Computational Modeling
Brain
We aim to uncover critical principles of brain structure and function in health and disease based on the integration of computational, molecular and imaging neuroscience
Division Leader: Prof Alex Fornito
The Brain division undertakes interdisciplinary research to understand how the brain works in health and disease from a network perspective. The human brain is arguably the most complex network we know of, consisting of billions of nerve cells interconnected by trillions of axonal fibers. Interactions unfolding within this intricate web of connectivity form the basis of all our thoughts, emotions and behavior, and their derailment can lead to mental illnesses such as schizophrenia, depression and obsessive-compulsive disorder.
To understand this extraordinary complexity, we use techniques from a range of disciplines, spanning complex network science, mathematics, psychology and psychiatry, neuroscience and genetics. A major focus is on the application of graph theoretic methods to MRI data, particularly functional and diffusion MRI, and on integrating these findings with behavioral and clinical information. We hope to use this interdisciplinary approach to generate new insights into the workings of the brain and its dysfunction in mental illness.
Research Areas
Our research primarily uses brain imaging and other tools from cognitive neuroscience to understand human brain structure and function in health and disease. Our team has a diverse range of expertise, with particular strengths in structural, functional, diffusion and spectroscopic MRI, EEG, TMS, PET, graph theory and network science, and clinical neuropsychology. Our principal areas of research focus are:
- Network science and connectomics
- Analysis methods for magnetic resonance imaging
- Imaging genetics
- Schizophrenia and other psychoses
- Brain stimulation and electrophysiology
- Computational modelling