The realization of a truly autonomous and unobtrusive artificial pancreas has long been hindered by the bulky, rigid mechanical drives of commercial insulin pumps and the physically separated glucose sensing unit. In this study, we bridge this engineering gap using an ultra-compact, wireless theranostic platform that synergizes a 9-ANB-functionalized optical microneedle sensor with a structurally novel electrochemical micropump. By engineering a unique semi-dry sandwich electrode that uses highly porous nickel foam to clamp a localized NaOH-saturated fabric, the system achieves highly efficient electrolytic actuation via predictable gas expansion. This structural paradigm shift enables arbitrary internal layout customization, shrinking the integrated device to overall dimensions of approximately 2 cm in diameter and thickness. Furthermore, the synergistic integration of the actuation module with the optically responsive microneedle array establishes a highly robust closed-loop theranostic cycle. By continuously translating glucose-dependent fluorescence variations into precise dosing commands via a smartphone interface, the platform achieves highly predictable, microliter-scale intervention.

We demonstrate that the system is capable of localizing brain activation mapped to underlying anatomical structures, providing new capabilities for fNIRS for clinical applications in which single-subject specificity is desired. These include many applications for which fMRI is the main diagnostic imaging tool, including assessing the extent of damage after stroke or traumatic brain injury; localization of seizure foci in epilepsy; diagnosis and monitoring of psychiatric disorders such as depression, anxiety, and post-traumatic stress disorder, particularly in response to treatment; and monitoring the progression of neurodegenerative diseases. For glioblastoma, this device could allow for outpatient monitoring of cerebral blood flow such that vascular dysregulation at the site of a resected tumor could be identified and used as a marker for tumor recurrence. If the device is paired with a reconstruction backend that employs a neural network for improved convergence speeds, image reconstruction could be performed in real-time. This could enable an entire class of experiments related to biofeedback that would have very minimal complexity compared to fMRI biofeedback setups.

# Professional Summary AESSI (Around-Ear Silent Speech Interface) represents an innovative advancement in wearable technology designed for cross-language communication without audible vocalization. This research develops a non-invasive device worn around the ear that captures subtle articulatory movements and muscle signals associated with silent speech, enabling users to communicate discreetly across language barriers. The technology utilizes advanced signal processing and machine learning algorithms to interpret the biomechanical patterns of speech production, converting them into intelligible text or audio output. The system demonstrates particular value for accessibility applications, allowing individuals with speech impairments or those in noise-restricted environments to communicate effectively. The around-ear form factor offers practical advantages over traditional brain-computer interfaces while maintaining high accuracy in speech recognition. This development has significant implications for assistive technology, privacy-conscious communication applications, and multilingual interaction scenarios. The cross-language capabilities suggest potential for real-time translation and universal communication platforms, making AESSI a promising tool for diverse professional and personal use cases in an increasingly connected world.

VS3 Medical, Inc. has achieved FDA Breakthrough Device designation for its investigational VS3 system, a neurovascular implant designed to treat pulsatile tinnitus caused by venous sinus stenosis. The self-expanding device is engineered to conform to venous sinus anatomy and provide sufficient radial force to open both intrinsic and extrinsic stenoses, supported by a specialized stent delivery system for precise positioning. Pulsatile tinnitus results from abnormal blood flow in the brain's venous vasculature, typically caused by narrowing of the main drainage sinuses from either external compression or arachnoid granulations. Founded by Dr. Matthew Amans, Professor of Radiology and Neurological Surgery at UCSF, the company views this FDA recognition as a significant step toward improving diagnosis and treatment pathways for patients with this debilitating condition. The designation underscores the clinical importance of addressing the underlying anatomical causes of symptomatic venous sinus stenosis and reflects advances in imaging technology that have enhanced understanding of intracranial venous anatomy.

# Summary This article examines emerging technologies designed to restore vision for the blind, specifically comparing the vOICe system with Neuralink's Blindsight initiative. Rather than oversimplifying complex neurotechnology, the piece emphasizes that meaningful adaptation to visual restoration devices requires substantial user training and cognitive effort. Drawing on Einstein's principle that solutions should be simplified without sacrificing functionality, the article argues that mastering assistive visual technologies parallels learning a foreign language or musical instrument—demanding time, practice, and sustained engagement. The discussion underscores the importance of maintaining user agency throughout the adaptation process. By acknowledging the inherent complexity of neurotechnological interfaces while advocating for thoughtful design, the article provides important perspective on realistic expectations for vision restoration devices. This balanced approach highlights why successful implementation of such technologies depends equally on sophisticated engineering and realistic understanding of the learning curve users will inevitably face.

Closed-loop neuromodulation represents a transformative shift in treating neurological and psychiatric conditions by continuously monitoring neural activity and dynamically adjusting stimulation in real-time, rather than delivering fixed-parameter stimulation. This comprehensive review synthesizes foundational principles, mechanistic underpinnings, and clinical applications of invasive techniques like deep brain stimulation (DBS), non-invasive approaches including transcranial magnetic stimulation (TMS), and peripheral methods. The technology demonstrates superior efficacy, enhanced personalization, and improved safety compared to conventional open-loop paradigms across diverse conditions including epilepsy, major depression, chronic pain, and movement disorders, with emerging exploratory applications in cognitive enhancement for healthy individuals. Enabling technologies—advanced wireless biosensors, AI-driven adaptive algorithms, and novel stimulation modalities—are accelerating clinical translation. However, significant challenges persist, including robust biomarker validation, long-term device stability, and complex ethical considerations surrounding cognitive augmentation. The field represents a fundamental evolution in personalized medicine, grounded in neuroplasticity principles, requiring interdisciplinary collaboration to address implementation challenges and ensure responsible development for clinical and cognitive optimization applications.

Wearable and implantable bioelectronic devices are now used to routinely assess a person’s health and, for some conditions, provide interventions as needed. An ongoing challenge is the power and device size required for wireless communication between devices. Ghanim et al. designed an electronic circuit that emulates the functionality of a nervous system. The researchers were able to remotely trigger electrical stimulation devices through pulsed signals transmitted through body tissue using less power than protocols such as Bluetooth. Implants could be injected using a syringe, and multiple devices could be controlled by using different signal patterns.

For decades, the human brain operated as an entirely closed biological system. Our thoughts, sensory perceptions, and motor commands were confined within our skulls, translated to the physical world solely through the mechanical actuation of muscles and vocal cords. When illness, trauma, or neurological decline severed those pathways, individuals often found themselves trapped, possessing sharp cognitive faculties while lacking any reliable medium to interact with the environment around them. That biological boundary is rapidly dissolving. Brain-computer interfaces, commonly abbreviated as BCIs, have transitioned from theoretical neuroscience experiments into high-bandwidth translation platforms. By creating direct bidirectional communication channels between electrical neural activity and digital processors, BCIs are rewriting the rules of human-machine interaction. The trajectory of this technology promises not only to restore movement and speech to individuals living with severe motor impairment, but ultimately to alter how humans learn, work, and interact with the digital realm.

Endovascular brain–computer interfaces (BCIs) avoid craniotomy but require precise device delivery through anatomically variable cerebral veins. This work presents the first demonstration of in vitro autonomous robotic navigation for endovascular BCI access in the cerebral venous system. Soft Actor-Critic controllers were trained in silico for two sequential tasks spanning the right internal jugular vein to the superior sagittal sinus, using geometric augmentation of one training anatomy. Navigation was evaluated in a training anatomy and an anatomically unseen hold-out model over 250 in silico episodes and five fluoroscopy-guided in vitro robotic runs per task–anatomy condition, comprising 1,000 simulated episodes and 20 physical runs overall. Task recurrent predictors were also evaluated for online identification of impending navigation failure. In silico success rates for Tasks A and B were 85.6% and 98.4% in the training anatomy and 42.0% and 91.6% in the hold-out anatomy, respectively. Fourteen of 20 physical runs were successful (70% overall), including 80% success for Task B in the hold-out phantom. In silico the predictors detected 99.3–100.0% of failures with false-alarm rates of 0.8–6.7%. During in vitro evaluation, predicted risk increased before failed episodes, but elevated probabilities during some successful runs showed reduced calibration after transfer. These results demonstrate the feasibility of autonomous cerebral venous access and show how online failure prediction could support human oversight, while also identifying anatomical generalization and sim-to-real calibration as priorities before preclinical translation.

This work demonstrated that EIS could be used to determine the viability of electrode implanted chronically within a blood vessel. Impedance measurements alone were not observed to be a useful predictor of alterations occurring at the electrode tissue interface. However, measurement of 100 Hz phase angles was in good agreement with the capacitive changes predicted by the ECM and consistent with suggestions that this represents protein absorption on the electrode surface. 100 Hz phase angles stabilized after 8 days, consistent with histologically assessed samples. Significance. These findings demonstrate the potential application of this technology for use as a chronic neural recording system and indicate the importance of conducting EIS as a measure to identify viable electrodes and changes occurring at the electrode–tissue interface.

Stroke is a leading cause of paralysis, most frequently affecting the upper limbs and vocal folds. Despite recent advances in care, stroke recovery invariably reaches a plateau, after which there are permanent neurological impairments. Implantable brain-computer interface devices offer the potential to bypass permanent neurological lesions. They function by (1) recording neural activity, (2) decoding the neural signal occurring in response to volitional motor intentions, and (3) generating digital control signals that may be used to control external devices.

Endovascular stent-electrode arrays provide a minimally invasive approach to BMIs. Stent-electrode placement has been shown to be both efficacious and safe, although further data are necessary to draw comparisons between subdural and epidural electrode measurements given the heterogeneity of the studies included. Greater access to deep-seated brain regions is now more feasible with stent-electrode arrays; however, further validation is needed in large clinical trials to optimize this neural interface. This includes the determination of ideal electrode material type, venous versus arterial approaches, the feasibility of deep brain stimulation, and more streamlined computational decoding techniques.

In this study, a novel approach is demonstrated for fabricating endovascular micro-wire stent electrodes using laser welding and ablation technologies. The method significantly reduces the electrode size, making it suitable for narrower blood vessels. The quantitative results highlight the excellent electrochemical performance of the electrodes fabricated under optimal laser welding parameters, with a 1 kHz impedance of 4117 Ω, a 1 kHz phase of −68.23 degrees, a charge storage capacity (CSC) of 8.745 (mC/cm2), and a charge injection capacity (CIC) of 1.617 ×10−4C/cm2. These results indicate that the electrodes possess excellent stability and suitability for use as neural interfaces in confined vascular environments.

Here we demonstrate the feasibility of chronically recording brain activity from within a vein using a passive stent-electrode recording array (stentrode). We achieved implantation into a superficial cortical vein overlying the motor cortex via catheter angiography and demonstrate neural recordings in freely moving sheep for up to 190 d. Spectral content and bandwidth of vascular electrocorticography were comparable to those of recordings from epidural surface arrays. Venous internal lumen patency was maintained for the duration of implantation. Stentrodes may have wide ranging applications as a neural interface for treatment of a range of neurological conditions.

A novel balloon-in-basket pulsed field ablation (PFA) system integrated with electroanatomical mapping was evaluated for treating atrial fibrillation in a real-world clinical setting. Researchers enrolled 133 consecutive patients with symptomatic paroxysmal or persistent AF undergoing ablation between February 2024 and February 2026. The system achieved acute pulmonary vein isolation (PVI) in 96.2% of cases, with adjunctive posterior wall isolation performed in 25.6% of patients. Mean procedure time was 65.6 minutes, with minimal fluoroscopy exposure at 12.7 minutes. The technology demonstrated excellent safety, with only two periprocedural complications (1.5%), including one femoral arterial pseudoaneurysm and one pericarditis case. Exploratory biomarker analyses revealed no hemolysis-related renal safety concerns. Among 82 patients with at least six months of follow-up, clinically documented atrial arrhythmia recurrence occurred in 14.6%. The findings demonstrate that the balloon-in-basket PFA system offers high acute efficacy, low complication rates, and efficient workflow, with adjunctive lesions appearing feasible without increasing procedural burden or safety risks.

Closed-loop neuromodulation systems represent a fundamental paradigm shift in clinical neuroscience and personalized medicine. This comprehensive survey synthesizes foundational principles, mechanistic underpinnings, and systematic classifications of these advanced systems, which employ real-time feedback mechanisms to dynamically adjust neural stimulation parameters. Unlike traditional open-loop approaches that deliver fixed-parameter stimulation, closed-loop systems leverage advanced wireless biosensors and AI-driven adaptive algorithms to continuously monitor neural biomarkers and optimize therapeutic outcomes. The article covers invasive techniques such as deep brain stimulation, non-invasive modalities including transcranial magnetic stimulation, and peripheral approaches across multiple therapeutic domains including epilepsy, major depression, chronic pain syndromes, and movement disorders. Emerging evidence demonstrates superior efficacy, enhanced personalization, and improved safety profiles compared to conventional paradigms. Beyond clinical applications, closed-loop systems show exploratory potential for cognitive enhancement in healthy individuals. However, significant challenges persist, including robust biomarker validation, long-term device stability, and complex ethical considerations. The accelerating pace of technological innovation is rapidly translating these advances into clinical practice, necessitating interdisciplinary collaboration to overcome remaining obstacles and ensure responsible implementation of this transformative technology.

Endovascular brain–computer interfaces (BCIs) represent a promising approach for restoring communication and motor control in patients with severe paralysis from conditions such as ALS and spinal cord injury. Unlike traditional BCIs requiring craniotomy, endovascular systems deliver electrodes through cerebral blood vessels, though precise navigation through anatomically variable venous pathways remains challenging. Researchers developed the first autonomous robotic navigation system for this application, employing Soft Actor-Critic reinforcement learning controllers trained in simulation to guide catheters from the right internal jugular vein to the superior sagittal sinus. Testing across 1,000 simulated episodes and 20 physical fluoroscopy-guided runs achieved 70% overall success in vitro, including 80% success for the challenging Task B in unseen anatomies. The team also implemented task recurrent predictors achieving 99.3–100% failure detection rates with minimal false alarms. While results demonstrate autonomous cerebral venous access feasibility and highlight how real-time failure prediction could enhance human oversight, the work identifies anatomical generalization and simulation-to-reality calibration as critical priorities for advancing toward preclinical translation and ultimately enabling less-invasive BCI implantation.

In the current phase, it is advisable to temper expectations regarding Elon Musk’s endorsement of these initial clinical trials. As a businessman and the proprietor of Neuralink, Elon Musk has his own vested interests and requirements. He is adept at leveraging his influence to garner attention and potential investments through exaggeration and grandiose displays. However, he has not addressed the potential risks nor outlined strategies to mitigate or minimize them. In our view, the most significant risk is that the advancement of BCI may one day surpass human control. With artificial intelligence (AI) also rapidly progressing,4,5 BCI offers a conduit for AI to interface with the human mind, potentially paving the way for AI to exert control over humans. Therefore, the development of BCI (and AI) is a double-edged sword. While advanced BCI technology undoubtedly holds benefits for human well-being, it is crucial to objectively assess risks and formulate strategies and policies to prevent or mitigate them. Public opinion should not be swayed by a small cohort of individuals who wield cutting-edge technology.

As the power of modern computers grows alongside our understanding of the human brain, we move ever closer to making some pretty spectacular science fiction into reality. It isn't about convenience — for severely disabled people, development of a brain-computer interface (BCI) could be the most important technological breakthrough in decades. Imagine transmitting signals directly to someone's brain that would allow them to see, hear or feel specific sensory inputs. Consider the potential to manipulate computers or machinery with nothing more than a thought. In this article, we'll learn all about how BCIs work, their limitations and where they could be headed in the future.

This document outlines medical billing codes that do not satisfy current payment determination criteria and require careful evaluation before reimbursement. The list encompasses diverse diagnostic and surgical procedures spanning oncology, spine surgery, erectile dysfunction treatments, and cardiovascular risk assessment. Notable entries include COVID-19 antibody testing (code 0224U), which is currently denied due to unclear medical utility of quantitative IgG measurement, and advanced oncology diagnostic tests such as brain spheroid cell culture analysis (0249U) and breast phosphoprotein analysis (0250U) that employ sophisticated laboratory techniques. Surgical procedures listed include spinal fusion and disc arthroplasty procedures with specific anatomical specifications, penile revascularization procedures, and lipoprotein-associated phospholipase A2 (Lp-PLA2) testing for cardiovascular risk stratification. The document directs providers to append modifier code GA when appropriate criteria are met and references associated medical policies for detailed information. This guidance is essential for healthcare organizations and billing professionals to ensure compliance with current payment policies and avoid claim denials.