Results 61 to 70 of about 328,871 (251)

Small Extracellular Vesicles from Neural Cells: Physiological and Pathological Roles, and Potential in Neurodegenerative Therapy

Advanced Healthcare Materials, EarlyView.
Neural cell–derived small extracellular vesicles (sEVs) are emerging as pivotal mediators in neurodegenerative diseases, exerting both pathogenic and therapeutic functions. This review synthesizes current evidence on how sEVs from distinct neural cell types regulate neurodegeneration, neuroprotection, biomarker discovery, and targeted drug delivery ...
Muhammad Waqas Salim, Wei Zhang, Lyndsey Collins‐Praino, Yuling Wang, Andrew Care   +4 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

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

Correlation entropy of synaptic input-output dynamics

, 2006
The responses of synapses in the neocortex show highly stochastic and nonlinear behavior. The microscopic dynamics underlying this behavior, and its computational consequences during natural patterns of synaptic input, are not explained by conventional ...
A. Harsch, B. Sakmann, C. Webber, Jr., D. Cox, G. Fuhrmann, Hugh P. C. Robinson, Ingo C. Kleppe, J. A. Varela, J. S. Dittman, L. Cao, L. F. Abbott, R. C. Malenka   +11 more
core   +1 more source

Proteomics of synapse [PDF]

Analytical and Bioanalytical Chemistry, 2006
Large-scale phosphoproteome analysis on synaptosome and preparation of post-synaptic density (PSD) were investigated. It was found that protein phosphor is a common event in the synapse, which is consistent with the presence of diverse classes of kinases and phosphatases in the synapse.
openaire   +3 more sources

Room‐Temperature Skyrmionic Synapse in 2D Ferromagnet Fe3GaTe2 Operating via Collective Spin Texture Transformation

Advanced Materials, EarlyView.
We demonstrate a neuromorphic synapse in 2D Fe3GaTe2 flakes. The device operates via a current‐driven transformation from a skyrmion‐lattice to a stripe‐domain state, yielding a linear anomalous Hall resistance response with a tunable slope to enable multiply‐accumulate operations. Simulations confirm its viability in artificial neural networks.
Jixiang Huang, Tongji Zhu, PeiYu Cai, Xiaoming Ma, Zhen Wang, Ruifu Zhang, Yi Hao, Jingdi Lu, Liubing He, Jun Xu, Yuejie Zhang, Wanjun Jiang, Jing Tao, Shiming Lei, Pavel Parchinskiy, Jing Teng, Lingfei Wang, Wei Niu, Elton J.G. Santos, Xiaoqian Zhang, Peng Li   +20 more
wiley   +1 more source

An associative memory of Hodgkin-Huxley neuron networks with Willshaw-type synaptic couplings

, 2000
An associative memory has been discussed of neural networks consisting of spiking N (=100) Hodgkin-Huxley (HH) neurons with time-delayed couplings, which memorize P patterns in their synaptic weights.
Aihara K., Amari S., Amari S., Amit D. J., Anderson J. A., Aonishi T., Aoyagi T., Brown D., Brunel N., Buhmann J., Calvin W., Cao J., Carr C. E., Eckhorn R., Feng J., Gardner E. J., Gerstner W., Golomb G., Gray C. M., Hasegawa H., Hodgkin A. L., Hopfield J. J., Hoppensteadt F. C., Kanamaru T., Kempter R., Kohonen T., Kohring G. A., Konishi M., Krisement O., Lytton W. W., Maass W., Mueller R., Nadal J., Nemoto I., Perkel D. H., Rieke F., Rolls E. T., Shadlen M., Softky W. R., Softky W. R., Sompolinsky H., Stevens C. F., Suga N., Thorpe S., Treves A., Troyer T. W., Tsodyks M. V., Usher M., Vicente C. J. P., Willshaw D. J., Yoshioka M., Yoshioka M.   +51 more
core   +1 more source

Self‐Powered Flexible Triboelectric‐Gated Ion‐Gel Transistor for Neuromorphic Tactile Sensing and Human Activity Recognition

Advanced Materials, EarlyView.
A fully flexible ion‐gel‐gated graphene‐channel transistor driven by a triboelectric nanogenerator enables self‐powered tactile sensing and synaptic learning. Mimicking spike‐rate‐dependent plasticity, the device exhibits frequency‐selective potentiation and depression, supporting rate‐coded neuromorphic computation even under flex.
Hanseong Cho, Seoyeon Park, Youngmin Lee, Sejoon Lee   +3 more
wiley   +1 more source

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

Storage Capacity Diverges with Synaptic Efficiency in an Associative Memory Model with Synaptic Delay and Pruning [PDF]

, 2003
It is known that storage capacity per synapse increases by synaptic pruning in the case of a correlation-type associative memory model. However, the storage capacity of the entire network then decreases. To overcome this difficulty, we propose decreasing
Miyoshi, Seiji, Okada, Masato
core