  Electrocorticography (ECoG) provides direct measurements of synchronized
postsynaptic potentials at the exposed cortical surface. Patterns of signal
covariance across ECoG sensors have been associated with diverse cognitive
functions and remain a critical marker of seizure onset, progression, and
termination. Yet, a systems level understanding of these patterns (or networks)
has remained elusive, in part due to variable electrode placement and sparse
cortical coverage. Here, we address these challenges by constructing
inter-regional ECoG networks from multi-subject recordings, demonstrate
similarities between these networks and those constructed from
blood-oxygen-level-dependent signal in functional magnetic resonance imaging,
and predict network topology from anatomical connectivity, interregional
distance, and correlated gene expression patterns. Our models accurately
predict out-of-sample ECoG networks and perform well even when fit to data from
individual subjects, suggesting shared organizing principles across persons. In
addition, we identify a set of genes whose brain-wide co-expression is highly
correlated with ECoG network organization. Using gene ontology analysis, we
show that these same genes are enriched for membrane and ion channel
maintenance and function, suggesting a molecular underpinning of ECoG
connectivity. Our findings provide fundamental understanding of the factors
that influence interregional ECoG networks, and open the possibility for
predictive modeling of surgical outcomes in disease.

Neurons and Cognition