Results 121 to 130 of about 180,626 (262)

Neural coding of autonomic functions in different states of consciousness. [PDF]

J Neuroeng Rehabil, 2023
Liuzzi P, Hakiki B, Scarpino M, Burali R, Maiorelli A, Draghi F, Romoli AM, Grippo A, Cecchi F, Mannini A.   +9 more
europepmc   +1 more source

A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys

Advanced Engineering Materials, EarlyView.
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin, Marta Campolucci, Nicolas de Andrade Ishiki, Nathan Mirgot, Nadir Zhamantay, Frédéric Kanoufi, Jennifer Peron, Jean Charlety, Emiliano Fonda, Valérie Briois, Marco Faustini, Maria‐Letizia De Marco, Christine Goyhenex, Ovidiu Ersen, Hervé Bulou   +14 more
wiley   +1 more source

Homeostatic synaptic plasticity rescues neural coding reliability. [PDF]

Nat Commun, 2023
Rozenfeld E, Ehmann N, Manoim JE, Kittel RJ, Parnas M.   +4 more
europepmc   +1 more source

Emerging Post‐CMOS Hardware Neurons for Brain‐Inspired Computing: Devices, Circuits, and System Integration

Advanced Functional Materials, EarlyView.
The physical realization of artificial neurons is a critical challenge for energy‐efficient neuromorphic computing. This review presents a comprehensive analysis of the evolution of artificial neuron implementations from conventional CMOS to emerging post‐CMOS technologies.
Kannan Udaya Mohanan, Hocheon Yoo, Benoît H. Lessard, Ioannis Kymissis, Chang‐Hyun Kim   +4 more
wiley   +1 more source

An Epigenetic Fate Converter Based on Nuclei‐Targeting Lipid Nanoparticles Drives Neuronal Programming of Stem Cells for Spinal Cord Repair

Advanced Functional Materials, EarlyView.
Schematic illustration of LNP‐MPG nuclei‐targeting delivery of HMW‐FGF2 promoting histone acetylation to regulate the fate of DPSCs and treat spinal cord injury. LNPs components include pHMW‐FGF2 plasmid, DSPC, Dlin‐MC3‐DMA, cholesterol, and PEG2000, and are modified with MPG to form HMW‐FGF2@LNP‐MPG (HLM). HLM nuclei‐targets DPSCs to deliver HMW‐FGF2,
Heng Zhou, Qiang Qin, Xiqin Li, Hanyu Ding, Chun Xu, Yan He, Qingsong Ye   +6 more
wiley   +1 more source

Rate-distortion theory of neural coding and its implications for working memory. [PDF]

Elife, 2023
Jakob AMV, Gershman SJ.
europepmc   +1 more source

Additively Manufactured Geometry‐Reconfigurable Soft Neural Probes With Monolithic Multifunctionality

Advanced Functional Materials, EarlyView.
A geometry‐reconfigured additive manufacturing strategy converts planar printed soft materials into soft compact neural probes with integrated hydrogel electrodes and microfluidic channels. The resulting NeuroMAP platform enables scalable multichannel recording, localized chemical delivery, stable in vivo electrophysiological recording, and reduced ...
Hyunjin Lee, Xinyi Wang, Sirui Li, Jihyang Park, Hyunseok Lee, Jianting Yao, Kedar Narayan, Yuqi Wang, Jiashu Ren, Yueqi Deng, Salahuddin Ahmed, Denver I. Greenawalt, Archana Pandiyan, Loganathan Veeramuthu, Chi‐Ching Kuo, Tao Zhou   +15 more
wiley   +1 more source

Neural network based image and video coding technologies

Dianxin kexue, 2019
Deep neural networks have achieved tremendous success in artificial intelligence,which makes the broad and in-depth research of neural network resurge in recent years.Recently,the neural network based image and video coding has become one of the front ...
Chuanmin JIA, Zhenghui ZHAO, Shanshe WANG, Siwei MA   +3 more
doaj  

Questions and controversies surrounding the perception and neural coding of pitch. [PDF]

Front Neurosci, 2022
Oxenham AJ.
europepmc   +1 more source

Intelligent Orthopedics: Machine Learning in Diagnosis of Bone Disease, Implants, and Bone Health Monitoring

Advanced Healthcare Materials, EarlyView.
Efficient recovery from traumatic or degenerative diseases is a great challenge, even after all the advancements in bone and cartilage regeneration. Machine learning (ML) algorithms have presented opportunities to enhance these aspects by accurately analyzing imaging data.
Maryam Kamaei, Hesam Mohammadi, Shamim Golafshan, Mojtaba Alehosseini, Mahsa Mohammadzadeh, Atefeh Golshirazi, Nasim Golafshan, Tatiane Eufrásio‐da‐Silva, Alireza Dolatshahi‐Pirouz, Gorka Orive   +9 more
wiley   +1 more source