Surface-functionalized SERS platform for deep learning-assisted diagnosis of Alzheimer's disease.

Early diagnosis of Alzheimer's disease is crucial to stall the deterioration of brain function, but conventional diagnostic methods require complicated analytical procedures or inflict acute pain on the patient. Then, label-free Surface-enhanced Raman spectroscopy (SERS) analysis of blood-based biomarkers is a convenient alternative to rapidly obtain spectral information from biofluids. However, despite the rapid acquisition of spectral information from biofluids, it is challenging to distinguish spectral features of biomarkers due to interference from biofluidic components.

Improving performance in motor imagery BCI-based control applications via virtually embodied feedback.

Objective: Brain-computer interfaces (BCIs) based on motor imagery (MI) are commonly used for control applications. However, these applications require strong and discriminant neural patterns for which extensive experience in MI may be necessary. Inspired by the field of rehabilitation where embodiment is a key element for improving cortical activity, our study proposes a novel control scheme in which virtually embodiable feedback is provided during control to enhance performance.

Observing Actions Through Immersive Virtual Reality Enhances Motor Imagery Training.

Visual information plays an essential role in enhancing neural activity during mental practices. Previous research has shown that using different visual scenarios during mental practices that involve imagining the movement of a specific body part may result in differences in performance. Many of these scenarios utilize the concept of embodiment, or one's observation of another entity to be a part of oneself, to improve practice quality of the imagined body movement.