This is a collaborative space. In order to contribute, send an email to maximilien.chaumon@icm-institute.org
On any page, type the letter L on your keyboard to add a "Label" to the page, which will make search easier.

fast_tf

Owned by Former user (Deleted)
Last updated: May 18, 2017 by Maximilien CHAUMON

Time-Frequency Analysis

fast_tf is a standalone Linux software package dedicated to time-frequency analysis of MEG/EEG signals.

This software results from a collaboration between Pitié-Salpêtrière MEG/EEG Center and COGIMAGE team from CRICM.
Principal contributors to this version:

  • Time frequency analysis core programming}: C. Tallon-Baudery - D. Schwartz
  • Original wavelet algorithm: O. Bertrand (Lyon U821 INSERM)
  • I/O libraries}: J-D. Lemaréchal and A. Ducorps
  • Matlab routine}: L. Yahia-Cherif, A. Barbot, M. Chaumon, D. Schwartz

fast_tf was developed under Linux using CentOs 5.8 distribution.
fast_tf is available for Linux on Intel386 PC (both 32 bits and 64 bits are available) and MacOs X (compiled on 10.6 MacOS X system)
fast_tf is a standalone program and doesn't need any additional software. Visualization of time-frequency maps needs Muse, Matlab or a similar tool (necessary visualization functions are provided for matlab).

fast_tf is available on all CENIR workstations.

Fast TF is command line program dedicated to time frequency analysis of MEG/EEG signals. Using wavelets, it computes time frequency maps in term of power, z score relative to a given baseline, phase, phase locking factor, synchrony between sensors across trials and synchrony between sensors on a window of time. New to version 4.5, Fast TF also computes coherence between sensors. Fast TF takes advan- tage of FFTW 3.1 library to offer very fast computation and multi-processing capabilities. This version can read CTF/VSM ds files, Elekta-Neuromag fiff files, LENA files and ASCII data. It generates LENA files readable in matlab or Muse. Matlab functions to read and to plot time-frequency maps are pro- vided. The documentation begins with a quick start guide for impatient users followed by methodological considerations. A complete description of all options is available in the second part of the manual.

Full documentation: :|fast_tf_hr.pdf