Program: Systems Science and Mathematics
Current advisor: ShiNung Ching, PhD
Undergraduate university: University of Chicago
Clinical monitoring of patients with neurological disease generates large volumes of data, including electrophysiology (e.g. EEG), heart rate, blood pressure, and other physiological measures. The use of these data to generate actionable prognostic measures is a long-held goal in clinical neurophysiology. In this regard, the use of engineering theory, including signal processing methods and computational modeling paradigms, is providing new ways of interpreting neurological data and yielding new insights into brain mechanisms and disease pathophysiology.
My dissertation research focused on the analysis and modeling of aberrant brain dynamical phenomena that occur over hours-long temporal epochs. Particularly, we considered time-scale separated electrophysiological modulation, in which brain electrical activity contains distinct harmonic components that differ by orders of magnitude in the frequency domain. We proposed methods for detecting such modulation, apply these methods to characterize its incidence in multiple clinical populations, and develop a biophysical dynamical systems model to study its underlying physiological mechanisms. Our primary focus was on the spatiotemporal analysis of slow (millihertz range) narrowband modulation in electroencephalogram (EEG) recordings. We proposed a method to construct sparse spectral estimates of power envelope signals obtained from physiological frequency bands of EEG. The former are obtained through a regularized basis pursuit approach, solved using LASSO methods and applied to temporal windows of variable length. This approach successfully identified modulation in brain electrical activity on much slower (<0.01Hz) time-scales than conventional power spectral analyses. We applied these methods in several large clinical cohorts: neonatal patients with encephalopathy and adult patients with hemorrhagic or ischemic stroke. We established validity of the method and its ability to derive a predictive biomarker. In the neonatal encephalopathy patients, we observed correlations between our modulation index values and developmental outcomes measures. Finally we generated a biophysically-informed dynamical systems model of the phenomenon. We identified parameter sets to generate aberrant oscillatory regimes in intracranial pressure (ICP) and other physiological process variables. We described bifurcations in the model dynamics, providing hypotheses and predictions regarding potential mechanisms underlying millihertz electrophysiological modulation. We compared the model outputs and predictions against findings from patients with multimodal (EEG, hemodynamic, ICP) monitoring data. Graduate publications
Loe ME, Khanmohammadi S, Morrissey MJ, Landre R, Tomko SR, Guerriero RM, Ching S. 2022 Resolving and characterizing the incidence of millihertz EEG modulation in critically ill children. Clin Neurophysiol, 137():84-91.
Loe ME, Morrissey MJ, Tomko SR, Guerriero RM, Ching S. 2022 Detecting slow narrowband modulation in EEG signals. J Neurosci Methods, 378():109660.
Guerriero RM, Morrissey MJ, Loe M, Reznikov J, Binkley MM, Ganniger A, Griffith JL, Khanmohammadi S, Rudock R, Guilliams KP, Ching S, Tomko SR. 2021 Macroperiodic Oscillations Are Associated With Seizures Following Acquired Brain Injury in Young Children. J Clin Neurophysiol, 10.1097/WNP.0000000000000828():Online ahead of print.
Gerull KM, Loe M, Seiler K, McAllister J, Salles A. 2019 Assessing gender bias in qualitative evaluations of surgical residents. Am J Surg, 217(2):306-313.
Loe ME, Brier MR, McCarthy JE, Stern A, Kuffner T, Bateman RJ, Morris JC, Benzinger TLS, Ances BM. (2018) Singular Value Decomposition (SVD) Identification of PiB and FDG Topographies in Dominantly Inherited Alzheimer’s Network (DIAN). Human Amyloid Imaging annual meeting, Miami, FL, Abstract.
Loe ME, Gerull K, Seiler K, McAllister J, Salles A. (2018) Assessing Gender Bias in Qualitative Evaluations of Surgical Residents. Association for Surgical Education annual meeting, Austin, TX, Abstract.