CA1 PV+ fast-firing hippocampal interneuron (Ferguson et al. 2013)

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Accession:182843
This two-variable simple model is derived based on patch-clamp recordings from the CA1 region of a whole hippocampus preparation of PV+ fast-firing cells. Since basket cells, axo-axonic cells and bistratified cells can be PV+ and fast-firing, this model could be representative of these cell types. The model code will also be made available on OSB.
Reference:
1 . Ferguson KA, Huh CY, Amilhon B, Williams S, Skinner FK (2013) Experimentally constrained CA1 fast-firing parvalbumin-positive interneuron network models exhibit sharp transitions into coherent high frequency rhythms. Front Comput Neurosci 7:144 [PubMed]
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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: Hippocampus;
Cell Type(s): Hippocampus CA1 basket cell; Hippocampus CA1 bistratified cell; Hippocampus CA1 axo-axonic cell; Hippocampus CA1 PV+ fast-firing interneuron;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: Brian; Python;
Model Concept(s): Action Potentials;
Implementer(s):
/
FergusonEtAl2013
readme.html
PV_model.py
screenshot.png
                            
'''
PV cell model
@author: Ferguson et al. (2013) Front. Comput. Neurosci. 
'''
from brian import *

defaultclock.dt = 0.02*ms

#PV cell parameters
C=90 * pF 
vr=-60.6 * mV 
vpeak=2.5 * mV 
c=-70 * mV 
klow=1.7 * nS/mV 
khigh=14  * nS/mV 
a=0.1 /ms 
d=0.1 * pA 
vt=-43.1 *mV 
b=-0.1 * nS 

N=1   #number of cells
mean_Iapp=150 #mean Iapplied input

time=0

#cell eqns
pv_eqs = """
Iext  : amp
k=(v<vt)*klow+(v>=vt)*khigh : (siemens/volt)
du/dt = a*(b*(v-vr)-u)            : amp
dv/dt = (k*(v-vr)*(v-vt)+Iext -u)/C : volt
"""

#define neuron group
PV = NeuronGroup(N, model=pv_eqs, reset ="v = c; u += d" , threshold="v>=vpeak")

#set excitatory drive 
PV.Iext = mean_Iapp*pA

#set initial conditions for each neuron
PV.v = rand(len(PV))*0.01 -0.065

#record all spike times for the neuron group
PV_v = StateMonitor(PV, 'v', record=True)

#run for x seconds of simulated time
duration = 1 * second  # 0.01 * second

net =Network(PV,PV_v) 
net.run(duration)

####make plot of membrane potential####
plot(PV_v.times,PV_v[0]/mV)
xlabel("Time (s)")
ylabel("Membrane Potential (mV)")
title('PV cell model with %d pA input'%(mean_Iapp))
show()