Long time windows from theta modulated inhib. in entorhinal–hippo. loop (Cutsuridis & Poirazi 2015)

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Accession:181967
"A recent experimental study (Mizuseki et al., 2009) has shown that the temporal delays between population activities in successive entorhinal and hippocampal anatomical stages are longer (about 70–80 ms) than expected from axon conduction velocities and passive synaptic integration of feed-forward excitatory inputs. We investigate via computer simulations the mechanisms that give rise to such long temporal delays in the hippocampus structures. ... The model shows that the experimentally reported long temporal delays in the DG, CA3 and CA1 hippocampal regions are due to theta modulated somatic and axonic inhibition..."
Reference:
1 . Cutsuridis V, Poirazi P (2015) A computational study on how theta modulated inhibition can account for the long temporal windows in the entorhinal-hippocampal loop. Neurobiol Learn Mem 120:69-83 [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:
Cell Type(s): Dentate gyrus granule cell; Hippocampus CA1 pyramidal cell; Hippocampus CA3 pyramidal cell; Hippocampus CA3 interneuron basket cell; Dentate gyrus mossy cell; Dentate gyrus basket cell; Dentate gyrus hilar cell; Hippocampus CA1 basket cell; Hippocampus CA3 stratum oriens lacunosum-moleculare interneuron; Hippocampus CA1 bistratified cell; Hippocampus CA1 axo-axonic cell; Hippocampus CA3 axo-axonic cells;
Channel(s): I Na,t; I L high threshold; I N; I T low threshold; I A; I K; I M; I h; I K,Ca; I_AHP;
Gap Junctions:
Receptor(s): GabaA; AMPA; NMDA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Pattern Recognition; Temporal Pattern Generation; Spatio-temporal Activity Patterns; Brain Rhythms; Storage/recall;
Implementer(s): Cutsuridis, Vassilis [vcutsuridis at gmail.com];
Search NeuronDB for information about:  Dentate gyrus granule cell; Hippocampus CA1 pyramidal cell; Hippocampus CA3 pyramidal cell; Hippocampus CA3 interneuron basket cell; GabaA; AMPA; NMDA; I Na,t; I L high threshold; I N; I T low threshold; I A; I K; I M; I h; I K,Ca; I_AHP;
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CutsuridisPoirazi2015
Results
Weights
readme.html
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COMMENT
Two state kinetic scheme synapse described by rise time tau1,
and decay time constant tau2. The normalized peak condunductance is 1.
Decay time MUST be greater than rise time.

The solution of A->G->bath with rate constants 1/tau1 and 1/tau2 is
 A = a*exp(-t/tau1) and
 G = a*tau2/(tau2-tau1)*(-exp(-t/tau1) + exp(-t/tau2))
	where tau1 < tau2

If tau2-tau1 -> 0 then we have a alphasynapse.
and if tau1 -> 0 then we have just single exponential decay.

The factor is evaluated in the
initial block such that an event of weight 1 generates a
peak conductance of 1.

Because the solution is a sum of exponentials, the
coupled equations can be solved as a pair of independent equations
by the more efficient cnexp method.

ENDCOMMENT

NEURON {
	POINT_PROCESS MyExp2Syn
	RANGE tau1, tau2, e, i
	NONSPECIFIC_CURRENT i

	RANGE g
	GLOBAL total
}

UNITS {
	(nA) = (nanoamp)
	(mV) = (millivolt)
	(uS) = (microsiemens)
}

PARAMETER {
	tau1=.1 (ms) <1e-9,1e9>
	tau2 = 10 (ms) <1e-9,1e9>
	e=0	(mV)
}

ASSIGNED {
	v (mV)
	i (nA)
	g (uS)
	factor
	total (uS)
}

STATE {
	A (uS)
	B (uS)
}

INITIAL {
	LOCAL tp
	total = 0
	if (tau1/tau2 > .9999) {
		tau1 = .9999*tau2
	}
	A = 0
	B = 0
	tp = (tau1*tau2)/(tau2 - tau1) * log(tau2/tau1)
	factor = -exp(-tp/tau1) + exp(-tp/tau2)
	factor = 1/factor
}

BREAKPOINT {
	SOLVE state METHOD cnexp
	g = B - A
	i = g*(v - e)
}

DERIVATIVE state {
	A' = -A/tau1
	B' = -B/tau2
}

NET_RECEIVE(weight (uS)) {
	state_discontinuity(A, A + weight*factor)
	state_discontinuity(B, B + weight*factor)
	total = total+weight
}