Introduction to the NIRS AnalyzIR toolbox

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Pittsburgh 1 Background Started in 2014 by Jeff Barker, PhD

1 Introduction to the NIRS AnalyzIR toolbox Theodore Huppert PhD Associate Professor Dept of Radiology University of Pittsburgh 1 Background Started in 2014 by Jeff Barker, PhD (BioE grad student) Currently 2,018 unique downloads Average 37dn/day 2 1

2 Huppert Lab: +NIRS-toolbox Software Specs Matlab based 2014b or newer Statistics and signal processing toolboxes Open-source Command-line based (few GUIs added) Mercurial ( CVS ) control Wiki manual (in progress) Issue reporting Demo code and data Software Specs Matlab based 2014b or newer Statistics and signal processing toolboxes Open-source Command-line based (few GUIs added) Mercurial ( CVS ) control Wiki manual (in progress) Issue reporting Demo code and data 4 2

Open-source Command-line based (few GUIs added) Mercurial ( CVS ) control Wiki manual (in progress) Issue

3 Software Specs Matlab based 2014b or newer Statistics and signal processing toolboxes Open-source Command-line based (few GUIs added) Mercurial ( CVS ) control Wiki manual (in progress) Issue reporting Demo code and data 5 via TortoiseHG GUI 1) Install Windows or MacOS version 2) From GUI, Clone new repository 3) set source to 6 3

via TortoiseHG GUI https://tortoisehg.bitbucket.

4 via TortoiseHG GUI 1) Install Windows or MacOS version 2) From GUI, Clone new repository 3) set source to 7 via TortoiseHG GUI Pull Two-stage update system Public Web Version Update Push Pull Local Change History Commit Update Working Version 8 4

Commit Update Working Version 9 via Command Line (MacOS/Linux) https://www.

5 via TortoiseHG GUI Two-stage update system Public Web Version Push Pull Local Change History Commit Update Working Version 9 via Command Line (MacOS/Linux) Two-stage update system Public Web Version Push Pull Local Change History Commit Update Working Version 10 5

Adding to Matlab Path Note folders that start with + (e.g. /+nirs) denote Matlab namespaces and cannot be added directly to the path. You must add the parent folder containing this namespace.

6 Adding to Matlab Path Note folders that start with + (e.g. /+nirs) denote Matlab namespaces and cannot be added directly to the path. You must add the parent folder containing this namespace. 1) Add folder <root>/nirs-toolbox 2) Add with Subfolders <root>/nirs-toolbox/external <root>/nirs-toolbox/demos 11 +nirs/ NIRS analysis toolbox +eeg/ EEG & MEG analysis toolbox +dtseries/ Dense time series (CIFTI) formatted data (e.g. MRI [surface based] or MEEG/NIRS image reconstructed data +advanced/ repository for work in progress, depreciated code, and features for non-general use. << use with caution >> demos/ Example code for NIRS processing external Dependencies, and redistributed 3rd party code and GUIs called by toolboxes. This code is not intended to be called directly 12 6

5/18/18 http://www.dartmouth.edu/~nir/nirfast/ http://mcx.space/ http://iso2mesh.

html#/ 13 Matlab Namespaces Defines context specific function

m) Overwritten methods (e.g. nirs.core.data and eeg.core.data) Matlab Class Definitions custom classes (e.

data) contain common methods ( draw, table, etc) that act on the local object.

7 5/18/ Matlab Namespaces Defines context specific functions Called in form nirs.io.loaddirectory ( +nirs/+io/loaddirectory.m) Overwritten methods (e.g. nirs.core.data and eeg.core.data) Matlab Class Definitions custom classes (e.g. nirs.core.data) contain common methods ( draw, table, etc) that act on the local object. Abstract classes parent object classes defining inheritance to children not intended to be called directly Dependent variables read-only object fields that are computed on demand. E.g. Stats.p which depends on the beta, (noise covariance) and DFE fields 14 7

8 nirs.core.data main class for holding time-series data (also eeg.core.data, dtseries.core.data and nirs.core.genericdata). Encodes data, stimulus information, demographics, and probe >> raw.draw(<channels>) plots the data nirs.core.probe holds probe geometry, data labels ( link table) and registration information (including head model) >> probe.draw() plots the probe >> probe.defaultdrawfcn = sets the behavior (for registered probes) nirs.core.channelstats holds first and second-level statistical models >> stats.draw( tstat,[-5 5], q<0.05 ) draws the statistical map >> stats.ttest( A-B ) does a t-test of two conditions 15 Dictionary similar to use in Python holds variables based on keys MyDictionary( age ) =? nirs.design.stimulusevents holds discrete task events onset - onset time of events in seconds duration - duration of each event amp - amplitude of each event (used in parametric models) metadata - unused at moment (to encode reaction time etc) nirs.design.stimulusvector holds continuous task events (e.g. short-separation src-set data) amp - the regressor time-series data time - the sample times of data (interpt d to match nirs data) 16 8

Version Control Systems (VCS)

Version Control Systems (VCS) Xianyi Zeng xzeng@utep.edu Department of Mathematical Sciences The University of Texas at El Paso. September 13, 2016. Version Control Systems Let s get the textbook! Online