Frontiers in Human Neuroscience最新文献

Background: Cancer-related cognitive impairment (CRCI) is relatively common among middle-aged and older adult cancer patients, with working memory deficits being particularly prominent. However, the underlying structural basis of hippocampal subregions remains unclear. This study aimed to investigate differences in hippocampal subfield volumes and working memory function between cancer patients and healthy controls, as well as to analyze the correlation between hippocampal structural alterations and working memory impairment.

Methods: The cohort comprised 51 cancer patients and 45 healthy controls. All participants underwent 3D-T1 structural MRI scans and cognitive assessments. Hippocampal subfields were automatically segmented using FreeSurfer 7.4, and their volumes were calculated. Group differences in cognitive test scores were compared. After controlling for total intracranial volume (TIV), analysis of covariance (ANCOVA) was performed to examine differences in hippocampal subfield volumes between groups. Spearman correlation analysis was undertaken to assess the relationship between hippocampal subfield volumes and cognitive test scores in patients with cancer.

Results: Compared with healthy controls, cancer patients exhibited significantly lower scores in the digit span test (DST) total score (U = 716.50, p = 0.001) and digit span forward (DSF) subtest (U = 738.50, p = 0.002). Hippocampal subfield analysis revealed significant volume reductions in the cancer group, particularly in CA3 (F = 8.141, p = 0.005) and CA4 (F = 6.770, p = 0.011). Correlation analysis demonstrated that the volumes of the hippocampal head (r = 0.410, p = 0.003) and hippocampal molecular layer (r = 0.389, p = 0.005) were positively associated with DST scores in cancer patients.

Conclusion: Cancer patients exhibit working memory impairment and hippocampal subfield atrophy. The significant correlation between the volumes of the hippocampal head and molecular layer with working memory performance suggests that these regions may play a critical role in cancer-related cognitive dysfunction.

The purpose of this study is to provide basic data for the establishment of sustainable sports content and communication marketing strategies of effective OTT platforms by applying the extended technology acceptance model to clarify the causal relationship between the perceived usefulness, perceived ease of use, perceived enjoyment, perceived interactivity, usage intention, and usage behavior of users who watch OTT platform sports content. To achieve this purpose, 303 viewers with experience watching OTT platform sports content were used for the analysis. The data analysis methods were frequency analysis, correlation analysis, confirmatory factor analysis, and structural equation modeling analysis using SPSS 21.0 and AMOS 18.0. The results of this study are as follows. First, perceived usefulness was found to have no significant effect on usage intention. Second, perceived ease of use was found to have a significant effect on usage intention. Third, perceived enjoyment was found to have a significant effect on usage intention. Fourth, perceived interactivity was found to have a significant effect on usage intention. Fifth, usage intention was found to have a significant effect on usage behavior. Therefore, the intention of using OTT platform sports content will be to become a sustainable industry in terms of media business.

Introduction: Stroke ranks as the second leading cause of death and disability worldwide, with the resulting upper-limb spasticity severely impairing patients' motor function and quality of life. However, existing clinical assessment scales exhibit a degree of subjectivity, and research into the neurophysiological mechanisms underlying spasticity remains insufficient. Brain network analysis offers a novel perspective for investigating the neural mechanisms associated with spasticity.

Methods: Eight patients with upper limb spasticity due to stroke (MAS grades 1-2) and eight healthy controls were enrolled. Multi-channel EEG signals were recorded during different upper limb movements (fist clenching, elbow flexion, wrist flexion). Functional brain networks were constructed using the weighted phase delay index, and further calculations were performed on relevant brain network characteristics, including node degree, global efficiency, local efficiency, clustering coefficient, and small-world properties.

Results: Research findings indicate that functional connectivity in spasticity patients is significantly lower than in healthy subjects, particularly in the alpha and beta frequency bands, with weaker cross-regional synchrony in frontal, central, and temporal lobe regions. Graph theory analysis further reveals that compared to healthy controls, spasticity patients exhibit significantly reduced global efficiency, local efficiency, and clustering coefficient, while small-world properties remain relatively preserved. Node degree analysis revealed abnormal compensatory activation in temporal and parietal regions, whereas healthy participants exhibited higher node degrees in central and frontal areas. These findings suggest that spasticity is associated with impaired local and global network integration, accompanied by inefficient compensatory mechanisms.

Discussion: This study provides new evidence that post-stroke upper limb spasticity is not only a peripheral muscle phenomenon but also reflects disturbances in cortical network dynamics. Brain network metrics, particularly global and local efficiency, may serve as objective biomarkers to quantify spasticity severity and guide personalized rehabilitation interventions, offering a promising direction for developing precision rehabilitation strategies.

Pediatric Speech Sound Disorders (SSDs) are conventionally diagnosed using auditory-perceptual assessments, heavily relying on International Phonetic Alphabet (IPA) transcriptions. This approach, while prevalent, is increasingly criticized due to inherent perceptual biases, limited sensitivity to subtle speech motor variations, and insufficient reflection of underlying speech mechanisms. This paper critically re-examines a widely used diagnostic classification system for pediatric SSDs, namely Dodd's Model of Differential Diagnosis (MDD), emphasizing the limitations of perceptual methods and advocating for instrumental techniques to address significant ground truthing issues. Critical analysis in this paper integrates evidence from perceptual research, instrumental phonetics, and speech motor development studies, highlighting discrepancies between traditional classification methods and modern instrumental data. Findings indicate profound limitations in current auditory-perceptual classification methods, particularly regarding their inability to detect subtle motoric impairments such as jaw sliding, covert motor contrasts, and undifferentiated tongue gestures. Evidence from instrumental studies supports a speech-motor rather than purely cognitive-linguistic basis for many pediatric SSDs, revealing significant inadequacies in current clinical practices. To avoid the narrow interpretation of "motor speech" as referring only to childhood apraxia of speech (CAS) or dysarthria, we explicitly broaden its scope to include a wider range of motoric influences on SSDs. Given these critical ground truthing concerns, the paper proposes adopting instrumental-based methodologies that offer greater precision in identifying underlying motor-based impairments, thereby promoting a more accurate and nuanced understanding of pediatric SSDs. Furthermore, the discussion advocates for adopting a dimensional rather than categorical classification framework, emphasizing gradual developmental trajectories and foundational speech motor skills. Aligning with modern precision medicine principles, the proposed approach aims to refine diagnostic accuracy, improve intervention effectiveness, and ultimately enhance clinical outcomes for children with SSDs.

Introduction: Color is a critical determinant of esthetic experience, shaping both immersion and cognitive responses. However, the extent to which the sequence of color exposure modulates the interplay between neural activation and ocular behavior remains insufficiently understood.

Methods: Ten chromatic landscape paintings were collected and converted into achromatic versions, yielding a total of 20 visual stimuli. Participants were assigned to two conditions: Condition A (achromatic to chromatic) and Condition B (chromatic to achromatic). Visual attention and prefrontal activation were assessed using eye-tracking techniques and functional near-infrared spectroscopy.

Results: Analyses revealed significantly greater neural activation in Condition A within the left dorsolateral prefrontal cortex (p-raw = 0.006), left orbitofrontal cortex (p-raw = 0.043), and right orbitofrontal cortex (p-raw = 0.043). Eye-tracking metrics indicated longer Total duration of fixation (p-raw = 0.015), Maximum duration of fixation (p-raw = 0.036), and Total duration of whole fixation (p-raw = 0.025) under Condition A. Subjective evaluations also showed significant differences, with higher ratings for Match (p-raw = 0.005) and Feel (p-raw = 0.029).

Discussion: These findings demonstrate that color stimuli exert a decisive influence not only on subjective immersion but also on objective neurocognitive processes. The study extends the scientific foundation of empirical esthetics and offers novel implications for the design of museum and exhibition environments.

Quantum-like modeling (QLM)-quantum theory applications outside of physics-are intensively developed with applications in biology, cognition, psychology, and decision-making. For cognition, QLM should be distinguished from quantum reductionist models in the spirit of Hameroff and Penrose, as well as Umezawa and Vitiello. QLM is not only concerned with just quantum physical processes in the brain but also with QL information processing by macroscopic neuronal structures. Although QLM of cognition and decision-making has seen some success, it suffers from a knowledge gap that exists between oscillatory neuronal network functioning in the brain and QL behavioral patterns. Recently, steps toward closing this gap have been taken using the generalized probability theory and prequantum classical statistical field theory (PCSFT)-a random field model beyond the complex Hilbert space formalism. PCSFT is used to move from the classical "oscillatory cognition" of the neuronal networks to QLM for decision-making. In this study, we addressed the most difficult problem within this construction: QLM for entanglement generation by classical networks, that is, "mental entanglement." We started with the observational approach to entanglement based on operator algebras describing "local observables" and bringing into being the tensor product structure in the space of QL states. Moreover, we applied the standard states entanglement approach: entanglement generation by spatially separated networks in the brain. Finally, we discussed possible future experiments on "mental entanglement" detection using the EEG/MEG technique.

Background and objectives: Mild traumatic brain injury (mTBI) frequently results in persistent cognitive deficits with limited evidence-based rehabilitation options. Visual timing deficits, potentially linked to dorsal visual pathway dysfunction, represent a promising therapeutic target. This study examined whether a novel intervention targeting dorsal visual pathways (PATH) demonstrates superior efficacy compared to conventional cognitive therapies targeting ventral pathway deficits or working memory impairments.

Methods: Twenty-four participants (aged 23-62 years) with mTBI were randomized to receive one of three interventions over 12 weeks: (1) PATH training targeting dorsal visual pathway function, (2) Orientation Discrimination (OD) targeting ventral pathway pattern discrimination, both of these 20-min interventions followed by 10-min of digit memory exercises, or (3) ReCollect, working memory training. Each intervention consisted of 36 sessions (30 min each, three times weekly). Primary outcome was visual working memory (VWM) performance; secondary outcomes included processing speed, reading speed, auditory working memory, selective attention, and cognitive flexibility assessed via standardized neuropsychological measures. Magnetoencephalography (MEG) recordings during resting state and an N-Back task provided neurophysiological validation.

Results: PATH training yielded significantly greater VWM improvements (49%) compared to ReCollect (13%) and OD (8%) interventions. Repeated-measures ANOVA confirmed superior efficacy of dorsal pathway training (significant at p = 0.011). Similar gains for PATH training were also found for processing speed, reading speed, and cognitive flexibility, especially when compared to the OD group, revealing importance of strengthening the dorsal stream before digit memory exercises. MEG analysis revealed PATH-specific activation in not only bilateral dorsolateral prefrontal cortex, anterior cingulate cortex, posterior parietal cortex, superior occipital gyri, but also the left anterior temporal lobe and hippocampus, primary motor cortex, and the cerebellum, as well as lower gamma-band noise, suggesting enhanced neural timing, attention, working memory, memory consolidation and retrieval mechanisms beyond the targeted dorsal pathways.

Conclusion: Dorsal visual pathway retraining followed by targeted working memory exercises demonstrates superior therapeutic efficacy for cognitive rehabilitation following mTBI compared to conventional approaches. The intervention promotes beneficial neuroplasticity extending to memory-related brain regions, supporting its potential as a targeted, mechanistically-informed therapy for post-concussive cognitive deficits.

Background: Optimization of brain health is a focal point in medical science, yet data regarding measuring, improving, and preserving lifelong brain health are lacking. This void demands an objective, change-sensitive measure of brain health and proven strategies to strengthen brain performance. The BrainHealth Project addresses these key issues, drawing upon neuroplasticity evidence of persistent modifiability of brain function across the lifespan. This landmark study aims to (i) evaluate and refine multidimensional change indices of brain health, (ii) evaluate the impact of evidenced-based cognitive strategies and lifestyle interventions on improving/maintaining brain health, and (iii) elucidate the mechanisms associated with brain health gains/losses.

Methods: This quantitative, longitudinal, interventional, open-label, single-arm clinical trial aims to recruit 100,000 generally healthy adults ages 18-100 and evaluate changes for 10 years or longer. Assessments, coaching, and training are conducted online through the secure BrainHealth Platform, allowing utilization tracking. The BrainHealth Index (BHI) - a multidimensional assessment - is offered at baseline and every 6 months. Participants have access to coaching every 3 months and continual access to self-paced trainings and resources. The primary outcome is the composite BrainHealth Index score and its empirically derived subdomain scores: Clarity (cognitive health), Connectedness (social health), and Emotional Balance (mental health). The BHI includes validated measures sensitive to change, including gains or losses associated with behavior change and integration of cognitive strategies into daily life. This Index contrasts with traditional assessments focused primarily on detecting cognitive decline or diagnosing pathological conditions, yet it, too, has been found to be sensitive to small incremental losses. The primary online training, SMART (Strategic Memory Advanced Reasoning Tactics), is a strategy-based program validated with 25+ years of research. SMART promotes improvements in neural health, cognition, wellbeing, connectedness, and real-life function, previously reported in randomized controlled trials (RCTs). Statistical approaches focus on individual prediction using nonlinear models trained with large samples and on assessing mechanisms influencing gains or losses on brain health metrics.

Discussion: This research extends prior RCT evidence to a longitudinal, epidemiologic approach, leveraging digital health and machine learning tools to deliver a generalizable measure of longitudinal brain health and actionable ways to achieve precision brain health. By integrating advanced statistical methods and large-scale data, the BrainHealth Project aims to provide medicine and society with accurate, multidimensional, sensitive, and actionable ways to optimize brain health practices across the lifespan.

The n-back task has become a central paradigm for investigating the mechanisms of working memory (WM) and related executive functions. This review provides an integrative analysis of the n-back experiment, covering its cognitive operations, task variants, neuroimaging findings, and practical applications across multiple domains. We first delineate three core cognitive components-updating, maintenance, and attentional control-and summarize converging evidence that these functions rely on overlapping fronto-striatal and fronto-parietal networks. We then examine major task variants and review applications in: (1) cognitive training and transfer effects, particularly the proposed association between WM and fluid intelligence; (2) clinical contexts including attention deficit hyperactivity disorder (ADHD), depression, and neurological rehabilitation; (3) developmental and educational settings; and (4) emerging research on social cognition, stress, and emotional regulation. Critically, this review evaluates ongoing inconsistencies in how the n-back task is interpreted as a measure of WM and highlights methodological factors, such as task heterogeneity, multi-process interference, and mental fatigue, that complicate both behavioral and neural inferences. To address these issues, we outline methodological recommendations including adaptive task design, multimodal physiological monitoring, and standardized experimental protocols. We further discuss future directions involving virtual reality (VR), mobile platforms, and brain-computer interface (BCI) integration to improve ecological validity and translational relevance. By synthesizing behavioral and neural evidence, this review underscores the n-back task's versatility while emphasizing the need for improved construct clarity and methodological rigor.