Dynamic imaging of coherent sources: Studying neural interactions in the human brain

Functional connectivity between cortical areas may appear as correlated tim e behavior of neural activity. It has been suggested that merging of separa te features into a single percept ("binding") is associated with coherent g amma band activity across the cortical areas involved. Therefore, it would be of utmost interest to image cortico-cortical coherence in the working hu man brain. The frequency specificity and transient nature of these interact ions requires time-sensitive tools such as magneto- or electroencephalograp hy (MEG/EEG). Coherence between signals of sensors covering different scalp areas is commonly taken as a measure of functional coupling, However, this approach provides vague information on the actual cortical areas involved, owing to the complex relation between the active brain areas and the senso r recordings. We propose a solution to the crucial issue of proceeding beyo nd the MEG sensor level to estimate coherences between cortical areas. Dyna mic imaging of coherent sources (DICS) uses a spatial filter to localize co herent brain regions and provides the time courses of their activity. Refer ence points for the computation of neural coupling may be based on brain ar eas of maximum power or other physiologically meaningful information, or th ey may be estimated starting from sensor coherences. The performance of DIG S is evaluated with simulated data and illustrated with recordings of spont aneous activity in a healthy subject and a parkinsonian patient. Methods fo r estimating functional connectivities between brain areas will facilitate characterization of cortical networks involved in sensory, motor, or cognit ive tasks and will allow investigation of pathological connectivities in ne urological disorders.