Motor cortex-based intracortical BCI performance is robust to changes in attentional load during dual-tasking

OBJECTIVE: High performance intracortical brain-computer interface (iBCI) control has been demonstrated in research settings, but performance can still vary within and between sessions. One potential source of this variability is the change in attentional load that comes from processing naturally occurring distractors such as thoughts, sounds, fatigue, or pain. To improve the consistency of iBCI performance in real-world environments where this sort of multi-tasking is inevitable, we must understand how shifts in attention can impact performance. Approach: Here we examined the effect of attentional load on iBCI performance and movement-related neural activity using a 2D cursor translation + click iBCI task paired with an N-Back working memory task to increase attentional load during dual-task performance. Two participants (P2 and P4) with tetraplegia completed the study while enrolled in a long-term clinical trial of an iBCI device. Common neural correlates of attention (theta and alpha band power) were measured with simultaneously recorded scalp electroencephalography (EEG). Main Results: While the EEG metrics and difficulty ratings suggested increased attentional load during dual-tasking, iBCI performance was quite robust across the various dual-tasking conditions. One participant, P2, experienced a small but significant increase in trial completion time and normalized path length during the mild attentional load condition compared to the moderate load condition. Signal quality differences between the two participants may have impacted the results, as P2 had lower signal quality and was therefore likely more vulnerable to attentional load. P4's higher signal quality likely allowed him to accommodate increased attentional load without a drop in performance. Significance: Overall, iBCI performance appears to be robust to attentional load, but the complex trends observed here reflect a need for continued investigation of BCI use under different cognitive states to elucidate potential challenges and compensatory mechanisms across participants. .

Authors

Institutions

Publication Details

Journal
Journal of Neural Engineering
Published
2026-10-29
DOI
https://doi.org/10.1088/1741-2552/aebb65
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Motor cortex-based intracortical BCI performance is robust to changes in attentional load during dual-tasking

Chloe Shearer, Murat Akçakaya, Jennifer L. Collinger, Douglas J. Weber et al.
Journal of Neural Engineering
EEG and Brain-Computer Interfaces
article

Motor cortex-based intracortical BCI performance is robust to changes in attentional load during dual-tasking

Chloe Shearer, Murat Akçakaya, Jennifer L. Collinger, Douglas J. Weber, Edgar Canario, Steven M. Chase
article en

Abstract

OBJECTIVE: High performance intracortical brain-computer interface (iBCI) control has been demonstrated in research settings, but performance can still vary within and between sessions. One potential source of this variability is the change in attentional load that comes from processing naturally occurring distractors such as thoughts, sounds, fatigue, or pain. To improve the consistency of iBCI performance in real-world environments where this sort of multi-tasking is inevitable, we must understand how shifts in attention can impact performance. Approach: Here we examined the effect of attentional load on iBCI performance and movement-related neural activity using a 2D cursor translation + click iBCI task paired with an N-Back working memory task to increase attentional load during dual-task performance. Two participants (P2 and P4) with tetraplegia completed the study while enrolled in a long-term clinical trial of an iBCI device. Common neural correlates of attention (theta and alpha band power) were measured with simultaneously recorded scalp electroencephalography (EEG). Main Results: While the EEG metrics and difficulty ratings suggested increased attentional load during dual-tasking, iBCI performance was quite robust across the various dual-tasking conditions. One participant, P2, experienced a small but significant increase in trial completion time and normalized path length during the mild attentional load condition compared to the moderate load condition. Signal quality differences between the two participants may have impacted the results, as P2 had lower signal quality and was therefore likely more vulnerable to attentional load. P4's higher signal quality likely allowed him to accommodate increased attentional load without a drop in performance. Significance: Overall, iBCI performance appears to be robust to attentional load, but the complex trends observed here reflect a need for continued investigation of BCI use under different cognitive states to elucidate potential challenges and compensatory mechanisms across participants. .

Journal of Neural Engineering
University of Pittsburgh (US), Carnegie Mellon University (US)
U.S. Department of Defense, University of Pittsburgh, National Institutes of Health, National Institute of Neurological Disorders and Stroke
Good health and well-being
Openalex Percentile: Top 14%
EEG and Brain-Computer Interfaces
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.

Laika access coming soon