Hippocampal CA1 NN with spontaneous theta, gamma: full scale & network clamp (Bezaire et al 2016)

 Download zip file   Auto-launch 
Help downloading and running models
Accession:187604
This model is a full-scale, biologically constrained rodent hippocampal CA1 network model that includes 9 cells types (pyramidal cells and 8 interneurons) with realistic proportions of each and realistic connectivity between the cells. In addition, the model receives realistic numbers of afferents from artificial cells representing hippocampal CA3 and entorhinal cortical layer III. The model is fully scaleable and parallelized so that it can be run at small scale on a personal computer or large scale on a supercomputer. The model network exhibits spontaneous theta and gamma rhythms without any rhythmic input. The model network can be perturbed in a variety of ways to better study the mechanisms of CA1 network dynamics. Also see online code at http://bitbucket.org/mbezaire/ca1 and further information at http://mariannebezaire.com/models/ca1
Reference:
1 . Bezaire MJ, Raikov I, Burk K, Vyas D, Soltesz I (2016) Interneuronal mechanisms of hippocampal theta oscillations in a full-scale model of the rodent CA1 circuit. Elife [PubMed]
2 . Bezaire M, Raikov I, Burk K, Armstrong C, Soltesz I (2016) SimTracker tool and code template to design, manage and analyze neural network model simulations in parallel NEURON bioRxiv
Citations  Citation Browser
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; Hippocampus CA1 interneuron oriens alveus GABA cell; Hippocampus CA1 basket cell; Hippocampus CA1 stratum radiatum interneuron; Hippocampus CA1 bistratified cell; Hippocampus CA1 axo-axonic cell; Hippocampus CA1 PV+ fast-firing interneuron;
Channel(s): I Na,t; I K; I K,leak; I h; I K,Ca; I Calcium;
Gap Junctions:
Receptor(s): GabaA; GabaB; Glutamate; Gaba;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON; NEURON (web link to model);
Model Concept(s): Oscillations; Methods; Connectivity matrix; Laminar Connectivity; Gamma oscillations;
Implementer(s): Bezaire, Marianne [mariannejcase at gmail.com]; Raikov, Ivan [ivan.g.raikov at gmail.com];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal GLU cell; Hippocampus CA1 interneuron oriens alveus GABA cell; GabaA; GabaB; Glutamate; Gaba; I Na,t; I K; I K,leak; I h; I K,Ca; I Calcium; Gaba; Glutamate;
TITLE Hyperpolarization-activated, CN-gated channel (voltage dependent, for O-LM cells)

COMMENT
Hyperpolarization-activated, CN-gated channel (voltage dependent, for O-LM cells)

Ions: non-specific

Style: quasi-ohmic

From: 1.	Maccaferri, G. and McBain, C.J. The hyperpolarization-activated current
	(Ih) and its contribution to pacemaker activity in rat CA1 hippocampal
	stratum oriens-alveus interneurons, J. Physiol. 497.1:119-130,
	1996.

		V1/2 = -84.1 mV
		   k = 10.2
		reversal potential = -32.9 +/- 1.1 mV

at -70 mV, currents were fitted by a single exponetial of t = 2.8+/- 0.76 s
at -120 mV, two exponentials were required, t1 = 186.3+/-33.6 ms 
t2 = 1.04+/-0.16 s


2.	Maccaferri, G. et al. Properties of the
	Hyperpoarization-activated current in rat hippocampal CA1 Pyramidal
	cells. J. Neurophysiol. Vol. 69 No. 6:2129-2136, 1993.

		V1/2 = -97.9 mV
		   k = 13.4
		reversal potential = -18.3 mV

3.	Pape, H.C.  Queer current and pacemaker: The
	hyperpolarization-activated cation current in neurons, Annu. Rev. 
	Physiol. 58:299-327, 1996.

		single channel conductance is around 1 pS
		average channel density is below 0.5 um-2
		0.5 pS/um2 = 0.00005 mho/cm2 = 0.05 umho/cm2		
4.	Magee, J.C. Dendritic Hyperpolarization-Activated Currents Modify
	the Integrative Properties of Hippocampal CA1 Pyramidal Neurons, J.
	Neurosci., 18(19):7613-7624, 1998

Deals with Ih in CA1 pyramidal cells.  Finds that conductance density
increases with distance from the soma.

soma g = 0.0013846 mho/cm2
dendrite g (300-350 um away) = 0.0125 mho/cm2
see Table 1 in th paper

Updates:
2014 December (Marianne Bezaire): documented
ENDCOMMENT



 UNITS {
        (mA) = (milliamp)
        (mV) = (millivolt)
}
 
NEURON {
        SUFFIX ch_HCNolm
        USEION h READ eh WRITE ih VALENCE 1
        RANGE gmax,ih, g
        GLOBAL rinf, rexp, tau_r
        RANGE myi
}
 
INDEPENDENT {t FROM 0 TO 1 WITH 1 (ms)}
 
PARAMETER {
        v (mV)
        dt (ms)
        gmax = 0.001385 (mho/cm2)
		g (mho/cm2)
        eh = -32.9 (mV)
}
 
STATE {
        r
}
 
ASSIGNED {
        ih (mA/cm2)
	rinf rexp
	tau_r
	myi (mA/cm2)
}
 
BREAKPOINT {
	SOLVE deriv METHOD derivimplicit
	g = gmax*r
	ih = g*(v - eh)
	myi = ih
}
 
INITIAL {
	rates(v)
	r = rinf
}

DERIVATIVE deriv { :Computes state variable h at current v and dt.
	rates(v)
	r' = (rinf - r)/tau_r
}


PROCEDURE rates(v) {  :Computes rate and other constants at current v.
                      :Call once from HOC to initialize inf at resting v.
        TABLE rinf, tau_r, rexp DEPEND dt FROM -200
TO 100 WITH 300
	rinf = 1/(1 + exp((v+84.1)/10.2))
	tau_r = 100 + 1/(exp(-17.9-0.116*v)+exp(-1.84+0.09*v))
	rexp = 1 - exp(-dt/(tau_r))
}

FUNCTION efun(z) {
  if (fabs(z) < 1e-4) {
    efun = 1 - z/2
  } else {
    efun = z/(exp(z) - 1)
  }
}

 
UNITSON