Parvalbumin-positive basket cells differentiate among hippocampal pyramidal cells (Lee et al. 2014)

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Accession:153280
This detailed microcircuit model explores the network level effects of sublayer specific connectivity in the mouse CA1. The differences in strengths and numbers of synapses between PV+ basket cells and either superficial sublayer or deep sublayer pyramidal cells enables a routing of inhibition from superficial to deep pyramidal cells. At the network level of this model, the effects become quite prominent when one compares the effect on firing rates when either the deep or superficial pyramidal cells receive a selective increase in excitation.
Reference:
1 . Lee SH, Marchionni I, Bezaire M, Varga C, Danielson N, Lovett-Barron M, Losonczy A, Soltesz I (2014) Parvalbumin-positive basket cells differentiate among hippocampal pyramidal cells. Neuron 82:1129-44 [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; Hippocampus CA1 basket cell;
Channel(s): I Sodium; I Calcium; I Potassium;
Gap Junctions:
Receptor(s): GabaA; Glutamate;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Detailed Neuronal Models; Connectivity matrix; Laminar Connectivity;
Implementer(s): Bezaire, Marianne [mariannejcase at gmail.com];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal GLU cell; GabaA; Glutamate; I Sodium; I Calcium; I Potassium;
use_cache_efficient=1
get_spike_hist=0
use_bin_queue=0
use_spike_compression=0
if (use_spike_compression==1) {
	maxstepval = 2.5
} else {
	maxstepval = 10
}	

{cvode.cache_efficient(use_cache_efficient)} // always double check that this addition does not affect the spikeraster (via pointers in mod files, etc)

if (use_bin_queue==1) {
	use_fixed_step_bin_queue = 1 // boolean
	use_self_queue = 0 // boolean - this one may not be helpful for me, i think it's best for large numbers of artificial cells that receive large numbers of inputs
	{mode = cvode.queue_mode(use_fixed_step_bin_queue, use_self_queue)}
}

if (use_spike_compression==1) {
	nspike = 3 // compress spiketimes or not
	gid_compress = 0 //only works if fewer than 256 cells on each proc
	{nspike = pc.spike_compress(nspike, gid_compress)}
}