MAP

% Fiber types are specified in terms of tauCa

nANfiberTypes= length(IHCpreSynapseParams.tauCa);

tauCas= IHCpreSynapseParams.tauCa;

% Calcium control (more calcium, greater release rate)

ECa=IHCpreSynapseParams.ECa;

gamma=IHCpreSynapseParams.gamma;

beta=IHCpreSynapseParams.beta;

tauM=IHCpreSynapseParams.tauM;

GmaxCa=IHCpreSynapseParams.GmaxCa;

synapse_z= IHCpreSynapseParams.z;

synapse_power=IHCpreSynapseParams.power;

% 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);

% proportion (0 - 1) of Ca channels open at IHCrestingV

mICaCurrent=((1+beta^-1 * exp(-gamma*IHCrestingV))^-1)...

    *ones(nBFs*nANfiberTypes,1);

% 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;

AN_refractory_period= AN_IHCsynapseParams.refractory_period;

y=AN_IHCsynapseParams.y;

M=round(AN_IHCsynapseParams.M);

% probability            (NB initial 'P' on everything)

PAN_rdt_plus_ldt = PAN_rdt + PAN_ldt;

PAN_M=round(AN_IHCsynapseParams.M);

Pavailable    = Pcleft*(l+r)./kt0;

Preprocess    = Pcleft*r/x; % canbe fractional

lengthAbsRefractoryP= round(AN_refractory_period/dt);

% special variables for monitoring synaptic cleft (specialists only)

% spikes     % !  !  !    ! !        !   !  !

lengthAbsRefractory= round(AN_refractory_period/ANdt);

%% 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

% CNtauGk (Potassium time constant) determines the rate of firing of

%  the unit when driven hard by a DC input (not normally >350 sp/s)

ANavailableFibersPerChan=AN_IHCsynapseParams.numFibers;

CNmembranePotential=zeros(nCNneurons,reducedSegmentLength);

% establish which ANfibers (by name) feed into which CN nuerons

unitNo=1;

    % Each channel contains a number of units =length(listOfFanInValues)

    for idx=1:nCNneuronsPerChannel

    end

end

CNtimeSinceLastSpike=zeros(nCNneurons,1);

% tauGk is the main distinction between neurons

%  in fact they are all the same in the standard model

CNoutput=false(nCNneurons,reducedSignalLength);

%% MacGregor (IC - second nucleus) --------

ICspikeWidth=0.00015;   % this may need revisiting

epochsPerSpike=round(ICspikeWidth/ANdt);

ICtrailingAlphas=zeros(nICcells, length(IC_CNalphaFunction));

ICfiberTypeRates=zeros(nANfiberTypes,reducedSignalLength);

ICmembranePotential=zeros(nICcells,reducedSegmentLength);

ICmembraneOutput=zeros(nICcells,signalLength);

                % releaseProb is the release probability per channel

                %  but each channel has many synapses

                releaseProb=repmat(releaseProb',nFibersPerChannel,1);

                % AN_available=round(AN_available); % vesicles must be integer, (?needed)

                M_q=AN_M- AN_available;     % number of missing vesicles

            % Create the dendritic current for that neuron

            % First get input spikes to this neuron

            synapseNo=1;

                for idx=1:nCNneuronsPerChannel

                    % determine candidate fibers for this unit

                    fibersUsed=CNinputfiberLists(synapseNo,:);

            %% IC ----------------------------------------------

                %  MacGregor or some other second order neurons

                %  to generate inputs to single IC unit

                channelNo=0;

                for idx=1:nCNneuronsPerChannel:nCNneurons-nCNneuronsPerChannel+1;