Motion anticipation allows the visual system to compensate for the slow speed of phototransduction so that a moving object can be accurately located. This correction is already present in the signal that ganglion cells send from the retina but the biophysical mechanisms underlying this computation are not known. Here we demonstrate that motion anticipation is computed autonomously within the dendritic tree of each ganglion cell and relies on feedforward inhibition. The passive and non-linear interaction of excitatory and inhibitory synapses enables the somatic voltage to encode the actual position of a moving object instead of its delayed representation. General rather than specific features of the retinal connectome govern this computation: an excess of inhibitory inputs over excitatory, with both being randomly distributed, allows tracking of all directions of motion, while the average distance between inputs determines the object velocities that can be compensated for.
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http://dx.doi.org/10.7554/eLife.06250 | DOI Listing |
Neuroscience
January 2025
Departamento de Ciencias Médicas y de la Vida, Centro Universitario de la Ciénega, Universidad de Guadalajara, Ocotlán, Mexico; Laboratorio de Conducta Animal, Departamento de Psicología, Centro Universitario de la Ciénega, Universidad de Guadalajara, Ocotlán, Mexico.
Motor actions adapt dynamically to external changes through the brain's ability to predict sensory outcomes and adjust for discrepancies between anticipated and actual sensory inputs. In this study, we investigated how changes in target speed (v) and direction influenced visuomotor responses, focusing on gaze and manual joystick control during an interception task. Participants tracked a moving target with sinusoidal variations in v and directional changes, generating sensory prediction errors and requiring real-time adjustments.
View Article and Find Full Text PDFPhilos Trans A Math Phys Eng Sci
January 2025
KIOS Research and Innovation Center of Excellence (KIOS CoE) and Department of Electrical and Computer Engineering, University of Cyprus, Nicosia 1678, Cyprus.
This work proposes a coverage controller that enables an aerial team of distributed autonomous agents to collaboratively generate non-myopic coverage plans over a rolling finite horizon, aiming to cover specific points on the surface area of a three-dimensional object of interest. The collaborative coverage problem, formulated as a distributed model predictive control problem, optimizes the agents' motion and camera control inputs, while considering inter-agent constraints aiming at reducing work redundancy. The proposed coverage controller integrates constraints based on light-path propagation techniques to predict the parts of the object's surface that are visible with regard to the agents' future anticipated states.
View Article and Find Full Text PDFJ Exp Psychol Gen
January 2025
Department of Experimental Psychology, Helmholtz Institute, Utrecht University.
Predicting the location of moving objects in noisy environments is essential to everyday behavior, like when participating in traffic. Although many objects provide multisensory information, it remains unknown how humans use multisensory information to localize moving objects, and how this depends on expected sensory interference (e.g.
View Article and Find Full Text PDFInfant Behav Dev
January 2025
Universität zu Köln, Richard Strauss Straße 2, Cologne 50931, Germany.
The study examined the saccadic behavior of 4- to 10-month-old infants when tracking a two-dimensional linear motion of a circle that occasionally bounced off a barrier constituted by the screen edges. It was investigated whether infants could anticipate the angle of the circle's direction after the bounce and the circle's displacement from the location of bounce. Seven bounce types were presented which differed in the angle of incidence.
View Article and Find Full Text PDFBiomimetics (Basel)
January 2025
Robotic, Brain, and Cognitive Sciences Research Unit, Italian Institute of Technology, Center for Human Technologies, Via Enrico Melen 83, Bldg B, 16152 Genoa, Italy.
Trunk-like robots have attracted a lot of attention in the community of researchers interested in the general field of bio-inspired soft robotics, because trunk-like soft arms may offer high dexterity and adaptability very similar to elephants and potentially quite superior to traditional articulated manipulators. In view of the practical applications, the integration of a soft hydrostatic segment with a hard-articulated segment, i.e.
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