MEG Software and Analysis: Difference between revisions
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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. |
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. |
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* [[CTF Tools|The CTF Tools in a Singularity |
* [[CTF Tools|The CTF Tools in a Singularity Container]] |
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* [[Accessing CTF Datasets from Python]] |
* [[Pyctf|Accessing CTF Datasets from Python]] |
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* [[Time Frequency Analysis|Time Frequency Analysis Tools]] |
* [[Time Frequency Analysis|Time Frequency Analysis Tools]] |
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* [[Fun Stuff - How to make a movie| Fun Stuff - How to make a movie ]] |
* [[Fun Stuff - How to make a movie| Fun Stuff - How to make a movie ]] |
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* [[BIDS_GUIs | GUI: Creating and QA-ing MEG BIDS datasets + helpful preprocessing]] |
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* [[MEG analysis on Biowulf| MEG analysis on Biowulf]] |
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* [[Mne bids pipeline | MNE Bids Pipeline and BIDS background]] |
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* [[External MEG Analysis Toolboxes | Other Software packages]] |
* [[External MEG Analysis Toolboxes | Other Software packages]] |
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* Converting Brainsight Localizers or AFNI fiducials [https://github.com/nih-megcore/nih_to_mne to tags or MNE transforms] |
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* Connectivity Analysis [[Connectivity Resources | Resources]] |
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* ICA Cleaning/Analysis [[ICA cleaning | ICA]] |
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* Github MEG Code for NIH Labs doing MEG research [[NIH Labs Github Pages | Github Links]] |
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==== Basic Tutorials for New/Inexperienced Researchers==== |
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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. |
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* HPC: Introduction to Linux -- https://hpc.nih.gov/training/handouts/Introduction_to_Linux.pdf |
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* HPC: Bash Class -- https://hpc.nih.gov/training/bash_class/ |
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* Python Tutorial -- https://docs.python.org/3/tutorial/ |
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* AFNI Introduction -- https://andysbrainbook.readthedocs.io/en/latest/AFNI/AFNI_Short_Course/AFNI_fMRI_Intro.html |
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* HPC: Introduction to Biowulf -- https://hpc.nih.gov/training/intro_biowulf |
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==== Stimulus Presentation Software ==== |
==== Stimulus Presentation Software ==== |
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Latest revision as of 11:33, 11 December 2024
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.
- 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™ ).
Presentation: NeuroBehavioral Systems (NBS), Inc. Presentation® is a stimulus delivery and experiment control program for neuroscience written for Microsoft Windows.
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!
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
