Notes:
Matlab files that accompany "Biomarkers Based on Comprehensive
Hierarchical EEG Coherence Analysis: Example Application to Social
Competence in Autism (Preliminary Results)" by Mo Modarres, David
Cochran, David N. Kennedy, Richard Schmidt, Paula Fitzpatrick, and
Jean A. Frazier.
Usage Notes: BCMs.m
% BCMs.m is a Matlab Script that computes a General Brain Coherence
Marker
% (BCM). BCM is based on EEG magnitude squared coherence estimate,
computed
% over user specified:
% (1) Brain Regions
% (2) Time Periods
% (3) Frequency Bands
%
% by Mo H Modarres, PhD
% Eunice Kennedy Shriver Center
% University of Massachusetts Medical School
% 02/02/2021
%
% Usage:
% Step 1: Place EEG time series in a matrix X, where each column of
X
% correspond to EEG data from a single EEG channel
%
% Step 2: Select the time period of analysis ;
%
% Step 3: Compute a matrix of coherence functions between all
desired EEG
% pairs, using function BCMpairs.m. This step will produece
% a matrix of coherence functions with L columns,
% where L=Factorial[(No. of Columns of X) 1]
%
% Example if X consists of 4 EEG channels (4 columns of
% data), then a coherence matrix with Factorial(41)=3+2+1=6
% columns is produced, where each column corresponds to a coherence
% function beween unqiue pairs of EEG channels .
%
% Step 4: Perform Averaging of coherences of Step 3 over a
specified
% frequency band:
%
% Step 5: Compute the averaged coherences of Step 4 over a
specified brain
% region
%
% Define the following variables
%
% Tp = [k1 k2];where k1 and k2 correspond to the start and the end
of
% analysis segment in Seconds
TP=[ ]
%
% Fs = Sampling frequency specified in Hertz.
Fs=
% Frq_Res= Frequency Resolution in Hertz.
Frq_Res=
% Overlap= a Value that selects the amount of overlap between two
% consecutive segments of analysis, in fraction of Fs, values
% 0.1 to 1.0; Default overlap=1;
Overlap=
% Frq_band=[f1,f2 ] where f1 and f2 correspond to the start and end
of
% frequency band (in Hertz) over which the coherences will be
% averaged
Frq_band=[ ]
% ROI: Brain Region of Interest; ROI is a vector of numerical
values that correpond
% to the column number of allcoh, which is a matrix of all
coherence functions
% Each column is the coherence function from a single EEG pair
ROI=[]
% Output: Coh_F_Region_Average, a coherence value averaged over ROI
and
% Frequency band of Interest
Usage Notes: BCMpairs.m
% Computes COherence functions between any two EEG channels.
Utlizes
% Matlab's MSCOHERE function, which calculates Magnitude Squared
% Coherence estimates using Welch's averaged, modified periodogram
method,
% with values between 0 and 1 indicating the level of synchrocity
between
% two EEG waveforms.
%
% Input Variables:
% X, Y: EEG channel data,
% Fs = Sampling frequency specified in hertz.
% Frq_Res= Frequency Resolution in hertz.
% Overlap= a Value that selects the amount of overlap between two
consecutive
% segments of analysis, in fraction of Fs, values 0.1 to 1.0;
% Default overlap=1;
Changes:
