Identifying functional networks using endogenous connectivity in gamma band electrocorticography.

Correlations in spontaneous, infra-slow (<0.1 Hz) fluctuations in gamma band (70-100 Hz) signal recorded using electrocorticography (ECoG) reflect the functional organization of the brain, appearing in auditory and visual sensory cortex, motor cortex, and the default mode network (DMN). We have developed a data-driven method using co-modulation in spontaneous, infra-slow, and gamma band power fluctuations in ECoG to characterize the connectivity between cortical areas. A graph spectral clustering algorithm was used to identify networks that appear consistently. These networks were compared with clinical mapping results obtained using electrocortical stimulation (ECS). We identify networks corresponding to motor and visual cortex with good specificity. Anatomic and functional evidence indicates that other networks, such as the DMN, are also identified by this algorithm. These results indicate that it may be possible to map functional cortex using only spontaneous ECoG recordings. In addition, they support the hypothesis that infra-slow co-modulations of gamma band power represent the neurophysiological basis underlying resting-state networks. Methods examining infra-slow co-modulations in gamma band power will be useful for studying changes in brain connectivity in differing behavioral contexts. Our observations can be made in the absence of observable behavior, suggesting that the electrical mapping of functional cortex is feasible without the use of ECS or task-mediated evoked responses.