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

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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;
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codes
pandora-matlab-1.4compat2
classes
@tests_db
private
.cvsignore *
abs.m
addColumns.m
addLastRow.m
addRow.m
allocateRows.m
anyRows.m
approxMappingLIBSVM.m
approxMappingNNet.m
approxMappingSVM.m
assignRowsTests.m
checkConsistentCols.m
compareRows.m
corrcoef.m
cov.m
crossProd.m
dbsize.m
delColumns.m
diff.m
display.m
displayRows.m
displayRowsCSV.m
displayRowsTeX.m
end.m
enumerateColumns.m
eq.m
factoran.m
fillMissingColumns.m
ge.m
get.m *
getColNames.m
groupBy.m
gt.m
histogram.m
invarValues.m
isinf.m
isnan.m
isnanrows.m
joinRows.m
kmeansCluster.m
le.m
lt.m
matchingRow.m
max.m
mean.m
meanDuplicateRows.m
min.m
minus.m
mtimes.m
ne.m
noNaNRows.m
onlyRowsTests.m
physiol_bundle.m
plot.m
plot_abstract.m
plot_bars.m
plotBox.m
plotCircular.m
plotCovar.m
plotImage.m
plotrow.m
plotrows.m
plotScatter.m
plotScatter3D.m
plotTestsHistsMatrix.m
plotUITable.m
plotUniquesStats2D.m
plotUniquesStatsBars.m
plotUniquesStatsStacked3D.m
plotXRows.m
plotYTests.m
plus.m
princomp.m
processDimNonNaNInf.m
rankMatching.m
rdivide.m
renameColumns.m
rop.m
rows2Struct.m
set.m *
setProp.m *
setRows.m
shufflerows.m
sortrows.m
sqrt.m
statsAll.m
statsBounds.m
statsMeanSE.m
statsMeanStd.m
std.m
subsasgn.m
subsref.m
sum.m
swapRowsPages.m
tests_db.m
tests2cols.m
tests2idx.m
tests2log.m
testsHists.m
times.m
transpose.m
uminus.m
unique.m
uop.m
vertcat.m
                            
function obj = tests_db(test_results, col_names, row_names, id, props)

% tests_db - Construct a numeric database organized in a matrix format.
%
% Usage:
% obj = tests_db(test_results, col_names, row_names, id, props)
%
% Parameters:
%   test_results: Either a text file (e.g., CSV) name or a matrix that contains
%   		measurement columns and separate observations as rows.
%   col_names: Cell array of column names of test_results.
%   row_names: Cell array of row names of test_results.
%   id: An identifying string.
%   props: A structure with any optional properties.
%     textDelim: Delimiter in text file to be used by dlmread (Default:
%  	',' for CSV). Use '' for all whitespace, '\t' for tabs.
%     csvArgs: Cell array of arguments passed to dlmread function (e.g.,
%     	{R, C, [r1 c1 r2 c2]}) for (R)ow and (C)olumn offset/range to read.
%     csvReadColNames: If 1, first row of the file or at the given offset
%     	(see csvArgs) is used to read column names. Double quotes must be
%     	used consistently.
%     paramDescFile: Load parameter names from file (one line per name).
%		
% Returns a structure object with the following fields:
%   data: The data matrix.
%   row_idx, col_idx: Structure associating row/column names to indices.
%   id, props.
%
% Description:
%   This is the base database class. Note for loading text files:
% Matlab's dlmread commands is used, and it is unable to handle files that
% have any non-numeric data (except skipped rows). Therefore, those files
% are best filtered with outside tools before importing.
%
% General operations on tests_db objects:
%   tests_db		- Construct a new tests_db object.
%   allocateRows	- Preallocate rows before filling the DB.
%   setRows		- Fill the DB with rows.
%   addRow		- Add a single row to DB.
%   addLastRow		- Add a single row to the end of DB.
%   display		- Returns and displays the identification string.
%   displayRows		- Display one row of data from the DB.
%   subsref		- Allows referencing rows/cols via () to get new 
%			  tests_db objects and allows usage of . operator.
%   eq			- Overloaded == operator that returns row indices.
%   ne			- Overloaded ~= operator that returns row indices.
%   lt			- Overloaded < operator that returns row indices.
%   gt			- Overloaded > operator that returns row indices.
%   le			- Overloaded <= operator that returns row indices.
%   ge			- Overloaded >= operator that returns row indices.
%   size		- Overloaded, returns size of database.
%   isnan		- Overloaded, returns non-NaN elements logical array.
%   get			- Gets attributes of this object and parents.
%   kcluster		- Returns k tests_db objects, one for each cluster 
%			  found in this one (N/I).
%   rankMatching	- Returns a tests_db object having an additional
%			  rank column and sorted according to relevance to 
%			  given query (N/I).
%   sort		- Sort rows and return new object and scrambling 
%			  order (N/I).
%   pca			- Returns a new tests_db object with the principal
%			  components of this one (N/I).
%   ica			- Returns a new tests_db object with the independent
%			  components of this one (N/I).
%   valDistributions - Returns mean and STDs of all values and 
%			  boundaries to be plotted (N/I).
%   withinValRange	- Returns a tests_db object with data within the range
%			  requested (N/I).
%   onlyTests		- Returns a tests_db object which contains only 
%			  the requested test columns (N/I).
%   histogram		- Returns histogram of given test.
%
% Additional methods:
%	See methods('tests_db')
%
% See also: params_tests_db, dlmread
%
% $Id$
%
% Author: Cengiz Gunay <cgunay@emory.edu>, 2004/09/01

% Copyright (c) 2007-2014 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
   obj.data = [];
   obj.col_idx = struct([]);
   obj.row_idx = struct([]);
   obj.id = '';
   obj.props = struct([]);
   obj = class(obj, 'tests_db');
 elseif isa(test_results,'tests_db') % copy constructor?
   obj = test_results;
 else

   if ~ exist('props', 'var')
     props = struct([]);
   end

   % Is it a file name?
   if ischar(test_results) 
     [path, filename, ext] = fileparts(test_results);
     % assert file has correct extension? [not necessary]
     %strcmpi(ext, '.csv')
     csv_args = getFieldDefault(props, 'csvArgs', {});
     
     % CSV?
     delim = getFieldDefault(props, 'textDelim', ',');
     
     % read column names from 1st row
     if isfield(props, 'csvReadColNames')
       [fid, msg] = fopen(test_results);
       if fid < 0
         error(['Can''t find file "' test_results '" to open: ' msg]);
       end
       if length(csv_args) > 0 && csv_args{1} > 0
         for skip_rows = 1:csv_args{1}, fgetl(fid); end
       end
       oneline = fgetl(fid);
       col_names = textscan(oneline, '"%[^"]"', 'Delimiter', delim);
       if isempty(col_names{1})
         col_names = textscan(oneline, '%s', 'Delimiter', delim);
       end
       fclose(fid);
       col_names = properAlphaNum(col_names{1}');
       
       % skip 1st row
       if length(csv_args) == 0 
         csv_args = {1 0};
       elseif length(csv_args{1}) == 1
         % add one more row if an offset is given
         csv_args{1} = max(1, csv_args{1} + 1);
       else
         rc = csv_args{1};
         rc(1) = max(1, rc(1));
         csv_args{1} = rc;
       end
       
       % remove from props to not clutter the tests_db object
       props = rmfield(props, 'csvReadColNames');
     end
     
     test_results = ...
         dlmread(test_results, delim, csv_args{:});
   end     

   % Only allow numeric arrays as test_results
   % TODO: add cell arrays?
   if ~ isnumeric(test_results) 
     error('Only numeric arrays allowed as test_results.');
   end
   
   % if given, load param names from file
   if isfield(props, 'paramDescFile')
     [fid msg] = fopen(props.paramDescFile);
     if fid < 0
       error(['Can''t find file "' props.paramDescFile '" to open: ' msg]);
     end
     col_names = textscan(fid, '%s');
     col_names = col_names{1};
     fclose(fid);
   end

   if size(test_results, 1) > 0 && ~ isempty(col_names) && ...
	 size(test_results, 2) ~= length(col_names)
     col_names
     error([ 'Number of columns in test_results (' ...
             num2str(size(test_results, 2)) ') and items in col_names (' ...
             num2str(length(col_names)) ') must match.']);
   end

   obj.data = test_results;


   % Prepare *_idx
   obj.col_idx = makeIdx(col_names);
   obj.row_idx = makeIdx(row_names);
   obj.id = id;
   obj.props = props;

   obj = class(obj, 'tests_db');
end


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