title: Emergence of persistent networks in long-term intracranial EEG recordings.
abstract: Over the past two decades, the increased ability to analyze network relationships among neural structures has provided novel insights into brain function. Most network approaches, however, focus on static representations of the brain's physical or statistical connectivity. Few studies have examined how brain functional networks evolve spontaneously over long epochs of continuous time. To address this, we examine functional connectivity networks deduced from continuous long-term electrocorticogram recordings. For a population of six human patients, we identify a persistent pattern of connections that form a frequency-band-dependent network template, and a set of core connections that appear frequently and together. These structures are robust, emerging from brief time intervals (~100 s) regardless of cognitive state. These results suggest that a metastable, frequency-band-dependent scaffold of brain connectivity exists from which transient activity emerges and recedes.
authors: Department of Mathematics and Statistics, Boston University, Boston, Massachusetts 02215, USA. mak@bu.edu
authors: Mark A
authors: MA
authors: Kramer
authors: Uri T
authors: UT
authors: Eden
authors: Kyle Q
authors: KQ
authors: Lepage
authors: Eric D
authors: ED
authors: Kolaczyk
authors: Matt T
authors: MT
authors: Bianchi
authors: Sydney S
authors: SS
authors: Cash
mesh_terms: D000328:Adult; D001921:Brain / Q000503:physiopathology*; D001931:Brain Mapping; D004566:Electrodes; D004569:Electroencephalography; D017029:Epilepsy, Complex Partial / Q000473:pathology* / Q000503:physiopathology; D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D008959:Models, Neurological; D009434:Neural Pathways / Q000503:physiopathology; D017711:Nonlinear Dynamics; D055815:Young Adult