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

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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]
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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;
Transmitter(s): Gaba; Glutamate;
Simulation Environment: GENESIS;
Model Concept(s): Synaptic Integration;
Implementer(s): Jaeger, Dieter [djaeger at];
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 [tapers,eigs]=dpsschk(tapers,N,Fs)
% Helper function to calculate tapers and, if precalculated tapers are supplied, 
% to check that they (the precalculated tapers) the same length in time as
% the time series being studied. The length of the time series is specified
% as the second input argument N. Thus if precalculated tapers have
% dimensions [N1 K], we require that N1=N.
% Usage: tapers=dpsschk(tapers,N,Fs)
% Inputs:
% tapers        (tapers in the form of: 
%                                   (i) precalculated tapers or,
%                                   (ii) [NW K] - time-bandwidth product, number of tapers) 
% N             (number of samples)
% Fs            (sampling frequency - this is required for nomalization of
%                                     tapers: we need tapers to be such
%                                     that integral of the square of each taper equals 1
%                                     dpss computes tapers such that the
%                                     SUM of squares equals 1 - so we need
%                                     to multiply the dpss computed tapers
%                                     by sqrt(Fs) to get the right
%                                     normalization)
% Outputs: 
% tapers        (calculated or precalculated tapers)
% eigs          (eigenvalues) 
if nargin < 3; error('Need all arguments'); end
if sz(1)==1 && sz(2)==2;
    tapers = tapers*sqrt(Fs);
elseif N~=sz(1);
    error('seems to be an error in your dpss calculation; the number of time points is different from the length of the tapers');