netpyne.analysis.info module
Module for analyzing and plotting information theory results
- netpyne.analysis.info.nTE(cells1=[], cells2=[], spks1=None, spks2=None, timeRange=None, binSize=20, numShuffle=30)[source]
Function that calculates the Normalized Transfer Entropy (nTE) between two spike train signals.
Transfer entropy is a model-free statistic that is able to measure the time-directed transfer of information between stochastic variables and therefore provides an asymmetric method to measure information transfer. In simple words, the nTE represents the fraction of information in X explained by its own past which is not explained by the past of Y.
Kale, P. et al (2018, July). Normalized Transfer Entropy as a Tool to Identify Multisource Functional Epileptic Networks IEEE Engineering in Medicine and Biology Society (EMBC) https://doi.org/10.1109/embc.2018.8512532
- Parameters:
cells1 (list) – Subset of cells from which to obtain spike train 1. Default:
[]
Options:['all']
plots all cells and stimulations,['allNetStims']
plots just stimulations,['popName1']
plots a single population,['popName1', 'popName2']
plots multiple populations,[120]
plots a single cell,[120, 130]
plots multiple cells,[('popName1', 56)]
plots a cell from a specific population,[('popName1', [0, 1]), ('popName2', [4, 5, 6])]
, plots cells from multiple populationscells2 (list) – Subset of cells from which to obtain spike train 2. Default:
[]
Options: same as for cells1spks1 (list) – Spike train 1; list of spike times; if omitted then obtains spikes from cells1. Default:
None
Options:<option>
<description of option>spks2 (list) – Spike train 2; list of spike times; if omitted then obtains spikes from cells2. Default:
None
Options:<option>
<description of option>timeRange (list [min, max]) – Range of time to calculate nTE in ms. Default:
None
uses the entire simulation time range Options:<option>
<description of option>binSize (int) – Bin size used to convert spike times into histogram. Default:
20
Options:<option>
<description of option>numShuffle (int) – Number of times to shuffle spike train 1 to calculate TEshuffled; note: nTE = (TE - TEShuffled)/H(X2F|X2P). Default:
30
Options:<option>
<description of option>
- netpyne.analysis.info.plotGranger(cells1=None, cells2=None, spks1=None, spks2=None, label1=None, label2=None, timeRange=None, binSize=5, testGranger=False, plotFig=True, saveData=None, saveFig=None, showFig=True)[source]
Function that calculates Granger Causality between two spike train signals.
The Granger causality test is a statistical hypothesis test for determining whether one time series is useful in forecasting another. G-causality is based on the simple idea that causes both precede and help predict their effects.
Seth, A. K., Barrett, A. B., & Barnett, L. (2015). Granger Causality Analysis in Neuroscience and Neuroimaging. Journal of Neuroscience, 35(8), 3293–3297. https://doi.org/10.1523/jneurosci.4399-14.2015
- Parameters:
cells1 (list) – Subset of cells from which to obtain spike train 1. Default:
None
Options:['all']
plots all cells and stimulations,['allNetStims']
plots just stimulations,['popName1']
plots a single population,['popName1', 'popName2']
plots multiple populations,[120]
plots a single cell,[120, 130]
plots multiple cells,[('popName1', 56)]
plots a cell from a specific population,[('popName1', [0, 1]), ('popName2', [4, 5, 6])]
, plots cells from multiple populationscells2 (list) – Subset of cells from which to obtain spike train 2. Default:
None
Options: same as for cells1spks1 (list) – Spike train 1; list of spike times; if omitted then obtains spikes from cells1. Default:
None
spks2 (list) – Spike train 2; list of spike times; if omitted then obtains spikes from cells2. Default:
None
label1 (str) – Label for spike train 1 to use in plot. Default:
None
label2 (str) – Label for spike train 2 to use in plot. Default:
None
timeRange (list [min, max]) – Range of time to calculate nTE in ms. Default:
None
uses the entire simulation time rangebinSize (int) – Bin size used to convert spike times into histogram. Default:
5
testGranger (bool) – Whether to test the Granger calculation. Default:
False
plotFig (bool) – Whether to plot a figure showing Granger Causality Fx2y and Fy2x Default:
True
saveData (bool or str) – Whether and where to save the data used to generate the plot. Default:
False
Options:True
autosaves the data,'/path/filename.ext'
saves to a custom path and filename, valid file extensions are'.pkl'
and'.json'
saveFig (bool or str) – Whether and where to save the figure. Default:
False
Options:True
autosaves the figure,'/path/filename.ext'
saves to a custom path and filename, valid file extensions are'.png'
,'.jpg'
,'.eps'
, and'.tiff'
showFig (bool) – Shows the figure if
True
. Default:True
- netpyne.analysis.info.granger(cells1=None, cells2=None, spks1=None, spks2=None, label1=None, label2=None, timeRange=None, binSize=5, testGranger=False, plotFig=True, saveData=None, saveFig=None, showFig=True)
Function that calculates Granger Causality between two spike train signals.
The Granger causality test is a statistical hypothesis test for determining whether one time series is useful in forecasting another. G-causality is based on the simple idea that causes both precede and help predict their effects.
Seth, A. K., Barrett, A. B., & Barnett, L. (2015). Granger Causality Analysis in Neuroscience and Neuroimaging. Journal of Neuroscience, 35(8), 3293–3297. https://doi.org/10.1523/jneurosci.4399-14.2015
- Parameters:
cells1 (list) – Subset of cells from which to obtain spike train 1. Default:
None
Options:['all']
plots all cells and stimulations,['allNetStims']
plots just stimulations,['popName1']
plots a single population,['popName1', 'popName2']
plots multiple populations,[120]
plots a single cell,[120, 130]
plots multiple cells,[('popName1', 56)]
plots a cell from a specific population,[('popName1', [0, 1]), ('popName2', [4, 5, 6])]
, plots cells from multiple populationscells2 (list) – Subset of cells from which to obtain spike train 2. Default:
None
Options: same as for cells1spks1 (list) – Spike train 1; list of spike times; if omitted then obtains spikes from cells1. Default:
None
spks2 (list) – Spike train 2; list of spike times; if omitted then obtains spikes from cells2. Default:
None
label1 (str) – Label for spike train 1 to use in plot. Default:
None
label2 (str) – Label for spike train 2 to use in plot. Default:
None
timeRange (list [min, max]) – Range of time to calculate nTE in ms. Default:
None
uses the entire simulation time rangebinSize (int) – Bin size used to convert spike times into histogram. Default:
5
testGranger (bool) – Whether to test the Granger calculation. Default:
False
plotFig (bool) – Whether to plot a figure showing Granger Causality Fx2y and Fy2x Default:
True
saveData (bool or str) – Whether and where to save the data used to generate the plot. Default:
False
Options:True
autosaves the data,'/path/filename.ext'
saves to a custom path and filename, valid file extensions are'.pkl'
and'.json'
saveFig (bool or str) – Whether and where to save the figure. Default:
False
Options:True
autosaves the figure,'/path/filename.ext'
saves to a custom path and filename, valid file extensions are'.png'
,'.jpg'
,'.eps'
, and'.tiff'
showFig (bool) – Shows the figure if
True
. Default:True