Neural processing of imminent collision in humans

Detecting a looming object and its imminent collision is imperative to survival. For most humans, it is a fundamental aspect of daily activities such as driving, road crossing and participating in sport, yet little is known about how the brain both detects and responds to such stimuli. Here we use functional magnetic resonance imaging to assess neural response to looming stimuli in comparison with receding stimuli and motion-controlled static stimuli. We demonstrate for the first time that, in the human, the superior colliculus and the pulvinar nucleus of the thalamus respond to looming in addition to cortical regions associated with motor preparation. We also implicate the anterior insula in making timing computations for collision events

Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 182, July 1978

This bibliography lists 165 reports, articles, and other documents introduced into the NASA scientific and technical information system in June 1978

A modified model for the Lobula Giant Movement Detector and its FPGA implementation

The Lobula Giant Movement Detector (LGMD) is a wide-field visual neuron located in the Lobula layer of the Locust nervous system. The LGMD increases its firing rate in response to both the velocity of an approaching object and the proximity of this object. It has been found that it can respond to looming stimuli very quickly and trigger avoidance reactions. It has been successfully applied in visual collision avoidance systems for vehicles and robots. This paper introduces a modified neural model for LGMD that provides additional depth direction information for the movement. The proposed model retains the simplicity of the previous model by adding only a few new cells. It has been simplified and implemented on a Field Programmable Gate Array (FPGA), taking advantage of the inherent parallelism exhibited by the LGMD, and tested on real-time video streams. Experimental results demonstrate the effectiveness as a fast motion detector

Cortical Dynamics of Navigation and Steering in Natural Scenes: Motion-Based Object Segmentation, Heading, and Obstacle Avoidance

Visually guided navigation through a cluttered natural scene is a challenging problem that animals and humans accomplish with ease. The ViSTARS neural model proposes how primates use motion information to segment objects and determine heading for purposes of goal approach and obstacle avoidance in response to video inputs from real and virtual environments. The model produces trajectories similar to those of human navigators. It does so by predicting how computationally complementary processes in cortical areas MT-/MSTv and MT+/MSTd compute object motion for tracking and self-motion for navigation, respectively. The model retina responds to transients in the input stream. Model V1 generates a local speed and direction estimate. This local motion estimate is ambiguous due to the neural aperture problem. Model MT+ interacts with MSTd via an attentive feedback loop to compute accurate heading estimates in MSTd that quantitatively simulate properties of human heading estimation data. Model MT interacts with MSTv via an attentive feedback loop to compute accurate estimates of speed, direction and position of moving objects. This object information is combined with heading information to produce steering decisions wherein goals behave like attractors and obstacles behave like repellers. These steering decisions lead to navigational trajectories that closely match human performance.National Science Foundation (SBE-0354378, BCS-0235398); Office of Naval Research (N00014-01-1-0624); National Geospatial Intelligence Agency (NMA201-01-1-2016

Perceiving Collision Impacts in Alzheimer’s Disease: The Effect of Retinal Eccentricity on Optic Flow Deficits

The present study explored whether the optic flow deficit in Alzheimer’s disease (AD) reported in the literature transfers to different types of optic flow, in particular, one that specifies collision impacts with upcoming surfaces, with a special focus on the effect of retinal eccentricity. Displays simulated observer movement over a ground plane toward obstacles lying in the observer’s path. Optical expansion was modulated by varying tau-dot. The visual field was masked either centrally (peripheral vision) or peripherally (central vision) using masks ranging from 10° to 30° in diameter in steps of 10°. Participants were asked to indicate whether their approach would result in collision or no collision with the obstacles. Results showed that AD patients’ sensitivity to tau-dot was severely compromised, not only for central vision but also for peripheral vision, compared to age- and education-matched elderly controls. The results demonstrated that AD patients’ optic flow deficit is not limited to radial optic flow but includes also the optical pattern engendered by tau-dot. Further deterioration in the capacity to extract tau-dot to determine potential collisions in conjunction with the inability to extract heading information from radial optic flow would exacerbate AD patients’ difficulties in navigation and visuospatial orientation

Neuronal processing of translational optic flow in the visual system of the shore crab Carcinus maenas

This paper describes a search for neurones sensitive to optic flow in the visual system of the shore crab Carcinus maenas using a procedure developed from that of Krapp and Hengstenberg. This involved determining local motion sensitivity and its directional selectivity at many points within the neurone's receptive field and plotting the results on a map. Our results showed that local preferred directions of motion are independent of velocity, stimulus shape and type of motion (circular or linear). Global response maps thus clearly represent real properties of the neurones' receptive fields. Using this method, we have discovered two families of interneurones sensitive to translational optic flow. The first family has its terminal arborisations in the lobula of the optic lobe, the second family in the medulla. The response maps of the lobula neurones (which appear to be monostratified lobular giant neurones) show a clear focus of expansion centred on or just above the horizon, but at significantly different azimuth angles. Response maps such as these, consisting of patterns of movement vectors radiating from a pole, would be expected of neurones responding to self-motion in a particular direction. They would be stimulated when the crab moves towards the pole of the neurone's receptive field. The response maps of the medulla neurones show a focus of contraction, approximately centred on the horizon, but at significantly different azimuth angles. Such neurones would be stimulated when the crab walked away from the pole of the neurone's receptive field. We hypothesise that both the lobula and the medulla interneurones are representatives of arrays of cells, each of which would be optimally activated by self-motion in a different direction. The lobula neurones would be stimulated by the approaching scene and the medulla neurones by the receding scene. Neurones tuned to translational optic flow provide information on the three-dimensional layout of the environment and are thought to play a role in the judgment of heading

08291 Abstracts Collection -- Statistical and Geometrical Approaches to Visual Motion Analysis

From 13.07.2008 to 18.07.2008, the Dagstuhl Seminar 08291 ``Statistical and Geometrical Approaches to Visual Motion Analysis\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general

Bio-inspired vision-based leader-follower formation flying in the presence of delays

Flocking starlings at dusk are known for the mesmerizing and intricate shapes they generate, as well as how fluid these shapes change. They seem to do this effortlessly. Real-life vision-based flocking has not been achieved in micro-UAVs (micro Unmanned Aerial Vehicles) to date. Towards this goal, we make three contributions in this paper: (i) we used a computational approach to develop a bio-inspired architecture for vision-based Leader-Follower formation flying on two micro-UAVs. We believe that the minimal computational cost of the resulting algorithm makes it suitable for object detection and tracking during high-speed flocking; (ii) we show that provided delays in the control loop of a micro-UAV are below a critical value, Kalman filter-based estimation algorithms are not required to achieve Leader-Follower formation flying; (iii) unlike previous approaches, we do not use external observers, such as GPS signals or synchronized communication with flock members. These three contributions could be useful in achieving vision-based flocking in GPS-denied environments on computationally-limited agents