Understanding the brain through topological data analysis

The primary objective of this project is to leverage methods from Topological Data Analysis (TDA) to help us understand how individual brains differ.

By changing certain parameters, Magnetic Resonance Imaging (MRI) scanners allow us to collect two types of data: structural and functional. Structural data reveals the integrity of certain brain regions, e.g., is a certain part of the brain big or small? Functional data furnishes us with an indication of whether that brain region is being 'used' at a certain time point.

This project will apply methods from topological data analysis (TDA) on structural and functional datasets acquired by the University of Plymouth's Brain Research & Imaging Centre (BRIC). It will aim to provide ways to quantify how individual brains differ.

The challenge addressed by this research is a critical bottleneck in neuroscience and psychology - the scarcity of effective quantitative metrics for analysing the brain. The current approaches, using methods such as the General Linear Model and linear time-invariant systems, assume a highly modular organisation of the brain, where distinct regions support specific aspects of psychological functioning.

Work emanating from this project will allow us to break free from these conventional constraints, offering a more flexible and comprehensive perspective on the brain.