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Title: Graph theoretical analysis of human brain networks
Author: Bassett, D. S.
Awarding Body: University of Cambridge
Current Institution: University of Cambridge
Date of Award: 2009
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In the first study, functional brain networks are derived from magnetoencephalography (MEG) data from 12 healthy subjects in two task conditions (resting and finger tapping). The brain’s function is found to be characterized by a topological structure intermediate between random (short-cut connections) and highly ordered (provincial clustering). The architecture, as measured by a range of graph metrics, remains scale-invariant throughout the functioning brain’s classical frequency bands (from low frequency δ to high frequency γ) and in both the resting and motor states. Despite the general conservation of functional architecture, the brain does adjust the length of its high frequency (especially γ, >37.5 Hz) connections when it is required to perform a finger tapping task. The relatively shorter connections in the resting state suggest the existence of an energy efficiency constraint. In the second study, we therefore hypothesized that the brain functions on a balanced platform of maximum efficiency for minimum cost, and that the successfulness of this optimization predicts the cognitive ability of the system. Frequency specific functional networks were again derived from the MEG data of 28 healthy controls and 29 people with schizophrenia taken during a working memory task. A measure of the cost-efficiency of the high frequency (β band, 15-30 Hz) networks was found to be strongly predictive of a person’s cognitive performance independent of the health of the subject (whether non-psychotic or diagnosed with schizophrenia). In a third study, we used structural magnetic resonance imaging (sMRI) data from 259 healthy subjects and 203 people with schizophrenia to construct anatomical networks from the pairwise covariation of regional gray matter volumes. We found that the anatomical structure in the healthy brain contains a hierarchical organization which is inverted in schizophrenia and may thus be a vestige of abnormal neurodevelopmental processes.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available