Bayesian model

From the retina to action: Dynamics of predictive processing in the visual system
Within the central nervous system, visual areas are essential in transforming the raw luminous signal into a representation which …
Preprint PDF Cite Code DOI
From the retina to action: Dynamics of predictive processing in the visual system
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 …
Preprint PDF Cite DOI
Bayesian Modeling of Motion Perception using Dynamical Stochastic Textures
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Due to its inherent neural delays, the visual system has an outdated access to sensory information about the current position of moving …
Preprint PDF Cite Code DOI
The flash-lag effect as a motion-based predictive shift
Estimating and anticipating a dynamic probabilistic bias in visual motion direction
see a write-up in “Humans adapt their anticipatory eye movements to the volatility of visual motion properties”
PDF Cite
Anticipating a moving target: role of vision and reinforcement
PDF Cite
Eye tracking a self-moved target with complex hand-target dynamics
PDF Cite
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. …
Preprint PDF Cite DOI
Active inference, eye movements and oculomotor delays
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
PDF Cite DOI
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
PDF Cite
Signature of an anticipatory response in area V1 as modeled by a probabilistic model and a spiking neural network
As it is confronted to inherent neural delays, how does the visual system create a coherent representation of a rapidly changing …
PDF Cite DOI
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 …
PDF Cite DOI
Motion-based prediction and development of the response to an 'on the way' stimulus
Based on Laurent U Perrinet, Guillaume S Masson (2012). Motion-based prediction is sufficient to solve the aperture problem. Neural Computation. Preprint PDF Cite see follow-up on motion extrapolation: Mina A Khoei, Guillaume S Masson, Laurent U Perrinet (2013).
PDF Cite DOI
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 …
PDF Cite DOI
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
PDF Cite
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
PDF Cite
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 …
PDF Cite
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 …
Preprint PDF Cite
Motion-based prediction is sufficient to solve the aperture problem
Perceptions as Hypotheses: Saccades as Experiments
If perception corresponds to hypothesis testing (Gregory, 1980); then visual searches might be construed as experiments that generate …
PDF Cite DOI
Perceptions as Hypotheses: Saccades as Experiments
Role of motion-based prediction in motion extrapolation
Based on Laurent U Perrinet, Guillaume S Masson (2012). Motion-based prediction is sufficient to solve the aperture problem. Neural Computation. Preprint PDF Cite see follow-up on motion extrapolation: Mina A Khoei, Guillaume S Masson, Laurent U Perrinet (2013).
PDF Cite
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
PDF Cite
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 …
PDF Cite DOI
Role of motion inertia in dynamic motion integration for smooth pursuit
Based on Laurent U Perrinet, Guillaume S Masson (2012). Motion-based prediction is sufficient to solve the aperture problem. Neural Computation. Preprint PDF Cite see follow-up on motion extrapolation: Mina A Khoei, Guillaume S Masson, Laurent U Perrinet (2013).
PDF 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 …
Dec 17, 2010
PDF Cite
Models of low-level vision: linking probabilistic models and neural masses
see this more recent talk @ UCL, London
Jan 8, 2010
PDF Cite
A recurrent Bayesian model of dynamic motion integration for smooth pursuit
PDF Cite DOI
Dynamical emergence of a neural solution for motion integration
Based on Laurent U Perrinet, Guillaume S Masson (2012). Motion-based prediction is sufficient to solve the aperture problem. Neural Computation. Preprint PDF Cite see follow-up on motion extrapolation: Mina A Khoei, Guillaume S Masson, Laurent U Perrinet (2013).
PDF Cite
Dynamical emergence of a neural solution for motion integration
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 …
PDF Cite
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 …
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 …
PDF Cite DOI
Dynamics of distributed 1D and 2D motion representations for short-latency ocular following
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 …
Cite
Decoding the population dynamics underlying ocular following response using a probabilistic framework
Modeling spatial integration in the ocular following response to center-surround stimulation using a probabilistic framework
Cite
What adaptive code for efficient spiking representations? A model for the formation of receptive fields of simple cells
PDF Cite
What adaptive code for efficient spiking representations? A model for the formation of receptive fields of simple cells
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 …
PDF Cite DOI
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 …
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 …
PDF Cite DOI
Modeling spatial integration in the ocular following response using a probabilistic framework
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 …
Cite
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 …
PDF Cite DOI
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 …
Cite
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
PDF Cite
Dynamics of motion representation in short-latency ocular following: A two-pathways Bayesian model
The integration of information is essential to measure the exact 2D motion of a surface from both local ambiguous 1D motion produced by …
Cite
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 …
Preprint PDF Cite DOI
Feature detection using spikes : the greedy approach