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Humans adapt their anticipatory eye movements to the volatility of visual motion properties

Humans are able to accurately track a moving object with a combination of saccades and smooth eye movements. These movements allow us to align and stabilize the object on the fovea, thus enabling high*resolution visual analysis. …

An adaptive homeostatic algorithm for the unsupervised learning of visual features

The formation of structure in the visual system, that is, of the connections between cells within neural populations, is by large an unsupervised learning process: the emergence of this architecture is mostly self-organized. In the primary visual …

A dual foveal-peripheral visual processing model implements efficient saccade selection

In computer vision, the visual search task consists in extracting a scarce and specific visual information (the target) from a large and crowded visual display. This task is usually implemented by scanning the different possible target identities at …

Suppressive waves disambiguate the representation of long-range apparent motion in awake monkey V1

Traveling waves have recently been observed in different animal species, brain areas and behavioral states. However, it is still unclear what are their functional roles. In the case of cortical visual processing, waves propagate across retinotopic maps and can hereby generate interactions between spatially and temporally separated instances of feedforward driven activity. Such interactions could participate in processing long-range apparent motion stimuli, an illusion for which no clear neuronal mechanisms have yet been proposed. Using this paradigm in awake monkeys, we show that suppressive traveling waves produce to a spatio-temporal normalization of apparent motion stimuli. Our study suggests that cortical waves shape the representation of illusory moving stimulus within retinotopic maps for an straightforward read-out by downstream areas.

Sparse Deep Predictive Coding captures contour integration capabilities of the early visual system

Both neurophysiological and psychophysical experiments have pointed out the crucial role of recurrent and feedback connections to process context-dependent information in the early visual cortex. While numerous models have accounted for feedback …

Top-down feedback in Hierarchical Sparse Coding

From a computer science perspective, the problem of optimal representation using Hierarchical Sparse Coding (HSC) is often solved using a stack of independent subproblems with for instance the Lasso formulation at each layer. However, recent …

Speed-Selectivity in Retinal Ganglion Cells is Sharpened by Broad Spatial Frequency, Naturalistic Stimuli

Motion detection represents one of the critical tasks of the visual system and has motivated a large body of research. However, it remains unclear precisely why the response of retinal ganglion cells (RGCs) to simple artificial stimuli does not …

Illusions et 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 public qui proposent des situations souvent incongrues, dans lesquelles l'eau remonte une cascade, les personnes volent …

Bayesian Modeling of Motion Perception using Dynamical Stochastic Textures

A common practice to account for psychophysical biases in vision is to frame them as consequences of a dynamic process relying on optimal inference with respect to a generative model. The present study details the complete formulation of such a …

Reinforcement effects in anticipatory smooth eye movements

The flash-lag effect as a motion-based predictive shift

Due to its inherent neural delays, the visual system has an outdated access to sensory information about the current position of moving objects. In contrast, living organisms are remarkably able to track and intercept moving objects under a large …

Testing the odds of inherent vs. observed overdispersion in neural spike counts

The repeated presentation of an identical visual stimulus in the receptive field of a neuron may evoke different spiking patterns at each trial. Probabilistic methods are essential to understand the functional role of this variance within the neural …

Push-Pull Receptive Field Organization and Synaptic Depression: Mechanisms for Reliably Encoding Naturalistic Stimuli in V1

Neurons in the primary visual cortex are known for responding vigorously but with high variability to classical stimuli such as drifting bars or gratings. By contrast, natural scenes are encoded more efficiently by sparse and temporal precise spiking …

Edge co-occurrences can account for rapid categorization of natural versus animal images

Making a judgment about the semantic category of a visual scene, such as whether it contains an animal, is typically assumed to involve high-level associative brain areas. Previous explanations require progressively analyzing the scene hierarchically …

Active inference, eye movements and oculomotor delays

This paper considers the problem of sensorimotor delays in the optimal control of (smooth) eye movements under uncertainty. Specifically, we consider delays in the visuo-oculomotor loop and their implications for active inference. Active inference …

Motion-based prediction explains the role of tracking in motion extrapolation

During normal viewing, the continuous stream of visual input is regularly interrupted, for instance by blinks of the eye. Despite these frequents blanks (that is the transient absence of a raw sensory source), the visual system is most often able to …

Anisotropic connectivity implements motion-based prediction in a spiking neural network

Predictive coding hypothesizes that the brain explicitly infers upcoming sensory input to establish a coherent representation of the world. Although it is becoming generally accepted, it is not clear on which level spiking neural networks may …

Smooth Pursuit and Visual Occlusion: Active Inference and Oculomotor Control in Schizophrenia

This paper introduces a model of oculomotor control during the smooth pursuit of occluded visual targets. This model is based upon active inference, in which subjects try to minimise their (proprioceptive) prediction error based upon posterior …

The behavioral receptive field underlying motion integration for primate tracking eye movements

Short-latency ocular following are reflexive, tracking eye movements that are observed in human and non-human primates in response to a sudden and brief translation of the image. Initial, open-loop part of the eye acceleration reflects many of the …

Motion Clouds: Model-based stimulus synthesis of natural-like random textures for the study of motion perception

Choosing an appropriate set of stimuli is essential to characterize the response of a sensory system to a particular functional dimension, such as the eye movement following the motion of a visual scene. Here, we describe a framework to generate …

Complex dynamics in recurrent cortical networks based on spatially realistic connectivities

Most studies on the dynamics of recurrent cortical networks are either based on purely random wiring or neighborhood couplings. Neuronal cortical connectivity, however, shows a complex spatial pattern composed of local and remote patchy connections. …

More is not always better: dissociation between perception and action explained by adaptive gain control

Moving objects generate motion information at different scales, which are processed in the visual system with a bank of spatiotemporal frequency channels. It is not known how the brain pools this information to reconstruct object speed and whether …

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 global percept. This is well demonstrated for the detection of motion in the aperture problem: as luminance of an …

Perceptions as Hypotheses: Saccades as Experiments

If perception corresponds to hypothesis testing (Gregory, 1980); then visual searches might be construed as experiments that generate sensory data. In this work, we explore the idea that saccadic eye movements are optimal experiments, in which data …

Qui créera le premier ordinateur intelligent?

Qui créera le premier ordinateur intelligent? Les ordinateurs classiques sont de plus en plus puissants, mais restent toujours aussi « stupides ». Impossible d’en trouver un avec lequel on puisse dialoguer de façon naturelle. Aucun système visuel artificiel ne voit aussi bien que nous, ou qu’une mouche ! Alors qui inventera le premier calculateur intelligent ? Le code neural (En haut : © F. Chavane, en bas : © T.

Pursuing motion illusions: a realistic oculomotor framework for Bayesian inference

Accuracy in estimating an object's global motion over time is not only affected by the noise in visual motion information but also by the spatial limitation of the local motion analyzers (aperture problem). Perceptual and oculomotor data demonstrate …

Saccadic foveation of a moving visual target in the rhesus monkey

When generating a saccade toward a moving target, the target displacement that occurs during the period spanning from its detection to the saccade end must be taken into account to accurately foveate the target and to initiate its pursuit. Previous …

Phase space analysis of networks based on biologically realistic parameters

We study cortical network dynamics for a spatially embedded network model. It represents, in terms of spatial scale, a large piece of cortex allowing for long-range connections, resulting in a rather sparse connectivity. The spatial embedding also …

Role of homeostasis in learning sparse representations

Neurons in the input layer of primary visual cortex in primates develop edge-like receptive fields. One approach to understanding the emergence of this response is to state that neural activity has to efficiently represent sensory data with respect …

Functional consequences of correlated excitatory and inhibitory conductances in cortical networks

Neurons in the neocortex receive a large number of excitatory and inhibitory synaptic inputs. Excitation and inhibition dynamically balance each other, with inhibition lagging excitation by only few milliseconds. To characterize the functional …

Computational Neuroscience, from Multiple Levels to Multi-level

Despite the long and fruitful history of neuroscience, a global, multi-level description of cardinal brain functions is still far from reach. Using analytical or numerical approaches, emphComputational Neuroscience aims at the emergence of such …

Phase space analysis of networks based on biologically realistic parameters

We study cortical network dynamics for a more realistic network model. It represents, in terms of spatial scale, a large piece of cortex allowing for long-range connections, resulting in a rather sparse connectivity. We use two different types of …

Dynamics of distributed 1D and 2D motion representations for short-latency ocular following

Integrating information is essential to measure the physical 2D motion of a surface from both ambiguous local 1D motion of its elongated edges and non-ambiguous 2D motion of its features such as corners or texture elements. The dynamics of this …

PyNN: A Common Interface for Neuronal Network Simulators

Computational neuroscience has produced a diversity of software for simulations of networks of spiking neurons, with both negative and positive consequences. On the one hand, each simulator uses its own programming or configuration language, leading …

Introduction to Topics in Dynamical Neural Networks: From Large Scale Neural Networks to Motor Control and Vision

Bayesian modeling of dynamic motion integration

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 ambiguity due to the spatial limi- tation of the visual motion analyzers (aperture prob- lem). Perceptual and oculomotor …

Self-Invertible 2D Log-Gabor Wavelets

Meanwhile biorthogonal wavelets got a very popular image processing tool, alternative multiresolution transforms have been proposed for solving some of their drawbacks, namely the poor selectivity in orientation and the lack of translation in- …

Modeling spatial integration in the ocular following response using a probabilistic framework

The machinery behind the visual perception of motion and the subsequent sensori-motor transformation, such as in Ocular Following Response (OFR), is confronted to uncertainties which are efficiently resolved in the primate's visual system. We may …

Sparse Approximation of Images Inspired from the Functional Architecture of the Primary Visual Areas

Visual tracking of ambiguous moving objects: A recursive Bayesian model

Perceptual and oculomotor data demonstrate that, when the visual information about an object's motion differs on the local (edge-related) and global levels, the local 1D motion cues dominate initially, whereas 2D information takes progressively over …

Coding static natural images using spiking event times: do neurons cooperate?

To understand possible strategies of temporal spike coding in the central nervous system, we study functional neuromimetic models of visual processing for static images. We will first present the retinal model which was introduced by Van Rullen and …

Feature detection using spikes : the greedy approach

A goal of low-level neural processes is to build an efficient code extracting the relevant information from the sensory input. It is believed that this is implemented in cortical areas by elementary inferential computations dynamically extracting the …

Sparse spike coding in an asynchronous feed-forward multi-layer neural network using matching pursuit

Finding Independent Components using spikes : a natural result of hebbian learning in a sparse spike coding scheme

To understand possible strategies of temporal spike coding in the central nervous system, we study functional neuromimetic models of visual processing for static images. We will first present the retinal model which was introduced by Van Rullen and …

Emergence of filters from natural scenes in a sparse spike coding scheme

Coherence detection in a spiking neuron via Hebbian learning

Coherence detection in a spiking neuron via hebbian learning

It is generally assumed that neurons in the central nervous system communicate through temporal firing patterns. As a first step, we will study the learning of a layer of realistic neurons in the particular case where the relevant messages are formed …

Network of integrate-and-fire neurons using Rank Order Coding A: how to implement spike timing dependant plasticity

Network of integrate-and-fire neurons using Rank Order Coding B: spike timing dependant plasticity and emergence of orientation selectivity

Rank Order Coding is an alternative to conventional rate coding schemes that uses the order in which a neuron's inputs fire to encode information. In a visual system framework, we simulated the asynchronous waves of retinal spikes produced in …