38 citations · 81 across the 9 of their papers we have counts for
10 papers
Adaptive State-Space Multitaper Spectral Estimation
Andrew H. Song, Seong-Eun Kim, Emery N. Brown
Short-time Fourier transform (STFT) is the most common window-based approach for analyzing the spectrotemporal dynamics of time series. To mitigate the effects of high variance on…
Inferring neural dynamics during burst suppression using a neurophysiology-inspired switching state-space model
Gabriel Schamberg, Sourish Chakravarty, Taylor E. Baum +1
Burst suppression is an electroencephalography (EEG) pattern associated with profoundly inactivated brain states characterized by cerebral metabolic depression. Its distinctive fea…
PLSO: A generative framework for decomposing nonstationary time-series into piecewise stationary oscillatory components
Andrew H. Song, Demba Ba, Emery N. Brown
To capture the slowly time-varying spectral content of real-world time-series, a common paradigm is to partition the data into approximately stationary intervals and perform infere…
Controlling Level of Unconsciousness by Titrating Propofol with Deep Reinforcement Learning
Gabe Schamberg, Marcus Badgeley, Emery N. Brown
Reinforcement Learning (RL) can be used to fit a mapping from patient state to a medication regimen. Prior studies have used deterministic and value-based tabular learning to learn…
Constructing a control-ready model of EEG signal during general anesthesia in humans
John H. Abel, Marcus A. Badgeley, Taylor E. Baum +3
Significant effort toward the automation of general anesthesia has been made in the past decade. One open challenge is in the development of control-ready patient models for closed…
A state-space model for dynamic functional connectivity
Sourish Chakravarty, Zachary D. Threlkeld, Yelena G. Bodien +2
Dynamic functional connectivity (DFC) analysis involves measuring correlated neural activity over time across multiple brain regions. Significant regional correlations among neural…