Next-generation neural computations
Next-generation neural computations
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Guillaume S Masson
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An open-source vision-science tool for the auto-regressive generation of dynamic stochastic textures Motion Clouds
A Behavioral Receptive Field for Ocular Following in Monkeys: Spatial Summation and Its Spatial Frequency Tuning
Anticipatory Responses along Motion Trajectories in Awake Monkey Area V1
Speed uncertainty and motion perception with naturalistic random textures
The flash-lag effect as a motion-based predictive shift
How the dynamics of human smooth pursuit is influenced by speed uncertainty
Voluntary tracking the moving clouds : Effects of speed variability on human smooth pursuit
Effects of motion predictability on anticipatory and visually-guided eye movements: a common prior for sensory processing and motor control?
Push-Pull Receptive Field Organization and Synaptic Depression: Mechanisms for Reliably Encoding Naturalistic Stimuli in V1
Voluntary tracking the moving clouds : Effects of speed variability on human smooth pursuit
Voluntary tracking the moving clouds : Effects of speed variability on human smooth pursuit
Voluntary tracking the moving clouds : Effects of speed variability on human smooth pursuit
Visual motion processing and human tracking behavior
Beyond simply faster and slower: exploring paradoxes in speed perception
Motion-based prediction model for flash lag effect
The characteristics of microsaccadic eye movements varied with the change of strategy in a match-to-sample task
WP5 - Demo 1.3 : Spiking model of motion-based prediction
Motion-based prediction explains the role of tracking in motion extrapolation
Anisotropic connectivity implements motion-based prediction in a spiking neural network
How and why do image frequency properties influence perceived speed?
Measuring speed of moving textures: Different pooling of motion information for human ocular following and perception
Pattern discrimination for moving random textures: Richer stimuli are more difficult to recognize
The behavioral receptive field underlying motion integration for primate tracking eye movements
Motion Clouds: Model-based stimulus synthesis of natural-like random textures for the study of motion perception
Effect of image statistics on fixational eye movements
Measuring speed of moving textures: Different pooling of motion information for human ocular following and perception.
More is not always better: dissociation between perception and action explained by adaptive gain control
Motion-based prediction is sufficient to solve the aperture problem
Motion-based prediction is sufficient to solve the aperture problem
Role of motion-based prediction in motion extrapolation
Pattern discrimination for moving random textures: Richer stimuli are more difficult to recognize
Pursuing motion illusions: a realistic oculomotor framework for Bayesian inference
Role of motion inertia in dynamic motion integration for smooth pursuit
Functional consequences of correlated excitatory and inhibitory conductances in cortical networks
Models of low-level vision: linking probabilistic models and neural masses
A recurrent Bayesian model of dynamic motion integration for smooth pursuit
Different pooling of motion information for perceptual speed discrimination and behavioral speed estimation
Dynamical emergence of a neural solution for motion integration
Dynamical emergence of a neural solution for motion integration
Reading out the dynamics of lateral interactions in the primary visual cortex from VSD data
Control of the temporal interplay between excitation and inhibition by the statistics of visual input
Decoding low-level neural information to track visual motion
Decoding center-surround interactions in population of neurons for the ocular following response
Functional consequences of correlated excitation and inhibition on single neuron integration and signal propagation through synfire chains
Inferring monkey ocular following responses from V1 population dynamics using a probabilistic model of motion integration
Functional properties of feed-forward inhibition
Decoding the population dynamics underlying ocular following response using a probabilistic framework
Dynamics of distributed 1D and 2D motion representations for short-latency ocular following
Control of the temporal interplay between excitation and inhibition by the statistics of visual input: a V1 network modelling study
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
Synchrony in thalamic inputs enhances propagation of activity through cortical layers
Bayesian modeling of dynamic motion integration
Dynamic inference for motion tracking
Modeling spatial integration in the ocular following response using a probabilistic framework
Visual tracking of ambiguous moving objects: A recursive Bayesian model
Bayesian modeling of dynamic motion integration
Contrast sensitivity adaptation in a virtual spiking retina and its adequation with mammalians retinas
Input-output transformation in the visuo-oculomotor loop: modeling the ocular following response to center-surround stimulation in a probabilistic framework
Input-output transformation in the visuo-oculomotor loop: modeling the ocular following response to center-surround stimulation in a probabilistic framework
Input-output transformation in the visuo-oculomotor loop: modeling the ocular following response to center-surround stimulation in a probabilistic framework
Dynamics of motion representation in short-latency ocular following: A two-pathways Bayesian model
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