Robust transmission in the inhibitory Purkinje Cell to Cerebellar Nuclei pathway (Abbasi et al 2017)

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Accession:229279

Reference:
1 . Abbasi S, Hudson AE, Maran SK, Cao Y, Abbasi A, Heck DH, Jaeger D (2017) Robust Transmission of Rate Coding in the Inhibitory Purkinje Cell to Cerebellar Nuclei Pathway in Awake Mice PLOS Computational Biology
2 . Steuber V, Schultheiss NW, Silver RA, De Schutter E, Jaeger D (2011) Determinants of synaptic integration and heterogeneity in rebound firing explored with data-driven models of deep cerebellar nucleus cells. J Comput Neurosci 30:633-58 [PubMed]
3 . Steuber V, Jaeger D (2013) Modeling the generation of output by the cerebellar nuclei. Neural Netw 47:112-9 [PubMed]
4 . Steuber V, De Schutter E, Jaeger D (2004) Passive models of neurons in the deep cerebellar nuclei: the effect of reconstruction errors Neurocomputing 58-60:563-568
5 . Luthman J, Hoebeek FE, Maex R, Davey N, Adams R, De Zeeuw CI, Steuber V (2011) STD-dependent and independent encoding of input irregularity as spike rate in a computational model of a cerebellar nucleus neuron. Cerebellum 10:667-82 [PubMed]
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Cerebellum;
Cell Type(s): Cerebellum deep nucleus neuron;
Channel(s): I h; I T low threshold; I L high threshold; I Na,p; I Na,t; I K,Ca; I K;
Gap Junctions:
Receptor(s): AMPA; NMDA; GabaA;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: GENESIS;
Model Concept(s): Synaptic Integration;
Implementer(s): Jaeger, Dieter [djaeger at emory.edu];
Search NeuronDB for information about:  GabaA; AMPA; NMDA; I Na,p; I Na,t; I L high threshold; I T low threshold; I K; I h; I K,Ca; Gaba; Glutamate;
function [N,C]=check_consistency(data1,data2,sp)
% Helper routine to check consistency of data dimensions
% Usage: [N,C]=check_consistency(data1,data2,sp)
% Inputs:
% data1 - first dataset
% data2 - second dataset
% sp - optional argument to be input as 1 when one of the two data sets is
% spikes times stored as a 1d array.
% Outputs:
% Dimensions of the datasets - data1 or data2 (note that 
%    routine stops with an error message if dimensions don't match - [N,C]
%    N left empty for structure arrays
N1=[]; N2=[];
if nargin < 3 || isempty(sp); sp=0; end;
if isstruct(data1);
    C1=length(data1);
else
    [N1,C1]=size(data1);
end;
if isstruct(data2);
    C2=length(data2);
else
    [N2,C2]=size(data2);
end;
if C1~=C2; error('inconsistent dimensions'); end;
if sp==0;
   if ~isstruct(data1) && ~isstruct(data2);
      if N1~=N2; error('inconsistent dimensions'); end;
   end;
end;
N=N1; C=C1;