Recent & Upcoming Talks

Learning hetero-synaptic delays of Spiking Neurons for motion detection
The response of a biological neuron depends on the precise timing of afferent spikes. This temporal aspect of the neuronal code is …
Last updated on May 20, 2022
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Ultra-rapid visual search in natural images using active deep learning
Visual search, that is, the simultaneous localization and detection of a visual target of interest, is a vital task. Applied to the …
Last updated on May 20, 2022
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Which sparsity problem does the brain solve?
Experimental evidence suggests that activity in sensory cortices is sparse in that only few neurons out of a large pool that could …
Last updated on May 20, 2022
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Learning hetero-synaptic delays of Spiking Neurons for motion detection
Last updated on May 20, 2022
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Retinotopic mapping improves the reliability of image classification
Follows a previous work Emmanuel Daucé, Pierre Albigès, Laurent U Perrinet (2020). A dual foveal-peripheral visual processing model implements efficient saccade selection. Journal of Vision. Preprint PDF Cite Code DOI
Last updated on May 20, 2022
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Polychrony detection using heterosynaptic delays
Follow this future presentations Antoine Grimaldi, Laurent U Perrinet (2022). Learning hetero-synaptic delays of Spiking Neurons for motion detection. NeuroVision Workshop in conjunction with CVPR 2022. Cite URL Glad to meet the @centuri_ls crowd at the #CENTURIday !
May 19, 2022
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Réseaux de neurones artificiels et apprentissage machine appliqués à la compréhension de la vision
Où: Salle PHY51 - Marseille (France) Quoi: Master 1 Neurosciences et Sciences Cognitives Réseaux neuronaux artificiels pour la vision Mercredi 23/03/2022 de 9h-12h Introduction aux Neurosciences de la Vision Réseaux de neurones artificiels et apprentissage machine slides Neurones impulsionnels et modèles des fonctions visuelles Mercredi 23/03/2022 de 13h30-16h30 TP via notebook https://github.
Mar 23, 2022
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Statistics of the sparse representations of natural images
In most mammals, the primary visual cortex (V1) processes complex mixtures of orientations to construct an accurate neural …
Last updated on Oct 12, 2021
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Des illusions aux hallucinations visuelles: une porte sur la perception
Les illusions visuelles sont des créations d’artistes, de scientifiques et plus récemment, grâce aux réseaux sociaux, du grand …
Jan 12, 2022
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Dynamical processing of orientation precision in the primary visual cortex
The primary visual cortex (V1) processes complex mixtures of orientations to build neural representations of our visual environment. It …
Last updated on Jul 12, 2021
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Pooling in a predictive model of V1 explains functional and structural diversity across species
Presenting my poster tonight at 8:00p #cosyne2020, a work developed using Sparse Deep Predictive Coding (SDPC) during my PhD @laurentperrinet @NeuroSchool_mrs pic.twitter.com/LtUEBnlPNt — AF (@Angelo_RDN) February 28, 2020 This is from:
Last updated on Jun 14, 2021
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Dynamical processing of orientation precision in the primary visual cortex
The primary visual cortex (V1) processes complex mixtures of orientations to build neural representations of our visual environment. It …
Last updated on Jul 12, 2021
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Understanding natural vision using deep predictive coding
Building models which efficiently process images is a great source of inspiration to better understand the processes which underly our …
Sep 25, 2020
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Visual search as active inference
Visual search is an essential cognitive ability, offering a prototypical control problem to be addressed with Active Inference. Under a …
Sep 14, 2020
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From the retina to action: Understanding visual processing
Visual areas are essential in transforming the raw luminous signal into a representation which efficiently conveys information about …
Apr 3, 2020
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Des illusions aux hallucinations visuelles: une porte sur la perception
Les illusions visuelles sont des créations d’artistes, de scientifiques et plus récemment, grâce aux réseaux sociaux, du grand …
Jan 20, 2020
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Learning where to look: a foveated visuomotor control model
In computer vision, the visual search task consists in extracting a scarce and specific visual information (the target) from a large …
Jul 15, 2019
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Should I stay or should I go? Humans adapt to the volatility of visual motion properties, and know about it
Animal behavior must constantly adapt to changes, for example when the state of an environmental context changes unexpectedly. For an …
May 23, 2019
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Des illusions aux hallucinations visuelles: une porte sur la perception
Les objectifs sont : – mieux comprendre la fonction de la perception visuelle en explorant certaines limites ; – mieux comprendre l’importance de l’aspect dynamique de la perception ; – mieux comprendre le rôle de l’action dans la perception.
Apr 18, 2019
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Des illusions aux hallucinations visuelles: une porte sur la perception
Should I stay or should I go? Adaption of human observers to the volatility of visual inputs
Animal behavior has to constantly adapt to changes, for instance when unexpectedly switching the state of an environmental context. For …
Apr 5, 2019
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From the retina to action: Understanding visual processing
Visual areas are essential in transforming the raw luminous signal into a representation which efficiently conveys information about …
Apr 3, 2019
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From the retina to action: Predictive processing in the visual system
Visual areas are essential in transforming the raw luminous signal into a representation which efficiently conveys information about …
Mar 25, 2019
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Should I stay or should I go? Adaption of human observers to the volatility of visual inputs
See the final publication @ Chloé Pasturel, Anna Montagnini, Laurent U Perrinet (2020). Humans adapt their anticipatory eye movements to the volatility of visual motion properties. PLoS Computational Biology.
Jan 18, 2019
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Role of dynamics in neural computations underlying visual processing
Jan 17, 2019
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Efficient coding of visual information in neural computations
Jan 16, 2019
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Modelling spiking neural networks using Brian, Nest and pyNN
Jan 14, 2019
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Rencontre avec les collégiens marseillais
Le jeudi 10 janvier 2019, je suis venu échanger au côté de Serge Dentin autour de films traitant du rapport fiction/réel, des illusion …
Jan 10, 2019
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La modélisation biomorphique de la perception visuelle
La modélisation biomorphique de la perception visuelle in “La modélisation de la genèse physico-mathématique du vivant” BIOMORPHISME ET CREATION ARTISTIQUE – Session 3 Date 11 Octobre 2018 Atelier Séminaire/workshop organisé dans le cadre du projet Biomorphisme.
Oct 11, 2018
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Intervention fête de la science 2018
FÊTE DE LA SCIENCE 2018 : Alcazar / MERLAN L’Association Polly Maggoo http://www.pollymaggoo.org/ met en place tout le long de l’année, des actions de culture scientifique et artistique en direction du grand public et des lycées, au cours desquelles l’association programme des films à caractère scientifique.
Oct 10, 2018
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Principles and psychophysics of Active Inference in anticipating a dynamic, switching probabilistic bias
See the final publication @ Chloé Pasturel, Anna Montagnini, Laurent U Perrinet (2020). Humans adapt their anticipatory eye movements to the volatility of visual motion properties. PLoS Computational Biology.
Apr 5, 2018
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Probabilities, Bayes and the Free-energy principle
Mar 26, 2018
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Estimating and anticipating a dynamic probabilistic bias in visual motion direction
See the final publication @ Chloé Pasturel, Anna Montagnini, Laurent U Perrinet (2020). Humans adapt their anticipatory eye movements to the volatility of visual motion properties. PLoS Computational Biology.
Feb 1, 2018
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Expériences autour de la perception de la forme en art et science
Meetup Art et Neurosciences Quoi Meetup Art et Neurosciences Qui Association NeuroNautes Quand 25 Janvier 2018 Où Salle des voutes campus Saint Charles Support visuel https://laurentperrinet.github.io/sciblog/files/2018-01-25_meetup-neuronautes.html (notes: la présentation peut mettre un certain temps à charger.
Jan 25, 2018
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Unsupervised learning applied to robotic vision
see a related work describing SDPC in: Victor Boutin, Angelo Franciosini, Frédéric Chavane, Franck Ruffier, Laurent U Perrinet (2021). Sparse Deep Predictive Coding captures contour integration capabilities of the early visual system.
Nov 24, 2017
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Participation au jury
FESTIVAL INTERFÉRENCES​ Cinéma Documentaire et Débat Public FESTIVAL INTERFÉRENCES​ Le collectif Scènes Publiques composé de citoyens, chercheurs et cinéastes, organise la deuxième édition du Festival Interférences du 8 au 18 novembre 2017 à Lyon.
Nov 17, 2017
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What dynamic neural codes for efficient visual processing
This seminar is an exercise to introduce the AMU masters into the format of international conferences. As such, we will try to …
Nov 15, 2017
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Back to the present: dealing with delays in biological and neuromorphic systems
Jun 28, 2017
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Tutorial on predictive coding
Jun 28, 2017
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Tutorial: Active inference for eye movements: Bayesian methods, neural inference, dynamics
Jan 20, 2017
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Tutorial: Sparse optimization in neural computations
Jan 19, 2017
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Back to the present: how neurons deal with delays
Jan 18, 2017
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Participation au jury et entretien avec Clara Delmon
RENCONTRES INTERNATIONALES SCIENCES & CINÉMAS cinéma les Variétés http://pollymaggoo.org/wp-content/uploads/2016/10/RISC2016_A3-724x1024.jpg L’Association Polly Maggoo http://www.pollymaggoo.org/ programme la 10e édition des RENCONTRES INTERNATIONALES SCIENCES & CINÉMAS (RISC) à Marseille, au cours desquelles l’association programme des films à caractère scientifique.
Nov 20, 2016
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The flash-lag effect as a motion-based predictive shift
Based on Perrinet et al, 2012 and Khoei et al, 2013 See a followup in Khoei et al, 2017
Nov 3, 2016
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Reinforcement contingencies modulate anticipatory smooth eye movements
Natural environments potentially contain several interesting targets for goal-directed behavior. Thus sensorimotor systems need to …
Nov 3, 2016
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Biologically-inspired characterization of sparseness in natural images
Oct 26, 2016
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Categorization of microscopy images using a biologically inspired edge co-occurrences descriptor
See a followup in Laurent U Perrinet, James A Bednar (2015). Edge co-occurrences can account for rapid categorization of natural versus animal images. Scientific Reports. Preprint PDF Cite Code DOI
Oct 26, 2016
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Eye movements as a model for active inference
See the final publication @ Chloé Pasturel, Anna Montagnini, Laurent U Perrinet (2020). Humans adapt their anticipatory eye movements to the volatility of visual motion properties. PLoS Computational Biology.
Oct 13, 2016
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Modelling the dynamics of cognitive processes: from the Bayesian brain to particles
See a followup in Perrinet et al, 2012
Jul 7, 2016
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Les illusions visuelles, un révélateur du fonctionnement de notre cerveau
Les illusions visuelles sont des créations d’artistes, de scientifiques et plus récemment, grâce aux réseaux sociaux, du grand …
Apr 28, 2016
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Les illusions visuelles, un révélateur du fonctionnement de notre cerveau
Les illusions visuelles, un révélateur du fonctionnement de notre cerveau
Ce lundi 25 avril de 9h à 12h, je suis venu échanger au côté de Serge Dentin autour de films traitant du rapport fiction/réel, des …
Apr 25, 2016
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Motion-based prediction with neuromorphic hardware
We stand at a point in history where our phones have become smart but lack a feature which prevails in most forms of living …
Nov 5, 2015
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Motion-based prediction with neuromorphic hardware
We stand at a point in history where our phones have become smart but lack a feature which prevails in most forms of living …
Oct 7, 2015
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Motion-based prediction with neuromorphic hardware
Signature of an anticipatory response in area V1 as modeled by a probabilistic model and a spiking neural network
see Kaplan and al, 2014
Apr 25, 2014
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WP5 - Demo 1.3 : Spiking model of motion-based prediction
The question how the visual system is able to create a coherent representation of a rapidly changing environment in the presence of …
Mar 20, 2014
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Axonal delays and on-time control of eye movements
Moving objects generate sensory information that may be noisy and ambiguous, yet it is important to be able to reconstruct object speed …
Jan 10, 2014
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Demo 1, Task4: Implementation of models showing emergence of cortical fields and maps
Together with Bernhard Kaplan, we talked about how we aim at “compiling” a predictive motion-based approach as a spiking neural networks and then as a parallel wafer systems in the BrainscaleS project (Demo 1, Task4).
Nov 26, 2013
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Edge co-occurrences and categorizing natural images
See a followup in Laurent U Perrinet, James A Bednar (2015). Edge co-occurrences can account for rapid categorization of natural versus animal images. Scientific Reports. Preprint PDF Cite Code DOI
Jul 5, 2013
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Why methods and tools are the key to artificial brain-like systems
This session aims at presenting new ideas that emerged during the first years of BrainScaleS. Indeed, the collaborations that were …
Mar 21, 2013
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Edge statistics in natural images versus laboratory animal environments: implications for understanding lateral connectivity in V1
Oriented edges in images of natural scenes tend to be aligned in collinear or co-circular arrangements, with lines and smooth curves …
May 10, 2012
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Apparent motion in V1 - Probabilistic approaches
Mar 23, 2012
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MotionClouds: Model-based stimulus synthesis of natural-like random textures for the study of motion perception
Mar 22, 2012
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Grabbing, tracking and sniffing as models for motion detection and eye movements
Moving objects generate sensory information that may be noisy and ambiguous, yet it is important to be able to reconstruct object speed …
Jan 27, 2012
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Edge statistics in natural images versus laboratory animal environments: implications for understanding lateral connectivity in V1
Oriented edges in images of natural scenes tend to be aligned in collinear or co-circular arrangements, with lines and smooth curves …
Jan 24, 2012
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Motion-based prediction is sufficient to solve the aperture problem
In low-level sensory systems, it is still unclear how the noisy information collected locally by neurons may give rise to a coherent …
Jan 12, 2012
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Edge statistics in natural images versus laboratory animal environments: implications for understanding lateral connectivity in V1
Oriented edges in images of natural scenes tend to be aligned in collinear or co-circular arrangements, with lines and smooth curves …
Nov 15, 2011
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Demo 1, Task4: Implementation of models showing emergence of cortical fields and maps
Oct 5, 2011
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Edge statistics in natural images versus laboratory animal environments: implications for understanding lateral connectivity in V1
Oriented edges in images of natural scenes tend to be aligned in collinear or co-circular arrangements, with lines and smooth curves …
Sep 28, 2011
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Propriétés émergentes d'un modèle de prédiction probabiliste utilisant un champ neural
Sensory informations such as visual images are inherently variable. We use probabilistic models to describe how the low-level visual …
Jul 2, 2011
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Probabilistic models of the low-level visual system: the role of prediction in detecting motion
Sensory informations such as visual images are inherently variable. We use probabilistic models to describe how the low-level visual …
Dec 17, 2010
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Diffraction monochromatique, spectre audiographique
En perception, les neurones « parlent » tous en même temps par de brèves impulsions électrochimiques, générant un mélange de signaux, …
Apr 14, 2010
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Diffraction monochromatique, spectre audiographique
Models of low-level vision: linking probabilistic models and neural masses
see this more recent talk @ UCL, London
Jan 8, 2010
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Reading out the dynamics of lateral interactions in the primary visual cortex from VSD data
Short presentation of a large moving pattern elicits an ocular following response that exhibits many of the properties attributed to …
Nov 30, 2009
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Peut-on parler d'intelligence mécanique?
Nous parlerons de cette partie "mécanique" du cerveau animal ou humain qui permet de percevoir les mouvements et de … …
Nov 24, 2009
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Control of the temporal interplay between excitation and inhibition by the statistics of visual input
see this subsequent paper in the Journal of Computational Neuroscience
Jul 18, 2009
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Decoding low-level neural information to track visual motion
Moving the eyes rapidly to track a visual object moving in a cluttered environment is an essential function. However, doing so rapidly …
Apr 1, 2009
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Decoding the population dynamics underlying ocular following response using a probabilistic framework
The machinery behind the visual perception of motion and the subsequent sensorimotor transformation, such as in Ocular Following …
Jun 1, 2008
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From neural activity to behavior: computational neuroscience as a synthetic approach for understanding the neural code.
Computational Neuroscience is a synthetic, inter-disciplinary approach aiming at understanding cognition by analyzing the mechanisms …
Apr 1, 2008
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Modeling of spikes, sparseness and adaptation in the primary visual cortex: applications to imaging
related publications @ FENS 2006, @ NeuroComp 2008 and @ AREADNE 2008
Feb 1, 2008
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What efficient code for adaptive spiking representations?
Dec 1, 2007
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Neural Codes for Adaptive Sparse Representations of Natural Images
I will illustrate in this talk how computational neuroscience may inspire and be inspired by mathematical image processing. Focusing on …
Sep 1, 2007
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Input-output transformation in the visuo-oculomotor loop: modeling the ocular following response to center-surround stimulation in a probabilistic framework
The quality of the representation of an object’s motion is limited by the noise in the sensory input as well as by an intrinsic …
Jan 1, 2006
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