SRT.m --- a/multithreshold 1.46/paradigms/paradigm_SRT.m +++ b/multithreshold 1.46/paradigms/paradigm_SRT.m @@ -28,20 +28,12 @@ betweenRuns.variableList1=1000; betweenRuns.variableName2='maskerDuration'; betweenRuns.variableList2=0.1 ; -% 1='fixed sequence', 2='randomize within blocks', 3='randomize across -% blocks' -betweenRuns.randomizeSequence=1; % 'random sequence' % delay > masker > gap > target - stimulusParameters.stimulusDelay=0.3; % maskerTypes={'tone','noise', 'pinkNoise','TEN','whiteNoise'}; -stimulusParameters.maskerType='tone'; -stimulusParameters.maskerPhase='sin'; -stimulusParameters.maskerDuration=0.0; -stimulusParameters.maskerLevel= -50; -stimulusParameters.maskerRelativeFrequency= 1 ; % not used +experiment.maskerInUse=0; stimulusParameters.gapDuration=0.0; diff -r b51bf546ca3f -r 1a502830d462 multithreshold 1.46/paradigms/paradigm_TENtest.m --- a/multithreshold 1.46/paradigms/paradigm_TENtest.m +++ b/multithreshold 1.46/paradigms/paradigm_TENtest.m @@ -12,7 +12,8 @@ betweenRuns.variableList1=[250 500 1000 2000 4000 8000 ]; betweenRuns.variableName2='targetDuration'; betweenRuns.variableList2= 0.25; -betweenRuns.randomizeSequence=1; % 'random sequence' + +experiment.maskerInUse=0; stimulusParameters.targetType='tone'; stimulusParameters.targetPhase='sin'; diff -r b51bf546ca3f -r 1a502830d462 multithreshold 1.46/paradigms/paradigm_TMC.m --- a/multithreshold 1.46/paradigms/paradigm_TMC.m +++ b/multithreshold 1.46/paradigms/paradigm_TMC.m @@ -17,8 +17,8 @@ betweenRuns.variableName2='targetFrequency'; % retain existing targetFrequencies betweenRuns.variableList2=str2num(get(handles.edittargetFrequency,'string')); -betweenRuns.randomizeSequence=1; % 'random sequence' +experiment.maskerInUse=1; stimulusParameters.maskerType='tone'; stimulusParameters.maskerPhase='sin'; stimulusParameters.maskerDuration=0.108; diff -r b51bf546ca3f -r 1a502830d462 multithreshold 1.46/paradigms/paradigm_absThreshold.m --- a/multithreshold 1.46/paradigms/paradigm_absThreshold.m +++ b/multithreshold 1.46/paradigms/paradigm_absThreshold.m @@ -8,6 +8,8 @@ betweenRuns.variableName2='targetDuration'; betweenRuns.variableList2= 0.25; +experiment.maskerInUse=0; + stimulusParameters.targetFrequency=betweenRuns.variableList1; stimulusParameters.targetDuration=betweenRuns.variableList2; stimulusParameters.targetLevel=stimulusParameters.WRVstartValues(1); diff -r b51bf546ca3f -r 1a502830d462 multithreshold 1.46/paradigms/paradigm_absThreshold_16.m --- a/multithreshold 1.46/paradigms/paradigm_absThreshold_16.m +++ b/multithreshold 1.46/paradigms/paradigm_absThreshold_16.m @@ -8,10 +8,8 @@ betweenRuns.variableList1=str2num(get(handles.edittargetFrequency,'string')); betweenRuns.variableName2='targetDuration'; betweenRuns.variableList2=0.016; -betweenRuns.randomizeSequence=1; % 'random sequence' -% delay > masker > gap > target - +experiment.maskerInUse=0; stimulusParameters.targetType='tone'; stimulusParameters.targetPhase='sin'; diff -r b51bf546ca3f -r 1a502830d462 multithreshold 1.46/paradigms/paradigm_discomfort.m --- a/multithreshold 1.46/paradigms/paradigm_discomfort.m +++ b/multithreshold 1.46/paradigms/paradigm_discomfort.m @@ -12,10 +12,13 @@ betweenRuns.variableList1=[1000]; betweenRuns.variableName2='targetDuration'; betweenRuns.variableList2=0.5 ; -betweenRuns.randomizeSequence=2; % 'fixed sequence' +% 'randomize within blocks', 'fixed sequence', 'randomize across blocks' +betweenRuns.randomizeSequence='fixed sequence'; stimulusParameters.stimulusDelay=0; +experiment.maskerInUse=0; + stimulusParameters.targetType='tone'; stimulusParameters.targetPhase='sin'; stimulusParameters.targetFrequency=1000; diff -r b51bf546ca3f -r 1a502830d462 multithreshold 1.46/paradigms/paradigm_forwardMasking.m --- a/multithreshold 1.46/paradigms/paradigm_forwardMasking.m +++ b/multithreshold 1.46/paradigms/paradigm_forwardMasking.m @@ -11,13 +11,13 @@ betweenRuns.variableName1='gapDuration'; betweenRuns.variableList1=[.005 0.01 0.02 0.04]; betweenRuns.variableName2='maskerLevel'; -betweenRuns.variableList2=[20 40 60 80]; -betweenRuns.randomizeSequence=1; % 'random sequence' +betweenRuns.variableList2=[80 60 40 20]; +experiment.maskerInUse=1; stimulusParameters.maskerType='tone'; -stimulusParameters.maskerPhase='sin'; +stimulusParameters.maskerPhase='cos'; stimulusParameters.maskerDuration=0.108; -stimulusParameters.maskerLevel=betweenRuns.variableList2; +stimulusParameters.maskerLevel=20; stimulusParameters.maskerRelativeFrequency=1; stimulusParameters.gapDuration=betweenRuns.variableList1; diff -r b51bf546ca3f -r 1a502830d462 multithreshold 1.46/paradigms/paradigm_overShoot.m --- a/multithreshold 1.46/paradigms/paradigm_overShoot.m +++ b/multithreshold 1.46/paradigms/paradigm_overShoot.m @@ -1,5 +1,5 @@ function paradigm_overShoot(handles) -global stimulusParameters betweenRuns +global stimulusParameters betweenRuns experiment paradigm_training(handles) % default @@ -14,11 +14,11 @@ % betweenRuns.variableList1=[-.350 -.238 -.213 -.180 -.160 -.100 -.040 -.020 0 .010 .040 .140]; betweenRuns.variableName2='maskerLevel'; betweenRuns.variableList2=50; -betweenRuns.randomizeSequence=1; % 'random sequence' % delay > masker > gap > target stimulusParameters.stimulusDelay=0.3; +experiment.maskerInUse=1; stimulusParameters.maskerType='tone'; stimulusParameters.maskerPhase='sin'; stimulusParameters.maskerDuration=0.4; diff -r b51bf546ca3f -r 1a502830d462 multithreshold 1.46/paradigms/paradigm_profile.m --- a/multithreshold 1.46/paradigms/paradigm_profile.m +++ b/multithreshold 1.46/paradigms/paradigm_profile.m @@ -7,10 +7,6 @@ betweenRuns.variableList1=[250 500 1000 2000 4000 8000 ]; betweenRuns.variableName2='targetDuration'; betweenRuns.variableList2=0.016; -betweenRuns.randomizeSequence=1; % 'random sequence' - -% delay > masker > gap > target - stimulusParameters.targetType='tone'; stimulusParameters.targetPhase='sin'; diff -r b51bf546ca3f -r 1a502830d462 multithreshold 1.46/paradigms/paradigm_psychometric.m --- a/multithreshold 1.46/paradigms/paradigm_psychometric.m +++ b/multithreshold 1.46/paradigms/paradigm_psychometric.m @@ -15,7 +15,8 @@ betweenRuns.variableList1=1000.01:0.01:1000.05; betweenRuns.variableName2='targetDuration'; betweenRuns.variableList2=0.1 ; -betweenRuns.randomizeSequence=1; % 'random sequence' + +experiment.maskerInUse=0; stimulusParameters.targetType='tone'; stimulusParameters.targetPhase='sin'; diff -r b51bf546ca3f -r 1a502830d462 multithreshold 1.46/paradigms/paradigm_threshold_duration.m --- a/multithreshold 1.46/paradigms/paradigm_threshold_duration.m +++ b/multithreshold 1.46/paradigms/paradigm_threshold_duration.m @@ -12,7 +12,8 @@ betweenRuns.variableList1=[ .016 .032 .064 .128 .256 .512]; betweenRuns.variableName2='targetFrequency'; betweenRuns.variableList2=1000; -betweenRuns.randomizeSequence=1; % 'random sequence' + +experiment.maskerInUse=0; stimulusParameters.targetType='tone'; stimulusParameters.targetPhase='sin'; diff -r b51bf546ca3f -r 1a502830d462 multithreshold 1.46/paradigms/paradigm_training.m --- a/multithreshold 1.46/paradigms/paradigm_training.m +++ b/multithreshold 1.46/paradigms/paradigm_training.m @@ -30,26 +30,26 @@ betweenRuns.variableList1=1000; betweenRuns.variableName2='targetDuration'; betweenRuns.variableList2=0.1 ; -% 1='fixed sequence', 2='randomize within blocks', 3='randomize across -% blocks' -betweenRuns.randomizeSequence=1; % 'random sequence' +% 'randomize within blocks', 'fixed sequence', 'randomize across blocks' +betweenRuns.randomizeSequence='randomize within blocks'; % delay > masker > gap > target stimulusParameters.stimulusDelay=0.3; % maskerTypes={'tone','noise', 'pinkNoise','TEN','whiteNoise'}; +experiment.maskerInUse=0; stimulusParameters.maskerType='tone'; -stimulusParameters.maskerPhase='sin'; +stimulusParameters.maskerPhase='cos'; stimulusParameters.maskerDuration=0.0; stimulusParameters.maskerLevel= -50; -stimulusParameters.maskerRelativeFrequency= 1 ; % not used +stimulusParameters.maskerRelativeFrequency= 1 ; stimulusParameters.gapDuration=0.0; % targetTypes={'tone','noise', 'pinkNoise','whiteNoise','OHIO'}; stimulusParameters.targetType='tone'; -stimulusParameters.targetPhase='sin'; +stimulusParameters.targetPhase='cos'; %{'sin','cos','alt','rand'} stimulusParameters.targetFrequency=1000; stimulusParameters.targetDuration=0.1; stimulusParameters.targetLevel=stimulusParameters.WRVstartValues(1); diff -r b51bf546ca3f -r 1a502830d462 multithreshold 1.46/paradigms/paradigm_trainingIFMC.m --- a/multithreshold 1.46/paradigms/paradigm_trainingIFMC.m +++ b/multithreshold 1.46/paradigms/paradigm_trainingIFMC.m @@ -17,8 +17,8 @@ betweenRuns.variableName2='targetFrequency'; % keep old list of target frequencies betweenRuns.variableList2=str2num(get(handles.edittargetFrequency,'string')); -betweenRuns.randomizeSequence=1; % 'random sequence' +experiment.maskerInUse=1; stimulusParameters.maskerType='tone'; stimulusParameters.maskerPhase='sin'; stimulusParameters.maskerDuration=0.108; diff -r b51bf546ca3f -r 1a502830d462 multithreshold 1.46/profile.mat Binary file multithreshold 1.46/profile.mat has changed diff -r b51bf546ca3f -r 1a502830d462 multithreshold 1.46/savedData/mostRecentResults.mat Binary file multithreshold 1.46/savedData/mostRecentResults.mat has changed diff -r b51bf546ca3f -r 1a502830d462 multithreshold 1.46/subjGUI_MT.m --- a/multithreshold 1.46/subjGUI_MT.m +++ b/multithreshold 1.46/subjGUI_MT.m @@ -200,6 +200,8 @@ % Create two sequence vectors to represent the sequence of var1 and var2 % values. 'var1' changes most rapidly. switch betweenRuns.randomizeSequence + % {'randomize within blocks', 'fixed sequence',... + % 'randomize across blocks'} case 'fixed sequence' var1Sequence=repmat(betweenRuns.variableList1, 1,nVar2); var2Sequence=reshape(repmat(betweenRuns.variableList2, ... diff -r b51bf546ca3f -r 1a502830d462 parameterStore/MAPparamsNormalIC.m --- /dev/null +++ b/parameterStore/MAPparamsNormalIC.m @@ -0,0 +1,302 @@ +function method=MAPparamsNormalIC ... + (BFlist, sampleRate, showParams, paramChanges) +% MAPparams<> establishes a complete set of MAP parameters +% Parameter file names must be of the form +% +% 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= 0.100; % 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= [ 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= [0.001 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.numFibers3 && ~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=[]; diff -r b51bf546ca3f -r 1a502830d462 testPrograms/test_MAP1_14x.m --- /dev/null +++ b/testPrograms/test_MAP1_14x.m @@ -0,0 +1,190 @@ +function test_MAP1_14x +% 'x' is a trial file +% test_MAP1_14 is a general purpose test routine that can be adjusted to +% test a number of different applications of MAP1_14 +% +% A range of options are supplied in the early part of the program +% +% One use of the function is to create demonstrations; filenames +% to illustrate particular features +% +% #1 +% Identify the file (in 'MAPparamsName') containing the model parameters +% +% #2 +% Identify the kind of model required (in 'AN_spikesOrProbability'). +% A full brainstem model (spikes) can be computed or a shorter model +% (probability) that computes only so far as the auditory nerve +% +% #3 +% Choose between a tone signal or file input (in 'signalType') +% +% #4 +% Set the signal rms level (in leveldBSPL) +% +% #5 +% Identify the channels in terms of their best frequencies in the vector +% BFlist. +% +% Last minute changes to the parameters fetched earlier can be made using +% the cell array of strings 'paramChanges'. +% Each string must have the same format as the corresponding line in the +% file identified in 'MAPparamsName' +% +% When the demonstration is satisfactory, freeze it by renaming it + +dbstop if error +restorePath=path; +addpath (['..' filesep 'MAP'], ['..' filesep 'wavFileStore'], ... + ['..' filesep 'utilities']) + +%% #1 parameter file name +MAPparamsName='NormalIC'; + + +%% #2 probability (fast) or spikes (slow) representation +AN_spikesOrProbability='spikes'; + +% or +% NB probabilities are not corrected for refractory effects +% AN_spikesOrProbability='probability'; + + +%% #3 pure tone, harmonic sequence or speech file input +signalType= 'tones'; +sampleRate= 50000; +duration=0.250; % seconds +toneFrequency= 250:250:8000; % harmonic sequence (Hz) +% toneFrequency= 1000; % or a pure tone (Hz8 +rampDuration=.005; % seconds + +% or + +% signalType= 'file'; +% fileName='twister_44kHz'; + + +%% #4 rms level +% signal details +leveldBSPL= 30; % dB SPL + + +%% #5 number of channels in the model +% 21-channel model (log spacing) +numChannels=21; +lowestBF=250; highestBF= 8000; +BFlist=round(logspace(log10(lowestBF), log10(highestBF), numChannels)); + +% or specify your own channel BFs +% numChannels=1; +% BFlist=toneFrequency; + + +%% #6 change model parameters +paramChanges=[]; + +% or +% Parameter changes can be used to change one or more model parameters +% *after* the MAPparams file has been read +% This example declares only one fiber type with a calcium clearance time +% constant of 80e-6 s (HSR fiber) when the probability option is selected. + +% paramChanges={'AN_IHCsynapseParams.ANspeedUpFactor=5;', ... +% 'IHCpreSynapseParams.tauCa=86e-6;'}; + +% paramChanges={'DRNLParams.rateToAttenuationFactorProb = 0;'}; + +% paramChanges={'IHCpreSynapseParams.tauCa=86e-6;', +% 'AN_IHCsynapseParams.numFibers= 1000;'}; + +% fixed MOC attenuation(using negative factor) +paramChanges={'DRNLParams.rateToAttenuationFactorProb=-0.005;'}; + +%% delare 'showMap' options to control graphical output + +showMapOptions.printModelParameters=1; % prints all parameters +showMapOptions.showModelOutput=1; % plot of all stages +showMapOptions.printFiringRates=1; % prints stage activity levels +showMapOptions.showACF=0; % shows SACF (probability only) +showMapOptions.showEfferent=1; % tracks of AR and MOC +showMapOptions.surfProbability=1; % 2D plot of HSR response +showMapOptions.surfSpikes=1; % 2D plot of spikes histogram + +% disable certain silly options +if strcmp(AN_spikesOrProbability, 'spikes') + % avoid nonsensical options + showMapOptions.surfProbability=0; + showMapOptions.showACF=0; +else + showMapOptions.surfSpikes=0; +end +if strcmp(signalType, 'file') + % needed for labeling plot + showMapOptions.fileName=fileName; +else + showMapOptions.fileName=[]; +end + +%% Generate stimuli + +switch signalType + case 'tones' + inputSignal=createMultiTone(sampleRate, toneFrequency, ... + leveldBSPL, duration, rampDuration); + + case 'file' + %% file input simple or mixed + [inputSignal sampleRate]=wavread(fileName); + dt=1/sampleRate; + inputSignal=inputSignal(:,1); + targetRMS=20e-6*10^(leveldBSPL/20); + rms=(mean(inputSignal.^2))^0.5; + amp=targetRMS/rms; + inputSignal=inputSignal*amp; + silence= zeros(1,round(0.1/dt)); + inputSignal= [silence inputSignal' silence]; +end + + +%% run the model +tic + +fprintf('\n') +disp(['Signal duration= ' num2str(length(inputSignal)/sampleRate)]) +disp([num2str(numChannels) ' channel model']) +disp('Computing ...') + +MAP1_14(inputSignal, sampleRate, BFlist, ... + MAPparamsName, AN_spikesOrProbability, paramChanges); + + +% the model run is now complete. Now display the results +UTIL_showMAP(showMapOptions, paramChanges) + +toc +path(restorePath) + + +function inputSignal=createMultiTone(sampleRate, toneFrequency, ... + leveldBSPL, duration, rampDuration) +% Create pure tone stimulus +dt=1/sampleRate; % seconds +time=dt: dt: duration; +inputSignal=sum(sin(2*pi*toneFrequency'*time), 1); +amp=10^(leveldBSPL/20)*28e-6; % converts to Pascals (peak) +inputSignal=amp*inputSignal; + +% apply ramps +% catch rampTime error +if rampDuration>0.5*duration, rampDuration=duration/2; end +rampTime=dt:dt:rampDuration; +ramp=[0.5*(1+cos(2*pi*rampTime/(2*rampDuration)+pi)) ... + ones(1,length(time)-length(rampTime))]; +inputSignal=inputSignal.*ramp; +ramp=fliplr(ramp); +inputSignal=inputSignal.*ramp; + +% add 10 ms silence +silence= zeros(1,round(0.05/dt)); +inputSignal= [silence inputSignal silence]; + diff -r b51bf546ca3f -r 1a502830d462 utilities/stimulusCreate.m --- a/utilities/stimulusCreate.m +++ b/utilities/stimulusCreate.m @@ -1471,7 +1471,8 @@ %--------------------------------------------------------------------checkDescriptors -function [globalStimParams, stimComponents]=checkDescriptors(globalStimParams, stimComponents); +function [globalStimParams, stimComponents]=... + checkDescriptors(globalStimParams, stimComponents) try % if FS exists, it takes priority @@ -1481,7 +1482,10 @@ globalStimParams.FS=1/globalStimParams.dt; end -globalStimParams.nSignalPoints=round(globalStimParams.overallDuration/globalStimParams.dt); +sampleRate=globalStimParams.FS; + +globalStimParams.nSignalPoints=... + round(globalStimParams.overallDuration* sampleRate); % optional field (ears) try @@ -1514,8 +1518,6 @@ globalStimParams.doPlot=0; end - - [ears nComponentSounds]=size(stimComponents); for ear=1:2 % 1=left/ 2=right @@ -1567,16 +1569,17 @@ % end silence is measured to fit into the global duration if stimComponents(ear,componentNo).endSilence==-1, - endSilenceNpoints=... - globalStimParams.nSignalPoints ... - -round(stimComponents(ear,componentNo).beginSilence*globalStimParams.FS)... - -round(stimComponents(ear,componentNo).toneDuration*globalStimParams.FS); - stimComponents(ear,componentNo).endSilence=endSilenceNpoints/globalStimParams.FS; - % if endSilence < 0, we have a problem - if stimComponents(ear,componentNo).endSilence<0 - globalStimParams - descriptorError( 'component durations greater than overallDuration', stimComponents, ear, componentNo) - end + stimComponents(ear,componentNo).endSilence=... + globalStimParams.overallDuration-... + stimComponents(ear,componentNo).beginSilence -... + stimComponents(ear,componentNo).toneDuration; + + endSilenceNpoints=stimComponents(ear,componentNo).endSilence... + *sampleRate; + end + if stimComponents(ear,componentNo).endSilence<0 + globalStimParams + descriptorError( 'component durations greater than overallDuration', stimComponents, ear, componentNo) end % check overall duration of this component against global duration @@ -1590,26 +1593,12 @@ globalStimParams.overallDuration= totalDuration; end - - if round(totalDuration*globalStimParams.FS)>round(globalStimParams.overallDuration*globalStimParams.FS) - globalStimParams - descriptorError( 'Component durations greater than overallDuration', stimComponents, ear, componentNo) - end - % check total duration - totalSignalPoints= round((stimComponents(ear,componentNo).beginSilence+ stimComponents(ear,componentNo).toneDuration+... - stimComponents(ear,componentNo).endSilence)/globalStimParams.dt); + totalSignalPoints= round(totalDuration* sampleRate); if totalSignalPoints >globalStimParams.nSignalPoints descriptorError( 'Signal component duration does not match overall duration ', stimComponents, ear, componentNo) end - % no ramps for clicks please! - % if strcmp(stimComponents(ear,componentNo).type, 'clicks') & stimComponents(ear,componentNo).clickRepeatFrequency==-1 - % if strcmp(stimComponents(ear,componentNo).type, 'clicks') - % stimComponents(ear,componentNo).rampOnDur=0; - % stimComponents(ear,componentNo).rampOffDur=0; - % end - if isfield(stimComponents(ear,componentNo), 'filter') if ~isequal(length(stimComponents(ear,componentNo).filter), 3) descriptorError( 'Filter parameter must have three elements ', stimComponents, ear, componentNo)