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
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 ouput. Useful for debugging.
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
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).
