Hippocampal CA3 network and circadian regulation (Stanley et al. 2013)

 Download zip file 
Help downloading and running models
This model produces the hippocampal CA3 neural network model used in the paper below. It has two modes of operation, a default mode and a circadian mode. In the circadian mode, parameters are swept through a range of values. This model can be quite easily adapted to produce theta and gamma oscillations, as certain parameter sweeps will reveal (see Figures). BASH scripts interact with GENESIS 2.3 to implement parameter sweeps. The model contains four cell types derived from prior papers. CA3 pyramidal are derived from Traub et al (1991); Basket, stratum oriens (O-LM), and Medial Septal GABAergic (MSG) interneurons are taken from Hajos et al (2004).
1 . Stanley DA, Talathi SS, Parekh MB, Cordiner DJ, Zhou J, Mareci TH, Ditto WL, Carney PR (2013) Phase shift in the 24-hour rhythm of hippocampal EEG spiking activity in a rat model of temporal lobe epilepsy. J Neurophysiol 110:1070-86 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Hippocampus; Medial Septum;
Cell Type(s): Hippocampus CA3 pyramidal GLU cell; Hippocampus CA3 interneuron basket GABA cell; Hippocampus CA3 stratum oriens lacunosum-moleculare interneuron; Hippocampus septum medial GABAergic neuron;
Channel(s): I Na,t; I A; I K; I h; I K,Ca; I Calcium;
Gap Junctions:
Receptor(s): GabaA; AMPA;
Transmitter(s): Gaba; Glutamate;
Simulation Environment: GENESIS; MATLAB;
Model Concept(s): Epilepsy; Brain Rhythms; Circadian Rhythms;
Implementer(s): Stanley, David A ;
Search NeuronDB for information about:  Hippocampus CA3 pyramidal GLU cell; Hippocampus CA3 interneuron basket GABA cell; GabaA; AMPA; I Na,t; I A; I K; I h; I K,Ca; I Calcium; Gaba; Glutamate;
function s = betas_dave(s,opt_strct)

use_wvlets = 1;

if nargin > 1
    if isfield (opt_strct, 'use_wvlets'); use_wvlets = opt_strct.use_wvlets; end

if use_wvlets
    plotting = 0;               %Turn on/off plotting
    display_power = 1;          %Turn on/off plotting power spect subplot
    display_wavelets = 0;       %Turn on/off displaying wavelet info
    clean_memory = 0;
    clean_filtered = 0;
    len = length (s.data);

    %Check if the work has already been done!
    if isfield (s,'betas.b') == 1
        already_calculated = 1;
        already_calculated = 0;
    already_calculated = 0        %Hard coding to force recalculation of values
                                  %Essential for debugging!

    if ~already_calculated
        numcoefs = round(log2(len)) - 2;    %default fudge factor = 4
        s.wvstruct = dwt_dave (s.datafilt, numcoefs, display_wavelets * plotting);

        s.betas.b = zeros(2, numcoefs);         %beta array: first row is the scale index (j)
        s.betas.b(1,:) = 2.^(1:numcoefs);            %the second row is the actual coefficient
        s.betas.b(1,1) = -1;                    %first is undefinied

        for i = 1:numcoefs
            s.betas.power.val(i) = davePower(s.wvstruct.dwt(i).coefs);  % Should not use variance since it subtracts the mean - we want that left in there
            s.betas.power.scale(i) = 2^i;
            s.betas.power.freq(i) = 1/(2^i * s.dt1);

        for i = 2:numcoefs
            coefs2 = s.wvstruct.dwt(i).coefs;
            coefs1 = s.wvstruct.dwt(i-1).coefs;
            s.betas.b(2,i) = log2(davePower(coefs2)) - log2(davePower(coefs1));
        %     s.betas.b(2,i) = log2(var(coefs2)) - log2(var(coefs1));
        %     mean(coefs2)
        %     mean(coefs1)
        %     std(coefs1)
        %     std(coefs2) 

    if plotting == 1
        betas_plot (s, display_power)
    if clean_memory == 1
        s = rmfield(s, 'data');
        s = rmfield(s, 'datatimes');
        s = rmfield(s, 'datafilt');    
        s = rmfield(s, 'datafilt2');
        s = rmfield(s, 'nfft');

    if clean_filtered == 1
       s = rmfield(s, 'datafilt');
       s = rmfield(s, 'datafilt2');


Loading data, please wait...