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]
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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;
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 [f,findx]=getfgrid(Fs,nfft,fpass)
% Helper function that gets the frequency grid associated with a given fft based computation
% Called by spectral estimation routines to generate the frequency axes 
% Usage: [f,findx]=getfgrid(Fs,nfft,fpass)
% Inputs:
% Fs        (sampling frequency associated with the data)-required
% nfft      (number of points in fft)-required
% fpass     (band of frequencies at which the fft is being calculated [fmin fmax] in Hz)-required
% Outputs:
% f         (frequencies)
% findx     (index of the frequencies in the full frequency grid). e.g.: If
% Fs=1000, and nfft=1048, an fft calculation generates 512 frequencies
% between 0 and 500 (i.e. Fs/2) Hz. Now if fpass=[0 100], findx will
% contain the indices in the frequency grid corresponding to frequencies <
% 100 Hz. In the case fpass=[0 500], findx=[1 512].
if nargin < 3; error('Need all arguments'); end;
df=Fs/nfft;
f=0:df:Fs; % all possible frequencies
f=f(1:nfft);
if length(fpass)~=1;
   findx=find(f>=fpass(1) & f<=fpass(end));
else
   [fmin,findx]=min(abs(f-fpass));
   clear fmin
end;
f=f(findx);