Next-generation neural computations
Next-generation neural computations
Home
Latest
Events
Projects
People
Publications
Talks
Grants
BlogBook
Contact
Eye Movements
An open-source vision-science tool for the auto-regressive generation of dynamic stochastic textures Motion Clouds
Motion Clouds are a generative model for naturalistic visual stimulation that offer full parametric control and more naturalism than …
Nikos Gekas
,
Andrew Isaac Meso
,
Jonathan Vacher
,
Laurent Uand Mamassian, Pascal Perrinet
,
Guillaume S Masson
Cite
Pdf
URL
Reinforcement effects in anticipatory smooth eye movements
Jean-Bernard Damasse
,
Laurent U Perrinet
,
Laurent Madelain
,
Anna Montagnini
Cite
DOI
URL
HAL
Dynamic modulation of volatility by reward contingencies: effects on anticipatory smooth eye movement
Jean-Bernard Damasse
,
Anna Montagnini
,
Laurent U Perrinet
Cite
DOI
URL
How the dynamics of human smooth pursuit is influenced by speed uncertainty
Kiana Mansour-Pour
,
Laurent U Perrinet
,
Guillaume S Masson
,
Anna Montagnini
Cite
Pdf
URL
Voluntary tracking the moving clouds : Effects of speed variability on human smooth pursuit
The properties of motion processing for driving smooth eye movements have bee investigated using simple, artificial stimuli such as …
Kiana Mansour-Pour
,
Laurent U Perrinet
,
Guillaume S Masson
,
Anna Montagnini
Cite
URL
Operant reinforcement versus reward expectancy: effects on anticipatory eye movements
Jean-Bernard Damasse
,
Laurent U Perrinet
,
Jérémie Jozefowiez
,
Laurent Madelain
,
Anna Montagnini
Cite
DOI
URL
Effects of motion predictability on anticipatory and visually-guided eye movements: a common prior for sensory processing and motor control?
Anna Montagnini
,
Jean-Bernard Damasse
,
Laurent U Perrinet
,
Guillaume S Masson
Cite
URL
Modeling the effect of dynamic contingencies on anticipatory eye movements
Jean-Bernard Damasse
,
Anna Montagnini
,
Laurent U Perrinet
Cite
URL
Voluntary tracking the moving clouds : Effects of speed variability on human smooth pursuit
Kiana Mansour-Pour
,
Laurent U Perrinet
,
Guillaume S Masson
,
Anna Montagnini
Cite
URL
Voluntary tracking the moving clouds : Effects of speed variability on human smooth pursuit
Kiana Mansour-Pour
,
Laurent U Perrinet
,
Guillaume S Masson
,
Anna Montagnini
Cite
URL
Voluntary tracking the moving clouds : Effects of speed variability on human smooth pursuit
Kiana Mansour-Pour
,
Laurent U Perrinet
,
Guillaume S Masson
,
Anna Montagnini
Cite
URL
Anticipatory smooth eye movements and reinforcement
When an object is moving in the visual field, we are able to accurately track it with a combination of saccades and smooth eye …
Jean-Bernard Damasse
,
Laurent Madelain
,
Laurent U Perrinet
,
Anna Montagnini
Cite
DOI
URL
Anticipatory smooth eye movements as operant behavior
Jean-Bernard Damasse
,
Laurent Madelain
,
Laurent U Perrinet
,
Anna Montagnini
Cite
URL
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. …
Laurent U Perrinet
,
Rick A Adams
,
Karl Friston
Cite
DOI
URL
arXiv
The characteristics of microsaccadic eye movements varied with the change of strategy in a match-to-sample task
Under natural viewing conditions, large eye movements are interspace by small eye movements (microsaccade). Recent works have shown …
Claudio Simoncini
,
Anna Montagnini
,
Laurent U Perrinet
,
Guillaume S Masson
Cite
DOI
URL
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 …
Laurent U Perrinet
2014-01-10
Cite
URL
On the nature of anticipatory eye movements and the factors affecting them
Jean-Bernard Damasse
,
Laurent Madelain
,
Laurent U Perrinet
,
Anna Montagnini
Cite
URL
Measuring speed of moving textures: Different pooling of motion information for human ocular following and perception
The visual system does not process information instantaneously, but rather integrates over time. Integration occurs both for stationary …
Claudio Simoncini
,
Laurent U Perrinet
,
Anna Montagnini
,
Guillaume S Masson
Cite
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 …
Rick A Adams
,
Laurent U Perrinet
,
Karl Friston
PDF
Cite
DOI
URL
Pattern discrimination for moving random textures: Richer stimuli are more difficult to recognize
In order to analyze the characteristics of a rich dynamic visual environment, the visual system must integrate information collected at …
Claudio Simoncini
,
Anna Montagnini
,
Laurent U Perrinet
,
Pascal Mamassian
,
Guillaume S Masson
Cite
DOI
URL
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 …
Guillaume S Masson
,
Laurent U Perrinet
PDF
Cite
DOI
URL
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 …
Laurent U Perrinet
2012-01-27
Cite
URL
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 …
Laurent U Perrinet
2012-01-12
Cite
URL
Effect of image statistics on fixational eye movements
Under natural viewing conditions, small movements of the eyes prevent the maintenance of a steady direction of gaze. It is unclear how …
Claudio Simoncini
,
Anna Montagnini
,
Laurent U Perrinet
,
Guillaume S Masson
Cite
DOI
URL
Measuring speed of moving textures: Different pooling of motion information for human ocular following and perception.
To measure speed and direction of moving objects, the cortical motion system pools information across different spatiotemporal …
Claudio Simoncini
,
Laurent U Perrinet
,
Anna Montagnini
,
Pascal Mamassian
,
Guillaume S Masson
Cite
DOI
URL
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 …
Claudio Simoncini
,
Laurent U Perrinet
,
Anna Montagnini
,
Pascal Mamassian
,
Guillaume S Masson
PDF
Cite
DOI
URL
Perceptions as Hypotheses: Saccades as Experiments
If perception corresponds to hypothesis testing (Gregory, 1980); then visual searches might be construed as experiments that generate …
Karl Friston
,
Rick A Adams
,
Laurent U Perrinet
,
Michael Breakspear
PDF
Cite
DOI
URL
Pattern discrimination for moving random textures: Richer stimuli are more difficult to recognize
In order to analyze the characteristics of a rich dynamic visual environment, the visual system must integrate information collected at …
Claudio Simoncini
,
Anna Montagnini
,
Laurent U Perrinet
,
Pascal Mamassian
,
Guillaume S Masson
Cite
DOI
URL
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 …
Laurent U Perrinet
2011-07-02
Cite
URL
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 …
Jérôme Fleuriet
,
Sandrine Hugues
,
Laurent U Perrinet
,
Laurent Goffart
Cite
DOI
URL
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 …
Laurent U Perrinet
2010-12-17
Cite
URL
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 …
Laurent U Perrinet
PDF
Cite
DOI
Hal
Code
URL
arXiv
Models of low-level vision: linking probabilistic models and neural masses
see this more recent talk @
UCL, London
Laurent U Perrinet
,
Guillaume S Masson
2010-01-08
Cite
URL
Different pooling of motion information for perceptual speed discrimination and behavioral speed estimation
Claudio Simoncini
,
Laurent U Perrinet
,
Anna Montagnini
,
Pascal Mamassian
,
Guillaume S Masson
Cite
Dynamical emergence of a neural solution for motion integration
Laurent U Perrinet
,
Guillaume S Masson
Cite
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 …
Laurent U Perrinet
Cite
URL
Decoding center-surround interactions in population of neurons for the ocular following response
Short presentation of a large moving pattern elicits an Ocular Following Response (OFR) that exhibits many of the properties attributed …
Laurent U Perrinet
,
Nicole Voges
,
Jens Kremkow
,
Guillaume S Masson
Cite
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 …
Frédéric v Barthélemy
,
Laurent U Perrinet
,
Eric Castet
,
Guillaume S Masson
PDF
Cite
DOI
URL
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 …
Laurent U Perrinet
,
Guillaume S Masson
Cite
Modeling spatial integration in the ocular following response to center-surround stimulation using a probabilistic framework
Laurent U Perrinet
,
Guillaume S Masson
Cite
Dynamical Neural Networks: modeling low-level vision at short latencies
The machinery behind the visual perception of motion and the subsequent sensori-motor transformation, such as in ocular following …
Laurent U Perrinet
PDF
Cite
DOI
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 …
Laurent U Perrinet
,
Guillaume S Masson
PDF
Cite
DOI
URL
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 …
Laurent U Perrinet
,
Frédéric v Barthélemy
,
Guillaume S Masson
Cite
Cite
×