Results 81 to 90 of about 10,435,031 (361)
Dynamic layer-span connecting spiking neural networks with backpropagation training
Complex & Intelligent Systems, 2023 Spiking Neural Network (SNN) is one of the mainstream frameworks for brain-like computing and neuromorphic computing, which has the potential to overcome current AI challenges, for example, low-power learning dynamic processes.
Zijjian Wang +4 more
doaj +1 more source
Neuronal Synchronization Can Control the Energy Efficiency of Inter-Spike Interval Coding [PDF]
, 2018 The role of synchronous firing in sensory coding and cognition remains controversial. While studies, focusing on its mechanistic consequences in attentional tasks, suggest that synchronization dynamically boosts sensory processing, others failed to find ...
Ghavami, Siavash +3 more
core +1 more source
Bioinspired Adaptive Sensors: A Review on Current Developments in Theory and Application
Advanced Materials, EarlyView.This review comprehensively summarizes the recent progress in the design and fabrication of sensory‐adaptation‐inspired devices and highlights their valuable applications in electronic skin, wearable electronics, and machine vision. The existing challenges and future directions are addressed in aspects such as device performance optimization ...
Guodong Gong +12 more
wiley +1 more source
PLoS Biology, 2019 Neurons receive a large number of active synaptic inputs from their many presynaptic partners across their dendritic tree. However, little is known about how the strengths of individual synapses are controlled in balance with other synapses to ...
Mathieu Letellier +3 more
doaj +1 more source
Detachable and Reusable: Reinforced π‐Ion Film for Modular Synaptic Reservoir Computing
Advanced Materials, EarlyView.This study presents a reinforced π‐ion film for organic electrochemical transistors (OECTs), addressing the rapid degradation of organic semiconductor layers. By introducing a mesh support and utilizing a scalable solvent exchange method, the π‐ion film enhances detachability and stability.
Gyu Won Woo +8 more
wiley +1 more source
Journal of Neurorestoratology, 2013 Tatsuo Suzuki,1 Wei-Dong Yao21Department of Neuroplasticity, Shinshu University Graduate School of Medicine, Matsumoto, Japan; 2Department of Psychiatry, Beth Israel Deaconess Medical Center, and Division of Neuroscience, New England Primate Research ...
Suzuki T, Yao WD
doaj
Alterations in brain connectivity due to plasticity and synaptic delay
, 2017 Brain plasticity refers to brain's ability to change neuronal connections, as a result of environmental stimuli, new experiences, or damage. In this work, we study the effects of the synaptic delay on both the coupling strengths and synchronisation in a ...
Batista, A. M. +8 more
core +1 more source
Hardware Implementation of On‐Chip Hebbian Learning Through Integrated Neuromorphic Architecture
Advanced Materials, EarlyView.This work presents a neuromorphic hardware platform that integrates presynaptic transistors, threshold switching neurons, and adaptive feedback synapses. The architecture enables on‐chip Hebbian learning through correlation‐based weight updates without external training circuits.
Seonkwon Kim +6 more
wiley +1 more source
Imbalance of Excitation and Inhibition at Threshold Level In the Auditory Cortex
Frontiers in Neural Circuits, 2015 The interplay of cortical excitation and inhibition is a fundamental feature of cortical information processing. Excitation and inhibition in single cortical neurons are balanced in their response to optimal sensory stimulation due to thalamocortical ...
Yan eZhao +6 more
doaj +1 more source
Synaptic partner prediction from point annotations in insect brains
, 2018 High-throughput electron microscopy allows recording of lar- ge stacks of neural tissue with sufficient resolution to extract the wiring diagram of the underlying neural network.
A Kreshuk +8 more
core +1 more source