Frontiers in Human Neuroscience最新文献

Introduction: Maternal and child undernutrition are linked to atypical brain development in children. Provision of pre- and post-natal small-quantity lipid-based nutrient supplements (SQ-LNS) has been shown to positively impact children's growth and development. It is unknown, however, whether SQ-LNS affects child brain morphology.

Methods: The present study used data from the International Lipid-based Nutrient Supplements randomized controlled trial in Ghana. Participants were 231 children (M _age = 10.6 years; 49.4% female) exposed to maternal iron and folic acid supplements prenatally (n = 113, control group) or maternal SQ-LNS prenatally until 6 mo postpartum and child SQ-LNS from age 6 to 18 months (n = 118, SQ-LNS group). Children underwent magnetic resonance imaging (MRI) of brain anatomy. Primary outcomes were total gray matter volume, cortical gray matter thickness, and cortical gray matter volume assessed with whole-brain analyses. Secondary outcomes were thickness and volume of a priori specified cortical and subcortical regions assessed with region-of-interest (ROI) analyses. Basic and full covariate models were tested and corrected for multiple comparisons.

Results: Whole-brain analyses revealed no significant differences between groups in total gray matter volume or cortical gray matter thickness or volume. Cortical ROI analyses showed the SQ-LNS versus control group had greater right caudal anterior cingulate cortex (ACC) thickness [mean (95%CI): 2.78 (2.73, 2.84) vs. 2.72 (2.67, 2.77); effect size = 0.21] and reduced left rostral ACC volume [2575.1 (2477.3, 2672.8) vs. 2678.74 (2568.7, 2788.8); effect size = 0.18]. Subcortical ROI analyses showed the SQ-LNS versus control group had greater volume of the left pallidus [1794.45 (1759.10, 1829.80) vs. 1726.13 (1685.05, 1767.21); effect size = 0.33] and right nucleus accumbens [751.54 (729.83, 773.24) vs. 705.73 (684.21, 727.24); effect size = 0.39]. Significant group differences did not hold after correction for multiple comparisons.

Discussion: In this cohort, pre- and post-natal SQ-LNS supplementation did not significantly alter total or cortical gray matter thickness and volume at 10 years, though secondary ROI analyses indicated subtle, non-robust differences in selected regions.

Electroencephalography (EEG) is a longstanding means of non-invasively recording brain signals and has become highly valuable for the study of neurological and cognitive processes. Recent progress in deep learning has also greatly improved both EEG signal analysis and interpretation, making more accurate, reliable and scalable solutions in various healthcare applications. In this review, we present a comprehensive summary of the convergence of EEG and deep learning, with an emphasis on diagnostic of neurological disorders, brain recovery, mental health conditions, and brain-computer interface (BCI) applications. We methodically investigate the application of convolutional neural networks (CNNs), recurrent neural networks (RNNs), long short-term memory (LSTM) models, transformer models and hybrid architectures for EEG-based tasks. Key challenges that have been hampering emerging solutions are critically covered, namely signal-related variability, the lack of data, and deep learning model limited interpretability. Finally, we highlight emerging trends, open issues and promising research directions, with the aim of laying a solid ground toward the improvement of EEG-based healthcare applications and to drive future research in this fast-growing research area.

Introduction: Meige syndrome is a rare adult-onset segmental dystonia characterized by blepharospasms and oromandibular dystonia. Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an established treatment, but it can lead to stimulation-induced dyskinesia (SID) in some patients. Refractory SID in Meige syndrome after STN-DBS is clinically challenging. We report a case of a Meige syndrome patient who developed refractory SID following STN-DBS and was successfully managed using a novel timed-stimulation programming strategy employing different contacts.

Case description: A 47-year-old female with a two-year history of Meige syndrome developed refractory SID after the treatment of STN-DBS. Various programming strategies were attempted, including monopolar stimulation, interleaved stimulation, bipolar stimulation et al., but none achieved a balance between symptom control and SID. A novel approach involving timed alternation between ventral contacts (contacts 3 and 7) and dorsal contacts (contacts 4 and 8) was implemented. The stimulation was gradually programmed, the duration of ventral stimulation was increased while decreasing dorsal stimulation. Eventually, the patient achieved significant symptom improvement without SID. The reconstruction of the volume of tissue activated (VTA) revealed that this stimulation strategy likely modulates the neural circuits of pallidothalamic fibers (PTF) to suppress SID.

Conclusion: This case demonstrates that this noval timed stimulation programming can effectively manage refractory SID in Meige syndrome patients, offering a viable alternative when conventional methods fail. The findings suggest that PTF stimulation plays a key role in SID suppression, and this strategy warrants further investigation in larger cohorts.

Cancer-related cognitive impairment (CRCI) is a cognitive dysfunction of the brain caused by the tumor itself and antitumor treatments such as radiotherapy, chemotherapy, endocrine therapy, and surgery. As a common complication of cancer, CRCI significantly affects patients' quality of life. In recent years, the neurobiological mechanisms of CRCI have garnered widespread attention. Research indicates that cancer-related therapies lead to CRCI by affecting brain structure, function, metabolism, and blood perfusion. Various neuroimaging techniques, including magnetic resonance imaging (MRI), positron emission tomography (PET), and electroencephalography (EEG), have been extensively employed to investigate the neurobiological underpinnings of CRCI. This article reviews recent advancements in neuroimaging research on CRCI, focusing on its influencing factors and the neural mechanisms underlying different cognitive domains, and summarizes findings from relevant animal model studies.

Parkinson's Disease (PD) is a common neurological disorder that diminishes neuromotor control. Exercise training provides a nonpharmacological treatment option that may help motor symptom severity and trajectory. In the present case series, we assessed linear and non-linear measures of neuromotor control along with functional measures of mobility in six men living with PD across a year of multimodal exercise training. Our measurements encompassed mobility, balance, strength, and force control metrics and were captured at baseline as well as at defined intervals following exercise engagement. The results appear to indicate a favorable preservation of functional ability and neuromotor control for most of the cohort across the yearlong exercise intervention. Our linear measures of neuromotor control generally remained stable with slight improvements from baseline to month 12, with visually distinct trends for our non-linear measures (Sample Entropy) of neuromotor control suggestive of more adaptive motor control strategies for both postural and force control. These data corroborate reports showing favorable outcomes for people with Parkinson's Disease following exercise engagement. Our year-long assessment of neuromotor control in a cohort of men with Parkinson's disease provides a novel contribution to the trajectory of change in this population while undergoing multimodal exercise training.

Hereditary diffuse leukoencephalopathy with axonal spheroids (HDLS) is a rare autosomal dominant leukodystrophy primarily caused by mutations in the colony-stimulating factor 1 receptor (CSF1R) gene, characterized by progressive cognitive and motor decline. We present a case of a 42-year-old Chinese woman with a rapidly progressive syndrome featuring prominent apathy, cognitive impairment, and hypoactivity. Brain magnetic resonance imaging (MRI) revealed extensive confluent white matter hyperintensities (Fazekas grade 3) predominantly in frontal and parietal lobes, cerebral atrophy, and thinning of the corpus callosum. Comprehensive genetic testing identified a heterozygous missense mutation in the CSF1R gene (c.2342C > T, p.Ala781Val), located within the tyrosine kinase domain, confirming the Diagnosis of HDLS. This case highlights early apathy and hypoactivity as red-flag manifestations of CSF1R-related leukoencephalopathy in a 42-year-old woman with rapidly progressive cognitive decline. The atypical presentation, initially mimicking psychiatric or demyelinating disease, underscores the need to consider CSF1R sequencing when encountering early-onset cognitive or behavioral deterioration with unexplained white-matter changes, thereby facilitating timely diagnosis and genetic counseling.

Introduction: As a privileged group within the social structure, the wealthy play a significant role in social philanthropy and public welfare initiatives, making their empathic capacity a subject of considerable interest. Previous research has found that wealthy individuals who have experienced upward class mobility paradoxically demonstrate reduced empathy toward the poor. However, these studies were predominantly conducted in individualistic cultural contexts, leaving the collectivist cultural perspective largely unexplored.

Methods: The present study employed a virtual-society paradigm to experimentally simulate class mobility in a collectivist context. Objective mobility direction (upward vs. horizontal) and subjective evaluation of mobility (positive vs. negative) were manipulated to construct four types of wealthy roles (upward-positive, upward-negative, horizontal-positive, horizontal-negative). Chinese university students from a collectivist cultural background were instructed to sequentially adopt each wealthy role and judge painful versus neutral pictures of the same low-status target, while event-related potentials (ERPs) were recorded.

Results: The results revealed that in the early N2 component, under upward mobility conditions, pain stimuli elicited significantly smaller N2 amplitudes compared to neutral stimuli, while no significant difference was observed under horizontal mobility conditions. In positive evaluation conditions, pain stimuli evoked significantly smaller N2 amplitudes than neutral stimuli, whereas no significant difference emerged in negative evaluation conditions. For the late LPP component, pain stimuli consistently elicited significantly larger LPP amplitudes than neutral stimuli, regardless of either the objective direction of class mobility or subjective evaluation.

Discussion: These findings suggest that, within this simulated class-mobility context, upward mobility experiences and positive appraisal primarily influence early neural processing of the poor target's pain, while later evaluative processing remains relatively stable. This study provides neural-level evidence for understanding how class mobility affects pain empathy among the wealthy in collectivist cultures, thereby enriching research on the relationship between social stratification and pain empathy.

Introduction: Exposure to violence has been associated with alterations in how the brain organizes thought, regulates emotions, and guides behavior. In Colombia, decades of armed conflict have generated heterogeneous patterns of cognitive vulnerability, yet evidence on executive and emotional functioning in adult victims remains limited.

Methods: This cross-sectional study compared executive and emotional functioning between victims and non-victims of the Colombian armed conflict. A total of 300 middle-aged adults from the Department of Bolívar were assessed using a neuropsychological battery (MMSE, Tower of Hanoi, Wisconsin Card Sorting Test, Stroop Test, and Frontal Assessment Battery) and emotional screening instruments (GAD-7 and PHQ-2). Executive function was modeled as a latent construct using confirmatory factor analysis and Multiple Indicators Multiple Causes (MIMIC) models adjusted for sociodemographic covariates. Random Forest was implemented as a complementary, assumption-free analytic strategy.

Results: Victims showed significantly poorer performance in planning, cognitive flexibility, and inhibitory control (β = -0.178; p = 0.024). Educational attainment emerged as the strongest predictor of executive functioning (β = -0.249; p < 0.001). The factorial model showed modest fit (CFI = 0.76), reflecting ecological and educational heterogeneity. Machine learning analyses converged with latent-variable results, identifying exposure to violence and structural inequalities as the strongest predictors of executive variability, whereas emotional factors played a marginal role.

Discussion: The findings delineate a cognitive profile associated with conflict-related victimization, characterized by vulnerabilities in executive control processes. These results underscore the need for clinical and public policy interventions that integrate neuroscientific approaches to strengthen planning and decision-making capacities in populations affected by armed conflict.

Predictive coding (PC) has become a central framework in contemporary cognitive neuroscience, proposing that the brain operates as a hierarchical inference system that continuously minimizes the mismatch between predicted and actual sensory input. Its extension into clinical neuroscience has been accompanied by considerable enthusiasm, yet attempts to translate its computational principles into explanations of psychiatric and neurological disorders have yielded uneven results. The present review critically examines the clinical applicability of PC across three diagnostic domains: schizophrenia, autism spectrum disorder (ASD), and mood and anxiety disorders. Drawing on findings from neuroimaging, electrophysiology, and computational modeling, the discussion evaluates how disturbances in prediction error signaling, the precision weighting of sensory evidence relative to prior beliefs, and hierarchical inference have been proposed to relate to core clinical phenomena such as hallucinations, sensory hypersensitivity, and affective dysregulation. Particular attention is given to persistent theoretical tensions, including debates surrounding prior precision, the mapping between neural proxies and behavior, and the inconsistent use of PC terminology across diagnostic contexts. By adopting a structured and comparative approach, this review aims to clarify where predictive coding offers testable mechanistic insight into psychopathology, and where its explanatory scope remains limited or provisional.