Preserving Motor Features by Alternative Re‐Referencing to Remove Heart Artifact on the Stentrode

Vascular electrocorticography (vECoG) has shown great promise as a less-invasive alternative to penetrating electrode arrays for neural signal acquisition. This study investigates the signal quality of the Stentrode device, a leading vECoG platform, by contrasting artifact persistence with the preservation of low frequency motor cortical activity. Typical (re-)referencing schemes, including a monopolar stent-mounted reference, a common average reference, and a Laplacian reference, are shown to significantly reduce the presence of electrocardiogram (ECG) artifacts compared to a distal monopolar reference. However, resting state beta activity is also significantly diminished when employing these techniques. By using Band-Limited Independent Component Analysis (BL-ICA), a type of spatial filter that allows weighting of the noise on each electrode differently, ECG artifacts are easily separated from vECoG recordings. With this cleaning methodology, signals are reconstructed without the ECG component and the reduction in cross-channel correlation is evaluated, as well as the increase in relative entropy between rest and go distributions. To ensure that low-frequency motor features are preserved, beta bursts features are evaluated in both the source space and reconstructed signal space. BL-ICA is an effective technique to remove widespread ECG artifacts while maintaining typical motor-related features in beta band activity.

Authors

Institutions

Publication Details

Journal
Advanced Science
Published
2026-09-04
DOI
https://doi.org/10.1002/advs.76647
Primary Topic
Cardiac electrophysiology and arrhythmias
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

Preserving Motor Features by Alternative Re‐Referencing to Remove Heart Artifact on the Stentrode

Kriti Kacker, Jennifer L. Collinger, David Putrino, Peter E. Yoo et al.
Advanced Science
Cardiac electrophysiology and arrhythmias
article

Preserving Motor Features by Alternative Re‐Referencing to Remove Heart Artifact on the Stentrode

Kriti Kacker, Jennifer L. Collinger, David Putrino, Peter E. Yoo, Douglas J. Weber, Nicholas L. Opie, Ariel K. Feldman, Nikole Chetty, Rahyun Yun, Thomas J. Oxley, James Bennett, Raul G. Nogueira
article en

Abstract

Vascular electrocorticography (vECoG) has shown great promise as a less-invasive alternative to penetrating electrode arrays for neural signal acquisition. This study investigates the signal quality of the Stentrode device, a leading vECoG platform, by contrasting artifact persistence with the preservation of low frequency motor cortical activity. Typical (re-)referencing schemes, including a monopolar stent-mounted reference, a common average reference, and a Laplacian reference, are shown to significantly reduce the presence of electrocardiogram (ECG) artifacts compared to a distal monopolar reference. However, resting state beta activity is also significantly diminished when employing these techniques. By using Band-Limited Independent Component Analysis (BL-ICA), a type of spatial filter that allows weighting of the noise on each electrode differently, ECG artifacts are easily separated from vECoG recordings. With this cleaning methodology, signals are reconstructed without the ECG component and the reduction in cross-channel correlation is evaluated, as well as the increase in relative entropy between rest and go distributions. To ensure that low-frequency motor features are preserved, beta bursts features are evaluated in both the source space and reconstructed signal space. BL-ICA is an effective technique to remove widespread ECG artifacts while maintaining typical motor-related features in beta band activity.

Advanced Science
The Royal Melbourne Hospital (AU), University of Pittsburgh (US), Center for the Neural Basis of Cognition (US), University of Pittsburgh Medical Center (US), Synchronoss (United States) (US), Fluid Synchrony (United States) (US), Carnegie Mellon University (US), Icahn School of Medicine at Mount Sinai (US)
Openalex Percentile: Top 10%
Cardiac electrophysiology and arrhythmias
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.