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]
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 J=mtfftc(data,tapers,nfft,Fs)
% Multi-taper fourier transform - continuous data
% Usage:
% J=mtfftc(data,tapers,nfft,Fs) - all arguments required
% Input: 
%       data (in form samples x channels/trials or a single vector) 
%       tapers (precalculated tapers from dpss) 
%       nfft (length of padded data)
%       Fs   (sampling frequency)
% Output:
%       J (fft in form frequency index x taper index x channels/trials)
if nargin < 4; error('Need all input arguments'); end;
[NC,C]=size(data); % size of data
[NK K]=size(tapers); % size of tapers
if NK~=NC; error('length of tapers is incompatible with length of data'); end;
tapers=tapers(:,:,ones(1,C)); % add channel indices to tapers
data=data(:,:,ones(1,K)); % add taper indices to data
data=permute(data,[1 3 2]); % reshape data to get dimensions to match those of tapers
data_proj=data.*tapers; % product of data with tapers
J=fft(data_proj,nfft)/Fs;   % fft of projected data

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