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A University of Pittsburgh team (Bose et al.) tested the crossmodal congruency effect (CCE) task in 15 able-bodied volunteers to see whether it can quantify how intuitive lower-limb sensory feedback feels. At the knee, the task distinguished more natural pneumatic stimulation from less natural electrical stimulation; at the foot, it could not tell the same stimuli apart. The study was posted to bioRxiv on August 10, 2026. Lower-limb amputees often have balance and gait problems because their prostheses give no somatosensory feedback; electrical-stimulation neuroprostheses can partly restore sensation, but there has been no way to quantify how intuitive that sensation is. The authors stress that external factors affecting the CCE must be identified before it can be used with amputees.

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 The medRxiv preprint has not been peer reviewed.

The FDA has cleared Precision Neuroscience's Layer 7 Cortical Interface to stay implanted for up to 30 days, up from a previous 510(k) limit of 30 minutes of intraoperative use. The longer window opens the door to extended clinical studies and marks an intermediate step toward a permanent implant.

Researchers released a multi-paradigm longitudinal EEG dataset from 24 stroke patients, covering a novel 'sixth-finger' motor imagery paradigm and affected-hand motor imagery. The dataset spans the full pre-training, post-training and follow-up stages and includes raw EEG, preprocessed data and patient clinical information. Preliminary analysis with classical classifiers (CSP+SVM, CSP+LDA) kept average cross-paradigm classification accuracy at roughly 85%–86%.

Researchers evaluated the technical feasibility of a multimodal imaging workflow for deploying Synchron's Stentrode endovascular brain-computer interface in a human head phantom. The workflow — thin-slice CT, transfer of DICOM data to an external core laboratory for target identification and marking, re-import of the marked CT, 3D rotational angiography, and registration with the marked reconstruction and intraoperative fluoroscopy — produced a dataset suitable for anatomical analysis, with the core laboratory marking the intended deployment region and the markings persisting through transfer and re-import, and the annotated CT fusing with 3D angiography without significant misregistration or artifacts. The authors say the workflow can generate intraprocedural targeting guidance for Stentrode deployment, as a preclinical technical validation.

Researchers at the University of Michigan, Ann Arbor have built SpikeCleaner, an algorithm that grades neural units after automated spike sorting, reaching 97% accuracy and a 92% F1 score on single units in benchmarking. It combines spike rate, spike-timing metrics and waveform features to classify units as good, noise or multi-unit activity, a job that otherwise falls to manual curation.

US researchers using intracortical microelectrode arrays identified distinct neural patterns in the motor and somatosensory cortex of patients with spinal cord injury that separately encode the timing and force of grasping, offering new ideas for developing more precise brain-computer interface (BCI) systems.

The Center for Neurotechnology listed nine new papers spanning experimental and computational neuroscience, neural interfaces and neuroethics. The selection includes Smart Dura for multimodal neural recording and modulation, work on transcutaneous spinal-stimulation trials, primate optogenetics, co-adaptive interfaces, motor-cortex activity and participatory neuroethics research.

Researchers at the University of Washington have built mechanically compliant, precision-porous brain implants and tested them in rat brains. At 4 weeks, the porous scaffolds drew less astrocyte encapsulation than solid hydrogel rods, softer hydrogels reduced pro-inflammatory macrophage polarization, and new blood vessels, neuronal markers and neurogenesis appeared inside the pores. The authors present the design as a route to limiting glial scarring and improving regeneration in implant-based central nervous system therapies.

Brown University researchers have posted a preprint proposing Neural SS-DMP, a movement decoder that does not output hand coordinates directly: it first infers a compact set of parameters describing the motion the user intends, then hands them to a generator governed by physical dynamics that draws the full trajectory, so decoded output stays within motion a body can actually produce. The generator is tuned per person, blending general movement dynamics with the individual's own patterns estimated from training data, and the authors say that across two kinds of neural recording the model came out ahead of strong existing methods on both accuracy and trajectory smoothness while holding performance longer on recordings made after training ended. The study is a preprint, has not been peer reviewed, and its results come entirely from offline data rather than live control.

The VA Office of Research and Development is advancing a high-performance implanted brain-computer interface (BCI) to improve independence for Veterans and others with tetraplegia or inability to speak due to ALS, spinal cord injury, or stroke. The project enhances deep learning decoders and multi-state gesture decoding, deployed on a battery-powered mobile BCI device for independent home use of computers and touch-enabled devices. Accuracy and usability will be evaluated in participants already enrolled in the BrainGate investigational clinical trial.

The study uses spatial proteomics to assess tissue around non-functional intracortical microelectrodes implanted for four weeks in mice, measuring neuronal integrity, immune-cell activation and local cytokine expression around probes coated with drug-loaded, controlled-release titanium dioxide nanotube array (TNA) coatings. The authors note that blood-brain barrier disruption can translocate gut-derived bacteria to the implant site and sustain chronic inflammation, and that the TNA coating's therapeutic loading and controlled release further damp residual neuroinflammation. They conclude that TNA offers a multifunctional, tunable interface for locally regulating the neuroimmune microenvironment, a step toward long-term reliable intracortical recordings.

Researchers evaluated ruthenium-oxide-coated amorphous silicon-carbide microelectrode arrays during 25 weeks of intracortical microstimulation in rodents. Perception thresholds stabilized at about 0.4 nC per phase per electrode by week nine, behavioral performance remained around 91%, and reliable sensation persisted through week 25.

UC Davis researchers trained a transformer-based speech decoder across six people with intracortical BCIs. The pooled model cut relative word error rates by more than 50% on average compared with subject-only models and, after fine-tuning on fewer than 200 sentences from an unseen user, achieved a word error rate below 7%. The bioRxiv preprint has not been peer reviewed.

Surgeons in Michigan have implanted Paradromics' Connexus brain-computer interface in a patient with motor neuron disease who had lost most of her ability to speak. Connexus records from individual neurons through 421 microelectrodes seated 1.5 millimeters into the motor cortex; the signals pass to a transceiver in the patient's chest, where AI converts them into text on a screen. Austin, Texas-based Paradromics received FDA approval in the fall of 2025 to begin the clinical trial.

The University of Texas at Austin has registered a study on ClinicalTrials.gov to explore whether an EEG-based brain-computer interface (BCI) decoding the P300 event-related potential in real time, combined with non-invasive interventions such as mindfulness relaxation or transcranial electrical stimulation, can enhance attention and memory neural markers—proxies for cognitive reserve—in healthy older adults and those with mild cognitive impairment (MCI). The trial is recruiting and aims to test whether targeted modulation of attention-related brain activity can support cognitive reserve.

UC Irvine researchers tested an EEG category-decoding task in 30 participants viewing pictures and words from five semantic groups. All picture-category pairs were statistically separable, but only one word-category pair was; parietal and left-temporal electrodes contributed more to picture decoding than frontal and right-temporal sites. The bioRxiv preprint has not been peer reviewed.

Researchers report a preprint, posted to arXiv on July 25, 2026 and not yet peer reviewed, that contrasts Bayesian complete-pooling models against frequentist baselines for cross-subject, left-hand versus right-hand motor imagery EEG classification across 20 datasets. Six frequentist pipelines were each paired with an analogous Bayesian pipeline sharing identical feature engineering and fit via Markov chain Monte Carlo posterior sampling. Bayesian complete-pooling produced statistically but not practically significant improvements in reliability and increased predictive uncertainty, with no significant differences in Brier score, resolution, or discrimination. Bayesian pipelines consumed roughly 13 times more energy than their frequentist counterparts, and the authors conclude that complete pooling alone offers limited practical benefit, pointing to partial pooling as a more promising direction.

A registry-based cross-sectional analysis found only 11 pediatric brain-computer interface (pBCI) clinical trials worldwide, spanning 7 countries. Eight evaluated non-implanted devices and 3 evaluated implanted systems. Non-implanted trials had a median enrollment of 29 participants and median duration of 56.0 days; implanted trials had a median enrollment of 8 and median duration of 365.3 days. Only 4 studies enrolled exclusively pediatric participants; the rest recruited both children and adults. The authors conclude that current pBCI research is limited in scope and that children may be inadequately prioritized.

Placing electrodes on the brain's surface rather than inserting them into tissue is the key difference between Precision Neuroscience's approach and the BrainGate approach Donoghue pioneered. The New York-based company develops minimally invasive, safely removable, high-bandwidth BCIs; its first system, Layer 7, is aimed at people with ALS, spinal cord injury and brainstem stroke, a population the company estimates at 315,000 in the US. The company says its Layer 7 cortical surface array has been implanted in nearly 100 patients at several leading academic medical centers, that it has raised $180 million from investors, and that it has received FDA 510(k) clearance. Donoghue, a professor emeritus at Brown University, will advise on device design, signal decoding and clinical strategy as the company pushes ahead with a long-term implant study and commercial launch.

The study shows mouse primary motor cortex encodes locomotion speed through a sigmoidal state-transition mechanism carried by two functionally distinct spiking populations, a framework that also extends to local field potential (LFP) band power. Using chronic 32-channel laminar arrays in 8 mice, the team recorded 5,889 single units across 384 channels and clustered them into speed-positively related (70.8%) and speed-inversely related (29.2%) groups sharing a speed threshold of about 2.3 m/min. The minority speed-inversely related population decoded speed more accurately via inverse-sigmoid transformation, generalizing across animals. The authors say the findings point toward stable, calibration-light brain-machine interface design.

A post from SpikeGadgets surveys how far multichannel electrophysiology has scaled: its Modular Stacking Headstage supports chronic recording of 1,024 channels across 10 brain regions; the University of Pittsburgh's MePhys platform uses 992 electrode contacts to cover an entire macaque hemisphere; and a Rice University preprint describes a custom ASIC that supports 5,376 simultaneous recording channels.

Researchers at the Center for Neurotechnology at the University of Washington recorded from two male monkeys with high-density laminar microelectrode arrays and found that reaching-related activity in frontal motor cortex is unevenly distributed both across the cortical surface and with depth. Target-direction information varied sharply between neural populations, but the amount of task information a population carried predicted which populations shared similar temporal dynamics. The authors say the pattern should inform where electrodes are placed in future brain-computer interface implants.

An early feasibility study followed five people with spinal cord injury, each implanted with two Blackrock NeuroPort arrays in somatosensory cortex. Across two to 10 years of implantation, more than 168 million intracortical stimulation pulses were delivered over 27 combined implant-years without a serious adverse event or direct harm to electrode health. An average of 64% ± 13% of electrodes still evoked touch, including 60% after 10 years in one participant.

Researchers decoded 15 semantic categories from sEEG high-gamma activity in epilepsy patients at 29.8% accuracy (chance 6.7%), supporting semantic decoding feasibility for language BCIs. Preprint; not yet peer-reviewed.

Carnegie Mellon University researchers report a sensory-guided joint learning framework that pairs human motor learning with adaptive machine learning to train motor imagery BCI users. Across 31 BCI-naive participants, average online discrete accuracy was 86.0% in one dimension and 77.5% in two, with continuous control accuracy at 77.5% and 66.9% respectively; tactile guidance reduced how much users had to explore and accelerated neural adaptation, while sample reweighting kept decoder updates aligned with the learner's own trajectory. The authors frame the approach as a shift from passive calibration to active human-machine joint learning; the study appears in Nature Communications.

University of Washington Seattle researchers combine optogenetic stimulation with micro-ECoG in a semi-chronic implant, enabling stable causal connectivity measurement in macaques over weeks to years.

UC Riverside researchers propose a theoretical framework explaining why mesoscale temporal integration is often optimal for information representation in neural decoding.