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

 Download zip file 
Help downloading and running models
Accession:229279

References:
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;
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 obj = params_results_profile(params, results, id, props)

% params_results_profile - Profile with parameters and results together.
%
% Usage 1:
% obj = params_results_profile(params, results, id, props)
%
% Usage 2:
% obj = params_results_profile(params, results_obj)
%
% Parameters:
%   params: Structure with parameter names and values.
%   results: Structure with result names and values (Usage 1).
%   results_obj: A results_profile object with test results.
%   id: Identification string (Usage 1).
%   props: A structure with any optional properties (Usage 1).
%
% Returns a structure object with the following fields:
%   params, results (results_obj above)
%
% Description:
%   This is a subclass of results_profile, improved by including
% parameter names and values. Should make it easier to code dataset
% classes. Usage 1 is for convenience, same information is contained in
% results_obj in Usage 2.
%		
% General methods of params_results_profile objects:
%   params_results_profile - Construct a new object.
%
% Additional methods:
%   See methods('params_results_profile')
%
% See also: results_profile, params_tests_dataset
%
% $Id$
%
% Author: Cengiz Gunay <cgunay@emory.edu>, 2011/07/05

% Copyright (c) 2011 Cengiz Gunay <cengique@users.sf.net>.
% This work is licensed under the Academic Free License ("AFL")
% v. 3.0. To view a copy of this license, please look at the COPYING
% file distributed with this software or visit
% http://opensource.org/licenses/afl-3.0.php.

if nargin == 0 % Called with no params, creates empty object
  obj.params = struct;
  obj = class(obj, 'params_results_profile', results_profile);
elseif isa(params, 'params_results_profile') % copy constructor?
  obj = params;
else 
  % Create new object
  props = defaultValue('props', struct);

  obj = struct;
  obj.params = params;
  
  if ~ isa(results, 'results_profile')
    results = ...
        results_profile(results, id, props);
  end

  % Create the object
  obj = class(obj, 'params_results_profile', results);
end



Loading data, please wait...