electroencephalography-network-indices-as-biomarkers-upper-limb

Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke

Alteration of electroencephalography (EEG) signals during task-specific movement of the impaired limb has been reported as a potential biomarker for the ...

Korea University

Currently in diagnostic setting for breast cancer, FFDM and DBT are performed conjunctively. However, performing two imaging modalities may increase radiation exposure by double. Two-dimensional reconstructed images created from DBT with 2DSM, has a potential to replace conventional FFDM in concerning both radiation dosage and image quality. With increasing concerns for individual radiation exposure, studies analyzing radiation dosage in breast imaging modalities are needed. This study compared radiation dosage and image quality between DBT + 2DSM versus FFDM.

Quantitative analysis of radiation dosage and image quality between digital breast tomosynthesis (DBT) with two-dimensional synthetic mammography and full-field digital mammography (FFDM).

Electroencephalography (EEG) measured during transcranial direct current stimulation (tDCS) can help understand the accurate impact of tDCS on the brain, but this has been hindered due to significant inflow of tDCS-induced electrical artifacts.

Development of a transcranial direct current stimulation device based on current limiter for simultaneous measurement of electroencephalography: A feasibility study.

 Impaired movement after stroke is closely associated with altered brain functions, and thus the investigation on neural substrates of patients with stroke can pave a way for not only understanding the underlying mechanisms of neuropathological traits, but also providing an innovative solution for stroke rehabilitation. The objective of this study was to precisely investigate altered brain functions in terms of power spectral and brain network analyses.  Altered brain function was investigated by using electroencephalography (EEG) measured while 34 patients with chronic stroke performed movement tasks with the affected and unaffected hands. The relationships between functional brain network indices and Fugl-Meyer Assessment (FMA) scores were also investigated.  A stronger low-beta event-related desynchronization was found in the contralesional hemisphere for both affected and unaffected movement tasks compared with that of the ipsilesional hemisphere. More efficient whole-brain networks (increased strength and clustering coefficient, and prolonged path length) in the low-beta frequency band were revealed when moving the unaffected hand compared with when moving the affected hand. In addition, the brain network indices of the contralesional hemisphere indicated higher efficiency and cost-effectiveness than those of the ipsilesional hemisphere in both the alpha and low-beta frequency bands. Moreover, the alpha network indices (strength, clustering coefficient, path length, and small-worldness) were significantly correlated with the FMA scores.  Efficient functional brain network indices are associated with better motor outcomes in patients with stroke and could be useful biomarkers to monitor stroke recovery during rehabilitation.

Altered Functional Networks of Alpha and Low-Beta Bands During Upper Limb Movement and Association with Motor Impairment in Chronic Stroke.

To apply transcranial electrical stimulation (tES) to the motor cortex, motor hotspots are generally identified using motor evoked potentials by transcranial magnetic stimulation (TMS). The objective of this study is to validate the feasibility of a novel electroencephalography (EEG)-based motor-hotspot-identification approach using a machine learning technique as a potential alternative to TMS.

Ga-Young Choi

Department of Electronics and Information Engineering

Korea University

Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke

Ga-Young Choi

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Department of Electronics and Information Engineering

Korea University

Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke

Department of Electronics and Information Engineering