I will introduce Brain Algorithmics, a novel framework to reconnect cognitive neuroscience with the longstanding tradition of information processing explanations in the sciences of cognition. At its core, Brain Algorithmics identifies the abstract information goals that the brain must process in a cognitive task to accomplish behavior—i.e. the information ontology. Then, with information theoretic tools, the framework reveals where, when and how an algorithmic network model of brain activity represents, transmits and transforms the information ontology between stimulus onset and behavior—i.e. the functional ontology. Brain Algorithmics can also realize the promise of other neuroimaging analyses and deep convolutional networks.

Speaker: Philippe Schyns is professor of visual neuroscience, Director of the Institute of Neuroscience and Psychology and Head of the School of Psychology at the University of Glasgow. He did his undergraduate training in Psychology at University of Liege (Belgium) and in Computer Science at University of Louvain-la-Neuve (Belgium). In 1992, he completed a PhD in Cognitive Science at Brown University. Following a post-doc with Tommaso Poggio in the Department of Brain and Cognitive Sciences at MIT he joined the faculty at University of Montreal. A year later, he moved to Glasgow University. He leads a team researching the behavioural and neural aspects of information processing in vision.

Rachael Jack & Philippe Schyns

Rachael Jack et Philippe Schyns sont deux figures proéminentes du monde de la psychologie et des neurosciences cognitives, et des pionniers de l'approche dite de 'reverse corrélation' et de l'utilisation d'outils computationnels pour la recherche en cognition et neurosciences sociales. Leurs travaux sont pour l'instant dans le domaine de la cognition visuelle (ex. expressions faciales http://www.pnas.org/content/109/19/7241), qu'ils visent à étendre dans le domaine auditif.