Proceedings of the National Academy of Sciences of the United States of America
Nov 18, 2025
The architectures of biological neural networks result from developmental processes shaped by genetically encoded rules, biophysical constraints, stochasticity, and learning. Understanding these processes is crucial for comprehending neural circuits'...
Neural Cellular Automata have proven to be effective in various fields, with numerous biologically inspired applications. Particularly, neural cellular automata have been proven to be successful models for procedural generation of textures. They mode...
Journal of molecular neuroscience : MN
Nov 15, 2025
Spinal cord injury (SCI), a traumatic type of central nervous system injury, is closely associated with neuronal apoptosis. However, the specific biomarkers and regulatory mechanisms of neuronal apoptosis in SCI patients remain unclear. In this study...
Proceedings of the National Academy of Sciences of the United States of America
Nov 13, 2025
Covert visual attention allows the brain to select different regions of the visual world without eye movements. Predictive cues of a target location orient covert attention and improve perceptual performance. In most computational models, researchers...
Spiking Neural Networks (SNNs), designed to more accurately model the brain's neurobiological processes, have been proposed as energy-efficient alternatives to conventional Artificial Neural Networks (ANNs), which typically incur high computational a...
Amphetamine has widespread effects on multiple neurotransmitter systems, potentially altering the physiological connectivity and network dynamics across various regions of the brain. In this study, we investigated the effects of D-amphetamine using o...
Cellular and molecular life sciences : CMLS
Oct 30, 2025
The interaction between spinal cord neural networks and myocytes in postnatal mammals plays a crucial role in development, and the neural regulation of motor and visceral functions. Here, spinal cord neural network tissue (SC-NNT) was constructed wit...
Self-supervised denoising methods significantly enhance the signal-to-noise ratio in fluorescence neural imaging, yet real-time solutions remain scarce in high-speed applications. Here, we present the FrAme-multiplexed SpatioTemporal learning strateg...
Alzheimer's disease (AD) is characterized by progressive neurodegeneration, synaptic dysfunction, and cognitive decline. Regenerative strategies aim to replace lost neurons and modulate the inflammatory milieu to restore neural networks. This study e...
The time-elapsed model for neural assemblies is a nonlinear age-structured equation where the renewal term describes the network activity and influences the discharge rate, possibly with a delay due to the length of connections. We first solve a long...
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