Brain-computer interface technology for chronic pain management

Introduction Chronic pain remains inadequately managed by pharmacological and interventional therapies, which carry risks including opioid-related complications and limited long-term efficacy. Brain-computer interfaces (BCI) have emerged as a non-pharmacological therapeutic approach, most commonly implemented using noninvasive modalities such as scalp EEG or fMRI, that aims to target neural activity patterns associated with chronic pain.Areas covered This review examines the principles underlying BCI systems and their application in chronic pain, including EEG-based neurofeedback targeting oscillatory activity, infraslow-frequency neurofeedback, a theta-controlled vibrotactile BCI, real-time fMRI-based neurofeedback, and emerging closed-loop neuromodulation systems. Advantages, limitations, and future directions are discussed.Expert opinion BCI technology represents a promising, but still early-stage, approach for chronic pain management. Clinical translation will depend less on decoding accuracy than on addressing regulatory and reimbursement barriers, conducting adequately powered, sham-controlled trials, and implementing patient stratification. Convergence with artificial intelligence and closed-loop neuromodulation is promising, but algorithmic sophistication should not be equated with clinical applicability. Wearable platforms raise data privacy and transparency concerns. BCIs are likely to be adjuncts within multimodal pain management, not replacements for existing treatments. Preliminary evidence supports feasibility, but adequately powered, sham-controlled trials are needed to establish treatment-specific and durable efficacy.

Authors

Institutions

Publication Details

Journal
Expert Review of Neurotherapeutics
Published
2026-10-29
DOI
https://doi.org/10.1080/14737175.2026.2752959
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Brain-computer interface technology for chronic pain management

Nabi Rustamov
Expert Review of Neurotherapeutics
EEG and Brain-Computer Interfaces
article

Brain-computer interface technology for chronic pain management

Nabi Rustamov
article en

Abstract

Introduction Chronic pain remains inadequately managed by pharmacological and interventional therapies, which carry risks including opioid-related complications and limited long-term efficacy. Brain-computer interfaces (BCI) have emerged as a non-pharmacological therapeutic approach, most commonly implemented using noninvasive modalities such as scalp EEG or fMRI, that aims to target neural activity patterns associated with chronic pain.Areas covered This review examines the principles underlying BCI systems and their application in chronic pain, including EEG-based neurofeedback targeting oscillatory activity, infraslow-frequency neurofeedback, a theta-controlled vibrotactile BCI, real-time fMRI-based neurofeedback, and emerging closed-loop neuromodulation systems. Advantages, limitations, and future directions are discussed.Expert opinion BCI technology represents a promising, but still early-stage, approach for chronic pain management. Clinical translation will depend less on decoding accuracy than on addressing regulatory and reimbursement barriers, conducting adequately powered, sham-controlled trials, and implementing patient stratification. Convergence with artificial intelligence and closed-loop neuromodulation is promising, but algorithmic sophistication should not be equated with clinical applicability. Wearable platforms raise data privacy and transparency concerns. BCIs are likely to be adjuncts within multimodal pain management, not replacements for existing treatments. Preliminary evidence supports feasibility, but adequately powered, sham-controlled trials are needed to establish treatment-specific and durable efficacy.

Expert Review of Neurotherapeutics
National Institutes of Health (US), Howard University (US)
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