Decoding motor responses from the EEG during altered states of consciousness induced by propofol
Y. Blokland, J. Farquhar, J. Lerou, Jo Mourisse, G. Scheffer, G. Geffen, Loukianos Spyrou, J. Bruhn
Journal of Neural Engineering February 9, 2016 DOI: 10.1088/1741-2560/13/2/026014 via Semantic Scholar
Summary
AI-generated from the abstractA brain-computer interface (BCI) can detect movement attempts from EEG signals with high accuracy even under propofol sedation. At a propofol concentration of 0.5 μg ml⁻¹, mean classification accuracy was 85% (95% CI 81%–89%), and a classifier trained before sedation and tested during sedation achieved 83% (79%–88%). At 1.0 μg ml⁻¹, accuracies were 81% (76%–86%) and 72% (66%–79%), respectively. In four subjects at the highest concentration, movement-related brain responses largely diminished and transfer classification accuracy was not significantly above chance; these subjects showed slower, more erratic task responses, indicating an altered state of consciousness. The findings suggest BCI technology could detect intra-operative awareness, but the relationship between motor responses and consciousness requires further investigation.
Study at a glance
| Characteristics | Observational cohort Peer reviewed |
|---|---|
| Sample size | 12 |
| Population | Healthy subjects |
| Intervention | Propofol |
| Dose | 0.5 μg ml⁻¹ and 1.0 μg ml⁻¹ effect-site concentrations |
| Keywords | Medicine Physics Psychology |
| Key finding | A movement-based BCI can classify movement attempts from EEG with high accuracy at propofol concentrations up to 1.0 μg ml⁻¹, but at higher concentrations some subjects show diminished movement-related brain responses and chance-level classification. |
Abstract
Objective. Patients undergoing general anesthesia may awaken and become aware of the surgical procedure. Due to neuromuscular blocking agents, patients could be conscious yet unable to move. Using brain–computer interface (BCI) technology, it may be possible to detect movement attempts from the EEG. However, it is unknown how an anesthetic influences the brain response to motor tasks. Approach. We tested the offline classification performance of a movement-based BCI in 12 healthy subjects at two effect-site concentrations of propofol. For each subject a second classifier was trained on the subject’s data obtained before sedation, then tested on the data obtained during sedation (‘transfer classification’). Main results. At concentration 0.5 μg ml−1, despite an overall propofol EEG effect, the mean single trial classification accuracy was 85% (95% CI 81%–89%), and 83% (79%–88%) for the transfer classification. At 1.0 μg ml−1, the accuracies were 81% (76%–86%), and 72% (66%–79%), respectively. At the highest propofol concentration for four subjects, unlike the remaining subjects, the movement-related brain response had been largely diminished, and the transfer classification accuracy was not significantly above chance. These subjects showed a slower and more erratic task response, indicating an altered state of consciousness distinct from that of the other subjects. Significance. The results show the potential of using a BCI to detect intra-operative awareness and justify further development of this paradigm. At the same time, the relationship between motor responses and consciousness and its clinical relevance for intraoperative awareness requires further investigation.