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University of Glasgow, Scotland
Philippe G. Schyns is the Director of the Institute of Neuroscience and Psychology and Head of the School of Psychology at the University of Glasgow. He obtained his Ph.D. degree in Cognitive Science at Brown University (USA) in 1992. After a post-doc in the Department of Brain and Cognitive Sciences he joined the Department of Psychology at the University of Montréal (Canada) as an Assistant Professor. He is a Fellow of the Royal Society of Edinburgh, Action Editor for Psychological Science and Editor of Frontiers in Perception Science.
In his research prof. Schyns investigates the information processing mechanisms of face, object and scene categorization in the brain from computational, behavioral and brain imaging perspectives. In order to bridge the gap between the recorded brain activity and the information processing it represents, his team is developing data-driven methodologies that can deliver information processing from behavior and brain activity.
Their recent publication topics include the role of cultural facial expressions in conveying emotion category and intensity as well as the impact of stereotype-related facial features on social class perception. The most commonly utilized techniques are magnetoencephalography (MEG), electroencephalography (EEG), mathematical modelling, and behavioral tasks.
In cognitive neuroscience, a pivotal remaining challenge is the translation of brain activity into comprehensible information processing. Though sophisticated tools measure brain activity with exceptional spatial and temporal resolution, across varying scales of observation, how do we interpret this activity as a process that computes information? To address this critical question, I will introduce a framework that leverages generative models of visual categories to enable interpretation of the information that brain networks represent and transmit, and the computations that underlie perception. Using this approach, we can extract meaningful insights into information processing from dynamic brain activity and its Deep Neural Network models, thereby pushing the frontiers of brain imaging and computational neuroscience.
Adolphs R, Gosselin F, Buchanan TW, Tranel D, Schyns P, Damasio AR. A mechanism for impaired fear recognition after amygdala damage. Nature. 2005 Jan 6;433(7021):68-72. doi: 10.1038/nature03086. PMID: 15635411.
Jack, R. E., Garrod, O. G., Yu, H., Caldara, R., & Schyns, P. G. (2012). Facial expressions of emotion are not culturally universal. Proceedings of the National Academy of Sciences of the United States of America, 109(19), 7241–7244. https://doi.org/10.1073/pnas.1200155109
Schyns, P. G., & Oliva, A. (1994). From Blobs to Boundary Edges: Evidence for Time- and Spatial-Scale-Dependent Scene Recognition. Psychological Science, 5(4), 195-200. https://doi.org/10.1111/j.1467-9280.1994.tb00500.x
Gosselin, F., & Schyns, P. G. (2001). Bubbles: a technique to reveal the use of information in recognition tasks. Vision research, 41(17), 2261–2271. https://doi.org/10.1016/s0042-6989(01)00097-9