MAP

function Pavel_MAP1_14

% 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>

%%  #1 parameter file name

MAPparamsName='Normal';

%% #2 probability (fast) or spikes (slow) representation

AN_spikesOrProbability='spikes';

% or

% AN_spikesOrProbability='probability';

% NB probabilities are not corrected for refractory effects

%% #3 pure tone, harmonic sequence or speech file input

signalType= 'tones';

sampleRate= 100000;

duration=0.1;                 % 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.

% It also removes the speed up that normally takes place for AN spikes

% It also increases the number of AN fibers computed to 500.

paramChanges={...

    'AN_IHCsynapseParams.ANspeedUpFactor=1;', ...

    'IHCpreSynapseParams.tauCa=86e-6;',...

    'AN_IHCsynapseParams.numFibers=	500;' };

%% delare 'showMap' options to control graphical output

global showMapOptions

% or (example: show everything including an smoothed SACF 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=0;          % tracks of AR and MOC

showMapOptions.surfProbability=0;       % 2D plot of HSR response 

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

%% Generate stimuli

dbstop if error

restorePath=path;

addpath (['..' filesep 'MAP'],    ['..' filesep 'wavFileStore'])

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 ...')

restorePath=path;

addpath (['..' filesep 'MAP'])

MAP1_14(inputSignal, sampleRate, BFlist, ...

    MAPparamsName, AN_spikesOrProbability, paramChanges);

path(restorePath)

toc

% the model run is now complete. Now display the results

% the model run is now complete. Now display the results

disp(' param changes to list of parameters below')

for i=1:length(paramChanges)

    disp(paramChanges{i})

end

UTIL_showMAP(showMapOptions)

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(0.03/dt));

inputSignal= [silence inputSignal silence];