A Systematic Evaluation of Euclidean Alignment with Deep Learning for EEG Decoding

Information Science, Computer Science, Artificial Intelligence, Medicine, Neurology,
brain-computer interfaces   deep learning   euclidean alignment   EEG decoding   transfer learning  

Systematic Evaluation of Euclidean Alignment with Deep Learning for EEG Decoding Background Introduction Electroencephalogram (EEG) signals are widely used in brain-computer interface (BCI) tasks due to their non-invasive nature, portability, and low acquisition cost. However, EEG signals suffer from low signal-to-noise ratio, sensitivity to electr...

Changes in Brain Functional Networks Induced by Visuomotor Integration Task

Engineering, Electrical Engineering, Information Science, Electronic Information, Medicine, Neurology,
visuomotor integration   EEG   connectivity   functional networks   dominant hand   non-dominant hand   electroencephalographic  

Frequency-Specific Reorganization of Brain Networks during Visuomotor Tasks Research Background Executing movements is a complex cognitive function that relies on the coordinated activation of spatially proximal and distal brain regions. Visuomotor integration tasks require processing and interpreting visual inputs to plan motor execution and adjus...

Bayesian Estimation of Group Event-Related Potential Components: Testing a Model for Synthetic and Real Datasets

Information Science, Electronic Information, Artificial Intelligence, Medicine, Neurology, Life Sciences, Biophysics,
electroencephalogram   event-related potentials   hidden sources   bayesian estimation  

Background Introduction The study of Event-Related Potentials (ERPs) provides important information about brain mechanisms, particularly in elucidating various psychological processes. In these studies, multi-channel electroencephalograms (EEGs) are typically recorded while subjects perform specific tasks, and the trials are categorized based on st...

Neuritogenic Glycosaminoglycan Hydrogels Promote Functional Recovery After Severe Traumatic Brain Injury

Chemistry, Polymer Chemistry, Medicinal Chemistry, Materials Science, Organic Polymeric Materials, Medicine, Neurology, Life Sciences, Bioengineering,
neuritogenic   glycosaminoglycan   hydrogel   traumatic brain injury   functional recovery   cell adhesion   neurons  

Neuritogenic Glycosaminoglycan Hydrogels Promote Functional Recovery After Severe Traumatic Brain Injury Traumatic brain injury (TBI) is a serious neurological disorder, and the complexity of its treatment has long plagued the medical community. TBI not only leads to immediate loss of neurological function in patients, but also causes long-term tis...

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

Information Science, Electronic Information, Artificial Intelligence, Medicine, Basic Medical Sciences, Neurology, Life Sciences, Biophysics,
brain-computer interface   brain circuit   LFP synchronization   visual cortex   neuroinflammation  

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

Engineering, Electrical Engineering, Information Science, Computer Science, Artificial Intelligence, Medicine, Psychiatry, Neurology, Clinical Psychology, Medical Imaging,
Major Depressive Disorder   EEG   Deep Learning   Phase Locking Value   Contrastive Learning  

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

Engineering, Electrical Engineering, Information Science, Electronic Information, Computer Science, Medicine, Neurology, Life Sciences, Biophysics,
surface electromyogram   hand gesture decoding   Riemannian manifold   electrode array   multivariate timeseries  

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

Medicine, Neurology, Medical Imaging, Life Sciences, Bioengineering, Biophysics,
PNS   peripheral nerve stimulation   magnetostimulation   chronaxie   MRI  

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

Information Science, Electronic Information, Computer Science, Automation, Medicine, Neurology, Life Sciences, Bioengineering, Biophysics,
brain-computer interface   preparatory movement state   premovement intention   encoding paradigm   neural representation  

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

Medicine, Neurology, Medical Imaging, Life Sciences, Bioengineering, Biophysics,
Cross-frequency interactions   Phase-amplitude coupling   Bifocal transcranial alternating current stimulation   Motion direction discrimination   Visual stroke  

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...