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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Due to its inherent neural delays, the visual system has an outdated access to sensory information about the current position of moving …
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The flash-lag effect as a motion-based predictive shift
Motion-based prediction model for flash lag effect
The flash lag effect (FLE) is a well known visual illusion that reveals the perceptual difference in position coding of moving and …
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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 …
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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 …
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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 …
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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. PDF Cite Pdf arXiv see follow-up on motion extrapolation: Mina A Khoei, Guillaume S Masson, Laurent U Perrinet (2013).
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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. PDF Cite Pdf arXiv see follow-up on motion extrapolation: Mina A Khoei, Guillaume S Masson, Laurent U Perrinet (2013).
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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. PDF Cite Pdf arXiv see follow-up on motion extrapolation: Mina A Khoei, Guillaume S Masson, Laurent U Perrinet (2013).
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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. PDF Cite Pdf arXiv see follow-up on motion extrapolation: Mina A Khoei, Guillaume S Masson, Laurent U Perrinet (2013).
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NeuralEnsemble: Towards a meta-environment for network modeling and data analysis
NeuralEnsemble (http://neuralensemble.org) is a multilateral effort to coordinate and organise neuroscience software development …
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Proceedings of the second french conference on Computational Neuroscience, Marseille
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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 …
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Decoding the population dynamics underlying ocular following response using a probabilistic framework
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 …
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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 …
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Dynamic inference for motion tracking
When the visual information about an object’s motion differs at the local level, the visuomotor system needs to integrate …
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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 …
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Modeling spatial integration in the ocular following response using a probabilistic framework
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 …
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Neural Codes for Adaptive Sparse Representations of Natural Images
On efficient sparse spike coding schemes for learning natural scenes in the primary visual cortex
We describe the theoretical formulation of a learning algorithm in a model of the primary visual cortex (V1) and present results of the …
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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 …
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