Wireless Injectable Ultrasound Sensor for Intracranial Signal Monitoring Background Introduction Direct and accurate monitoring of intracranial physiological conditions is extremely important for injury classification, prognosis assessment, and disease prevention. However, traditional wired clinical devices, such as percutaneous leads, although per...
Automated Spinal Cord Segmentation Pipeline Based on Convolutional Neural Network (CNN) for Individualized Cat Spinal Cord Stimulation Modeling Background and Research Motivation Spinal cord stimulation (SCS) is a widely used treatment method for chronic pain management. In recent years, it has also been used to modulate neural activity, aiming to ...
Application of Attention-guided Graph Structure Learning Network for EEG-enabled Auditory Attention Detection Academic Background The “cocktail party effect” describes the human brain’s ability to selectively concentrate attention on one speaker while ignoring others in a multi-talker environment. However, for individuals with hearing impairments, ...
Feasibility of Intravascular Femoral Nerve Stimulation using a Stent Electrode Array In recent years, electrical stimulation of peripheral nerves has gained attention as a potential therapeutic approach for restoring impaired nerve function. Traditional electrode arrays typically require invasive surgical implantation, which imposes a significant b...
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...
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...
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 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...
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: 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...