Papers

Researchers at Kunming University of Science and Technology reviewed the mechanisms and outcome evaluation of neurofeedback for post-traumatic stress disorder. They compared EEG, real-time functional magnetic resonance imaging and functional near-infrared spectroscopy in feedback targets, spatiotemporal resolution and clinical applicability. Neurofeedback provides real-time information about brain activity to guide patients in regulating abnormal neural patterns. Using clinical scales, neurophysiological measures and functional recovery indicators, the review discusses its clinical position relative to first-line treatments and potential synergy with psychological interventions. The authors identify inadequate control designs and non-standardized training parameters as ongoing limitations; therapeutic potential should not be treated as established efficacy.

A patient with chronic complete spinal cord injury improved from AIS A to AIS C and regained partial voluntary movement after one year of combined neuromodulation and conventional rehabilitation. The 53-year-old man had a T9 injury and received sequential spinal cord electrical stimulation, BCI training, motor cortex stimulation, and peripheral magnetic stimulation of both iliopsoas muscles, alongside 12 months of rehabilitation. His left lower limb motor score rose from 0 to 6, spontaneous defecation and penile erection returned, and his neuropathic pain score fell from 8 to 0. This uncontrolled case suggests a possible association with functional recovery but cannot distinguish the contributions of individual interventions or exclude spontaneous neurological recovery.

Running a motor-imagery BCI while transcranial alternating current stimulation (tACS) is switched on has been difficult, because stimulation artifacts swamp the brain rhythms the decoder relies on and push accuracy close to chance. In a controlled test with 14 healthy participants, a real-time spatial filtering pipeline combining spatio-spectral decomposition with beamforming held accuracy at 76 ± 9% during stimulation, while a standard Laplacian filter managed only 58 ± 9%. That makes closed-loop "stimulate while reading" operation feasible at the signal level; whether it actually improves BCI performance or produces neuroplastic changes, the paper explicitly leaves to future research.

The study was published in Journal of neural engineering on August 13, 2026, presenting the first strength-duration characterization of cortical evoked potentials elicited by endovascular stimulation adjacent to the cerebellum. The authors note that electrical stimulation and neural recording underpin neural prostheses for restoring function and treating neurological disorders, but that clinical adoption is limited by the invasiveness of implantation, while the Endovascular Neural Interface offers an alternative by accessing intracranial targets through the cerebral vasculature. A polymer-based stent-electrode array was deployed into the left transverse sinus of an ovine model, and biphasic current pulses targeting the cerebellum were delivered via the stent electrodes while a subdural electrocorticography grid recorded cortical responses. Endovascular stimulation consistently evoked time-locked cortical potentials with early and late components at approximately 40 ms and 100 ms post-stimulation, and impedance monitoring confirmed electrode functionality and stability throughout. Strength-duration analysis revealed rheobase and chronaxie values, providing a quantitative basis for parameter selection and comparison with established intracranial stimulation modalities.

Baylor College of Medicine researchers analyzed more than 200 hours of intracranial recordings from eight patients with treatment-resistant obsessive-compulsive disorder, five of whom also had bilateral orbitofrontal ECoG electrodes. Neural signals alone did not decode symptom severity or momentary distress above chance; adding facial and speech features raised performance to R=0.73 for severity and R=0.34 for distress. The medRxiv preprint has not been peer reviewed.

Brain-computer interfaces already help restore movement and communication, but attention and memory are a different problem: motor and language control rest on relatively localized, stable neural representations, while cognition is spread across brain networks and changes quickly. The review argues that neuromodulation, long used in neurological and psychiatric therapy and now applied causally to cognitive circuits, can complement decoding. Fold signal acquisition, algorithmic analysis and stimulation feedback into an adaptive closed loop, it suggests, and cognitive BCIs might restore mental function and become the basis for neurotherapeutics that monitor and shape cognition in real time. The article reports no new trial data.

Nova Southeastern University researchers combine intracranial ECoG network features with a support vector machine and Bayesian updating for real-time continuous seizure risk forecasting.