Probabilistic Functional Modes: population-informed individual specific modelling of brain networks

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• Rezvan Farahibozorg, University of Oxford, UK
• Monday 03 March 2025, 12:30-13:30
• MRC-CBU, 15 Chaucer Road, Cambridge.

If you have a question about this talk, please contact Dace Apšvalka.

Speaker: Visiting in person – Dr Rezvan Farahibozorg, University of Oxford, UK

Title: Probabilistic Functional Modes: population-informed individual specific modelling of brain networks.

Abstract: The human brain is a system of networks, each underlying a specific function, and interacting with each other. Brain networks at rest; also known as resting state networks (RSNs), have been very influential in characterisation of the functional organisation of the brain. The framework of Probabilistic Functional Modes (PROFUMO) is designed to estimate RSNs simultaneously for populations and every individual therein, thus permitting us to capture individual-specific characteristics beyond what has been possible using standard group-average-based techniques such as ICA . In this talk, I will first describe this modelling framework and its various extensions. I will then show some of its applications to large fMRI datasets such as the Human Connectome Project and UK Biobank, including the characterisation of multiscale brain modes, prediction of non-imaging traits, and potential for subgroup discovery.

Bio: Rezvan Farahibozorg is a Royal Academy of Engineering research fellow at FMRIB , Oxford. Her research aims to design new machine learning tools for big functional brain imaging data such as UK Biobank, and to make predictions about personalised traits (e.g. age or cognitive scores) and disease (e.g. Dementia). Before joining FMRIB , she was trained as a Biomedical Engineer and proceeded to complete her PhD at CBU , working on developing brain connectivity methods for magnetoencephalography, and application for characterising semantic networks in the brain.

Venue: MRC CBU West Wing Seminar Room and Zoom https://us02web.zoom.us/j/82385113580?pwd=RmxIUmphQW9Ud1JBby9nTDQzR0NRdz09 (Meeting ID: 823 8511 3580; Passcode: 299077)

This talk is part of the CBU Monday Methods Meeting series.

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