Noninvasive brain stimulation (NIBS) has emerged as a transformative tool in both cognitive neuroscience research and the treatment of a growing range of neuropsychiatric conditions. This commentary, based on the 2025 H. Houston Merritt Lecture, explores how NIBS can be applied within a translational cognitive neuroscience framework that bridges theoretical models of cognitive function with targeted neural interventions. Drawing on over 15 years of research, the major focus of this piece is on the use of transcranial magnetic stimulation (TMS) to characterize and enhance language function in persons with aphasia (PWA). A significant body of work has examined the role of the right hemisphere, particularly the right pars triangularis, which may exert a maladaptive influence within reorganized language networks in many PWA. Inhibitory TMS targeting this region has been shown to produce both transient and sustained improvements in language performance. Key predictors of response to TMS include the characteristics of participants' language deficits and genetic differences that influence neuroplasticity. Network neuroscience approaches can also enhance predictive accuracy by revealing how individual variations in brain structure influence stimulation outcomes. While TMS remains the most extensively studied NIBS modality, transcranial electrical stimulation is gaining momentum, with promising results in both poststroke and primary progressive aphasia. Emerging modalities such as focused ultrasound and transcranial temporal interference stimulation are also on the rise as tools for enhancing brain performance. However, the expanding use of NIBS also raises ethical considerations that must be addressed to ensure its equitable and responsible deployment. Ultimately, NIBS represents a powerful convergence of neuroscience and technology, offering renewed hope for restoring cognitive function in individuals affected by neurologic disease.

This article presents a conceptual review and theoretical synthesis of the relationship between music, language, and early childhood development. Early development unfolds through the interaction of perception, movement, social exchange, and culture; within this process, music and language operate as two highly structured auditory systems whose rhythmic, prosodic, and phonological regularities shape how children perceive, anticipate, and produce meaning. Drawing on research in cognitive neuroscience, developmental psychology, and music cognition, the article examines evidence that these domains rely on partially overlapping neural resources, particularly in temporal processing, prosodic organization, and aspects of syntactic integration. Using Patel’s OPERA framework (Overlap, Precision, Emotion, Repetition, Attention) as its central interpretive lens, the article argues that structured vocal activities may be understood as a pedagogically organized context for supporting core language-related capacities in young children, including phonological awareness, prosodic sensitivity, articulatory control, and verbal fluency. Rather than presenting new experimental data, the study synthesizes existing theoretical and empirical literature in order to clarify how musically guided vocal practice can be aligned with linguistic objectives in early educational settings. The discussion also considers the contribution of music to emotional regulation, social attunement, and affective engagement, all of which influence communicative development in early childhood. The article concludes that when musical activities are intentionally mapped onto language-learning aims, they can be interpreted not merely as enrichment practices, but as structured, potentially accessible tools for supporting early language development within educational and developmental frameworks.

Response inhibition (RI), the ability to suppress a prepotent or ongoing action in response to sensory information, is a core control function that supports adaptive behaviour in everyday life, sport, and rehabilitation. Although RI has been widely studied in cognitive neuroscience and clinical research, reviews have rarely focused specifically on how RI relates to physical activity. This Mini Review addresses this gap by integrating three strands: (i) conceptual foundations of RI including neural mechanisms supporting proactive and reactive inhibition, (ii) elite athletes as a model of long-term adaptation, and (iii) exercise-induced modulation of RI. We first outline the distinction between proactive and reactive inhibition and summarise representative behavioural paradigms for their assessment. We then review converging evidence implicating cortico-basal ganglia circuit in stopping, highlighting candidate pathways that may differentially support anticipatory and stimulus-driven control. Building on this mechanistic framework, we discuss athlete research as a natural model for understanding experience-dependent changes in RI, and we summarise evidence that acute exercise can transiently modulate inhibitory performance, with implications for ageing and rehabilitation. By synthesising definitions, neural substrates, adaptive models, and exercise effects, we aim to advance a practical and evaluatable framework for the assessment and targeting of RI in sport, clinical rehabilitation, and daily functioning.

Epistemic emotions, including curiosity, interest, and surprise, play a crucial role in learning and cognitive processes by bridging motivation and knowledge acquisition. The Magic Curiosity Arousing Tricks (MagicCATs) dataset, comprising 166 magic trick video clips, provides a standardized tool for studying these emotions in experimental settings. This study provides normative ratings for the dataset within an Italian context, based on a sample of 654 participants aged 18-86. Participants evaluated thevideos based on clarity, curiosity, interest, surprise, and confidence in solving the trick, using both binary and Likert scales. Rigorous data screening ensured integrity, enhancing the reliability of the findings. The dataset's ecological validity, dynamic stimuli, and capacity to elicit multiple epistemic emotions offer advantages over traditional methods. By contextualizing MagicCATs within an Italian framework, this study advances the investigation of epistemic emotions by supporting their simultaneous assessment across a broad adult age range. Applications include experimental psychology, neuroscience, and education, with potential implications for mental health and age-related cognitive research. Data and resources are available for replication and further exploration.

Recent advancements in cognitive impairment research have led to significant progress. Electroencephalography (EEG)-based cognitive state identification can detect early cognitive decline in the elderly, providing a critical window for intervention. As cognitive function worsens, neural activity patterns in the brain also change. Functional connectivity between brain regions, a key indicator of synchronized neural activity, is widely used to reveal brain network characteristics under different cognitive states. In this study, we introduce a novel framework, PowerSyncNet, based on functional connectivity to identify cognitive states. PowerSyncNet mainly consists of three modules. The Channel-Pair Feature Sequences Builder extracts features that characterize functional connectivity across different frequency bands. The Encoder4Band module captures temporal-frequency representations that reflect cognitive states and combines cross-band information to improve feature clarity. The Classifier then determines the corresponding cognitive states. We tested PowerSyncNet on the publicly available Chung-Ang University Hospital EEG (CAUEEG) dataset and our own collected Emotion and Cognition EEG (ECED) dataset. Results show that PowerSyncNet has superior cognitive identification capabilities compared with existing deep learning frameworks, facilitating early assessment and timely intervention for patients with cognitive impairment.

In pure coordination games, players aim to give the same response without communication. Cognitive science research has focused on the reasoning and common knowledge necessary as the background conditions for coordination, with less attention paid to the challenge of intuiting responses on which coordination might be possible. Most studies have examined coordination within university samples from a single country, and so the extent of the challenge of coordinating between heterogeneous groups of people may have been underestimated. We conducted three empirical studies (two preregistered) with participants from the United Kingdom, South Africa, and Chile, plus a globally distributed sample (total N = 520). Without communicating, participants were asked to coordinate on answers to simple questions such as "name a city." All groups coordinated at rates far above chance but often coordinated on different responses. Study 1 showed that participants from one group could nevertheless anticipate the responses of another group, while Studies 2 and 3 showed that participants could coordinate with a partner from a different group. Crucially, between-group partners most often coordinated on new responses that were rarely considered for within-group coordination, providing the strongest evidence to date to support Schelling's claim that coordination requires distinctive reasoning, beyond primary and secondary salience. These findings provide evidence that coordination decisions are variable and flexible, resulting in accurate adaptations to achieve coordination. Where previous work has focused predominantly on the forms of reasoning that support coordination, the present findings suggest that it is equally important to examine the content of coordination solutions. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

People often favour information aligned with their ideological motives. Can our tendency for directional motivated reasoning be overcome with cognitive control? It remains contested whether cognitive control processes, such as cognitive reflection and inhibitory control, are linked to a greater tendency to engage in politically motivated reasoning, as proposed by the "motivated reflection" hypothesis, or can help people overcome it, as suggested by cognitive science research. In this pre-registered study (N=504 UK participants rating n=4963 news messages), we first provide evidence for motivated reasoning on multiple political and non-political topics. We then investigated the associations of the two cognitive control variables cognitive reflection and inhibitory control with motivated reasoning. We find that associations between cognitive control processes and motivated reasoning are likely small. On political topics specifically, we find that a negative association with cognitive reflection is more likely than a positive association. This finding is contrary to predictions from the popular motivated reflection hypothesis. Results for inhibitory control are inconclusive. We discuss how these findings relate to interdisciplinary literature from cognitive and political psychology.

This study aims to construct a conceptual model of self-efficacy from the perspective of the Qur’an, positioning spiritual values as the foundational elements in shaping personal belief and confidence. In contrast to established Western psychological frameworkssuch as Bandura’s model, which emphasizes cognitive, social, and affective dimensionsthis research proposes a Qur’anic self-efficacy framework rooted in tawhid (monotheism), tawakkul (reliance on God), and belief in divine intervention as core components of human agency. Employing a qualitative grounded theory approach and thematic Qur’anic exegesis (tafsir maudhu‘i), the study analyzed selected Qur’anic verses through open, axial, and selective coding. The analysis identified 19 key verses that form the basis of three interconnected dimensions of Qur’anic self-efficacy: (1) Personal efficacy, which instills a transcendent belief that ease accompanies hardship (Q.S. Al-Inshirah: 5); (2) Behavioral efficacy, which links persistent effort (mujahadah) to divine guidance (Q.S. Al-‘Ankabut: 69); and (3) Spiritual efficacy, affirming that each soul is only burdened within its capacity (Q.S. Al-Baqarah: 286). The primary novelty of this research lies in the formulation of “spiritual efficacy” as a distinct dimension, absent in conventional self-efficacy theories. This contribution expands the theoretical scope of psychology by integrating spiritual-transcendental values rooted in Islamic epistemology. Furthermore, the findings offer a theoretical foundation for the development of Islamic psychology and Qur’an-based character education, presenting a comprehensive model of human self-efficacy that harmonizes reason, behavior, and faith.

Generative artificial intelligence increasingly mediates how individuals interpret information, perform cognitive tasks, and participate in economic and political life. While such systems promise efficiency and expanded access to knowledge, their societal effects are unevenly distributed. This article develops the concept of societal bifurcation to explain an emerging structural divergence between a cognitively resilient minority, capable of integrating AI reflectively, and a cognitively dependent majority, whose reliance on automated interpretation reduces interpretative autonomy. Drawing on contemporary empirical evidence from cognitive science, labour research, and human–AI interaction studies, the article shows how unstructured AI use diminishes metacognitive monitoring and inflates confidence, while labour-market restructuring amplifies differences in adaptability and resilience. These cognitive and economic dynamics interact with an increasingly fragile democratic information environment shaped by synthetic communication and declining epistemic trust. The article argues that these processes form a self-reinforcing sociotechnical mechanism through which cognitive dependency, economic inequality, and democratic vulnerability become mutually constitutive. By conceptualising societal bifurcation as a distinct analytical framework, the article contributes to sociological and science and technology studies debates on inequality, agency, and governance in AI-mediated societies, while highlighting the importance of sustaining interpretative autonomy in the age of generative AI.

Background: The Perri Auditory Verbal Learning Test (Perri-AVLT) is a cognitive tool designed to assess verbal learning and memory. Currently, demographically adjusted norms for the Perri-AVLT are not available for elderly Mexican adults. Objective: This study aimed to develop regression-based norms from elderly Mexican adults to enable demographic adjustments for clinical interpretation. Methods: The sample included 294 elderly Mexican adults aged 60-89 (224 cognitively normal individuals, and 70 clinical cases) from Mexico (Jalisco, Guanajuato, and Mexico City). Participants were administered the Perri-AVLT. A multivariate regression-based norming approach was used to evaluate the effects of age, sex, and years of education on test performance. Results: The multivariate regression model showed that years of education were a significant predictor of cognitive performance across all Perri-AVLT trials. The Pearson correlation for all Perri-AVLT trials was high. Conclusion: This study provides regression-based normative data for the Perri-AVLT adjusted for sociodemographic factors. These norms can be used to evaluate verbal learning and memory in elderly Mexican adults. This information can support a neuropsychologist in cognitive assessment, rehabilitation, and research.

Purpose This study aims to examine how the perceived hypotheticality of technological business ideas affects entrepreneurs' opportunity evaluations. Drawing on construal level theory (CLT), we explore how psychological distance – amplified by the abstract nature of emerging technologies – shapes beliefs about the timing, location and social context in which a business opportunity is considered viable. The aim is to advance understanding of cognitive mechanisms underlying early-stage entrepreneurial decision-making under uncertainty. Design/methodology/approach We conducted two vignette-based experimental studies using fictional but realistic technology scenarios in the textile and human recognition technology sectors. Each study employed a between-subjects design to manipulate levels of perceived hypotheticality (high vs low). Participants evaluated when, where and for whom each technological opportunity would be most viable. Data were analyzed using analysis of covariance, controlling for entrepreneurial experience and technological awareness. Findings Results from both studies show that higher hypotheticality increases psychological distance, leading entrepreneurs to associate the opportunity with later timeframes, geographically distant markets and socially dissimilar users. These effects were consistent across both technological domains, supporting the robustness of the findings and the theoretical propositions derived from CLT. Research limitations/implications The use of online samples may limit the generalizability of results, and the study focuses exclusively on technological enablers. Future research should test these mechanisms across different types of opportunities and with varied entrepreneurial populations. Longitudinal studies could also explore how hypotheticality perceptions evolve over time. Practical implications Understanding how hypotheticality shapes opportunity beliefs (OB) helps entrepreneurs and innovation managers make more grounded decisions about early-stage technologies. Tools that reduce psychological distance – such as prototyping or early market testing – can help overcome premature discounting of viable innovations. Social implications By clarifying how psychological distance influences technology adoption judgments, this research can inform policy initiatives that aim to democratize innovation and reduce perceived inaccessibility of advanced technologies in underserved regions or communities. Originality/value This study introduces hypotheticality as a cognitive antecedent of OB and applies CLT to entrepreneurship. It offers a novel framework for understanding how abstraction affects early-stage opportunity evaluations, extending entrepreneurial cognition research into emerging technology contexts.

With the rapid digitalization of media environments, multimodal audiovisual materials have become an increasingly important resource for information access and second language learning. This study examines the role of subtitles in information acquisition during audiovisual viewing by integrating eye-tracking measures with performance-based learning outcomes. A total of 108 Chinese university learners of English as a foreign language (EFL) participated in an eye-tracking experiment and completed post-viewing tests assessing information acquisition under subtitled and non-subtitled conditions. The results showed that learners in the subtitle condition achieved significantly higher overall learning outcomes than those in the no-subtitle condition. However, correlation analyses revealed no significant association between visual attention to subtitle regions and test performance. These findings indicate that while subtitles facilitate information acquisition at the group level, the amount of visual attention allocated to subtitles alone does not reliably predict individual learning gains. The study provides empirical evidence for the complex relationship between visual attention and learning outcomes in multimodal environments, contributing to cognitive research on audiovisual translation and offering pedagogical implications for the effective use of subtitles in multimodal language learning contexts.

ABSTRACT Digital legitimacy has become a critical determinant of entrepreneurial success in emerging economies, where institutional voids and information asymmetries sharply elevate entrepreneurs’ dependence on digital signals to gain stakeholder credibility. Existing entrepreneurial cognition theories, largely developed in advanced economies, insufficiently account for the structural heterogeneity of emerging markets. This study examines how creativity, alertness, and resilience shape digital literacy in Indonesia and Malaysia – two nations that, despite persistent differences, share cultural similarities but distinct economic structures. Using survey data from 346 Indonesian and Malaysian entrepreneurs and employing multi group analysis, we find that creativity strengthens alertness, resilience, and digital legitimacy in both contexts. However, Indonesian entrepreneurs rely more on resilience to build legitimacy in a volatile, domestically driven economy, whereas Malaysian entrepreneurs depend more on alertness within an export-oriented, policy-led environment. The findings extend entrepreneurial cognition research to emerging markets and offer context-specific implications for entrepreneurship education and digital policy design.

Spatial memory is a fundamental cognitive process that allows animals to navigate and interact with their environment effectively. While extensively studied in mammals and birds, the mechanisms underlying spatial cognition in reptiles remain less understood. In this study, we investigated spatial learning and the influence of behavioural lateralization in the common wall lizard (Podarcis muralis). We examined whether lizards could develop short-term spatial memory and whether lateralization affected their navigation in a complex maze. Experimental lizards received 3 days of training without reinforcement, while control lizards had no prior experience. We found that trained lizards learnt to navigate the maze rapidly, reaching a goal shelter faster and more reliably than controls. Additionally, strongly lateralized individuals took longer to reach the goal during training, but this did not impair escape performance once the route had been learned. Our study reports novel evidence on the role of lateralization during spatial exploration in lizards. Lateralization is hypothesized to enhance information processing, but our data suggest no benefit or cost of lateralization after a route was learnt. Our study contributes to a broader understanding of cognitive evolution across vertebrates and emphasizes the importance of reptiles as models for comparative cognition research.

The Consensus on subdomains and measures of Affective and Social cognition for research on Bipolar Disorder (CAS-BD) project aimed to formulate preliminary consensus-based recommendations for assessing affective and social cognition in BD. Three sequential surveys administered to experts on affective and social cognition in BD were conducted using the Delphi process. Experts responded to questions regarding affective and social cognition subdomains and rated their importance to research on BD. Experts also nominated measures, rated them for suitability, and ranked them by preference for use. Consensus was defined as ≥ 80% agreement. 31 experts completed the initial survey, with 20-23 completing subsequent surveys. Consensus was obtained for the subdomain structure of both affective cognition and social cognition, and the definition of each subdomain within. Explicit emotion regulation was ranked as being of highest priority for further research on affective cognition, and theory of mind as highest priority for further research on social cognition. The top-preferenced measures of all affective cognition subdomains were considered by consensus to be suitable for use in BD research. Agreement that the top-preferenced measures of social cognition were suitable ranged from 71.5% to 95.3%. Expert consensus on subdomains and measures of affective and social cognition for research on BD was obtained via a staged approach. Prior familiarity may have influenced some experts' rankings, but generally there was a notable lack of consistency in the use of available measures by BD experts. This reaffirms the need for more specific guidance and validated batteries of social and affective cognition to direct the field and allow for more consistency and replication of research in the future.

This term paper dives into the perplexing relationship between brain plasticity and multilingualism, utilizing a case study conducted in Lahore, Pakistan. Drawing on the system of sociocultural theory, the study explores how introduction to different languages in an assorted sociocultural and linguistic setting impacts cognitive forms and brain plasticity. The study intends to advance knowledge of the cognitive advantages of multilingualism, especially in light of Lahore's distinct sociocultural context. Based on the Sociocultural Theory, the research investigates how Lahore's sociocultural dynamics affect multilingual people' cognitive abilities and brain plasticity. The goal of the research is to understand how cultural factors and social interactions affect cognitive flexibility in a multilingual environment. It is expected that the results of this research will provide insightful information about the complex interplay among linguistic variety, sociocultural elements, and the plasticity of the human brain, with theoretical frameworks and useful applications for cognitive research and education in multilingual settings.

Virtual reality (VR) technology offers highly controlled immersive experiences that can be used to conduct spatial cognition research. However, there are VR-specific perceptual biases that reduce its ability to generalize all findings to real-world scenarios. One specific bias causes observers to perceive objects as closer than intended, a phenomenon called distance compression. Although prior research has focused primarily on visual and technological solutions to distance compression, using other senses as a potential remedy (e.g., hearing) for the bias has not been explored. Here, participants completed both a blind-walking task for distance estimation and a cross-modal perceptual-matching task to evaluate audiovisual spatial displacement. The results showed that real-world sounds spatially displaced both in front of and behind a corresponding visual target increased the accuracy of blind walking relative to vision-only cues, albeit with a small effect. Individual differences measures, including performance on the perceptual-matching task and the relative variability of auditory and visual stimuli, did not account for the individual differences in the effectiveness of spatially displaced sounds. Overall, this study demonstrates the potential for adding multisensory information (specifically the addition of non-virtual sounds) to improve the accuracy of distance perception in VR.

Background: Cognitive impairment and dementia impose increasing health and societal burdens, highlighting the need for scalable and objective approaches to characterize cognitive health across early identification and longitudinal monitoring. Traditional neuropsychological assessments have limited scalability and capture coarse performance outcomes, while digital technologies enable scalable multimodal assessment integrating cognitive, behavioral, and biological data. Accordingly, the Chinese mobile Brief Cognitive Test—Multimodal Integrated Neurocognitive Database (CmBCT-MIND) was established as a multicenter, smartphone-based multimodal database that integrates temporally coupled cognitive and behavioral data with complementary validated scales and biological measures for large-scale cognitive health research. Methods: This study represents the baseline phase of an ongoing longitudinal project initiated in July 2024. Participants without a history of diagnosed cognitive impairment were enrolled from three centers in Beijing. Each participant completed a clinical case report form, validated scales, and the Chinese mobile Brief Cognitive Test (CmBCT). Complementary molecular measures were obtained through fasting venous blood collection for Alzheimer’s disease (AD) biomarker testing (p-tau217, Aβ40, Aβ42) and 5-hydroxymethylcytosine (5hmC) sequencing. A subsample of participants also completed CmBCT with a professional eye-tracking device to capture gaze dynamics during cognitive tasks. Results: The current release of the CmBCT-MIND includes data from 682 participants, covering seven major domains: demographic information, validated scales, cognitive performance from the CmBCT, task-related parameters recorded during CmBCT, time-synchronized behavioral data including touch-interaction features and front-facing videos, molecular data from 481 participants, and eye-tracking recordings from 154 participants. Representative CmBCT-derived task metrics demonstrated expected group-wise differences between Normal and MCI participants, consistent covariate-adjusted associations with MoCA scores, stable effect directions across split samples, and moderate discriminative performance for MCI (AUCs 0.64–0.76). Conclusion: The CmBCT-MIND provides a comprehensive, standardized, and scalable resource for investigating cognitive health and digital biomarker discovery in aging populations. It links smartphone-based cognitive performance with temporally coupled behavioral features, complemented by demographic, neuropsychological, and biological data. The project serves as an evolving open platform that invites collaboration and secondary analyses to advance digital cognitive health research.

Accurate assessment of cognitive load is vital in cognitive research and human-machine interaction. This study investigates a multimodal approach for classifying graded cognitive load levels using cardiovascular signals derived from photoplethysmography (PPG) and impedance plethysmography (IPG). Data were collected from 15 healthy adults performing mental arithmetic tasks of increasing difficulty (Rest, Level 1, Level 2, and Level 3). Carotid PPG was used as a global indicator of cerebral perfusion, while frontal IPG captured localized changes in regional blood volume. Machine learning algorithms, including Decision Trees, Random Forest, and XGBoost, were applied to discriminate between workload levels. Among these models, Random Forest achieved the highest performance, reaching 96% accuracy in subject-dependent classification. Subject-independent accuracy was lower (66%), reflecting substantial inter-subject variability. IPG-derived features were among the most influential contributors to workload discrimination, highlighting the role of localized neurovascular responses to cognitive demand. These findings support the potential of PPG-IPG fusion as a noninvasive and physiologically grounded technique for continuous monitoring of cognitive workload.

Post-stroke cognitive impairment is a severe sequela of cerebral ischemia, with its underlying mechanisms remaining elusive and specific diagnostic biomarkers currently lacking. Growing evidence suggests that secondary neurodegeneration is closely associated with post-stroke cognitive impairment, although its metabolic basis has not been fully elucidated. Therefore, this study aimed to investigate the spatiotemporal changes and metabolic characteristics of secondary neurodegeneration and cognitive function after cortical stroke. We established a photothrombotic mouse model for post-stroke cognitive impairment research and conducted longitudinal assessments with final endpoints at 14, 32, and 84 days postsurgery. Voxel-based morphometry analysis of whole-brain regions using magnetic resonance imaging revealed that only the hippocampus exhibited gray matter alterations consistent with secondary neurodegeneration pathology. Morris water maze and open field tests demonstrated persistent impairments in recent and remote memory, along with anxietylike behaviors in photothrombotic mice. Untargeted metabolomic and lipidomic analyses were established to comprehensively characterize secondary neurodegeneration-related metabolic disturbances in the hippocampus, highlighting pathophysiological mechanisms involving oxidative stress, lipid peroxidation, neurotransmitter dysregulation, and disrupted energy metabolism. These important mechanisms were verified by immunohistochemistry, immunofluorescence staining, and real-time polymerase chain reaction. The screened potential biomarker, N-acetylneuraminic acid, was validated via targeted metabolomics in both photothrombotic mouse serum and 148 clinical samples, showing significant elevation in both cohorts. Receiver operating characteristic curve analysis and decision curve analysis confirmed the clinical utility of N-acetylneuraminic acid in diagnosing post-stroke cognitive impairment (area under the curve = 0.951, 95% confidence interval: 0.903-0.980). Flow cytometry and immunofluorescence staining revealed that N-acetylneuraminic acid activates microglia-driven neuroinflammation and oxidative stress. Our findings elucidate a potential pathological mechanism of post-stroke cognitive impairment: cortical stroke induces hippocampal accumulation of N-acetylneuraminic acid, which promotes microglial oxidative stress and inflammation, thereby triggering hippocampal secondary neurodegeneration and leading to persistent cognitive deficits. Importantly, N-acetylneuraminic acid serves as a dual-functional biomarker capable of predicting post-stroke cognitive impairment progression while dynamically tracking secondary neurodegeneration.