Brain–computer interfaces (BCIs) are rapidly transitioning from niche clinical tools to powerful technologies with the potential to reshape human–machine interaction, cognitive agency, and social structures. Initially developed to restore communication and motor function in individuals with severe neurological impairments, recent advances have expanded BCI applications into neurorehabilitation, mental health, and commercial domains, raising profound technical, ethical, and societal challenges. Here we critically examine the current state of BCI development, arguing that the field has reached a pivotal inflection point. Beyond engineering performance, unresolved issues, including long-term biocompatibility, decoding reliability, neural data privacy, identity and autonomy, regulatory gaps, and social equity, now constitute the primary barriers to responsible deployment. We contend that technological progress alone is insufficient to ensure beneficial outcomes and that the future trajectory of BCIs will be determined by the integration of robust ethical frameworks, inclusive governance, and long-term societal foresight. By synthesizing recent clinical breakthroughs with emerging ethical and regulatory concerns, we advocate for a precautionary yet forward-looking approach that prioritizes human dignity, safety, and equitable access alongside innovation. The choices made at this juncture will shape whether BCIs ultimately serve as instruments of empowerment or sources of new vulnerability in a deeply interconnected future.

Dementia remains a significant worldwide health concern, characterized by progressive cognitive decline and functional impairment. Brain-computer interface (BCI) technology, which allows direct interaction between brain signals and external devices, has emerged as a cutting-edge tool in the diagnosis, management, and treatment of neurodegenerative diseases. This review seeks to evaluate the existing evidence, basic concepts, and future prospects of BCI in dementia diagnosis, management, and treatment. The review covers various aspects of dementia, including its neurophysiological basis, diagnostic tools, cognitive rehabilitation, neuromodulation, and assistive technologies. Emerging evidence indicates that electroencephalogram-based BCIs could result in small improvements in attention, working memory, and executive functions. Furthermore, P300-based paradigms have shown significant diagnostic potential for identifying early-stage cognitive impairment. The most recent advancements highlight the integration of artificial intelligence (AI)-driven neural decoding and non-invasive closed-loop neuromodulation as high-precision interventions. Despite these developments, widespread clinical implementation is currently hindered by small sample sizes, methodological heterogeneity, and signal-to-noise constraints. While BCI technology is a promising platform for individualized dementia care, further large-scale longitudinal trials and hardware refinements are essential for routine clinical utilization.

Traumatic brain injury (TBI) is a leading cause of morbidity and mortality worldwide, characterized by complex neurological impairments and systemic consequences. The objective of this systematic review is to assess studies on gut microbiota modulation as a therapy in animal TBI models. The review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. To be eligible for inclusion, publications needed to (1) report original research involving preclinical animal subjects; (2) evaluate the impact of TBI on the microbiome; (3) be written in English; and (4) be published in a peer-reviewed journal. All studies reviewed found changes in the gut microbiome following TBI, with similar alterations in bacterial populations observed across the research. Of 125 records, 9 studies (mice/rats; fluid percussion, Controlled Cortical Impact, and weight-drop models) were included after screening. TBI consistently induces dysbiosis, leaky gut, inflammation, and impaired recovery. Microbiota therapies restore homeostasis, reduce neuroinflammation, and improve outcomes. Microbiota-targeted interventions show significant potential in preclinical models of TBI, effectively mitigating dysbiosis and reducing inflammation. However, translating these findings into clinical settings requires further investigation to establish efficacy and safety in human populations.

Background: Obesity is highly prevalent in Mexico and frequently coexists with psychiatric disorders that may influence postoperative outcomes in bariatric surgery candidates.

Materials and methods: We conducted an observational, descriptive, retrospective study including 123 adult patients evaluated by the Psychiatry Service as part of an institutional bariatric surgery protocol at the National Medical Center “20 de Noviembre” between 2020 and 2024. Of these, 117 (95.1%) underwent the surgical procedure; postoperative weight loss and adherence analyses were restricted to operated patients. Psychiatric diagnoses were coded according to ICD-10. Descriptive and inferential statistics were applied; all comparisons were unadjusted.

Results: Psychiatric diagnoses were present in 31.7% of patients. Those with a psychiatric disorder showed significantly lower absolute postoperative weight loss than those without (10.87 kg vs. 20.97 kg; p < 0.001; Cohen's d = 0.80) and a higher prevalence of low adherence (p = 0.047). More than half of patients with a psychiatric history experienced documented postoperative symptom improvement. Given the heterogeneous follow-up duration, the weight loss figures should be interpreted as exploratory.

Conclusion: Psychiatric disorders are common among bariatric surgery candidates at this institution and are associated with reduced postoperative weight loss and lower adherence in unadjusted analyses. Structured psychiatric evaluation should be integrated into bariatric care pathways; confirmatory studies with multivariable adjustment and standardized follow-up periods are needed.

Background: Retinal optical coherence tomography/angiography (OCT/OCTA) provides a noninvasive window into microvascular and neuronal integrity, but its relationship with quantitative magnetic resonance imaging (MRI) markers across cerebrovascular disease subtypes remains unclear. This study aimed to compare retinal OCT/OCTA and quantitative MRI profiles among patients with carotid artery stenosis-associated stroke (CAS), recent small subcortical infarct (RSSI), chronic cerebral small vessel disease (CSVD), and controls, and to assess differences in OCTA–MRI associations.

Materials and methods: This multicenter cross-sectional study included 651 participants (1,257 eyes): 228 controls, 283 CAS, 74 RSSI, and 66 CSVD. Retinal measures included retinal nerve fiber layer and ganglion cell–inner plexiform layer (GCIPL) thickness. OCTA-derived vessel length density (VLD) was quantified in the superficial vascular complex (SVC) and deep vascular complexes (DVC) and choriocapillaris. MRI measures included intracranial volume-normalized gray and white matter volumes, white matter hyperintensity (WMH) burden, and regional brain volumes. Multivariable linear regression and generalized estimating equation models were adjusted for vascular risk factors, with false discovery rate correction.

Results: CAS showed the most pronounced retinal microvascular impairment, with lower VLD across all OCTA layers than controls and RSSI, reduced GCIPL, and lower gray and white matter volumes. All patient groups had greater WMH burden than controls. CAS-related differences remained in sensitivity analyses addressing baseline imbalance and diabetes. SVC VLD showed the most consistent associations in CAS, including a positive association with gray matter volume and inverse associations with total and periventricular WMH. Regional analyses showed broader associations with cortical and subcortical volumes in CAS.

Discussion: Retinal OCTA alterations may provide subtype-relevant information in cerebrovascular disease. The consistent OCTA–MRI associations in CAS may reflect shared vulnerability of retinal and cerebral circulations in large-artery atherosclerosis.

Conclusion: CAS showed marked retinal microvascular rarefaction and consistent associations between retinal VLD and MRI markers. OCTA differences and OCTA–MRI associations were less consistent and less precisely estimated in RSSI and CSVD. Retinal OCTA may offer complementary information for cerebrovascular disease characterization, especially in CAS, but requires further validation.

The transition to the “Fourth paradigm” of data-driven science offers a major opportunity for Alzheimer’s disease (AD) and broader neurodegenerative disease (NDD) research. However, this potential is constrained by a “data void” caused by the long preclinical progression of AD pathology. We argue that the large-scale electroencephalography (EEG), when combined with clinical and biological validation, can provide a scalable functional window onto this gap. Yet, the current EEG data landscape emains fragmented, heterogeneous, and difficult to reuse. This perspective review presents a strategic blueprint to address this deadlock. We first examine existing foundational and AD-focused EEG resources. We then distinguish prospective standardization from retrospective harmonization, arguing that both are required to transform isolated recordings into interoperable and clinically validatable evidence. Furthermore, we analyze how advanced artificial intelligence (AI) architectures, including Transformer-based models, depend on robust data governance and explainable AI (XAI) strategies to avoid “Shortcut Learning” and support biological interpretation. Finally, we propose a collaborative ecosystem designed to ensure Robustness, Interpretability, and Scalability (RIS), linking standardized EEG with longitudinal cohorts, human brain banks, and post-mortem neuropathology. Together, this framework aims to transform EEG from a clinical tool into a scalable engine for discovery in AD and related NDDs.