Difference between revisions of "MEG Software and Analysis"

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* [[Image:adobe-ps.png]] [[Media:SensLayout-275.ps|SensLayout-275]] — a color picture showing the sensor names and relative locations (ps).
 
* [[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:SensLayout-275.pdf|SensLayout-275]] - a color picture showing the sensor names and relative locations (pdf).
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* [[Image:pdf.png]] [[Media:FileFormats.pdf|File Formats]] - CTF MEG data file format

Revision as of 15:07, 17 January 2019

MEG Core pyctf tools ported to Python 3

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.

parsemarks.py
usage: parsemarks.py [-h] [-l] dataset

Extract the marks from the marker file associated with dataset 
and print themin a useful format.

positional arguments:
  dataset     path to CTF dataset or MarkerFile.mrk (required)

optional arguments:
  -h, --help  show this help message and exit
  -l          the marks are labeled in the output. Useful for debugging.

parsemarks2.py provides provides more control over the output.

parsemarks2.py
usage: parsemarks2.py [-h] [-l] [-m marker...] [-s] dataset

Extract the marks from the marker file associated with dataset and print them
in a useful format.

positional arguments:
  dataset     path to CTF dataset (required)

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
Requires the xlsxwriter module for writing Excel files.
parsemarks_report.py
usage: parsemarks_report.py [-h] [-v] studydir

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.

positional arguments:
  studydir    path to a toplevel directory holding a set of dataset
              directories (required)

optional arguments:
  -h, --help  show this help message and exit

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!

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.

Miscellaneous Documentation

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