Healthy brain activity relies on the constant exchange of electrical signals between grey matter regions. The traffic of information across the brain allows distant areas to work together to create the neural dynamics that underpin perception, behaviour, and cognition.
Cutting-edge brain imaging techniques can be used to map the human connectome – the complex network of nerve fibres that interlinks all brain regions and supports their communication. It is easy to see that, for any pair of communicating regions, there exist an astounding number of paths through which signalling can take place. What propagation and routing strategies are used to navigate the brain’s complex wiring and establish communication between regions?
To answer this question, we develop models of network communication that approximate biological neural signalling. To do this, we combine innovative methods from computer science, physics and statistics with multimodal neuroimaging datasets comprising thousands of participants. Our research has revealed new fundamental insight into how the brain’s anatomical wiring shapes functional interactions between regions. Applications of these insights include mapping disrupted neural communication in the aftermath of stroke, machine-learning predictions of human behaviour from imaging data, and the refinement of brain stimulation protocols used for treatment of clinical conditions.
Further research and key questions
- Develop computational models of network communication that accurately approximate patterns of neural signalling
- Understanding disrupted neural communication in disease states
- Investigate how external stimuli are propagated through the brain, with emphasis on clinical brain stimulation
Caio Seguin & Andrew Zalesky
Further reading: General interest pieces
- Your brain has landmarks that drive neural traffic and help you make hard decisions. The Conversation.
- Like sightseeing in Paris – a new model for brain communication. The Conversation.
Further reading: Journal articles
- Seguin, C., Tian, Y., & Zalesky, A. (2020). Network communication models improve the behavioral and functional predictive utility of the human structural connectome. Network Neuroscience, 4:4, 980-1006.
- Seguin, C., Razi, A., & Zalesky, A. (2019). Inferring neural signalling directionality from undirected structural connectomes. Nature communications, 10(1), 1-13.
- Wang, X., Seguin, C., Zalesky, A., Wong, W. W., Chu, W. C. W., & Tong, R. K. Y. (2019). Synchronization lag in post stroke: relation to motor function and structural connectivity. Network Neuroscience, 3(4), 1121-1140.
- Seguin, C., Van Den Heuvel, M. P., & Zalesky, A. (2018). Navigation of brain networks. Proceedings of the National Academy of Sciences, 115(24), 6297-6302.
- Avena-Koenigsberger, A., Misic, B., & Sporns, O. (2018). Communication dynamics in complex brain networks. Nature Reviews Neuroscience, 19(1), 17.