Difference between revisions of "MEG Software and Analysis"

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pyctf tools are a collection of Python scripts useful in the analysis of data sets collected from the CTF scanner.
 
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.
 
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.
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* [https://megcore.nih.gov/MEG/parsemarks.py parsemarks.py download]
   
 
<syntaxhighlight lang="bash">
 
<syntaxhighlight lang="bash">
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-h, --help show this help message and exit
 
-h, --help show this help message and exit
 
-l the marks are labeled in the ouput. Useful for debugging.
 
-l the marks are labeled in the ouput. Useful for debugging.
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</syntaxhighlight>
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* [https://megcore.nih.gov/MEG/parsemarks_report.py parsemarks_report.py download]
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<syntaxhighlight lang="bash">
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parsemarks_report.py
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usage: parsemarks_report.py [-h] [-v] studydir
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Reports on the marker set from every dataset directory under a study
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directory. MEG studies consists of a collection of datasets, each with its own
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MarkerFile.mrk, organized under a top level (studydir) directory. Output is an
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excel file stored in your ~/excel folder.
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positional arguments:
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studydir path to a toplevel directory holding a set of dataset
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directories (required)
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optional arguments:
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-h, --help show this help message and exit
 
</syntaxhighlight>
 
</syntaxhighlight>
   

Revision as of 11:57, 16 September 2018

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

  • 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).