Results 71 to 80 of about 28,095 (262)

Polarization‐Dependent Synaptic‐Like Electro‐Optical Response in Ferroelectric Nematic Liquid Crystals

Advanced Functional Materials, EarlyView.
Ferroelectric nematic liquid crystals (FNLCs) offer fast, tunable polarization and low‐voltage operation but suffer from poor polarization retention at zero field. Semiconductor‐modified FNLCs enhance polarization retention and exhibit short‐ and long‐term electro‐optical responses, while also supporting spike‐type signal integrations.
Kutay Sagdic, Weiming Yao, Danqing Liu
wiley   +1 more source

A 3D Human Neuron‐on‐Chip Platform to Monitor Neuronal Injury Responses

Advanced Healthcare Materials, EarlyView.
This study presents a novel 3D Neuron‐on‐Chip model that can maintain human PSC‐derived excitatory prefrontal cortex neurons in 3D hydrogels and can be used to monitor neuronal injury responses over time. Results show injury‐induced acute neuronal excitotoxicity, declining neuronal connectivity, and the activation of a neurodegenerative, SASP‐like ...
Ruiping Tang, Charles‐Francois Latchoumane, Avi Chopra, Md Marzan Sarkar, Chunki Kim, Nathan Gonsalves, Hsueh‐Fu Wu, John C. Sentmanat, Alan Liu, Isha Mhatre‐Winters, Aditya Mishra, Andrei G. Fedorov, Jay M. Patel, Nadja Zeltner, Steven L. Stice, Jason R. Richardson, Lohitash Karumbaiah   +16 more
wiley   +1 more source

Ferroelectric Quantum Dots for Retinomorphic In‐Sensor Computing

Advanced Materials, EarlyView.
This work has provided a protocol for fabricating retinomorphic phototransistors by integrating ferroelectric ligands with quantum dots. The resulting device combines ferroelectricity, optical responsiveness, and low‐power operation to enable adaptive signal amplification and high recognition accuracy under low‐light conditions, while supporting ...
Tingyu Long, Huanyu Zhou, Jaewan Ko, Hongwei Tan, Jaemin Lim, Yanfei Zhao, Daehan Kang, Eojin Yoon, Gyeong‐Tak Go, Somin Kim, Seung‐Woo Lee, Chan‐Yul Park, Hyojun Choi, Hyeran Kim, Hyung Joong Yun, Sung Hyuk Park, Kwan Sik Park, Jeong Woo Park, Mungeun Kim, Yong Soo Cho, Ho Won Jang, Wenqiang Yang, Min Hyuk Park, Wan Ki Bae, Sebastiaan van Dijken, Joona Bang, Tae‐Woo Lee   +26 more
wiley   +1 more source

Implementing Signature Neural Networks with Spiking Neurons

Frontiers in Computational Neuroscience, 2016
Spiking Neural Networks constitute the most promising approach to develop realistic ArtificialNeural Networks (ANNs). Unlike traditional firing rate-based paradigms, information coding inspiking models is based on the precise timing of individual spikes.
José Luis Carrillo-Medina, Roberto Latorre   +1 more
doaj   +1 more source

Hopf Bifurcation in Mean Field Explains Critical Avalanches in Excitation-Inhibition Balanced Neuronal Networks: A Mechanism for Multiscale Variability

Frontiers in Systems Neuroscience, 2020
Cortical neural circuits display highly irregular spiking in individual neurons but variably sized collective firing, oscillations and critical avalanches at the population level, all of which have functional importance for information processing ...
Junhao Liang, Junhao Liang, Tianshou Zhou, Changsong Zhou, Changsong Zhou   +4 more
doaj   +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, You Zhou, Qingxiu Li, Wenyu Zhao, Sunyingyue Geng, Hangfei Li, Yan‐Bing Leng, Shirui Zhu, Guanglong Ding, Yongbiao Zhai, Ziyu Lv, Ye Zhou, Su‐Ting Han   +12 more
wiley   +1 more source

SNNAX - Spiking Neural Networks in JAX

2024 International Conference on Neuromorphic Systems (ICONS)
Spiking Neural Networks (SNNs) simulators are essential tools to prototype biologically inspired models and neuromorphic hardware architectures and predict their performance. For such a tool, ease of use and flexibility are critical, but so is simulation speed especially given the complexity inherent to simulating SNN.
Lohoff, Jamie, Finkbeiner, Jan, Neftci, Emre   +2 more
openaire   +3 more sources

Propagation of Spike Sequences in Neural Networks [PDF]

SIAM Journal on Applied Dynamical Systems, 2010
Precise spatiotemporal sequences of action potentials are observed in many brain areas and are thought to be involved in the neural processing of sensory stimuli. Here, we examine the ability of spiking neural networks to propagate stably a spatiotemporal sequence of spikes in the limit where each neuron fires only one spike.
openaire   +3 more sources

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Fast learning without synaptic plasticity in spiking neural networks

Scientific Reports
Spiking neural networks are of high current interest, both from the perspective of modelling neural networks of the brain and for porting their fast learning capability and energy efficiency into neuromorphic hardware. But so far we have not been able to
Anand Subramoney, Guillaume Bellec, Franz Scherr, Robert Legenstein, Wolfgang Maass   +4 more
doaj   +1 more source