Brain-inspired neural network architecture overcomes unsolved classical control theory problem for telerobotics.
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Multifunctional Artificial Electric Synapse of MoSe-Based Memristor toward Neuromorphic Application.
J Phys Chem Lett
January 2025
Key Laboratory of Atomic and Molecular Physics and Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou 730070, China.
Research on memristive devices to seamlessly integrate and replicate the dynamic behaviors of biological synapses will illuminate the mechanisms underlying parallel processing and information storage in the human brain, thereby affording novel insights for the advancement of artificial intelligence. Here, an artificial electric synapse is demonstrated on a one-step Mo-selenized MoSe memristor, having not only long-term stable resistive switching characteristics (reset 0.51 ± 0.
View Article and Find Full Text PDFModeling analysis of depolarization-assisted afterdischarge in hippocampal mossy fibers.
Front Neural Circuits
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Department of Neurobiology, Hokkaido University Graduate School of Medicine, Sapporo, Japan.
A strong repetitive stimulus can occasionally enhance axonal excitability, leading to the generation of afterdischarge. This afterdischarge outlasts the stimulus period and originates either from the physiological spike initiation site, typically the axon initial segment, or from ectopic sites for spike generation. One of the possible mechanisms underlying the stimulus-induced ectopic afterdischarge is the local depolarization due to accumulated potassium ions surrounding the axonal membranes of the distal portion.
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Front Comput Neurosci
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Department of Biosciences, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway.
Real-Time Unsupervised Learning and Image Recognition via Memristive Neural Integrated Chip Based on Negative Differential Resistance of Electrochemical Metallization Cell Neuron Device.
Small
January 2025
Department of Nano-scale Semiconductor Engineering, Hanyang University, Seoul, 04763, Republic of Korea.
Spiking neurons are essential for building energy-efficient biomimetic spatiotemporal systems because they communicate with other neurons using sparse and binary signals. However, the achievable high density of artificial neurons having a capacitor for emulating the integrate function of biological neurons has a limit. Furthermore, a low-voltage operation (<1.
View Article and Find Full Text PDFPaying attention to the SARS-CoV-2 dialect : a deep neural network approach to predicting novel protein mutations.
Commun Biol
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Dept. Electrical Engineering and Computer Science, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA.
Predicting novel mutations has long-lasting impacts on life science research. Traditionally, this problem is addressed through wet-lab experiments, which are often expensive and time consuming. The recent advancement in neural language models has provided stunning results in modeling and deciphering sequences.
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