Neural Mechanisms of Cortical Motion Computation Based on a Neuromorphic Sensory System

Abstract

The visual cortex analyzes motion information along hierarchically arranged visual areas that interact through bidirectional interconnections. This work suggests a bio-inspired visual model focusing on the interactions of the cortical areas in which a new mechanism of feedforward and feedback processing are introduced. The model uses a neuromorphic vision sensor (silicon retina) that simulates the spike-generation functionality of the biological retina. Our model takes into account two main model visual areas, namely V1 and MT, with different feature selectivities. The initial motion is estimated in model area V1 using spatiotemporal filters to locally detect the direction of motion. Here, we adapt the filtering scheme originally suggested by Adelson and Bergen to make it consistent with the spike representation of the DVS. The responses of area V1 are weighted and pooled by area MT cells which are selective to different velocities, i.e. direction and speed. Such feature selectivity is here derived from compositions of activities in the spatio-temporal domain and integrating over larger space-time regions (receptive fields). In order to account for the bidirectional coupling of cortical areas we match properties of the feature selectivity in both areas for feedback processing. For such linkage we integrate the responses over different speeds along a particular preferred direction. Normalization of activities is carried out over the spatial as well as the feature domains to balance the activities of individual neurons in model areas V1 and MT. Our model was tested using different stimuli that moved in different directions. The results reveal that the error margin between the estimated motion and synthetic ground truth is decreased in area MT comparing with the initial estimation of area V1. In addition, the modulated V1 cell activations shows an enhancement of the initial motion estimation that is steered by feedback signals from MT cells.

Probing Early Motion Processing With Eye Movements: Differences of Vestibular Migraine, Migraine With and Without Aura in the Attack Free Interval

“…Such a hypothesis predicts that the scaling is applied differently for OFR, PS, and the migraine subtypes: a scaling with a factor of one is applied to PS in all subgroups and OFR in control and MwoA, a scaling of 1.58 in OFR for MwA, and 1.44 in VM. Nevertheless, there still might be a hyperexcitability, an extended suppression of cortical excitability or a general lack of inhibition in the cortex in the motion sensitive area, which is ineffective in our case, as there might be a step of normalization during or after the averaging process as suggested in theoretical models for motion or processing or other ultrashort latency eye movements . Further experiments have to test this hypothesis in detail.…”

“…Nevertheless, there still might be a hyperexcitability, an extended suppression of cortical excitability or a general lack of inhibition in the cortex in the motion sensitive area, which is ineffective in our case, as there might be a step of normalization during or after the averaging process as suggested in theoretical models for motion or processing or other ultrashort latency eye movements. 28,29 Further experiments have to test this hypothesis in detail. Our data could therefore not differentiate if the pathology in cortex is a hyperexcitability, an extended suppression of cortical excitability, or a general lack of inhibition in the cortex in the motion sensitive area.…”

Shadow Detection and Elimination for Robot and Machine Vision Applications

“…This algorithm can be used in different applications, such as robot and machine vision. Unlike the state-of-art approaches ( [13] and [24], [25]) for shadow detection and removal, our algorithm does not require a training process on different shadows and shadowless images. Our mechanism reconstructs a target object in a shadowless image through five stages using Gaussian equations with different shapes and orientations.…”