KInNeSS : a modular framework for computational neuroscience (Versace et al. 2008)

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Accession:113939
The xml files provided here implement a network of excitatory and inhibitory spiking neurons, governed by either Hodgkin-Huxley or quadratic integrate-and-fire dynamical equations. The code is used to demonstrate the capabilities of the KInNeSS software package for simulation of networks of spiking neurons. The simulation protocol used here is meant to facilitate the comparison of KInNeSS with other simulators reviewed in <a href="http://dx.doi.org/10.1007/s10827-007-0038-6">Brette et al. (2007)</a>. See the associated paper "Versace et al. (2008) KInNeSS : a modular framework for computational neuroscience." for an extensive description of KInNeSS .
Reference:
1 . Versace M, Ames H, Léveillé J, Fortenberry B, Gorchetchnikov A (2008) KInNeSS: a modular framework for computational neuroscience. Neuroinformatics 6:291-309 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s): Neocortex V1 L6 pyramidal corticothalamic GLU cell; Neocortex V1 L2/6 pyramidal intratelencephalic GLU cell;
Channel(s): I Chloride; I Na,t; I K;
Gap Junctions:
Receptor(s): GabaA; AMPA;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: KInNeSS; NeuroML;
Model Concept(s): Activity Patterns; Methods;
Implementer(s): Gorchetchnikov, Anatoli [anatoli at cns.bu.edu];
Search NeuronDB for information about:  Neocortex V1 L6 pyramidal corticothalamic GLU cell; Neocortex V1 L2/6 pyramidal intratelencephalic GLU cell; GabaA; AMPA; I Chloride; I Na,t; I K; Gaba; Glutamate;
<!DOCTYPE neuroml>
<neuroml class="NeuromlPkg" version="1.3(KInNeSS)" author="Anatoli Gorchetchnikov" keywords="" description="Network to test performance for the paper using Hodgkin-Huxley spike generation" date="2007-11-30" >
 <models>
  <model class="NetworkPkg" name="KInNeSS_libkingeneric" >
   <network name="PaperHH" lastEdited="Network->Inhibitory->Soma" >
    <populations>
     <population name="Excitatory" lastEdited="Excitatory->Soma->4: GABA_A Fast" >
      <structure factorX="2" factorY="2" class="Grid2DStructure" scalingX="up" type="external" scalingY="up" />
      <neuron class="CableNeuron" >
       <structure class="tree" >
        <OrientedSubstructure output="false" diameter="0.002" length="0.005" monitorSpikes="true" E_leak="-60" g_leak="0.01" name="Soma" lastEdited="Compartment" monitor="false" >
         <channel name="Injection" lastEdited="1: My Channel" >
          <gatingVariable dependency="injection" input1="1e-07" input2="0" name="m1" input3="0" input4="0" >
           <refToSourceMethod target="connectFromMany" offset="scaled" >
            <Kernel ring="false" sigma_x="0.45" borderEffect="wrap" sigma_y="0.45" />
           </refToSourceMethod>
          </gatingVariable>
         </channel>
         <channel g_bar="50" equilibriumPotential="50" name="Na (Traub &amp; Miles, 91)" lastEdited="1: My Channel" >
          <gatingVariable exponent="3" format="alpha/beta" dependency="voltage" name="m1" representationForm="Parametrised" >
           <representation>
            <forward category="Linoid" V0="13" A="0.32" B="4" />
            <backward category="Linoid" V0="40" A="-0.28" B="-5" />
           </representation>
          </gatingVariable>
          <gatingVariable exponent="1" format="alpha/beta" dependency="voltage" name="m2" representationForm="Parametrised" >
           <representation>
            <forward category="Exponential" V0="17" A="0.128" B="18" />
            <backward category="Sigmoid" V0="40" A="4" B="5" />
           </representation>
          </gatingVariable>
         </channel>
         <channel g_bar="30" equilibriumPotential="-90" name="K_dr (Traub &amp; Miles, 91)" lastEdited="1: My Channel" >
          <gatingVariable exponent="4" dependency="voltage" format="alpha/beta" name="m1" representationForm="Parametrised" >
           <representation>
            <forward category="Linoid" V0="15" A="0.032" B="5" />
            <backward category="Exponential" V0="10" A="0.5" B="40" />
           </representation>
          </gatingVariable>
         </channel>
         <channel g_bar="2.5" equilibriumPotential="-70" name="GABA_A Fast" lastEdited="1: My Channel" >
          <gatingVariable tau_r="1" dependency="ligand" tau_f="7" name="m1" >
           <projection modifiable="false" >
            <refToPopulation target="Inhibitory" >
             <axonalDelay value="1" type="fixed" />
            </refToPopulation>
            <refToSourceMethod target="connectFromMany" offset="scaled" >
             <Kernel ring="false" sigma_x="1.15" borderEffect="wrap" sigma_y="1.15" />
             <synapticWeight value="0.45" type="fixed" />
            </refToSourceMethod>
           </projection>
          </gatingVariable>
         </channel>
        </OrientedSubstructure>
       </structure>
      </neuron>
     </population>
     <population name="Inhibitory" lastEdited="Inhibitory->Soma->3: AMPA" >
      <structure class="Grid2DStructure" type="external" />
      <neuron class="CableNeuron" >
       <structure class="tree" >
        <OrientedSubstructure output="false" diameter="0.002" length="0.002" g_leak="0.025" E_leak="-60" monitorSpikes="true" name="Soma" lastEdited="Compartment" monitor="false" >
         <channel g_bar="50" equilibriumPotential="50" name="Na (Traub &amp; Miles, 91)" lastEdited="1: My Channel" >
          <gatingVariable exponent="3" dependency="voltage" format="alpha/beta" name="m1" representationForm="Parametrised" >
           <representation>
            <forward category="Linoid" V0="13" A="0.32" B="4" />
            <backward category="Linoid" V0="40" A="-0.28" B="-5" />
           </representation>
          </gatingVariable>
          <gatingVariable exponent="1" dependency="voltage" format="alpha/beta" name="m2" representationForm="Parametrised" >
           <representation>
            <forward category="Exponential" V0="17" A="0.128" B="18" />
            <backward category="Sigmoid" V0="40" A="4" B="5" />
           </representation>
          </gatingVariable>
         </channel>
         <channel g_bar="30" equilibriumPotential="-90" name="K_dr (Traub &amp; Miles, 91)" lastEdited="1: My Channel" >
          <gatingVariable exponent="4" format="alpha/beta" dependency="voltage" name="m1" representationForm="Parametrised" >
           <representation>
            <forward category="Linoid" V0="15" A="0.032" B="5" />
            <backward category="Exponential" V0="10" A="0.5" B="40" />
           </representation>
          </gatingVariable>
         </channel>
         <channel g_bar="0.1" equilibriumPotential="0" name="AMPA" lastEdited="1: My Channel" >
          <gatingVariable tau_r="2" dependency="ligand" tau_f="2" name="m1" >
           <projection modifiable="false" >
            <refToPopulation target="Excitatory" >
             <axonalDelay type="fixed" value="1" />
            </refToPopulation>
            <refToSourceMethod offset="scaled" target="connectFromMany" >
             <Kernel ring="false" sigma_x="1" sigma_y="1" borderEffect="wrap" />
             <synapticWeight type="fixed" value="0.25" />
            </refToSourceMethod>
           </projection>
          </gatingVariable>
         </channel>
        </OrientedSubstructure>
       </structure>
      </neuron>
     </population>
    </populations>
   </network>
  </model>
 </models>
</neuroml>