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;
ANsyn.mod *
bgka.mod *
burststim2.mod *
cadyn.mod *
cagk.mod *
cal.mod *
calH.mod *
cancr.mod *
car.mod *
cat.mod *
ccanl.mod *
gskch.mod *
h.mod *
hha_old.mod *
hha2.mod *
hNa.mod *
IA.mod *
iccr.mod *
ichan2.mod *
ichan2aa.mod *
ichan2bc.mod *
ichan2bs.mod *
ichan2vip.mod *
Ih.mod *
Ihvip.mod *
ikscr.mod *
kad.mod *
kadistcr.mod *
kap.mod *
Kaxon.mod *
kca.mod *
Kdend.mod *
kdrcr.mod *
km.mod *
Ksoma.mod *
LcaMig.mod *
my_exp2syn.mod *
Naaxon.mod *
Nadend.mod *
nafcr.mod *
nap.mod *
Nasoma.mod *
nca.mod *
nmda.mod *
regn_stim.mod *
somacar.mod *
STDPE2Syn.mod *
vecstim.mod *
IA channel


1.	Zhang, L. and McBain, J. Voltage-gated potassium currents in
	stratum oriens-alveus inhibitory neurons of the rat CA1
	hippocampus, J. Physiol. 488.3:647-660, 1995.

		Activation V1/2 = -14 mV
		slope = 16.6
		activation t = 5 ms
		Inactivation V1/2 = -71 mV
		slope = 7.3
		inactivation t = 15 ms
		recovery from inactivation = 142 ms

2.	Martina, M. et al. Functional and Molecular Differences between
	Voltage-gated K+ channels of fast-spiking interneurons and pyramidal
	neurons of rat hippocampus, J. Neurosci. 18(20):8111-8125, 1998.	
	(only the gkAbar is from this paper)

		gkabar = 0.0175 mho/cm2
		Activation V1/2 = -6.2 +/- 3.3 mV
		slope = 23.0 +/- 0.7 mV
		Inactivation V1/2 = -75.5 +/- 2.5 mV
		slope = 8.5 +/- 0.8 mV
		recovery from inactivation t = 165 +/- 49 ms  

3.	Warman, E.N. et al.  Reconstruction of Hippocampal CA1 pyramidal
	cell electrophysiology by computer simulation, J. Neurophysiol.
	71(6):2033-2045, 1994.

		gkabar = 0.01 mho/cm2
		(number taken from the work by Numann et al. in guinea pig
		CA1 neurons)


    (mA) = (milliamp)
    (mV) = (millivolt)
    RANGE gkAbar,ik
    GLOBAL ainf, binf, aexp, bexp, tau_b
	v               (mV)
	dt              (ms)
	p      = 5      (degC)
	gkAbar = 0.0165 (mho/cm2)	:from Martina et al.
	ek     = -90    (mV)
	tau_a  = 5      (ms)
    a b
	ik (mA/cm2)
	ainf binf aexp bexp
    SOLVE deriv METHOD derivimplicit
    ik = gkAbar*a*b*(v - ek)
	a = ainf
	b = binf

	: Computes state variables m, h, and n rates(v)      
	: at the current v and dt.
    rates(v) : required to update inf and tau values
    a' = (ainf - a)/(tau_a)
    b' = (binf - b)/(tau_b)
PROCEDURE rates(v) {
	:Computes rate and other constants at current v.
    :Call once from HOC to initialize inf at resting v.
    LOCAL alpha_b, beta_b
	TABLE ainf, aexp, binf, bexp, tau_a, tau_b  DEPEND dt, p FROM -200 TO 100 WITH 300
	alpha_b = 0.000009/exp((v-26)/18.5)
	beta_b  = 0.014/(exp((v+70)/(-11))+0.2)
	ainf    = 1/(1 + exp(-(v + 14)/16.6))
	aexp    = 1 - exp(-dt/(tau_a))
	tau_b   = 1/(alpha_b + beta_b)
	binf    = 1/(1 + exp((v + 71)/7.3))
	bexp    = 1 - exp(-dt/(tau_b))