Journal of Neural Engineering
June 10, 2025
Daniel Polyakov, P A Robinson, Eli J Müller et al.
2 citations
A computational method uses a simplified brain model fitted to a patient's EEG power spectrum to design personalized electrical stimulation signals. In computer simulations, these signals induce healthy-like brain activity patterns in models of people with disorders of consciousness. When the model's parameters were near a stability boundary, stimulation caused a lasting change in activity beyond the stimulation period. The approach may activate plasticity mechanisms during long-term treatment, potentially leading to sustained improvements. Further clinical adjustments and validation are needed, but the method holds promise for improving therapeutic outcomes in disorders of consciousness and may extend to other neurological conditions.
Journal of Neural Engineering
June 9, 2025
Guangying Cui, Yi Yuan, Qiaoxuan Wang et al.
Ultrasound stimulation applied to the thalamus before or after propofol anesthesia shortened the time to recovery of consciousness in mice. Mice receiving stimulation before anesthesia regained consciousness in about 20 minutes, and those stimulated after anesthesia in about 18 minutes, compared to about 33 minutes for sham-treated mice. The stimulation directly activated neural activity in the paraventricular thalamus and indirectly in the prefrontal cortex in the 60-100 Hz frequency band. Higher correlations in neural activity between these two brain regions were observed in the 8-13 Hz band, suggesting that both structures contribute to the transition of consciousness and can be modulated by transcranial ultrasound.
Journal of Neural Engineering
April 11, 2025
Rick Evertz, Andria Pelentritou, John Cormack et al.
Resting EEG activity typically resembles a filtered random process, and alpha band (8-13 Hz) oscillations can be modeled as independent, stochastically driven relaxation oscillators. This study tested whether changes in alpha band power and spectral slope during anesthesia with xenon and nitrous oxide—both NMDA receptor antagonists—could be explained by alterations in the distribution of alpha band damping rates. In participants receiving step-level increases of xenon (n=24) or nitrous oxide (n=20), both agents produced dose-dependent reductions in alpha power and spectral slope (15-40 Hz), accounted for by increased mean alpha band damping.
Journal of Neural Engineering
December 22, 2025
Angeliki-Ilektra Karaiskou, Carolina Varon, Cem Ates Musluoglu et al.
Combining spatial and spectral alignment of EEG signals improves the classification of meditation versus rest states in new subjects without retraining. The Riemannian Space Data Alignment (RSDA) method adjusts brain activity patterns across electrodes, while Convolutional Monge Mapping Normalization (CMMN) aligns brain rhythms across frequencies. Together, they raised leave-one-subject-out classification accuracy to 66.6%, compared to 55.7% for non-aligned data and 59.6% for z-score normalization alone. Theta, Alpha, and Beta frequency bands contributed consistently, and Frontopolar and Temporal brain regions were key for distinguishing mental states. This approach offers a practical step toward calibration-free neurofeedback systems.
Journal of Neural Engineering
July 3, 2020
Julien Modolo, Mahmoud Hassan, Giulio Ruffini et al.
Conscious perception involves large-scale, coordinated activation of distant brain regions, a process called ignition or integration. Combining a magnetically-induced phosphene perception task with electroencephalography, functional cortical networks were identified using graph theory. Conscious phosphene perception activated frequency-specific networks, each linked to a particular spatial scale of information processing. Integration increased within an alpha-band functional network, while segregation changed in the beta band. These findings confirm the key role of integration processes for conscious perception in humans and bring evidence for the functional role of distinct brain oscillations.
Journal of Neural Engineering
February 9, 2016
Y. Blokland, J. Farquhar, J. Lerou et al.
A 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.