view userProgramsRM/test_Dolan_and_Nuttall.m @ 38:c2204b18f4a2 tip

End nov big change

function test_Dolan_and_Nuttall
% 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 <demoxx>
%  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 <demoxx>

global dt dtSpikes  savedBFlist saveAN_spikesOrProbability saveMAPparamsName...
    savedInputSignal OMEextEarPressure TMoutput OMEoutput ARattenuation ...
    DRNLoutput IHC_cilia_output IHCrestingCiliaCond IHCrestingV...
    IHCoutput ANprobRateOutput ANoutput savePavailable ANtauCas  ...
    CNtauGk CNoutput  ICoutput ICmembraneOutput ICfiberTypeRates ...
    MOCattenuation
global OMEParams DRNLParams IHC_cilia_RPParams IHCpreSynapseParams
global AN_IHCsynapseParams MacGregorParams MacGregorMultiParams
global ICrate


dbstop if error
restorePath=path;
addpath (['..' filesep 'MAP'],    ['..' filesep 'wavFileStore'], ...
    ['..' filesep 'utilities'])

%%  #1 parameter file name
MAPparamsName='Normal';


%% #2 probability (fast) or spikes (slow) representation
AN_spikesOrProbability='spikes';
%   or
% AN_spikesOrProbability='probability';


%% #3 pure tone, harmonic sequence or speech file input
signalType= 'tones';
toneFrequency= 4000;            % or a pure tone (Hz)

sampleRate= 44100;          % must agree with noise
duration=0.010;                 % seconds
beginSilence=0.010;
endSilence=0.010;
rampDuration=.001;              % raised cosine ramp (seconds)
noiseRampDuration=0.002;

%   or
% harmonic sequence (Hz)
% F0=210;
% toneFrequency= F0:F0:8000;

%   or
% signalType= 'file';
% fileName='twister_44kHz';



% %% #4 rms level
% % signal details
% leveldBSPL= 80;                  % dB SPL (80 for Lieberman)
% leveldBSPLNoise=-30;

%% #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={};

% 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.MOCtauProb =.25;', ...
%     'DRNLParams.rateToAttenuationFactorProb = 0.02; '};

paramChanges={'AN_IHCsynapseParams.numFibers=	50; ',...
    'DRNLParams.MOCtauProb =.15;', ...
    'DRNLParams.rateToAttenuationFactorProb = 0.00; '};

% paramChanges={'AN_IHCsynapseParams.numFibers=	50; ',...
% 'DRNLParams.rateToAttenuationFactorProb = -0.007;'};


%% delare 'showMap' options to control graphical output
showMapOptions.printModelParameters=1;   % prints all parameters
showMapOptions.showModelOutput=0;       % 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
showMapOptions.ICrates=0;               % IC rates by CNtauGk

% disable certain silly options
if strcmp(AN_spikesOrProbability, 'spikes')
    % avoid nonsensical options
    showMapOptions.surfProbability=0;
    showMapOptions.showACF=0;
end

if strcmp(signalType, 'file')
    % needed for labeling plot
    showMapOptions.fileName=fileName;
else
    showMapOptions.fileName=[];
end

fprintf('\n')
disp([num2str(numChannels) ' channel model: ' AN_spikesOrProbability])
disp('Computing ...')

%%systematic
probeLevels=30:10:80;
noiseLevels=[-100 30];
noRepeats=10;

% probeLevels=80;
% noiseLevels=[-30];
% noRepeats=10;

peakCAPs=zeros(4,length(probeLevels));

for noiseCondition=1:length(noiseLevels)
    leveldBSPLNoise=noiseLevels(noiseCondition);
    levelNo=0;
    for probeLevel=probeLevels
        leveldBSPL=probeLevel;
        levelNo=levelNo+1;
        summedCAP=[];
        for repeatNo= 1:noRepeats
            disp(['repeat no: ' num2str(repeatNo)])
            %% Generate stimuli

            switch signalType
                case 'tones'
                    % 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 silence
                    intialSilence= zeros(1,round(beginSilence/dt));
                    finalSilence= zeros(1,round(endSilence/dt));
                    inputSignal= [intialSilence inputSignal finalSilence];

                    %         [inputNoise sampleRateN]=wavread('babble');
                    [inputNoise sampleRateN]=wavread('white noise');
                    inputNoise=inputNoise(1:length(inputSignal));
                    inputNoise=inputNoise(:,1);
                    targetRMS=20e-6*10^(leveldBSPLNoise/20);
                    rms=(mean(inputNoise.^2))^0.5;
                    amp=targetRMS/rms;
                    inputNoise=inputNoise*amp;
                    time=dt: dt: dt*length(inputNoise);
                    rampTime=dt:dt:noiseRampDuration;
                    ramp=[0.5*(1+cos(2*pi*rampTime/(2*noiseRampDuration)+pi)) ...
                        ones(1,length(time)-length(rampTime))];
                    inputNoise=inputNoise'.*ramp;
                    ramp=fliplr(ramp);
                    inputNoise=inputNoise.*ramp;

                    inputSignal=inputSignal+inputNoise;
                    intialSilence= zeros(1,round(beginSilence/dt));
                    finalSilence= zeros(1,round(endSilence/dt));
                    inputSignal= [intialSilence inputSignal finalSilence];

                    toneOnset=2*beginSilence;

                    figure(2), subplot(3,1,1)
                    time=dt:dt:dt*length(inputSignal);
                    plot(time,inputSignal,'k')

                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;
                    intialSilence= zeros(1,round(0.1/dt));
                    finalSilence= zeros(1,round(0.2/dt));
                    inputSignal= [intialSilence inputSignal' finalSilence];

            end


            %% run the model
            tic

            MAP1_14(inputSignal, sampleRate, BFlist, ...
                MAPparamsName, AN_spikesOrProbability, paramChanges);


            %% the model run is now complete. Now display the results
                %                 UTIL_showMAP(showMapOptions, paramChanges)

                wholeNerveCAP  = UTIL_CAPgenerator...
                    (ANoutput, dtSpikes, BFlist, AN_IHCsynapseParams.numFibers, 1);

                if isempty(summedCAP)
                    summedCAP=wholeNerveCAP;
                else
                    summedCAP=summedCAP+wholeNerveCAP;
                end

                switch AN_spikesOrProbability
                    case 'spikes'
                        ANoutput = sum(ANoutput, 1);
                    case 'probability'
                        ANoutput = ANprobRateOutput(13+21,:);
                end
                figure(2), subplot(3,1,2), plot(ANoutput)
                spikeTimes=dtSpikes:dtSpikes:dtSpikes* length(wholeNerveCAP);
                figure(2), subplot(3,1,3), plot(spikeTimes,summedCAP/repeatNo)
                ylim([-50 50])
        end % repeat

        spikeTimes=dtSpikes:dtSpikes:dtSpikes* length(wholeNerveCAP);
        idx=find(spikeTimes>toneOnset & ...
            spikeTimes>toneOnset+duration+.005);
        averageCAP=summedCAP/repeatNo;
        peakCAP=max(averageCAP(idx));
        peakCAPs(noiseCondition,levelNo)=peakCAPs(noiseCondition,levelNo)+ peakCAP;

        if strcmp(signalType,'tones')
            disp(['duration=' num2str(duration)])
            disp(['level=' num2str(leveldBSPL)])
            disp(['toneFrequency=' num2str(toneFrequency)])
            disp(['leveldBSPLNoise=' num2str(leveldBSPLNoise)])

            disp(['attenuation factor =' ...
                num2str(DRNLParams.rateToAttenuationFactor, '%5.3f') ])
            disp(['attenuation factor (probability)=' ...
                num2str(DRNLParams.rateToAttenuationFactorProb, '%5.3f') ])
            disp(AN_spikesOrProbability)
        end


        disp([ 'peak CAP ' num2str(peakCAP)])

        for i=1:length(paramChanges)
            disp(paramChanges{i})
        end
    end % probe level
    figure(9), subplot(3,1,3), plot(probeLevels,peakCAPs)
end % condition
%%

path(restorePath)