Detection of objects that move in a scene is a fundamental computation performed by the visual system. This computation is greatly complicated by observer motion, which causes most objects to move across the retinal image. How the visual system detects scene-relative object motion during self-motion is poorly understood. Human behavioral studies suggest that the visual system may identify local conflicts between motion parallax and binocular disparity cues to depth and may use these signals to detect moving objects. We describe a novel mechanism for performing this computation based on neurons in macaque middle temporal (MT) area with incongruent depth tuning for binocular disparity and motion parallax cues. Neurons with incongruent tuning respond selectively to scene-relative object motion, and their responses are predictive of perceptual decisions when animals are trained to detect a moving object during self-motion. This finding establishes a novel functional role for neurons with incongruent tuning for multiple depth cues.
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http://dx.doi.org/10.7554/eLife.74971 | DOI Listing |
Eur Radiol
January 2025
Departments of Radiology and Nuclear Medicine, Erasmus MC - Sophia Children's Hospital, Rotterdam, the Netherlands.
Chest imaging in children presents unique challenges due to varying requirements across age groups. For chest radiographs, achieving optimal images often involves careful positioning and immobilisation techniques. Antero-posterior projections are easier to obtain in younger children, while lateral decubitus radiographs are sometimes used when expiratory images are difficult to obtain and for free air exclusion.
View Article and Find Full Text PDFBiological activities observed in living systems occur as the output of which nanometer-, submicrometer-, and micrometer-sized structures and tissues non-linearly and dynamically behave through chemical reaction networks, including the generation of various molecules and their assembly and disassembly. To understand the essence of the dynamic behavior in living systems, simpler artificial objects that exhibit cell-like non-linear phenomena have been recently constructed. However, most objects exhibiting cell-like dynamics have been found through trial-and-error experiments, and there are no strategies for designing them as molecular systems.
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 PDFProc Biol Sci
January 2025
Department of Neuroscience, Psychology, Pharmacology and Child Health, University of Florence, Florence, Italy.
Perceptual adaptation has been widely used to infer the existence of numerosity detectors, enabling animals to quickly estimate the number of objects in a scene. Here, we investigated, in humans, whether numerosity adaptation is influenced by stimulus feature changes as previous research suggested that adaptation is reduced when the colour of adapting and test stimuli did not match. We tested whether such adaptation reduction is due to unspecific novelty effects or changes of stimuli identity.
View Article and Find Full Text PDFNat Commun
January 2025
Department of Traffic Management School, People's Public Security University of China, Beijing, 100038, China.
The takeover issue, especially the setting of the takeover time budget, is a critical factor restricting the implementation and development of conditionally automated vehicles. The general fixed takeover time budget has certain limitations, as it does not take into account the driver's non-driving behaviors. Here, we propose an intelligent takeover assistance system consisting of all-round sensing gloves, a non-driving behavior identification module, and a takeover time budget determination module.
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