Multiple cortical areas contribute to visual processing in mice. However, the functional organization and development of higher visual areas are unclear. Here we used intrinsic signal optical imaging and two-photon calcium imaging to map visual responses in adult and developing mice. We found that visually driven activity was well correlated among higher visual areas within two distinct subnetworks resembling the dorsal and ventral visual streams. Visual response magnitude in dorsal stream areas slowly increased over the first 2 weeks of visual experience. By contrast, ventral stream areas exhibited strong responses shortly after eye opening. Neurons in a dorsal stream area showed little change in their tuning sharpness to oriented gratings while those in a ventral stream area increased stimulus selectivity and expanded their receptive fields significantly. Together, these findings provide a functional basis for grouping subnetworks of mouse visual areas and revealed stream differences in the development of receptive field properties.
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http://dx.doi.org/10.1038/nn.4469 | DOI Listing |
J Integr Neurosci
January 2025
Neuroscience Department, University of Connecticut Health, School of Medicine, Institute for Systems Genomics, Farmington, CT 06030, USA.
Background: In neuroscience, Ca imaging is a prevalent technique used to infer neuronal electrical activity, often relying on optical signals recorded at low sampling rates (3 to 30 Hz) across multiple neurons simultaneously. This study investigated whether increasing the sampling rate preserves critical information that may be missed at slower acquisition speeds.
Methods: Primary neuronal cultures were prepared from the cortex of newborn pups.
Nutrients
January 2025
Coimbra Health School (ESTeSC), Polytechnic University of Coimbra, 3046-854 Coimbra, Portugal.
Background: The dietary intake of hospitalised patients is often compromised during hospitalisation, which can be a causal factor for hospital malnutrition. This is considered a public health problem worldwide and is associated with an increased risk of other complications.
Objectives: Our objective was to determine the dietary intake of hospitalised individuals and if the prescribed diet influences it.
Sensors (Basel)
January 2025
Centre of Mechanical Technology and Automation (TEMA), Department of Mechanical Engineering, University of Aveiro, 3810-193 Aveiro, Portugal.
To automate the quality control of painted surfaces of heating devices, an automatic defect detection and classification system was developed by combining deflectometry and bright light-based illumination on the image acquisition, deep learning models for the classification of non-defective (OK) and defective (NOK) surfaces that fused dual-modal information at the decision level, and an online network for information dispatching and visualization. Three decision-making algorithms were tested for implementation: a new model built and trained from scratch and transfer learning of pre-trained networks (ResNet-50 and Inception V3). The results revealed that the two illumination modes employed widened the type of defects that could be identified with this system, while maintaining its lower computational complexity by performing multi-modal fusion at the decision level.
View Article and Find Full Text PDFSensors (Basel)
January 2025
The Higher Educational Key Laboratory for Measuring & Control Technology and Instrumentation of Heilongjiang Province, Harbin University of Science and Technology, Harbin 150080, China.
Video instance segmentation, a key technology for intelligent sensing in visual perception, plays a key role in automated surveillance, robotics, and smart cities. These scenarios rely on real-time and efficient target-tracking capabilities for accurate perception and intelligent analysis of dynamic environments. However, traditional video instance segmentation methods face complex models, high computational overheads, and slow segmentation speeds in time-series feature extraction, especially in resource-constrained environments.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Laboratory of Adaptive Lighting Systems and Visual Processing, Technical University of Darmstadt, Hochschulstr. 4a, 64289 Darmstadt, Germany.
Thermopile sensor arrays provide a sufficient counterbalance between person detection and localization while preserving privacy through low resolution. The latter is especially important in the context of smart building automation applications. Current research has shown that there are two machine learning-based algorithms that are particularly prominent for general object detection: You Only Look Once (YOLOv5) and Detection Transformer (DETR).
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