Let’s admit it: brains are not computers. Indeed, computers are still deceptive compared to biological perceptual systems. Think about rapidly detecting a novel object in clutter. Think about performing this with little supervision at a low energetic cost…
To narrow the gap between neuroscience and the theory of sensory processing computations, I am interested in bridging geometrical regularities found in natural scenes with the properties of neural computations as they are observed in sensory processes or behavior.
Laurent Perrinet is a computational neuroscientist specialized in large scale neural network models of low-level vision, perception and action, currently at the “Institut de Neurosciences de la Timone” (France), a joint research unit (CNRS / Aix-Marseille Université). He co-authored more than 40 articles in computational neuroscience and computer vision. He graduated from the aeronautics engineering school SUPAERO, in Toulouse (France) with a signal processing and applied mathematics degree. He received a PhD in Cognitive Science in 2003 on the mathematical analysis of temporal spike coding of images by using a multi-scale and adaptive representation of natural scenes. His research program is focusing in bridging the complex dynamics of realistic, large-scale models of spiking neurons with functional models of low-level vision. In particular, as part of the FACETS and BrainScaleS consortia, he has developed experimental protocols in collaboration with neurophysiologists to characterize the response of population of neurons. Recently, he extended models of visual processing in the framework of predictive processing in collaboration with the team of Karl Friston at the University College of London. This method aims at characterizing the processing of dynamical flow of information as an active inference process. His current challenge within the NeOpTo team is to translate, or compile in computer terminology, this mathematical formalism with the event-based nature of neural information with the aim of pushing forward the frontiers of Artificial Intelligence systems.
Habilitation à diriger des recherches , 2014
Aix Marseille Université
PhD. in Cognitive Science, 2003
Université P. Sabatier, Toulouse, France
M.S. in Engineering, 1998
Supaéro, Toulouse, France
MesoCentre (2018/2022) : access to the HPC resources of Aix-Marseille Université.
Le projet APROVIS3D est lauréat de l’appel à projets 2018 CHIST-ERA (2019).
Algorithmes événementiels d’Intelligence Artificielle / Event-Based Artificial Inteligence (2019).
ANR Horizontal-V1 (2017/2021): Connectivité Horizontale et Prédiction de Cohérences dans l’Intégration de Contour et Mouvement dans le Cortex Visuel Primaire
ANR PredictEye (2018/2020) : Mapping and predicting trajectories for eye movements
ANR SPEED: Traitement de la vitesse dans les scènes visuelles naturelles (2013/2016).
A grant from the Ph.D. program in Integrative and Clinical Neuroscience (PhD position, 2017 / 2021).
BrainScaleS: Brain-inspired multiscale computation in neuromorphic hybrid systems (2011/2014).
To enable the dissemination of the knowledge that is produced in our lab, we share all source code with open source licences.