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Computational Methods and Analyses for Assessing Cerebellar Electrophysiology with Magneto- and Electroencephalography

The cerebellum contains almost 80% of all neurons in the human brain and is now recognized as a critical node in the distributed neural circuits underlying autonomic, sensorimotor, cognitive, and emotional functions. Cerebellar dysfunction has furthermore been implicated in some of the most prevalent neuropsychiatric diseases including autism and schizophrenia, with new information implicating the cerebellum in neurodegenerative dementias and Parkinson's disease as well.

Despite advances in our understanding of cerebellar structure and function on the microscopic scale, and an increasing number of hemodynamic functional imaging studies, the macroscopic-scale electrophysiology of the cerebellum remains poorly characterized. Magneto- and electroencephalography (M/EEG) can non-invasively and directly measure neural activity at sub-millisecond temporal resolution and therefore hold promise to bridge this gap. M/EEG has, however, so far mainly been employed to study the cerebral cortex and its use in the study of cerebellar electrophysiology is largely unexplored.

This thesis presents a comprehensive investigation on assessing cerebellar neural activity with M/EEG. First, a new technique that allows for reconstruction of the cerebellar cortex from standard-resolution in-vivo MRI data is presented. This technique is used to create a surface source space and quantify the detectability of neural activity in the cerebellum with M/EEG using Monte Carlo simulations. We then develop a novel analytical framework to compare the performance of both linear and non-linear source estimators for cerebellar activity and quantify their spatial fidelity. These proposed analytical methods, implemented in open-source software, assume only standard MRI and M/EEG data. They are therefore readily applicable and enable unearthing cerebellar signal components from both new and already collected data, thus providing a new lens into cerebellar electrophysiology without the need of new equipment or subject scans.

Thesis Supervisors:
Matti Hämäläinen, PhD
Professor of Radiology, Harvard Medical School

Bruce Rosen, MD, PhD
Laurence Lamson Robbins Professor of Radiology, MGH, Harvard Medical School
Director, Athinoula A. Martinos Center for Biomedical Imaging

Thesis Committee Chair:
Elfar Adalsteinsson, PhD
Professor of Electrical Engineering and Computer Science, MIT
Professor, Institute for Medical Engineering and Science (IMES), MIT

Thesis Reader:
Martin Ingvar, MD, PhD
Barbro and Bernard Osher Professor of Integrative Medicine, Karolinska Institute (KI)

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John Gustaf Wilhelm Samuelsson is inviting you to a scheduled Zoom meeting.

Topic: John Gustaf Wilhelm Samuelsson Thesis Defense

Time: May 12, 2021 03:00 PM Eastern Time (US and Canada)

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