Math Modeling Seminar: A causal cross-frequency coupling framework for quantifying brain dynamic changes in dementia

Math Modeling Seminar
A causal cross-frequency coupling framework for quantifying brain dynamic changes in dementia

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Dr. Marco Pinto-Orellana
Assistant Professor
Rochester Institute of Technology

Abstract:
Cross-frequency coupling (CFC) is a phenomenon observed in electroencephalographic signals where oscillatory components at different frequencies interact with each other. CFC patterns have shown potential as biomarkers to predict seizure intervention outcomes, sleep patterns, and other diseases. Existing CFC metrics, including modulation index and phase-locking value, capture some categories of CFC phenomena while assuming non-directionality in such interactions. In this talk, we introduce an approach that captures Granger-causal cross-modulatory effects through an extended Bayesian vector autoregressive framework. This framework allows efficient computational estimation methods while also providing robust uncertainty estimation. We highlight the effectiveness of this framework to understand changes in brain dynamics in individuals with Alzheimer's and frontotemporal dementia.

Bio:
Dr. Marco Pinto-Orellana is an assistant professor in the department of neuroscience at RIT. His research focuses on developing efficient computational models to represent brain dynamics and extract biomarkers from electroencephalographic (EEG) and functional near-infrared spectroscopy (fNIRS) signals. He strongly values multidisciplinary research. He earned his PhD in Engineering from the Oslo Metropolitan University, where he focused on time-spectral modeling of brain signals. Following his PhD, he pursued postdoctoral research on pediatric epilepsy models at the University of California, Irvine, in the computational and translational neuroscience laboratory. Dr. Pinto-Orellana also holds an MS in Computer Science from the Federal University of Viçosa and a BS in Telecommunications Engineering from the Bolivian Catholic University. He complemented this work with interdisciplinary training in statistics at the King Abdullah University of Science and Technology.

Intended Audience:
Beginners, undergraduates, graduates. Those with interest in the topic.

Interpreters have been requested.