Within the central nervous system, visual areas are essential in transforming the raw luminous signal into a representation which efficiently conveys information about the environment. This process is constrained by the necessity of being robust and …
A common practice to account for psychophysical biases in vision is to frame them as consequences of a dynamic process relying on optimal inference with respect to a generative model. The present study details the complete formulation of such a …
Due to its inherent neural delays, the visual system has an outdated access to sensory information about the current position of moving objects.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 …
see a write-up in “ Humans adapt their anticipatory eye movements to the volatility of visual motion properties”
This paper considers the problem of sensorimotor delays in the optimal control of (smooth) eye movements under uncertainty. Specifically, we consider delays in the visuo-oculomotor loop and their implications for active inference. Active inference …
Moving objects generate sensory information that may be noisy and ambiguous, yet it is important to be able to reconstruct object speed as fast as possible. One unsolved question is to understand how the brain pools motion information to give an …
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 …
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 …
Based on Perrinet et al, 2012 See a followup in Khoei et al, 2013
This paper introduces a model of oculomotor control during the smooth pursuit of occluded visual targets. This model is based upon active inference, in which subjects try to minimise their (proprioceptive) prediction error based upon posterior …
Moving objects generate sensory information that may be noisy and ambiguous, yet it is important to be able to reconstruct object speed as fast as possible. One unsolved question is to understand how the brain pools motion information to give an …
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 …
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 …
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 …
If perception corresponds to hypothesis testing (Gregory, 1980); then visual searches might be construed as experiments that generate sensory data. In this work, we explore the idea that saccadic eye movements are optimal experiments, in which data …
Based on Perrinet et al, 2012 See a followup in Khoei et al, 2013
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 …
Accuracy in estimating an object's global motion over time is not only affected by the noise in visual motion information but also by the spatial limitation of the local motion analyzers (aperture problem). Perceptual and oculomotor data demonstrate …
Based on Perrinet et al, 2012 See a followup in Khoei et al, 2013
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 …
see this more recent talk @ UCL, London
Based on Perrinet et al, 2012 See a followup in Khoei et al, 2013
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 …
Short presentation of a large moving pattern elicits an Ocular Following Response (OFR) that exhibits many of the properties attributed to low-level motion processing such as spatial and temporal integration, contrast gain control and divisive …
Integrating information is essential to measure the physical 2D motion of a surface from both ambiguous local 1D motion of its elongated edges and non-ambiguous 2D motion of its features such as corners or texture elements. The dynamics of this …
The machinery behind the visual perception of motion and the subsequent sensorimotor transformation, such as in Ocular Following Response (OFR), is confronted to uncertainties which are efficiently resolved in the primate's visual system. We may …
The machinery behind the visual perception of motion and the subsequent sensori-motor transformation, such as in ocular following response (OFR), is confronted to uncertainties which are efficiently resolved in the primate's visual system. We may …
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 ambiguity due to the spatial limitation of the visual motion analyzers (aperture problem). Perceptual and oculomotor data …
The machinery behind the visual perception of motion and the subsequent sensori-motor transformation, such as in Ocular Following Response (OFR), is confronted to uncertainties which are efficiently resolved in the primate's visual system. We may …
Perceptual and oculomotor data demonstrate that, when the visual information about an object's motion differs on the local (edge-related) and global levels, the local 1D motion cues dominate initially, whereas 2D information takes progressively over …
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 ambiguity due to the spatial limitation of the visual motion analyzers (aperture problem). Perceptual and oculomotor data …
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 ambiguity due to the spatial limitation of the visual motion analyzers (aperture problem). Perceptual and oculomotor data …
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 ambiguity due to the spatial limitation of the visual motion analyzers (aperture problem). Perceptual and oculomotor data …
The integration of information is essential to measure the exact 2D motion of a surface from both local ambiguous 1D motion produced by elongated edges and local non-ambiguous 2D motion from features such as corners, end-points or texture elements. …
A goal of low-level neural processes is to build an efficient code extracting the relevant information from the sensory input. It is believed that this is implemented in cortical areas by elementary inferential computations dynamically extracting the …