title: A method for real-time cortical oscillation detection and phase-locked stimulation.
abstract: Neural oscillations are important features in a working central nervous system, facilitating efficient communication across large networks of neurons. To better study the role of these oscillations in various cognitive processes, and to be able to build clinical applications around them, accurate and precise estimations of the instantaneous frequency and phase are required. Here, we present methodology based on autoregressive modeling to accomplish this in real time. This allows the targeting of stimulation to a specific phase of a detected oscillation. Using intracranial EEG recorded from two patients performing a Sternberg memory task, we characterize our algorithm's phase-locking performance on physiologic theta oscillations.
authors.affiliation: Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA. wanderso68@gmail.com
authors.forename: L Leon
authors.initials: LL
authors.lastname: Chen
authors.forename: Radhika
authors.initials: R
authors.lastname: Madhavan
authors.forename: Benjamin I
authors.initials: BI
authors.lastname: Rapoport
authors.forename: William S
authors.initials: WS
authors.lastname: Anderson
mesh_terms: D000465:Algorithms; D002490:Central Nervous System / Q000502:physiology; D003071:Cognition; D009474:Neurons / Q000502:physiology*