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 a_db = rop(left_obj, right_obj, op_func, op_id)

% rop - Prepares aligned columns in two DBs or one DB and a scalar for an array arithmetic operation.
%
% Usage:
% a_db = rop(left_obj, right_obj, op_func, op_id)
%
% Description:
%   If DBs have mismatching columns only the common columns will be kept.
% In any case, the resulting DB columns will be sorted in the order of the
% left-hand-side DB. Array addition (plus), subtraction (minus),
% multiplication (mtimes) and division (rdivide) use this function to
% align columns.
%
% Parameters:
%   left_obj, right_obj: Operands of the operation. One must be of type tests_db
%		and the other can be a scalar or tests_db.
%   op_func: Operation function (e.g., @plus).
%   op_id: A string to represent the operation that will show up in the
%   	  returned id.
%		
% Returns:
%   a_db: The resulting tests_db.
%
% See also: tests_db/plus, tests_db/minus, tests_db/mtimes, tests_db/rdivide
%
% $Id$
%
% Author: Cengiz Gunay <cgunay@emory.edu>, 2007/12/13

% Copyright (c) 2007 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 isa(left_obj, 'tests_db') && isa(right_obj, 'tests_db')
  % check for column consistency
  [left_names, right_names] = ...
      checkConsistentCols(left_obj, right_obj, struct('useCommon', 1));
  if ~length(left_names) || ~length(right_names)
    error('No common columns between two databases!');
  end
  left_data = get(left_obj, 'data');
  % preserve column order of first DB
  right_data = get(onlyRowsTests(right_obj, ':', left_names), 'data');  
  a_db = left_obj;
  an_id = [ get(left_obj, 'id') ' ' op_id ' ' get(right_obj, 'id') ];
elseif isa(left_obj, 'tests_db') || isa(right_obj, 'tests_db')
  if isa(left_obj, 'tests_db')
    a_db = left_obj;
    left_data = get(left_obj, 'data');
    left_label = get(left_obj, 'id');
    right_data = right_obj;
    if isscalar(right_data)
      right_label = num2str(right_data);
    else
      right_label = 'numeric matrix';
    end
  else
    a_db = right_obj;
    left_data = left_obj;
    if isscalar(left_data)
      left_label = num2str(left_data);
    else
      left_label = 'numeric matrix';
    end
    right_data = get(right_obj, 'data');
    right_label = get(right_obj, 'id');
  end    
  an_id = [ left_label ' ' op_id ' ' right_label ];
else
  if ~isnumeric(left_obj)
    error(['Array division is defined only between tests_db objects and scalars. ' ...
	   'You gave the type: ' class(left_obj) '.' ]);
  end

  % left's a scalar, right one must be a DB for us to be here
  right_data = get(right_obj, 'data');
  left_data = left_obj * ones(size(1, right_data), 1) * ones(1, size(2, right_data));
  an_id = [ num2str(a_scalar) ' ' op_id ' ' get(right_obj, 'id') ];
  a_db = right_obj;
end

a_db = set(a_db, 'id', an_id);
a_db = set(a_db, 'data', feval(op_func, left_data, right_data));

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