Biomedical subjects

Alireza S Mahani

Publications and source records attributed to Alireza S Mahani.

4 recordsLinked to original sources

PubMed2006

Iterative cooperation between parallel pathways for object and background motion.

In a typical visual scene, one or more objects move relative to a larger background, which can itself be in motion as a result of the observer's eyes moving with respect to the outside world. Here we show that accurate estimation of the background motion from an image velocity field can be accomplished through an iterative cooperation between two modules: one that specializes in calculating a weighted average velocity and another one calculating a velocity contrast map. We build on our analysis to provide a model for the tectum-pretectum loop in the nonmammalian midbrain. Our model accounts for some of the known properties of the tectal neurons (sensitivity to relative motion) and pretectal neurons (sensitivity to whole-field motion). It also agrees with our knowledge of the pretectotectal projection (divergent and inhibitory), and with the results of lesion studies in which the pretectal input to the tectum was removed, leading to hyperactivity of the tectal neurons and the animal. Our model also makes a testable prediction regarding the tectopretectal projection, i.e., that the presence of a larger object and a bigger discrepancy between the directions of motion for the object and the background lead to a larger error by the pretectum in estimating the background motion when the tectal input is abolished.

Animals↗

PubMed2006

Sparse spatial sampling for the computation of motion in multiple stages.

The avian retino-tecto-rotundal pathway plays a central role in motion analysis and features complex connectivity. Yet, the relation between the pathway's structural arrangement and motion computation has remained elusive. For an important type of tectal wide-field neuron, the stratum griseum centrale type I (SGC-I) neuron, we quantified its structure and found a spatially sparse but extensive sampling of the retinal projection. A computational investigation revealed that these structural properties enhance the neuron's sensitivity to change, a behaviorally important stimulus attribute, while preserving information about the stimulus location in the SGC-I population activity. Furthermore, the SGC-I neurons project with an interdigitating topography to the nucleus rotundus, where the direction of motion is computed. We showed that, for accurate direction-of-motion estimation, the interdigitating projection of tectal wide-field neurons requires a two-stage rotundal algorithm, where the second rotundal stage estimates the direction of motion from the change in the relative stimulus position represented in the first stage.

Action Potentials↗

PubMed2005

Motion repulsion arises from stimulus statistics when analyzed with a clustering algorithm.

Motion repulsion is the perceived enlargement of the angle between the directions of motion of two transparently moving patterns. An explanation of this illusion has long been sought for in the neural circuitry of the brain. We show that motion repulsion already arises from the statistical properties of the motion transparency problem when analyzed with a clustering algorithm.

Adaptation, Ocular↗

PubMed2005

Motion contrast classification is a linearly nonseparable problem.

Sensitivity to image motion contrast, that is, the relative motion between different parts of the visual field, is a common and computationally important property of many neurons in the visual pathways of vertebrates. Here we illustrate that, as a classification problem, motion contrast detection is linearly nonseparable. In order to do so, we prove a theorem stating a sufficient condition for linear nonseparability. We argue that nonlinear combinations of local measurements of velocity at different locations and times are needed in order to solve the motion contrast problem.

Animals↗