Gap junction coupled network of striatal fast spiking interneurons (Hjorth et al. 2009)

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Accession:118389
Gap junctions between striatal FS neurons has very weak ability to synchronise spiking. Input uncorrelated between neighbouring neurons is shunted, while correlated input is not.
Reference:
1 . Hjorth J, Blackwell KT, Kotaleski JH (2009) Gap junctions between striatal fast-spiking interneurons regulate spiking activity and synchronization as a function of cortical activity. J Neurosci 29:5276-86 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Neuron or other electrically excitable cell; Synapse; Channel/Receptor; Dendrite;
Brain Region(s)/Organism: Basal ganglia;
Cell Type(s): Neostriatum fast spiking interneuron;
Channel(s): I A; I_K,Na;
Gap Junctions: Gap junctions;
Receptor(s):
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: GENESIS; MATLAB;
Model Concept(s): Activity Patterns; Ion Channel Kinetics; Synchronization; Detailed Neuronal Models;
Implementer(s): Hjorth, Johannes [hjorth at csc.kth.se];
Search NeuronDB for information about:  I A; I_K,Na; Gaba; Glutamate;
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FSGJ_Hjorth2009
matlabScripts
checkAllEqual.m *
correlationByDuplicationOfSpikes.m
correlationByJitteringOfSpikes.m
countSpikesWithNumNeighbourSpikes.m
findSpikes.m *
gaussJitterInputKeepCorr.m
makeAllExternalInputAllUpstate.m
makeDaughterInsignal.m
makeDaughterNoise.m *
makeFSconnectionMatrixOnlyPrimWrappedSetNGJ.m
makeFSconnectionMatrixOnlySecWrappedSetNGJ.m
makeFSMorph.m
makeFSrandomNetwork.m *
makeInputWithCorrShift.m
makeInputWithCorrShift125center.m
makeSCCCplot.m
makeTrainInsignal.m
makeTrainNoise.m *
mixTwoTrainsKeepCorr.m
poissonMaxTime.m *
showFSnetwork.m
writeCurrentInputInfo.m
writeInput.m *
writeParameters.m
                            
%
% Generates 2Hz square waves with 0.5 dutycycle.
%

function insignal = makeTrainInsignal(corrRudolph, nTrains, ...
                                      upFreq, downFreq, maxTime)

  nRudolph = nTrains - sqrt(corrRudolph)*(nTrains-1);

  baseFreq = 2;
  dutyCycle = 0.5;
  
  stateTime = dutyCycle/baseFreq;
  
  
  for i=1:nRudolph

    isUpstate = 1; % Start with upstate
    startTime = 0;

    trainSpikes{i} = [];
    
    for startTime = 0:stateTime:(maxTime-stateTime)

      if(isUpstate)
          curFreq = upFreq;          
      else
          curFreq = downFreq;          
      end
      
      trainSpikes{i} = [trainSpikes{i}; ...
                        startTime + poissonMaxTime(curFreq, stateTime)];
      
      isUpstate = ~isUpstate;
      
    end          
         
  end
  
  allSpikes = [];
  
  for i=1:nRudolph
      allSpikes = [allSpikes; trainSpikes{i}];
  end
  
  % Sortera spikarna!
  allSpikes = sort(allSpikes);
  
  disp('total antal spikar     unika')
  [length(allSpikes) length(unique(allSpikes))]

  for i=1:nTrains
    finalSpikes{i} = [];
  end
  
  for i=1:length(allSpikes)
     repeats = nTrains / nRudolph;
     repeats = floor(repeats) + (rand(1) < mod(repeats,1));

     freeTrains = 1:nTrains;
     
     for j=1:repeats
         idx = ceil(length(freeTrains)*rand(1));
         trainIdx = freeTrains(idx);
         freeTrains(idx) = [];
         
         finalSpikes{trainIdx} = [finalSpikes{trainIdx}; allSpikes(i)];
     end     
  end

  
  for i=1:nTrains
     trainLen(i) = length(finalSpikes{i}); 
  end

  maxLen = max(trainLen); 
  insignal = inf*ones(maxLen,nTrains);

  for i=1:nTrains
     insignal(1:length(finalSpikes{i}),i) = finalSpikes{i}; 
      
  end
  

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