Neuronal Functional Connectivity is Impaired in a Layer-dependent Manner Near Chronically Implanted Intracortical Microelectrodes in C57BL/6 Wildtype Mice

Layer-Dependent Effects of Chronic Neural Electrode Implants on Neural Functional Connectivity in Mice Introduction This study explores the long-term effects of chronically implanted microelectrodes on neural functional connectivity within the brains of C57BL6 wild-type mice. Implanted intracerebral electrodes enable the recording and electrical st...

GCTNet: A Graph Convolutional Transformer Network for Major Depressive Disorder Detection Based on EEG Signals

GCTNet: Graph Convolution Transformer Network for Detecting Major Depressive Disorder Based on EEG Signals Research Background Major Depressive Disorder (MDD) is a prevalent mental illness characterized by significant and persistent low mood, affecting over 350 million people worldwide. MDD is one of the leading causes of suicide, resulting in appr...

Topology of Surface Electromyogram Signals: Hand Gesture Decoding on Riemannian Manifolds

Topology of Surface Electromyography Signals: Decoding Hand Gestures Using Riemannian Manifolds This paper is authored by Harshavardhana T. Gowda (Department of Electrical and Computer Engineering, University of California, Davis) and Lee M. Miller (Center for Mind and Brain Sciences, Department of Neurophysiology and Behavior, Department of Otolar...

Influence of Peripheral Axon Geometry and Local Anatomy on Magnetostimulation Chronaxie

Influence of Peripheral Nerve Geometry and Local Anatomy on Magnetic Stimulation Time Constant Background Introduction Rapidly switching magnetic resonance imaging (MRI) gradient fields produce sufficiently strong electric fields within the human body, leading to peripheral nerve stimulation (PNS), which limits improvements in imaging speed and res...

Preparatory Movement State Enhances Premovement EEG Representations for Brain-Computer Interfaces

EEG of Pre-movement Phase Aids Brain-Computer Interface (BCI) in Recognizing Movement Intentions Background and Research Objectives Brain-Computer Interface (BCI) is a technology that translates human intentions directly through neural signals to control devices, holding extensive application prospects [1]. BCI has the potential to revolutionize va...

Single-Session Cross-Frequency Bifocal tACS Modulates Visual Motion Network Activity in Young Healthy Population and Stroke Patients

Report on Single-Session Cross-Frequency Dual-Focus tACS Modulation of Visuomotor Network Activity in Healthy Young Adults and Stroke Patients Academic Background and Research Significance In neuroscience research, neural oscillations play a crucial role in regulating communication within and between brain regions. Long-distance phase synchronizati...