MEG Software and Analysis

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 download

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 download

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

• parsemarks_report.py download

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™ ).

• 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

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.

• Viewing raw data: the CTF Data Editor

• Preprocessing: Dataset and Task Utilities

• Time Frequency Analysis Tools

• Head Localization and MRI Co-Registration

• Source Localization - the SAM pipeline

• Fun Stuff - How to make a movie

• Other Software packages

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).