Year: 2019
Type: dissertation
Abstract: The brain is a network of billions of neurons and even at rest, it exhibits complex patterns in activity such as synchrony. This is largely dependent on the temporal latencies in brain region interactions which represent an important aspect of healthy cognitive function, and play a role in neurological disorders such as epilepsy. An effective method of studying the variables involved in shaping these brain dynamics is through computational simulation of biophysical network models, such as the Wilson-Cowan and Kuramoto models. In this thesis, a computational pipeline is developed for inferring the macro-structure of temporal delays in brain region interactions, directly from neural time series data. This pipeline has great potential to be used as a tool to understand white matter and its relationship to brain dynamics.
Source: TSpace (University of Toronto)
Author: Noori, Rabiya
Institution: University of Toronto
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W2998549619