Ih tunes oscillations in an In Silico CA3 model (Neymotin et al. 2013)

 Download zip file   Auto-launch 
Help downloading and running models
" ... We investigated oscillatory control using a multiscale computer model of hippocampal CA3, where each cell class (pyramidal, basket, and oriens-lacunosum moleculare cells), contained type-appropriate isoforms of Ih. Our model demonstrated that modulation of pyramidal and basket Ih allows tuning theta and gamma oscillation frequency and amplitude. Pyramidal Ih also controlled cross-frequency coupling (CFC) and allowed shifting gamma generation towards particular phases of the theta cycle, effected via Ih’s ability to set pyramidal excitability. ..."
1 . Neymotin SA, Hilscher MM, Moulin TC, Skolnick Y, Lazarewicz MT, Lytton WW (2013) Ih Tunes Theta/Gamma Oscillations and Cross-Frequency Coupling In an In Silico CA3 Model PLoS ONE 8(10):e76285 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Hippocampus;
Cell Type(s): Hippocampus CA3 pyramidal cell; Hippocampus CA3 interneuron basket cell; Hippocampus CA3 stratum oriens lacunosum-moleculare interneuron;
Channel(s): I Na,t; I A; I K; I K,leak; I h; I K,Ca; I Sodium; I Potassium;
Gap Junctions:
Receptor(s): GabaA; AMPA; NMDA; Glutamate;
Gene(s): HCN1; HCN2;
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON; Python;
Model Concept(s): Oscillations; Brain Rhythms; Conductance distributions; Multiscale;
Implementer(s): Lazarewicz, Maciej [mlazarew at gmu.edu]; Neymotin, Sam [samn at neurosim.downstate.edu];
Search NeuronDB for information about:  Hippocampus CA3 pyramidal cell; Hippocampus CA3 interneuron basket cell; GabaA; AMPA; NMDA; Glutamate; I Na,t; I A; I K; I K,leak; I h; I K,Ca; I Sodium; I Potassium; Gaba; Glutamate;
caolmw.mod *
icaolmw.mod *
kcaolmw.mod *
kdrbwb.mod *
misc.mod *
MyExp2SynBB.mod *
MyExp2SynNMDABB.mod *
nafbwb.mod *
stats.mod *
vecst.mod *
aux_fun.inc *
declist.hoc *
decmat.hoc *
decnqs.hoc *
decvec.hoc *
default.hoc *
drline.hoc *
grvec.hoc *
labels.hoc *
local.hoc *
misc.h *
nqs.hoc *
nrnoc.hoc *
pyinit.py *
simctrl.hoc *
stats.hoc *
syncode.hoc *
xgetargs.hoc *
# $Id: pyinit.py,v 1.2 2012/02/15 16:22:52 samn Exp $ 

from neuron import h
import os
import sys
import datetime
import shutil
import pickle
from math import sqrt, pi
import numpy
import types

h("objref p")
h("p = new PythonObject()")

    import pylab
    from pylab import plot, arange, figure
    my_pylab_loaded = True
except ImportError:
    print "Pylab not imported"
    my_pylab_loaded = False

def htype (obj): st=obj.hname(); sv=st.split('['); return sv[0]
def secname (obj): obj.push(); print h.secname() ; h.pop_section()
def psection (obj): obj.push(); print h.psection() ; h.pop_section()

allsecs=None #global list containing all NEURON sections, initialized via mkallsecs

# still need to generate a full allsecs
def mkallsecs ():
  """ mkallsecs - make the global allsecs variable, containing
      all the NEURON sections.
  global allsecs
  allsecs=h.SectionList() # no .clear() command
  for s in roots:
  return allsecs

#forall syntax - c gets executed, allsecs has Sections
def forall (c):
    """ NEURON forall syntax - iterates through all the sections available
        note that there's a dummy loop variable called s used in this function,
        so any command that needs to access a section should be via s.
        example: forall('print s.name()') , will print all the section names.
        Also note that this function uses a global list, 'allsecs', which may
        need to get re-initialized when new sections are created, via the mkallsecs
        function above.
    global allsecs
    if (type(allsecs)==types.NoneType): mkallsecs()
    for s in allsecs: exec(c)

#forsec syntax - executes command for each section who's name
# contains secname as a substring
def forsec (secref="soma",command=""): 
    """ NEURON forsec syntax - iterates over all sections which have a substring
        in their names matching secref argument. command is executed if match found.
        this function also utilizes the allsecs global variable.
    global allsecs
    if (type(allsecs)==types.NoneType): mkallsecs()
    if (type(secref)==types.StringTypes[0]):
        for s in allsecs:
            if s.name().count(secref) > 0:
        for s in secref: exec(command)

Loading data, please wait...