Topographic maps showing how μECoG at Motor Cortex projects across the scalp

Simulating Scalp EEG from Ultrahigh-Density ECoG Data Illustrates Cortex to Scalp Projection Patterns

Using 1024-electrode ultrahigh-density electrocorticography (μECoG) data as ground truth, this study demonstrates that cortical activity from a small 3×3 cm patch projects broadly across the entire scalp surface, not just to nearby EEG electrodes. By applying ICA decomposition and forward-projecting through a high-definition head model, we show that scalp EEG channels reflect complex mixtures of distributed cortical sources rather than primarily local activity. These findings challenge conventional channel-level EEG interpretation approaches and underscore the critical importance of source-level analysis methods for accurate understanding of brain electrical activity.

Dual-layer electrode structure for biosignal detection and noise cancellation.

System and methods for biosignal detection and active noise cancellation

We developed a novel EEG system with a dual-electrode net structure for noise reduction and precise biosignal capture. Incorporating advanced software for signal processing, this invention enhances EEG accuracy, reduces setup complexity, and broadens EEG applications, including brain-computer interfaces, through real-time noise separation and immersive noise layering techniques.

Muscle faitgue can be characterized using a non-parametric functional muscle network.

Non-Parametric Functional Muscle Network as a Robust Biomarker of Fatigue

We show that the effects of fatigue on muscle coordination and neural drive can be reliably characterized using a non-parametric functional muscle network. The network demonstrated a consistent decrease in connectivity after the fatigue intervention, as indicated by network degree, weighted clustering coefficient (WCC), and global efficiency. The graph metrics displayed consistent and significant decreases at the group level, individual subject level, and individual muscle level. The proposed approach has the potential to be a sensitive biomarker of fatigue with superior performance to conventional spectrotemporal measures.

Re-referencing methods comparison

Re-Referencing Methods for High-Density EEG

This project investigates different re-referencing approaches for high-density EEG recordings, evaluating their effectiveness in reducing artifacts and improving source localization accuracy. The work contributes to best practices for EEG preprocessing pipelines.

The effect of fiducial mismarking on EEG source estimation.

Nonlinear functional muscle network based on information theory tracks sensorimotor integration post stroke

We show that InfoMuNet, a novel functional biomarker based on a nonlinear network graph of muscle connectivity, can quantify the role of sensory information on motor performance. We demonstrate its potential use in precision rehabilitation interventions.

The effect of fiducial mismarking on EEG source estimation.

Perilaryngeal-Cranial Functional Muscle Network Differentiates Vocal Tasks: A Multi-Channel sEMG Approach

We explored the potential of a functional muscle network to differentiate vocal tasks. The network robustly differentiated vocal tasks, while classic muscle activation assessment failed to differentiate. The study also discovered tasks with the highest network involvement, which may be utilized in the future to monitor voice disorders and rehabilitation.

The effect of fiducial mismarking on EEG source estimation.

Differential Theta-Band Signatures of the Anterior Cingulate and Motor Cortices During Seated Locomotor Perturbations

We demonstrate that seated locomotor perturbations produce differential theta-band responses in the anterior cingulate and supplementary motor areas, suggesting that tuning perturbation parameters can potentially modify electrocortical responses.

The five digitizing methods tested in this study.

More Reliable EEG Electrode Digitizing Methods Can Reduce Source Estimation Uncertainty, but Current Methods Already Accurately Identify Brodmann Areas

Download Paper Code and data Abstract Electroencephalography (EEG) and source estimation can be used to identify brain areas activated during a task, which could offer greater insight on cortical dynamics. Source estimation requires knowledge of the locations of the EEG electrodes. This could be provided with a template or obtained by digitizing the EEG electrode locations. Operator skill and inherent uncertainties of a digitizing system likely produce a range of digitization reliabilities, which could affect source estimation and the interpretation of the estimated source locations....

The effect of fiducial mismarking on EEG source estimation.

Influence of Mismarking Fiducial Locations on EEG Source Estimation

Mismarking fiducial locations can systematically change EEG source locations. We inestigated this effect by systematically moving the fiducial locations to simulate such errors.