Nature

Artificial brains with less drain

Computing systems that mimic biological neural networks underlie many artificial-intelligence applications. But these ...
Frontiers

Precision neurocircuitry: emerging tools to map, modulate, and model behavior

Unravelling how neural circuits generate complex behaviours remains one of the most compelling challenges in neuroscience. This endeavor requires tools that ...
eLife

Asymmetric neural entrainment at resonance frequencies underlies unilateral spatial neglect

This valuable study uses EEG and computational modeling to investigate hemispheric oscillatory asymmetries in unilateral spatial neglect. The work benefits from rare patient data and a careful ...
eLife

Functional Muscle Networks as Biomarkers of Post-Stroke Motor Impairment and Therapeutic Responsiveness

This important work employed a recent, functional muscle network analysis for evaluating rehabilitation outcomes in post-stroke patients. While the research direction is relevant and suggests the need ...
C&EN

SlaKoNet: A Unified Slater-Koster Tight-Binding Framework Using Neural Network Infrastructure for the Periodic Table

Department of Materials Science and Engineering, Whiting School of Engineering, The Johns Hopkins University, Baltimore, Maryland 21218, United States Department of Electrical and Computer Engineering ...
IEEE

Fault Classification in Distribution Networks Using Graph Neural Networks and Discrete Stockwell Transform

Abstract: Deep learning models have shown great potential for fault location and classification tasks in distribution systems. Emerging multi-scale data sources such as waveform measurement units, ...
IEEE

Adaptive Recursive Terminal Sliding Mode Control for MEMS Gyros Using Improved Neural Network With Constrained Input Mapping

Abstract: To drive the gyroscope into a command vibration mode, and to simultaneously estimate the angular velocity, this paper proposes an improved fully adjusted neural network-based adaptive ...