Monash University
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Statistical Machine Learning Methods for Modelling, Imaging, and Monitoring the Brain

thesis
posted on 2024-05-09, 22:28 authored by YUN ZHAO
This PhD study develops new computational frameworks and uses lots of experimental data to understand how the human brain works. It improves brain imaging techniques to directly measure brain activity, something current methods can't do well. The study introduces a framework called Neurophysiological Process Imaging (NPI), which uses advanced math methods and brain models to interpret brain scan data more accurately. This approach has helped understand brain conditions such as consciousness and epileptic seizures. It shows how brain networks change with consciousness and seizures. Overall, this research offers novel insights into brain functions and demonstrates the power of computational methods in studying the brain.

History

Campus location

Australia

Principal supervisor

Levin Kuhlmann

Additional supervisor 1

Mario Boley

Year of Award

2024

Department, School or Centre

Data Science & Artificial Intelligence

Course

Doctor of Philosophy

Degree Type

DOCTORATE

Faculty

Faculty of Information Technology