Parametric computation and persistent gamma in a cortical model (Chambers et al. 2012)

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Using the Traub et al (2005) model of the cortex we determined how 33 synaptic strength parameters control gamma oscillations. We used fractional factorial design to reduce the number of runs required to 4096. We found an expected multiplicative interaction between parameters.
1 . Chambers JD, Bethwaite B, Diamond NT, Peachey T, Abramson D, Petrou S, Thomas EA (2012) Parametric computation predicts a multiplicative interaction between synaptic strength parameters that control gamma oscillations. Front Comput Neurosci 6:53 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Axon; Synapse; Channel/Receptor; Dendrite;
Brain Region(s)/Organism:
Cell Type(s): Neocortex L5/6 pyramidal GLU cell; Neocortex L2/3 pyramidal GLU cell; Neocortex V1 interneuron basket PV GABA cell; Neocortex fast spiking (FS) interneuron; Neocortex spiny stellate cell; Neocortex spiking regular (RS) neuron; Neocortex spiking low threshold (LTS) neuron;
Channel(s): I A; I K; I K,leak; I K,Ca; I Calcium; I_K,Na;
Gap Junctions: Gap junctions;
Receptor(s): GabaA; AMPA; NMDA;
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Oscillations; Parameter sensitivity;
Implementer(s): Thomas, Evan [evan at]; Chambers, Jordan [jordandchambers at];
Search NeuronDB for information about:  Neocortex L5/6 pyramidal GLU cell; Neocortex L2/3 pyramidal GLU cell; Neocortex V1 interneuron basket PV GABA cell; GabaA; AMPA; NMDA; I A; I K; I K,leak; I K,Ca; I Calcium; I_K,Na; Gaba; Glutamate;
alphasyndiffeq.mod *
alphasynkin.mod *
alphasynkint.mod *
ampa.mod *
ar.mod *
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cat.mod *
cat_a.mod *
gabaa.mod *
iclamp_const.mod *
k2.mod *
ka.mod *
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kahp.mod *
kahp_deeppyr.mod *
kahp_slower.mod *
kc.mod *
kc_fast.mod *
kdr.mod *
kdr_fs.mod *
km.mod *
naf_tcr.mod *
napf.mod *
napf_spinstell.mod *
napf_tcr.mod *
par_ggap.mod *
pulsesyn.mod *
rampsyn.mod *
rand.mod *
traub_nmda.mod *
Four helpful hints:

1) before calling scale_connection_coef, one must call some NEURON
function (such as ri(x)) that forces calculation of all the connection
coefficients for all the sections.

2) if any diam or L is changed, then one must re-call the
scale_connection_coef procedure again for all compartments AFTER
re-forcing the normal calculation of them via a call to, e.g. ri(x).

3) note that ri(0.5) gives the resistance in mega ohms between 0.5
location and the 0 end and ri(1) gives the resistance in mega ohms
between the 0.5 location and the 1 end.

4) Call with a section access'ed.  Call below with (1,factor) to
change the axial resistance of (a parent's) x=0.5 to x=1 part and call
with (0.5, factor) to change the axial resistance for (a child's) x=0
to x=0.5 part.  Note: factor = current_ri_value/desired__ri_value.


NEURON { SUFFIX nothing }

char* secname();

PROCEDURE scale_connection_coef(x, factor) {
	Section* sec;
	Node* nd;
#if defined(t)
	_NrnThread* _nt = nrn_threads;
	sec = chk_access();
	if (_lx <= 0. || _lx > 1.) {
		hoc_execerror("out of range, must be 0 < x <= 1", (char*)0);
	/*printf("scale_connection_coefs %s(%g) %d\n", secname(sec), _lx, sec->nnode);*/
	/* assumes 0 end of child connected to parent */
	if (_lx == 1.) {
		nd = sec->pnode[sec->nnode-1];
		nd = sec->pnode[(int) (_lx*(double)(sec->nnode-1))];
	/*printf("%g %g\n", NODEA(nd), NODEB(nd));*/
#if defined(t)
	_nt = nd->_nt;
	NODEA(nd) *= _lfactor;
	NODEB(nd) *= _lfactor;