Events

Speaker: Daniel Tay, PhD Student, Department of Psychology, SFU

Abstract: In laboratory studies of visual distraction, participants repeatedly search for a target item that is sometimes accompanied by a salient distractor. Several competing theories have been introduced to explain behaviour in such search tasks, but in real life, people are not always actively searching when a salient-but-irrelevant stimulus appears. According to most contemporary theories, a salient stimulus should capture attention when a person is not searching for anything else, but using recordings of electrical brain activity, I discovered that such stimuli fail to capture attention when people know in advance that search is not required. This finding demonstrates that a person’s intentions can override stimulus salience to prevent unnecessary diversions of attention.

Speaker: Justin Wang, PhD Student, Department of Biomedical Physiology and Kinesiology, SFU

Abstract: Cognitive ageing reflects a complex interplay between structural changes and functional reorganization. Whole-brain dynamics arise from the coordination of regional activity, shaped by biophysical features such as bistability, neural noise, and global coupling (G). Bistability describes a neural population's capacity to switch between and stably inhabit high- and low-energy states; neural noise is stochasticity that enables this switching and the exploration of network configurations; G scales how strongly structurally connected regions influence one another. Brain modelling offers a way to characterize these features across the lifespan, but their joint effects remain underexplored. In this talk, I will present work using The Virtual Brain (TVB) to build personalized whole-brain network models from 429 healthy adults (ages 18–88) in the Cam-CAN dataset, linking regional bistability, neural noise, and global coupling to age, structure, and cognitive performance.

Using individually optimized Montbrió-Pazó-Roxin neural mass models, I generated simulated brain activity and derived a composite measure of bistability for each brain region. Preliminary findings show that whole-brain noise increases with age (r=0.49), while the variability of bistability across the brain decreases (r=-0.31), consistent with age-related dedifferentiation of dynamics. Partial Least Squares analyses reveal distinct bistability patterns associated with age, G, noise, structural connectivity, global functional dynamics, and cognitive performance. I will also discuss planned extensions: deriving empirical measures of bistability from MEG to validate simulated dynamics, applying this framework to the ADNI3 Alzheimer's cohort, and leveraging longitudinal data to characterize trajectories of cognitive decline. Together, this work will better characterize how neural dynamics and their underlying biophysical parameters change across the adult lifespan, in service of understanding reorganization in healthy ageing and its breakdown in neurodegeneration.