MEG Software and Analysis: Difference between revisions

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MEG Data Analysis

This section covers all aspects of MEG data analysis. The following pages assume that you have AFNI installed and have a reasonably good idea of how to use it.

The CTF Tools in a Singularity Container

Accessing CTF Datasets from Python

Time Frequency Analysis Tools

Head Localization and MRI Co-Registration

Source Localization - the SAM pipeline

Fun Stuff - How to make a movie

MEG analysis on Biowulf

MNE Bids Pipeline and BIDS background

Other Software packages

Converting Brainsight Localizers or AFNI fiducials to tags or MNE transforms

Connectivity Analysis Resources

ICA Cleaning/Analysis ICA

Github MEG Code for NIH Labs doing MEG research Github Links

Basic Tutorials for New/Inexperienced Researchers

Most MEG Core scripts are written in bash, which is the command line interface to Linux. Python is a more powerful programming language, and Tom and Jeff have written some of our scripts in Python, but you don't really need to know how they work, just what they do. The AFNI tutorial below is geared towards fMRI/BOLD analysis. For MEG analysis you can ignore all the BOLD things, we just use it for statistics and display of the final source reconstruction results. If you want to go more in depth, Tom can explain the ones we use. Biowulf can be employed later when you want it all to go faster.

HPC: Introduction to Linux -- https://hpc.nih.gov/training/handouts/Introduction_to_Linux.pdf
HPC: Bash Class -- https://hpc.nih.gov/training/bash_class/
Python Tutorial -- https://docs.python.org/3/tutorial/
AFNI Introduction -- https://andysbrainbook.readthedocs.io/en/latest/AFNI/AFNI_Short_Course/AFNI_fMRI_Intro.html
HPC: Introduction to Biowulf -- https://hpc.nih.gov/training/intro_biowulf

Stimulus Presentation Software

PsychoPy: Psychology software in Python PsychoPy is an open-source application that allows you to run a wide range of neuroscience, psychology and psychophysics experiments. It’s a free, powerful alternative to Presentation™ or to e-Prime™, written in Python (a free alternative to Matlab™ ).

Pyschopy documentation for release 1.90.2

Presentation: NeuroBehavioral Systems (NBS), Inc. Presentation® is a stimulus delivery and experiment control program for neuroscience written for Microsoft Windows.

Presentation online documentation

E-prime 3: Psychology Software Tools E-Prime® 3.0 software for behavioral research. Build your own experiments using E-Prime’s easy-to-use graphical interface. Design, collect, and analyze data – all within a few hours!

E-Prime 3.0 website

Miscellaneous Documentation

SensLayout-275 — a color picture showing the sensor names and relative locations (ps).
SensLayout-275 - a color picture showing the sensor names and relative locations (pdf).
File Formats - CTF MEG data file format

@@ Line 1: / Line 1: @@
-==== MEG Core pyctf tools ported to Python 3====
+==== MEG Data Analysis ====
-pyctf tools are a collection of Python scripts useful in the analysis of data sets collected from the CTF scanner.
-These tools have been rewritten using modern Python 3 syntax following standard coding conventions. Most of these programs will run unmodified under MacOS, Windows, and the various versions of Linux with a Python 3.4 distribution or later installed.  Python programs requiring modules not included in the standard Python library are indicated.
+This section covers all aspects of MEG data analysis. The following pages assume that you have [[afni.nimh.nih.gov|AFNI]] installed and have a reasonably good idea of how to use it.
-* [https://megcore.nih.gov/pyctf/parsemarks.py parsemarks.py download]
+* [[CTF Tools|The CTF Tools in a Singularity Container]]
-<syntaxhighlight lang="bash">
-parsemarks.py
-usage: parsemarks.py [-h] [-l] dataset
+* [[Pyctf|Accessing CTF Datasets from Python]]
-Extract the marks from the marker file associated with dataset
-and print themin a useful format.
+* [[Time Frequency Analysis|Time Frequency Analysis Tools]]
-positional arguments:
-  dataset     path to CTF dataset or MarkerFile.mrk (required)
+* [[Head Localization and MRI Coregistration|Head Localization and MRI Co-Registration]]
-optional arguments:
-  -h, --help  show this help message and exit
-  -l          the marks are labeled in the output. Useful for debugging.
-</syntaxhighlight>
+* [[Source Localization - SAM|Source Localization - the SAM pipeline]]
-parsemarks2.py provides provides more control over the output.
+* [[Fun Stuff - How to make a movie| Fun Stuff - How to make a movie ]]
-* [https://megcore.nih.gov/pyctf/parsemarks2.py parsemarks2.py download]
+* [[MEG analysis on Biowulf| MEG analysis on Biowulf]]
-<syntaxhighlight lang="bash">
-parsemarks2.py
-usage: parsemarks2.py [-h] [-l] [-m marker...] [-s] dataset
+* [[Mne bids pipeline | MNE Bids Pipeline and BIDS background]]
-Extract the marks from the marker file associated with dataset and print them
-in a useful format.
+* [[External MEG Analysis Toolboxes | Other Software packages]]
-positional arguments:
-  dataset     path to CTF dataset (required)
+* Converting Brainsight Localizers or AFNI fiducials [https://github.com/nih-megcore/nih_to_mne to tags or MNE transforms]
-optional arguments:
-  -h, --help  show this help message and exit
-  -l          the marks are labeled in the output. Useful for debugging.
-  -m marker   the specified mark(s) is reported (default is all markers)
-  -s          shows a list of markers in dataset and exits
-</syntaxhighlight>
+* Connectivity Analysis [[Connectivity Resources | Resources]]
-* [https://megcore.nih.gov/pyctf/parsemarks_report.py parsemarks_report.py download]
-Requires the ''xlsxwriter'' module for writing Excel files.
+* ICA Cleaning/Analysis [[ICA cleaning | ICA]]
-<syntaxhighlight lang="bash">
-parsemarks_report.py
-usage: parsemarks_report.py [-h] [-v] studydir
+* Github MEG Code for NIH Labs doing MEG research [[NIH Labs Github Pages | Github Links]]
-Reports on the marker set from every dataset directory under a study
-directory. MEG studies consists of a collection of datasets, each with its own
-MarkerFile.mrk, organized under a top level (studydir) directory. Output is an
-excel file stored in your ~/excel folder.
+==== Basic Tutorials for New/Inexperienced Researchers====
-positional arguments:
-  studydir    path to a toplevel directory holding a set of dataset
+Most MEG Core scripts are written in bash, which is the command line interface to Linux. Python is a more powerful programming language, and Tom and Jeff have written some of our scripts in Python, but you don't really need to know how they work, just what they do. The AFNI tutorial below is geared towards fMRI/BOLD analysis. For MEG analysis you can ignore all the BOLD things, we just use it for statistics and display of the final source reconstruction results. If you want to go more in depth, Tom can explain the ones we use. Biowulf can be employed later when you want it all to go faster.
-              directories (required)
+* HPC: Introduction to Linux --  https://hpc.nih.gov/training/handouts/Introduction_to_Linux.pdf
+* HPC: Bash Class -- https://hpc.nih.gov/training/bash_class/
+* Python Tutorial -- https://docs.python.org/3/tutorial/
+* AFNI Introduction -- https://andysbrainbook.readthedocs.io/en/latest/AFNI/AFNI_Short_Course/AFNI_fMRI_Intro.html
+* HPC: Introduction to Biowulf -- https://hpc.nih.gov/training/intro_biowulf
-optional arguments:
-  -h, --help  show this help message and exit
-</syntaxhighlight>
 ==== Stimulus Presentation Software ====
@@ Line 74: / Line 53: @@
 E-Prime® 3.0 software for behavioral research. ''Build your own experiments using E-Prime’s easy-to-use graphical interface. Design, collect, and analyze data – all within a few hours!''
 * [https://pstnet.com/products/e-prime/ E-Prime 3.0 website]
-===== MEG Data Analysis =====
-This section covers all aspects of MEG data analysis. The following pages assume that you have [[afni.nimh.nih.gov|AFNI]] installed and have a reasonably good idea of how to use it.
-* [[CTF DataEditor|Viewing raw data: the CTF Data Editor]]
-* [[Dataset and Task Utilities|Preprocessing: Dataset and Task Utilities]]
-* [[Time Frequency Analysis|Time Frequency Analysis Tools]]
-* [[Head Localization and MRI Coregistration|Head Localization and MRI Co-Registration]]
-* [[Source Localization - SAM|Source Localization - the SAM pipeline]]
-* [[Fun Stuff - How to make a movie| Fun Stuff - How to make a movie ]]
-* [[External MEG Analysis Toolboxes | Other Software packages]]
 ====Miscellaneous Documentation====
@@ Line 97: / Line 58: @@
 * [[Image:adobe-ps.png]] [[Media:SensLayout-275.ps|SensLayout-275]] — a color picture showing the sensor names and relative locations (ps).
 * [[Image:pdf.png]] [[Media:SensLayout-275.pdf|SensLayout-275]] - a color picture showing the sensor names and relative locations (pdf).
+* [[Image:pdf.png]] [[Media:FileFormats.pdf|File Formats]] - CTF MEG data file format

MEG Software and Analysis: Difference between revisions

Latest revision as of 12:20, 25 October 2022

Contents

MEG Data Analysis

Basic Tutorials for New/Inexperienced Researchers

Stimulus Presentation Software

Miscellaneous Documentation

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MEG Software and Analysis: Difference between revisions

Latest revision as of 12:20, 25 October 2022

MEG Data Analysis

Basic Tutorials for New/Inexperienced Researchers

Stimulus Presentation Software

Miscellaneous Documentation

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