motion prediction

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Due to its inherent neural delays, the visual system has an outdated access to sensory information about the current position of moving objects.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 …

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 stationary flashed objects. It has been reproduced experimentally in retina and V1 along with some relevant evidences …

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 environment? In this paper, we investigate the role of motion-based prediction in estimating motion trajectories …

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 …

Motion-based prediction and development of the response to an 'on the way' stimulus

Based on Perrinet et al, 2012 See a followup in Khoei et al, 2013

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 …

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 …

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 …

Role of motion-based prediction in motion extrapolation

Based on Perrinet et al, 2012 See a followup in Khoei et al, 2013

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 system could describe superposed and ambiguous information. This allows to describe the interactions of neighboring …

Role of motion inertia in dynamic motion integration for smooth pursuit

Based on Perrinet et al, 2012 See a followup in Khoei et al, 2013

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 system could describe superposed and ambiguous information. This allows to describe the interactions of neighboring …

Models of low-level vision: linking probabilistic models and neural masses

see this more recent talk @ UCL, London

Dynamical emergence of a neural solution for motion integration

Based on Perrinet et al, 2012 See a followup in Khoei et al, 2013

Dynamical emergence of a neural solution for motion integration