A framework for creating subject-specific mathematical brain models
This project aims to develop a framework for bridging the microscopic and macroscopic scales of neural dynamics. Methods will be developed to tailor macroscopic mean-field models to microscopic scale experimental data. The approach will be validated by comparing predictions of mean-field models to experimental data collected from calcium imaging and multi electrode arrays, which provide a ground truth. The creation of subject-specific models from data is important, as there is a large variability in neural circuits between individuals, despite seemingly similar network activity. The intended outcome is new insights into the processes that govern brain function and methods for improving interfacing to the brain.
This project will enable inference of microscopic aspects of neural circuits from macroscopic data.
Currently, most microscopic aspects of neural circuits cannot be measured in humans without major damage. The framework will enable the creation of subject-specific neural circuit diagrams, providing deep insights into brain function. The outcomes will eventually be applied to better understand and treat brain diseases that currently have no cure, and to develop new and improved medical bionics.
This project is jointly supervised by Dr Dean Freestone, Professor Mark Cook and Professor David Grayden (Department of Electrical and Electronic Engineering).
This research project is available to PhD students to join as part of their thesis.
Please contact the Research Group Leader to discuss your options.