On this week's Journal Club session, Emil Dmitruk will talk about his work in the presentation entitled "Topological Data Analysis Reveals Brain Connectivity Differences between Schizophrenia Subjects and Healthy Controls".

The aim of this study is to reveal structural connectivity patterns prevalent across a large population and whether any of these patterns differ between schizophrenia subjects (SCH) and healthy controls (HC). We use topological data analysis methods, namely persistent homology using the weight rank clique filtration on brain connectivity matrices obtained from a probabilistic fibre-tracking algorithm run on the Centre for Biomedical Research Excellence (COBRE) dataset (N = 44 SCH, N = 44 HC) to investigate group differences. We show that some of the connectivity structures differ in strength relative to connectivity structures affecting other brain regions. These differences would not have been apparent using traditional methods that explore only the absolute strength of connectivity between regions. We show that many connectivity structures (cycles) are shared among numerous subjects and some of the cycles are significantly different between the two studied populations- both on a whole brain level (all cycles combined), and also at the level of individual cycle classes. Brain regions involved in cycles that were found were mentioned in studies of brain alteration in schizophrenia, e.g. precuneus, motor, visual, and parietal cortices (the last being tied to experiences of psychosis). We show that HC and SCH subjects share a lot in their structural connectome and the effect of schizophrenia is an alteration in the relative strength, as measured by topological persistence, of various white matter connectivity structures. We believe that further studies could lead to prognostication for individual patients and be the first step to developing personalised treatment.

Date: 2024/07/05
Time: 14:00
Location: C258 & online