CA1 network model: interneuron contributions to epileptic deficits (Shuman et al 2020)

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Temporal lobe epilepsy causes significant cognitive deficits in both humans and rodents, yet the specific circuit mechanisms underlying these deficits remain unknown. There are profound and selective interneuron death and axonal reorganization within the hippocampus of both humans and animal models of temporal lobe epilepsy. To assess the specific contribution of these mechanisms on spatial coding, we developed a biophysically constrained network model of the CA1 region that consists of different subtypes of interneurons. More specifically, our network consists of 150 cells, 130 excitatory pyramidal cells and 20 interneurons (Fig. 1A). To simulate place cell formation in the network model, we generated grid cell and place cell inputs from the Entorhinal Cortex (ECLIII) and CA3 regions, respectively, activated in a realistic manner as observed when an animal transverses a linear track. Realistic place fields emerged in a subpopulation of pyramidal cells (40-50%), in which similar EC and CA3 grid cell inputs converged onto distal/proximal apical and basal dendrites. The tuning properties of these cells are very similar to the ones observed experimentally in awake, behaving animals To examine the role of interneuron death and axonal reorganization in the formation and/or tuning properties of place fields we selectively varied the contribution of each interneuron type and desynchronized the two excitatory inputs. We found that desynchronized inputs were critical in reproducing the experimental data, namely the profound reduction in place cell numbers, stability and information content. These results demonstrate that the desynchronized firing of hippocampal neuronal populations contributes to poor spatial processing in epileptic mice, during behavior. Given the lack of experimental data on the selective contributions of interneuron death and axonal reorganization in spatial memory, our model findings predict the mechanistic effects of these alterations at the cellular and network levels.
1 . Shuman T, Aharoni D, Cai DJ, Lee CR, Chavlis S, Page-Harley L, Vetere LM, Feng Y, Yang CY, Mollinedo-Gajate I, Chen L, Pennington ZT, Taxidis J, Flores SE, Cheng K, Javaherian M, Kaba CC, Rao N, La-Vu M, Pandi I, Shtrahman M, Bakhurin KI, Masmanidis SC, Khakh BS, Poirazi P, Silva AJ, Golshani P (2020) Breakdown of spatial coding and interneuron synchronization in epileptic mice. Nat Neurosci 23:229-238 [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: Hippocampus;
Cell Type(s): Hippocampus CA1 pyramidal GLU cell; Hippocampal CA1 CR/VIP cell; Hippocampus CA1 axo-axonic cell; Hippocampus CA1 basket cell; Hippocampus CA1 basket cell - CCK/VIP; Hippocampus CA1 stratum oriens lacunosum-moleculare interneuron ; Hippocampus CA1 bistratified cell;
Channel(s): I A; I h; I K,Ca; I K; I CAN; I M; I Sodium; I_AHP; I Calcium;
Gap Junctions:
Receptor(s): AMPA; GabaA; GabaB; NMDA;
Simulation Environment: NEURON; Brian;
Model Concept(s): Spatial Navigation;
Implementer(s): Chavlis, Spyridon [schavlis at]; Pandi, Ioanna ; Poirazi, Panayiota [poirazi at];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal GLU cell; GabaA; GabaB; AMPA; NMDA; I A; I K; I M; I h; I K,Ca; I CAN; I Sodium; I Calcium; I_AHP;
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TITLE K-A channel from Klee Ficker and Heinemann
: modified by Brannon and Yiota Poirazi ( 
: to account for Hoffman et al 1997 distal region kinetics
: used only in locations > 100 microns from the soma
: modified to work with CVode by Carl Gold, 8/10/03
:  Updated by Maria Markaki  12/02/03

	SUFFIX kadcr
	USEION k READ ki, ko WRITE ik 		:Changed from READ ek, 23/04/2010,Nassi
  RANGE gkabar,gka,ik
  GLOBAL ninf,linf,taul,taun,lmin

	(mA) = (milliamp)
	(mV) = (millivolt)

PARAMETER {    :parameters that can be entered when function is called in cell-setup   

  gkabar = 0      (mho/cm2)  :initialized conductance
  vhalfn = -1     (mV)       :activation half-potential (-1), change for pfc, activation at -40
  vhalfl = -56    (mV)       :inactivation half-potential
  a0n = 0.1       (/ms)      :parameters used
  : a0l = 0.05       (/ms)      :parameters used
  zetan = -1.8    (1)        :in calculation of
  zetal = 3       (1) 
  :zetal = 3       (1)        :steady state values
  gmn   = 0.39    (1)        :and time constants
  :gmn   = 0.39    (1)        :and time constants, original
  gml   = 1       (1)
  lmin  = 2       (ms)
  nmin  = 0.1     (ms)
  :	nmin  = 0.2     (ms)	:suggested
  pw    = -1      (1)
  tq    = -40     (mV)
  qq    = 5       (mV)
  q10   = 5                :temperature sensitivity

ASSIGNED {    :parameters needed to solve DE
  v         (mV)
  ek        (mV)
  celsius  	(degC)
  ik        (mA/cm2)
  taul      (ms)
  taun      (ms)
  gka       (mho/cm2)
  ki		    (mM)
  ko		    (mM)

STATE {       :the unknown parameters to be solved in the DEs 
	n l

: Solve qt once in initial block

INITIAL {    :initialize the following parameter using rates()
  qt = q10^((celsius-24)/10(degC))       : temperature adjustment factor

	SOLVE states METHOD cnexp
	ek = 25 * log(ko/ki)		:Changed, added, 23/04/2010, Nassi
	ik = gkabar*n*l*(v-ek)

DERIVATIVE states {     : exact when v held constant; integrates over dt step
  rates(v)              : do this here
  n' = (ninf - n)/taun
  l' = (linf - l)/taul

PROCEDURE rates(v (mV)) {		 :callable from hoc

  a = alpn(v)
  ninf = 1/(1 + a)		             : activation variable steady state value
  taun = betn(v)/(qt*a0n*(1+a))	   : activation variable time constant
	if (taun<nmin) {taun=nmin}	     : time constant not allowed to be less than nmin
    a = alpl(v)
    linf = 1/(1 + a)               : inactivation variable steady state value
  	:taul = 6 (ms)
  	taul = 0.26(ms/mV)*(v+50)      : inactivation variable time constant (0.26)
	if (taul<lmin) {taul=lmin}       : time constant not allowed to be less than lmin

FUNCTION alpn(v(mV)) { LOCAL zeta
  zeta = zetan+pw/(1+exp((v-tq)/qq))
  alpn = exp(1.e-3*zeta*(v-vhalfn)*9.648e4/(8.315*(273.16+celsius))) 

FUNCTION betn(v(mV)) { LOCAL zeta
  zeta = zetan+pw/(1+exp((v-tq)/qq))
  betn = exp(1.e-3*zeta*gmn*(v-vhalfn)*9.648e4/(8.315*(273.16+celsius))) 

FUNCTION alpl(v(mV)) {
  alpl = exp(1.e-3*zetal*(v-vhalfl)*9.648e4/(8.315*(273.16+celsius))) 

FUNCTION betl(v(mV)) {
  betl = exp(1.e-3*zetal*gml*(v-vhalfl)*9.648e4/(8.315*(273.16+celsius)))