Novel visual computations

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.

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Laurent U Perrinet

Laurent U Perrinet

Researcher in Computational Neuroscience

Biography

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.

Interests
  • Computational Neuroscience
  • Machine Learning
  • Vision
Education
  • 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

Recent & Upcoming Talks

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Current Students

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Hugo Ladret

Phd candidate in Computational Neuroscience

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Jean-Nicolas Jérémie

Phd candidate in Computational Neuroscience

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Antoine Grimaldi

Phd candidate in Computational Neuroscience

Former Students

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Victor Boutin

Phd in Computational Neuroscience

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Alberto Arturo Vergani

Post-Doc in Computational Neuroscience (04/2020 - 09/2021)

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Angelo Franciosini

Phd candidate in Computational Neuroscience

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Wahiba Taouali

PostDoc in Computational Neuroscience

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Jean-Bernard Damasse

Phd in Computational Neuroscience

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Kiana Mansour-Pour

Phd in Computational Neuroscience

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Mina A Khoei

Phd in Computational Neuroscience

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Jens Kremkow

Phd in Computational Neuroscience

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Nicole Voges

PostDoc in Computational Neuroscience

Contact

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