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 [dS,t,f]=mtdspecgrampb(data,movingwin,phi,params)
% Multi-taper derivatives of time-frequency spectrum - binned point process
% Usage:
% [dS,t,f]=mtdspecgrampb(data,movingwin,phi,params)
% Input: 
%   Note that all times can be in arbitrary units. But the units have to be
%   consistent. So, if E is in secs, win, t have to be in secs, and Fs has to
%   be Hz. If E is in samples, so are win and t, and Fs=1. In case of spike
%   times, the units have to be consistent with the units of data as well.
%       data        (in form samples x channels/trials or a single vector) -- required
%       movingwin         (in the form [window winstep] i.e length of moving
%                                                 window and step size.
%                                                 Note that units here have
%                                                 to be consistent with
%                                                 units of Fs
%       phi         (angle for evaluation of derivative) -- required.
%                       e.g. phi=[0,pi/2] giving the time and frequency
%                       derivatives
%       params: structure with fields tapers, pad, Fs, fpass,trialave
%       -optional
%           tapers : precalculated tapers from dpss or in the one of the following
%                    forms: 
%                    (1) A numeric vector [TW K] where TW is the
%                        time-bandwidth product and K is the number of
%                        tapers to be used (less than or equal to
%                        2TW-1). 
%                    (2) A numeric vector [W T p] where W is the
%                        bandwidth, T is the duration of the data and p 
%                        is an integer such that 2TW-p tapers are used. In
%                        this form there is no default i.e. to specify
%                        the bandwidth, you have to specify T and p as
%                        well. Note that the units of W and T have to be
%                        consistent: if W is in Hz, T must be in seconds
%                        and vice versa. Note that these units must also
%                        be consistent with the units of params.Fs: W can
%                        be in Hz if and only if params.Fs is in Hz.
%                        The default is to use form 1 with TW=3 and K=5
%                    Note that T has to be equal to movingwin(1).
%	        pad		    (padding factor for the FFT) - optional (can take values -1,0,1,2...). 
%                    -1 corresponds to no padding, 0 corresponds to padding
%                    to the next highest power of 2 etc.
%			      	 e.g. For N = 500, if PAD = -1, we do not pad; if PAD = 0, we pad the FFT
%			      	 to 512 points, if pad=1, we pad to 1024 points etc.
%			      	 Defaults to 0.
%           Fs   (sampling frequency) - optional. Default 1.
%           fpass    (frequency band to be used in the calculation in the form
%                                   [fmin fmax])- optional. 
%                                   Default all frequencies between 0 and
%                                   Fs/2
%           trialave (average over trials when 1, don't average when 0) -
%           optional. Default 0
% Output:
%       dS      (spectral derivative in form phi x time x frequency x channels/trials if trialave=0; 
%               phi x time x frequency if trialave=1)
%       t       (times)
%       f       (frequencies)

if nargin < 3; error('Need data, window parameters and angle'); end;
if nargin < 4; params=[]; end;

if length(params.tapers)==3 & movingwin(1)~=params.tapers(2);
    error('Duration of data in params.tapers is inconsistent with movingwin(1), modify params.tapers(2) to proceed')

clear err
Nwin=round(Fs*movingwin(1)); % number of samples in window
Nstep=round(movingwin(2)*Fs); % number of samples to step through
f=getfgrid(Fs,nfft,fpass); Nf=length(f);
params.tapers=dpsschk(tapers,Nwin,Fs); % check tapers

if trialave==0; dS=zeros(length(phi),nw,Nf,Ch); else dS=zeros(length(phi),nw,Nf); end;
for n=1:nw;
% if length(sz)==3;
%    dS=permute(dS,[2 1 3 4]);
% elseif length(phi)>1
%    dS=permute(dS,[2 1 3]);
% end;

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