RT Journal Article SR Electronic T1 Dynamic Brain Interactions during Picture Naming JF eneuro JO eNeuro FD Society for Neuroscience SP ENEURO.0472-18.2019 DO 10.1523/ENEURO.0472-18.2019 VO 6 IS 4 A1 Aram Giahi Saravani A1 Kiefer J. Forseth A1 Nitin Tandon A1 Xaq Pitkow YR 2019 UL http://www.eneuro.org/content/6/4/ENEURO.0472-18.2019.abstract AB Brain computations involve multiple processes by which sensory information is encoded and transformed to drive behavior. These computations are thought to be mediated by dynamic interactions between populations of neurons. Here, we demonstrate that human brains exhibit a reliable sequence of neural interactions during speech production. We use an autoregressive Hidden Markov Model (ARHMM) to identify dynamical network states exhibited by electrocorticographic signals recorded from human neurosurgical patients. Our method resolves dynamic latent network states on a trial-by-trial basis. We characterize individual network states according to the patterns of directional information flow between cortical regions of interest. These network states occur consistently and in a specific, interpretable sequence across trials and subjects: the data support the hypothesis of a fixed-length visual processing state, followed by a variable-length language state, and then by a terminal articulation state. This empirical evidence validates classical psycholinguistic theories that have posited such intermediate states during speaking. It further reveals these state dynamics are not localized to one brain area or one sequence of areas, but are instead a network phenomenon.