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Input Fluctuations effects on f-I curves (Arsiero et al. 2007)

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Accession:83590
"... We examined in vitro frequency versus current (f-I) relationships of layer 5 (L5) pyramidal cells of the rat medial prefrontal cortex (mPFC) using fluctuating stimuli. ...our results show that mPFC L5 pyramidal neurons retain an increased sensitivity to input fluctuations, whereas their sensitivity to the input mean diminishes to near zero. This implies that the discharge properties of L5 mPFC neurons are well suited to encode input fluctuations rather than input mean in their firing rates, with important consequences for information processing and stability of persistent activity at the network level."
Reference:
1 . Arsiero M, Lüscher HR, Lundstrom BN, Giugliano M (2007) The impact of input fluctuations on the frequency-current relationships of layer 5 pyramidal neurons in the rat medial prefrontal cortex. J Neurosci 27:3274-84 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Prefrontal cortex (PFC);
Cell Type(s): Neocortex L5/6 pyramidal GLU cell;
Channel(s): I Sodium; I Potassium;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Simplified Models; Action Potentials; Spike Frequency Adaptation;
Implementer(s):
Search NeuronDB for information about:  Neocortex L5/6 pyramidal GLU cell; I Sodium; I Potassium;
objectvar g[20]         // max 20 graphs
ngraph = 0

proc addgraph() { local ii  // define subroutine to add a new graph
                // addgraph("variable", minvalue, maxvalue)
    ngraph = ngraph+1
    ii = ngraph-1
    g[ii] = new Graph()
    g[ii].size(tstart,tstop,$2,$3)
    g[ii].xaxis()
    g[ii].yaxis()
    g[ii].addvar($s1,1,0)
    g[ii].save_name("graphList[0].")
    graphList[0].append(g[ii])
}

proc makegraph() { local ii // define subroutine to add a new graph
                // makeraph("variable", xmin,xmax,ymin,ymax)
    ngraph = ngraph+1
    ii = ngraph-1
    g[ii] = new Graph()
    g[ii].size($2,$3,$4,$5)
    g[ii].xaxis()
    g[ii].yaxis()
    g[ii].addvar($s1,1,0)
    g[ii].save_name("graphList[0].")
    graphList[0].append(g[ii])
}


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