Identifying true brain interaction from EEG data using the imaginary part of coherency.
OBJECTIVE
The main obstacle in interpreting EEG/MEG data in terms of brain connectivity is the fact that because of volume conduction, the activity of a single brain source can be observed in many channels. Here, we present an approach which is insensitive to false connectivity arising from volume conduction.


METHODS
We show that the (complex) coherency of non-interacting sources is necessarily real and, hence, the imaginary part of coherency provides an excellent candidate to study brain interactions. Although the usual magnitude and phase of coherency contain the same information as the real and imaginary parts, we argue that the Cartesian representation is far superior for studying brain interactions. The method is demonstrated for EEG measurements of voluntary finger movement.


RESULTS
We found: (a) from 5 s before to movement onset a relatively weak interaction around 20 Hz between left and right motor areas where the contralateral side leads the ipsilateral side; and (b) approximately 2-4 s after movement, a stronger interaction also at 20 Hz in the opposite direction.


CONCLUSIONS
It is possible to reliably detect brain interaction during movement from EEG data.


CONCLUSIONS
The method allows unambiguous detection of brain interaction from rhythmic EEG/MEG data.
Nolte
Guido
G
Human Motor Control Section, NINDS, NIH, 10 Center Drive MSC 1428, Bldg 10, Room 5N226, Bethesda, MD 20892-1428, USA. nolteg@ninds.nih.gov
Bai
Ou
O
Wheaton
Lewis
L
Mari
Zoltan
Z
Vorbach
Sherry
S
Hallett
Mark
M
D000465:Algorithms; D000513:Alpha Rhythm; D001611:Beta Rhythm; D001921:Brain / Q000502:physiology*; D003627:Data Interpretation, Statistical; D004569:Electroencephalography / Q000706:statistics & numerical data*; D007839:Functional Laterality / Q000502:physiology; D015225:Magnetoencephalography / Q000706:statistics & numerical data; D008959:Models, Neurological