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_p = plotYTests(a_db, x_vals, tests, axis_labels, title_str, short_title, ...
			  command, props)

% plotYTests - Create a plot given database measures against given X-axis values, for each row.
%
% Usage:
% a_p = plotYTests(a_db, x_vals, tests, axis_labels, title_str, short_title, command, props)
%
% Parameters:
%   a_db: A params_tests_db object.
%   x_vals: A vector of X-axis values.
%   tests: A vector or cell array of columns to correspond to each value from x_vals.
%   axis_labels: Cell array of X & Y axis labels.
%   title_str: (Optional) A string to be concatanated to the title.
%   short_title: (Optional) Few words that may appear in legends of multiplot.
%   command: (Optional) Command to do the plotting with (default: 'plot')
%   props: A structure with any optional properties.
%     LineStyle: Plot line style to use. (default: 'd-')
%     ShowErrorbars: If 1, errorbars are added to each point.
%     StatsDB: If given, use this stats_db for the errorbar (default=statsMeanStd(a_db)).
%     jitterX: Randomly jitter x-axis locations by this magnitude.
%     quiet: If 1, don't include database name on title.
%		
% Returns:
%   a_p: A plot_abstract.
%
% Description:
%
% Example:
% >> a_p = plotYTests(a_db_row, [0 40 100 200], ...
%		      {'IniSpontSpikeRateISI_0pA', 'PulseIni100msSpikeRateISI_D40pA', ...
%		       'PulseIni100msSpikeRateISI_D100pA', 'PulseIni100msSpikeRateISI_D200pA'}, ...
%		      {'current pulse [pA]', 'firing rate [Hz]'}, ', f-I curves', 'neuron 1');
% >> plotFigure(a_p);
%
% See also: plotFigure
%
% $Id$
%
% Author: Cengiz Gunay <cgunay@emory.edu>, 2006/01/23

% 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 ~ exist('title_str', 'var')
  title_str = '';
end

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

if ~ exist('short_title', 'var')
  short_title = '';
end

if ~ exist('command', 'var') || isempty(command)
  command = 'plot';
end

cols_db = onlyRowsTests(a_db, ':', tests);
jitter_x = getFieldDefault(props, 'jitterX', 0);

% set names on x-axis
test_names = getColNames(cols_db);
props.axisProps = ...
    mergeStructsRecursive(getFieldDefault(props, 'axisProps', struct), ...
                          struct('XTick', x_vals, ...
                                 'XTickLabel', {test_names}));

if ~ isfield(props, 'quiet')
  all_title = [ strrep(get(a_db, 'id'), '_', '\_') title_str ];
else
  all_title = title_str;
end

if isfield(props, 'LineStyle')
  line_style = {props.LineStyle};
else
  line_style = {};
  props.LineStyleOrder = {'d-', 'o-', '*-', 's-', 'x-', '+-'};
end

c_data = get(cols_db, 'data')';

if isfield(props, 'ShowErrorbars')
  % read the std from the second page of DB, if exists
  stats_db = getFieldDefault(props, 'StatsDB', statsMeanStd(cols_db));
  stats_db = onlyRowsTests(stats_db, ':', tests);
  a_p = ...
      plot_abstract({x_vals + rand(1, length(x_vals)) .* jitter_x - jitter_x/2, ...
                     c_data', get(onlyRowsTests(stats_db, 2, tests), 'data'), ...
                     line_style{:}}, ... % '+'
                    axis_labels, all_title, {short_title}, 'errorbar', props);
  % BUG: command is overridden in this case
else
  % Draw a regular line plot
  a_p = plot_abstract({x_vals + rand(1, length(x_vals)) .* jitter_x - jitter_x/2, c_data, line_style{:}}, ...
                      axis_labels, all_title, {short_title}, command, props);
end

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