Examples of edu.jhu.mb.ernst.model.Synapse

edu.jhu.mb.ernst.model.Synapse
Accessor interface for the neuron synaptic structure. @version $Date: 2012-04-15 13:41:48 -0500 (Sun, 15 Apr 2012) $ $Rev: 8 $ $Author: croft $ @author Yi Dong @author David Wallace Croft


      assertEquals ( -1, timeOfNextFire0, 0 );


      final double  weight = 1e-9;   


      final Synapse  synapse = MODEL_FACTORY.createSynapse (
        0,   // to
        ( byte ) 0, // type (0 = excitatory)
        ( float ) weight );


      double  timeOfNextFire = neuron.updateInput (

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      assertEquals ( -1, timeOfNextFire0, 0 );
      
      final double  weight = SIFNeuron.maxWeight / 10;
      
      final Synapse  synapse = MODEL_FACTORY.createSynapse (
        0, // to
        ( byte ) 0, // type (0 = excitatory)
        ( float ) weight );
      
      final double  timeOfNextFire1 = neuron.updateInput (

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      assertEquals ( -1, timeOfNextFire0, 0 );
      
      final double  weight = VSICLIFNeuron.maxWeight / 10;   
      
      final Synapse  synapse = MODEL_FACTORY.createSynapse (
        0,   // to
        ( byte ) 0, // type (0 = excitatory)
        ( float ) weight );
      
      final double  timeOfNextFire1 = neuron.updateInput (

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            {
              final double  inputEventTime
                = -Math.log ( Cnsran.ran2 ( seed ) )
                  / simulatorParser.backgroundFrequency;
              
              final Synapse  synapse = modelFactory.createSynapse (
                base + i,
                ( byte ) simulatorParser.bChannel,
                ( float ) simulatorParser.backgroundStrength );
              
              final PInputEvent  pInputEvent = new PInputEvent (

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          relativeStrength = relativeStrengthList.get ( i ).doubleValue ( );


        final double
          synapseStrength = relativeStrength * strength; 


        final Synapse  synapse = modelFactory.createSynapse (
          toNeuronIndex,
          ( byte ) type,
          ( float ) synapseStrength );


        final double  time = getNextTime ( onTime );

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      int ymagratio=0;
      int xborder,yborder;
      int newx=0;
      int newy=0;
      String fromNeur,toNeur;
      Synapse syn;
      TreeSet<Synapse> synapses;
      int[] xy=new int[2];




      if(type==1&&stre>0) // these maynot be useful for new neuronal model

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      // Update STDP variables.
        
        for ( final Map.Entry<Synapse,TimeWeight>  entry
          : histTable.entrySet ( ) )
        {
          final Synapse  syn = entry.getKey ( );
          
          // Get the relative weight.
          
          final TimeWeight  tw = entry.getValue();


          // Channel 0 has STDP.
          
          if ( syn.getType ( ) == 0 )
          {
            // LTP only for close spikes.
            
            if ( lastFireTime < tw.time )
            {

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        //Iterator<Synapse,WeightTime> it = histTable.iterator();
        
        for ( final Map.Entry<Synapse,TimeWeight>  entry
          : histTable.entrySet ( ) )
        {
          final Synapse  syn = entry.getKey ( );
          
          // get the relative weight
          
          final TimeWeight  tw = entry.getValue();


          // channel 0 has STDP
          
          if ( syn.getType ( ) == 0 )
          {
            // LTP only for close spikes
            
            if ( lastFireTime < tw.time )
            {

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Related Classes of edu.jhu.mb.ernst.model.Synapse

cnslab.cnsnetwork.LayerStructure

cnslab.cnsnetwork.MiNiNeuron

cnslab.cnsnetwork.Network

cnslab.cnsnetwork.Stimulus

cnslab.cnsnetwork.VSICLIFNeuronV2

edu.jhu.mb.ernst.test.ErnstMiNiNeuronTest

edu.jhu.mb.ernst.test.ErnstSifNeuronTest

edu.jhu.mb.ernst.test.ErnstVsiclifNeuronTest

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