MAP

function vectorStrength=testAN(probeFrequency,BFlist, levels, ...

    paramsName,paramChanges)

% testAN generates rate/level functions for AN and brainstem units.

%  also other information like PSTHs, MOC efferent activity levels.

% Vector strength calculations require the computation of period

% histograms. for this reason the sample rate must always be an integer

% multiple of the tone frequency. This applies to both the sampleRate and

% the spikes sampling rate.

% A full 'spikes' model is used.

% paramChanges is a cell array of strings containing MATLAB statements that

% change model parameters. See MAPparamsNormal for examples.

% e.g.

% testAN(1000,1000, -10:10:80,'Normal',{});

global IHC_VResp_VivoParams  IHC_cilia_RPParams IHCpreSynapseParams

global AN_IHCsynapseParams

global ANoutput dtSpikes CNoutput ICoutput ICmembraneOutput ANtauCas

global ARattenuation MOCattenuation

tic

dbstop if error

restorePath=path;

addpath (['..' filesep 'MAP'], ['..' filesep 'utilities'], ...

    ['..' filesep 'parameterStore'],  ['..' filesep 'wavFileStore'],...

    ['..' filesep 'testPrograms'])

if nargin<5, paramChanges={'IHCpreSynapseParams.tauCa= [30e-6 90e-6];'}; end

if nargin<4, paramsName='PL'; end

if nargin<3, levels=-10:10:80; end

if nargin==0, probeFrequency=1000; BFlist=1000; end

nLevels=length(levels);

toneDuration=.2;   rampDuration=0.005;   silenceDuration=.02;

localPSTHbinwidth=0.001;

%% guarantee that the sample rate is an interger multiple

%   of the probe frequency

% we want 5 bins per period for spikes

spikesSampleRate=5*probeFrequency;

% model sample rate must be an integer multiple of this and in the region

% of 50000

sampleRate=spikesSampleRate*round(50000/spikesSampleRate);

dt=1/sampleRate;

% avoid very slow spikes sampling rate

spikesSampleRate=spikesSampleRate*ceil(10000/spikesSampleRate);

%% pre-allocate storage

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);

figure(15), clf

set(gcf,'position',[980   356   401   321])

figure(5), clf

set(gcf,'position', [980 34 400 295])

drawnow

%% main computational loop (vary level)

levelNo=0;

for leveldB=levels

    levelNo=levelNo+1;

    amp=28e-6*10^(leveldB/20);

    fprintf('%4.0f\t', leveldB)

    %% generate tone and silences

    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));

    inputSignal=amp*sin(2*pi*probeFrequency'*time);

    inputSignal= ramp.*inputSignal;

    inputSignal=[silence inputSignal];

    %% run the model

    AN_spikesOrProbability='spikes';

    nExistingParamChanges=length(paramChanges);

    paramChanges{nExistingParamChanges+1}=...

        ['AN_IHCsynapseParams.spikesTargetSampleRate=' ...

        num2str(spikesSampleRate) ';'];

    MAP1_14(inputSignal, 1/dt, BFlist, ...

        paramsName, AN_spikesOrProbability, paramChanges);

    nTaus=length(ANtauCas);

    %% Auditory nerve evaluate and display (Fig. 5)

    %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, dtSpikes, 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));

    % AN HSR

    HSRspikes= ANoutput(end- numHSRfibers+1:end, :);

    PSTH=UTIL_PSTHmaker(HSRspikes, dtSpikes, 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])

    grid on

    set(gcf,'name',['PSTH: ' 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, dtSpikes);

    % AN - vector strength

    PSTH=sum(CNoutput (11:20,:));

    [PH, binTimes]=UTIL_periodHistogram...

        (PSTH, dtSpikes, probeFrequency);

    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 driven by LSR fibers

    [nCNneurons c]=size(CNoutput);

    nLSRneurons=round(nCNneurons/nTaus);

    CNLSRspikes=CNoutput(1:nLSRneurons,:);

    PSTH=UTIL_PSTHmaker(CNLSRspikes, dtSpikes, localPSTHbinwidth);

    PSTH=sum(PSTH)/nLSRneurons;

%     CNLSRrate(levelNo)=mean(PSTH(round(length(PSTH)/2):end))/localPSTHbinwidth;

    CNLSRrate(levelNo)=mean(PSTH)/localPSTHbinwidth;

    %CN HSR

    MacGregorMultiHSRspikes=...

        CNoutput(end-nLSRneurons+1:end,:);

    PSTH=UTIL_PSTHmaker(MacGregorMultiHSRspikes, dtSpikes, localPSTHbinwidth);

    PSTH=sum(PSTH)/nLSRneurons;

    PSTH=mean(PSTH,1)/localPSTHbinwidth; % sum across fibers (HSR only)

%     CNHSRsaturated(levelNo)=mean(PSTH(length(PSTH)/2:end));

    CNHSRsaturated(levelNo)=mean(PSTH);

    figure(5), subplot(2,2,3)

    bar(PSTHtime,PSTH)

    ylim([0 1000])

    xlim([0 length(PSTH)*localPSTHbinwidth])

    cvMMHSR= UTIL_CV(MacGregorMultiHSRspikes, dtSpikes);

    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, dtSpikes, localPSTHbinwidth);

%     ICLSRsaturated(levelNo)=mean(PSTH(round(length(PSTH)/2):end))/localPSTHbinwidth;

    ICLSRsaturated(levelNo)=mean(PSTH)/localPSTHbinwidth;

    %IC HSR

    MacGregorMultiHSRspikes=...

        ICoutput(end-nLSRneurons+1:end,:);

    PSTH=UTIL_PSTHmaker(MacGregorMultiHSRspikes, dtSpikes, localPSTHbinwidth);

    ICHSRsaturated(levelNo)= (sum(PSTH)/nLSRneurons)/toneDuration;

    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 HSR (last of two)

    plot(time,ICmembraneOutput(end-nLSRneurons+1, 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'), hold on

    plot(20*log10(AR), 'r'), hold off

    title(' MOC'), ylabel('dB attenuation')

    ylim([-30 0])

%     x=input('prompt')

end % level

%% plot with levels on x-axis

figure(5), subplot(2,2,1)

plot(levels,20*log10(MOC), 'k'),hold on

plot(levels,20*log10(AR), 'r'), hold off

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 summary results (Fig 15)

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])

if length(levels)>1

    xlim([min(levels) max(levels)])

end

ttl=['tauCa= ' num2str(IHCpreSynapseParams.tauCa)];

title( ttl)

xlabel('level dB SPL'), ylabel('peak rate (sp/s)'), grid on

text(0, 800, 'AN onset', 'fontsize', 14)

% 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)

if length(levels)>1

xlim([min(levels) max(levels)])

end

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', 14), grid on

% CN rate - level 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)

if length(levels)>1

xlim([min(levels) max(levels)])

end

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', 14), grid on

% IC rate - level 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)

if length(levels)>1

xlim([min(levels) max(levels)])

end

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', 14)

set(gcf,'name',' AN CN IC rate/level')

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))

path(restorePath)

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