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Neurons

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Developmental Plasticity-Inspired Adaptive Pruning for Deep Spiking and Artificial Neural Networks.

IEEE transactions on pattern analysis and machine intelligence
Developmental plasticity plays a prominent role in shaping the brain's structure during ongoing learning in response to dynamically changing environments. However, the existing network compression methods for deep artificial neural networks (ANNs) an...

A Bio-Inspired Spiking Attentional Neural Network for Attentional Selection in the Listening Brain.

IEEE transactions on neural networks and learning systems
Humans show a remarkable ability in solving the cocktail party problem. Decoding auditory attention from the brain signals is a major step toward the development of bionic ears emulating human capabilities. Electroencephalography (EEG)-based auditory...

Low Latency and Sparse Computing Spiking Neural Networks With Self-Driven Adaptive Threshold Plasticity.

IEEE transactions on neural networks and learning systems
Spiking neural networks (SNNs) have captivated the attention worldwide owing to their compelling advantages in low power consumption, high biological plausibility, and strong robustness. However, the intrinsic latency associated with SNNs during infe...

Aligned and oblique dynamics in recurrent neural networks.

eLife
The relation between neural activity and behaviorally relevant variables is at the heart of neuroscience research. When strong, this relation is termed a neural representation. There is increasing evidence, however, for partial dissociations between ...

Arithmetic abilities of SNP systems with astrocytes producing calcium.

Neural networks : the official journal of the International Neural Network Society
Are the membrane systems able of performing arithmetic operations? In the last dozen years, there were published several implementations of the arithmetic operations based on membrane systems by using all available topologies (cell-like, tissue-like,...

Spike-VisNet: A novel framework for visual recognition with FocusLayer-STDP learning.

Neural networks : the official journal of the International Neural Network Society
Current vision-inspired spiking neural networks (SNNs) face key challenges due to their model structures typically focusing on single mechanisms and neglecting the integration of multiple biological features. These limitations, coupled with limited s...

The evolution of patch-clamp electrophysiology: Robotic, multiplex, and dynamic.

Molecular pharmacology
The patch-clamp technique has been the gold standard for analysis of excitable cells. Since its development in the 1980s, it has contributed immensely to our understanding of neurons, muscle cells, and cardiomyocytes and the ion channels and receptor...

VC dimension of Graph Neural Networks with Pfaffian activation functions.

Neural networks : the official journal of the International Neural Network Society
Graph Neural Networks (GNNs) have emerged in recent years as a powerful tool to learn tasks across a wide range of graph domains in a data-driven fashion. Based on a message passing mechanism, GNNs have gained increasing popularity due to their intui...

Identification of movie encoding neurons enables movie recognition AI.

Proceedings of the National Academy of Sciences of the United States of America
Natural visual scenes are dominated by spatiotemporal image dynamics, but how the visual system integrates "movie" information over time is unclear. We characterized optic tectal neuronal receptive fields using sparse noise stimuli and reverse correl...

A digital neuromorphic system for working memory based on spiking neuron-astrocyte network.

Neural networks : the official journal of the International Neural Network Society
Among various types of memory, working memory (WM) plays a crucial role in reasoning, decision-making, and behavior regulation. Neuromorphic computing is a well-established engineering approach that offers promising avenues for advancing our understa...