Results 181 to 190 of about 25,328 (252)

Material Strategies for Stimulation and Recording in Neural Biocomputing Platforms

Advanced Electronic Materials, EarlyView.
Material strategies enabling stimulation and recording are central to neural biocomputing systems. This review examines how electronic materials govern the encoding of inputs and decoding of outputs in living neural networks. Advances in electrical, optical, and multimodal interfaces highlight emerging design principles for biocomputing platforms ...
Sehong Kang, Junggeon Park, Aryaman Joshi, Rakid Haque, Gyu Weon Hwang, Hyunjoon Kong   +5 more
wiley   +1 more source

Hierarchical Afferent Connectivity Drives Population-Wide Bursting Dynamics in a Computational Model of Human-Derived Excitatory Neuronal Networks. [PDF]

J Neurosci
Barabino V, Callegari F, Martinoia S, Massobrio P.   +3 more
europepmc   +1 more source

Cavity Microelectrode Arrays for Electrical Recordings From Neurons

Advanced Electronic Materials, EarlyView.
Microelectrode arrays (MEAs) are used to study electrophysiological activity. However, their signals are small with high noise. By adding a 100‐nanometer‐high cavity above the electrode, which reduces impedance without affecting resolution, we improve signal quality.
Johannes Lewen, Bernhard Wolfrum, Andreas Offenhäusser   +2 more
wiley   +1 more source

Structure and Spectroscopic Characterisation of Phenanthroline‐Based Iodobismuthate(III) Complexes Utilised for Raw Acoustic Signal Classification

Advanced Intelligent Discovery, EarlyView.
Memristors based on trimethylsulfonium (phenanthroline)tetraiodobismuthate have been utilised as a nonlinear node in a delayed feedback reservoir. This system allowed an efficient classification of acoustic signals, namely differentiation of vocalisation of the brushtail possum (Trichosurus vulpecula).
Ewelina Cechosz, Gisya Abdi, Andrzej Sławek, Marlena Gryl, Konrad Szaciłowski   +4 more
wiley   +1 more source

Smart Flexible Tactile Sensors: Recent Progress in Device Designs, Intelligent Algorithms, and Multidisciplinary Applications

Advanced Intelligent Discovery, EarlyView.
Flexible tactile sensors have considerable potential for broad application in healthcare monitoring, human–machine interfaces, and bioinspired robotics. This review explores recent progress in device design, performance optimization, and intelligent applications. It highlights how AI algorithms enhance environmental adaptability and perception accuracy
Siyuan Wang, Ming Dong, Rongrong Bao, Caofeng Pan   +3 more
wiley   +1 more source

Model-agnostic linear-memory online learning in spiking neural networks. [PDF]

Nat Commun
Wang C, Dong X, Ji Z, Xiao M, Jiang J, Liu X, Huan Y, Wu S.   +7 more
europepmc   +1 more source

Sampling Strategy: An Overlooked Factor Affecting Artificial Intelligence Prediction Accuracy of Peptides’ Physicochemical Properties

Advanced Intelligent Discovery, EarlyView.
This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan, Ankeer Abuduhebaier, Haojin Zhou, Jiaqi Wang   +3 more
wiley   +1 more source

Algorithm-hardware co-design of neuromorphic networks with dual memory pathways. [PDF]

Nat Mach Intell
Sun P, Su Z, Achterberg J, Indiveri G, Goodman DFM, Akarca D.   +5 more
europepmc   +1 more source

Real‐Time Multicolor Fluorescence Microscopy via Cross‐Channel Acquisition and Deep‐Learning‐Based Inference

Advanced Intelligent Discovery, EarlyView.
Sequential multicolor fluorescence imaging in dynamic microsystems is constrained by acquisition speed and excitation dose. This study introduces a real‐time framework to reconstruct spectrally separated channels from reduced cross‐channel acquisitions (frames containing mixed spectral contributions).
Juan J. Huaroto, Yuxin Jin, Nicholas Roy, Sarthak Misra   +3 more
wiley   +1 more source

SPCNNet: spiking point cloud neural network for morphological neuron classification. [PDF]

Sci Rep
Lin X, Yu M, Wang X.
europepmc   +1 more source