Frontiers in Neuroscience最新文献

Background/objectives: Schizophrenia is a highly heritable psychiatric disorder that affects approximately 1% of the global population. Genome-wide association studies (GWAS) have mapped most schizophrenia risk variants to noncoding regions, highlighting the role of regulatory processes and noncoding RNAs in schizophrenia pathology. Despite this, and schizophrenia's association with 5-hydroxytryptamine (serotonin) system dysfunction, HTR5A-AS1, a long noncoding RNA (lncRNA) antisense to the serotonin receptor (HTR, 5-hydroxytryptamine receptor) gene HTR5A, remains virtually unstudied. This study provides the first systematic characterization of HTR5A-AS1, validating its transcript structure and investigating its genetic associations, expression dynamics, developmental regulation, and potential synaptic and GABAergic functions in schizophrenia.

Methods: Transcriptome-wide association study (TWAS) summary statistics were integrated with postmortem RNA sequencing (RNA-seq), BrainSpan developmental transcriptomes, UCSC Genome Browser annotations, and functional prediction tools. These complementary approaches enabled validation of the transcript's structure, quantification of regional and developmental expression, and assessment of potential molecular functions.

Results: HTR5A-AS1 showed significant TWAS associations with schizophrenia in the hippocampus and dorsolateral prefrontal cortex (dlPFC). In postmortem schizophrenia donor tissue, expression was significantly reduced in the hippocampus, with a non-significant but directionally similar decrease in the dlPFC; sex-stratified analyses revealed that hippocampal reductions were strongest in male donors. Parallel analyses showed modest hippocampal downregulation of the paired receptor gene HTR5A, again driven primarily by males. Developmental transcriptomes revealed region-specific developmental trajectories, with steep increases during adolescence, aligning with the age range of typical schizophrenia onset. HTR5A-AS1 was strongly co-expressed with HTR5A, and functional predictions implicated involvement in synaptic and GABAergic signaling, consistent with cortico-hippocampal circuit disruption in schizophrenia.

Conclusions: These findings provide the first evidence that HTR5A-AS1 is a bona fide antisense transcript with developmental and synaptic roles that may contribute to schizophrenia risk. Future single-cell and functional perturbation studies are needed to test causality and define mechanisms of regulation.

Introduction: Monogenic neurodevelopmental disorders (mNDDs) such as SNAREopathies exhibit complex electrophysiological features and diversity among clinical symptoms, complicating the mapping of electro-clinical relationships, essential for improving diagnosis and treatment monitoring. Establishing robust normative electrophysiological feature distributions from typically developing populations enables precise, individualized quantification of patient-specific abnormalities. Here, we introduce a multivariate framework to reveal patient-specific electrophysiological phenotypes and clinical severity dimensions of direct relevance for individual prognosis and therapeutic tracking.

Methods: We analyzed resting-state electroencephalography (EEG) data from15 SNAREopathy subjects (STXBP1 and SYT1) and 96 age-matched healthy controls. EEG biomarkers, including absolute power, relative power, and long-range temporal correlations (LRTC), were estimated across frequency bands and functional networks. Normative baselines of EEG features were established using principal component analysis (PCA) on controls. We computed patient deviations from normative distributions using Mahalanobis distances. We summarized clinical severity by applying PCA to assessments of motor, manual, communication, adaptive functioning, and severity ranking of qualitative EEG.

Results: The normative qEEG space identified diffuse, spectro-spatial patterns for absolute power, while relative power and LRTC displayed frequency-specific distributions. Clinical PCA identified a primary dimension of clinical impairment integrating deficits in mobility, hand function, communication, and adaptive behavior, whereas the secondary component captured the severity of qualitative EEG abnormalities. Patient deviations from normative absolute and relative power correlated with the primary, while LRTC deviations aligned with the secondary severity component.

Discussion: Normative qEEG deviance metrics correspond to distinct clinical severity dimensions in SNAREopathies, making them promising for tracking disorder progression and therapeutic response.

Spiking Neural Networks (SNNs) offer a paradigm of energy-efficient, event-driven computation that is well-suited for processing asynchronous sensory streams. However, training deep SNNs robustly in an online and continual manner remains a formidable challenge. Standard Backpropagation-through-Time (BPTT) suffers from a prohibitive memory bottleneck due to the storage of temporal histories, while local plasticity rules often fail to balance the trade-off between rapid acquisition of new information and the retention of old knowledge (the stability-plasticity dilemma). Motivated by the tripartite synapse in biological systems, where astrocytes regulate synaptic efficacy over slow timescales, we propose Astrocyte-Gated Multi-Timescale Plasticity (AGMP). AGMP is a scalable, online learning framework that augments eligibility traces with a broadcast teaching signal and a novel astrocyte-mediated gating mechanism. This slow astrocytic variable integrates neuronal activity to dynamically modulate plasticity, suppressing updates in stable regimes while enabling adaptation during distribution shifts. We evaluate AGMP on a comprehensive suite of neuromorphic benchmarks, including N-Caltech101, DVS128 Gesture, and Spiking Heidelberg Digits (SHD). Experimental results demonstrate that AGMP achieves accuracy competitive with offline BPTT while maintaining constant $O\left(1\right)$ temporal memory complexity. Furthermore, in rigorous Class-Incremental Continual Learning scenarios (e.g., Split CIFAR-100), AGMP significantly mitigates catastrophic forgetting without requiring replay buffers, outperforming state-of-the-art online learning rules. This work provides a biologically grounded, hardware-friendly path toward autonomous learning agents capable of lifelong adaptation.

Nocifensive behavior (NB) is a protective response to noxious stimuli that threaten tissue damage. However, similar motor responses, termed nocifensive-like behavior (NLB), can be evoked by unexpected innocuous stimuli. This observation challenges strict "labeled-line" models of pain, raising a fundamental question: how does the nervous system discriminate true threats from false alarms? We review evidence suggesting NB and NLB exist on a shared behavioral continuum, where defensive responses aren't determined solely by sensory input but by the brain's integrated threat assessment. This assessment computes the probability of harm by weighing somatosensory input against contextual factors like prior experience and multisensory cues. We propose this process is governed by a threat prediction error (TPE) mechanism, which is computationally analogous to the reward prediction error (RPE) mechanism encoded by the dopaminergic system. Under this framework, defensive responses are scaled to the magnitude of the TPE - the discrepancy between expected and actual sensory outcomes. Critically, this means the surprise of a benign touch in a dangerous environment can produce a larger TPE - and a stronger withdrawal - than the anticipation of a noxious pinprick in a safe environment. Furthermore, while NLB represents an adaptive response that can be permanently resolved as the stimulus is learned to be non-threatening, NB represents an innate response, permitting only transient suppression due to the real risk of injury. This model positions defensive behaviors as dynamic perceptual decisions arising from probabilistic inference, offering a unified theory for how context and expectation gate the expression of protective motor programs.

Introduction: Resting-state functional magnetic resonance imaging (rs-fMRI) is a widely used non-invasive technique for investigating brain function and identifying potential disease biomarkers. Compared with task-based fMRI, rs-fMRI is easier to acquire because it does not require explicit task paradigms. However, functional connectivity measures derived from rs-fMRI often exhibit poor reliability, which substantially limits their clinical applicability.

Methods: To address this limitation, we propose a novel method termed time-enhanced functional connectivity, which improves reliability by identifying and removing poor-quality time points from rs-fMRI time series. This approach aims to enhance the quality of functional connectivity estimation without extending scan duration or relying on dataset-specific constraints.

Results: Experimental results demonstrate that the proposed method significantly improves performance in downstream machine learning tasks, such as sex classification. In addition, time-enhanced functional connectivity yields higher test-retest reliability and reveals more pronounced statistical differences between groups compared with conventional functional connectivity measures.

Discussion: These findings suggest that selectively removing low-quality time points provides a practical and effective strategy for improving the reliability and sensitivity of functional connectivity measurements in rs-fMRI, thereby enhancing their potential utility in both neuroscience research and clinical applications.

The autonomic nervous system (ANS) is a central regulator of cardiovascular function, coordinating involuntary control of heart rate, vascular tone, and blood pressure through its sympathetic (SNS) and parasympathetic (PNS) subdivisions. The SNS mediates the "fight or flight" response via catecholamines, increasing heart rate, contractility, and vasoconstriction, whereas the PNS promotes restorative processes through acetylcholine, decreasing heart rate and enhancing vasodilation. Nitric oxide further modulates vascular tone and autonomic balance, serving as a key neuromodulator. Assessment of cardiovascular autonomic function relies on heart rate variability, baroreflex sensitivity, and other physiological tests, which provide insight into the dynamic interplay between sympathetic and parasympathetic activity. Dysregulation of the ANS contributes to cardiovascular pathologies, including cardiovascular autonomic neuropathy, hypertension, and heart failure, where sympathetic overactivity and impaired parasympathetic modulation exacerbate disease progression. Pharmacologic interventions, such as β-blockers and ivabradine, alongside non-pharmacologic approaches, including structured exercise and respiratory training, aim to restore autonomic balance and improve clinical outcomes. Understanding the exact mechanisms of autonomic neurotransmission is essential for identifying novel therapeutic targets and optimizing cardiovascular care. Future research integrating molecular, genetic, and systems-level analyses will further elucidate autonomic regulation, guiding personalized interventions to mitigate cardiovascular morbidity and mortality.

Aim: This study aimed to investigate the brain activity involved in visually evoked auditory response (vEAR) using high-density electroencephalography (EEG) and explore the differences in connections between visual and auditory cortex.

Methods: Thirty-seven subjects with vEAR and Thirty four subjects without vEAR, matched by age and gender, were recruited. The hearing threshold, years of education, and the Trail Making Test (versions A and B) results were collected from all patients. All participants underwent a 256-channel EEG, and neurophysiological differences were evaluated using standardized low-resolution brain electromagnetic tomography (sLORETA).

Results: Trail Making Test scores in vEAR group were 17.3 ± 2.70 s and 26.28 ± 3.83 s for versions A and B, respectively, and 20.13 ± 6.88 s and 46.65 ± 5.971 s, respectively, in non-vEAR group. Significant difference in version B score was observed between two groups. Compared with non-vEAR group, significant differences were observed at the delta (p = 0.005), theta (p = 0.016), alpha1 (p = 0.016), alpha2 (p = 0.011), beta3 (p = 0.024), and gamma (p = 0.048) frequency bands in vEAR group. In addition, vEAR group showed significantly reduced activation of the posterior cingulate cortex (BA31, p = 0.0306) at the alpha2 frequency band and the insular cortex (BA13, p = 0.0306) at the beta2 frequency band. Moreover, significantly increased synchronized beta3 connectivity was found between the right part of the cingulate cortex (BA30) and the right primary auditory cortex (BA41) in vEAR group (p = 0.045).

Conclusion: vEAR group showed stronger regional connection characteristics than non-vEAR group, which may represent a neural signature associated with vEAR.

Background/objectives: The existing literature on normative data for accommodative facility (AF) in African populations is limited to high school students. There is no normative data for vergence facility (VF) in African children, so there are no benchmarks for comparison in case analysis, diagnosis, and management. The study aimed to establish normative data for AF in children aged 8-12 years. Additionally, the study sought to determine normative data for VF in children aged 8-17 years in the Cape Coast metropolis, Ghana.

Methods: Normal children (510) were recruited through a comprehensive oculo-visual examination of 2,300 basic school-going children, aged 8-17 years. AF was measured with a ± 2D flipper lens for 1 min. VF was measured with a 3-base-in/12 base-out flipper prism for 1 min. Normative data were derived using the median with interquartile ranges (IQR) and considering the spread of data within the minimum and maximum ranges.

Results: A median value of 13 cpm with IQR of 4 cpm was determined for monocular accommodative facility (MAF). The normative central tendency for MAF for school children 8-17 years ranges from 9 to 17 cpm; data were widely spread, with a minimum of 4 and a maximum of 20 cpm. A median value of 13 cpm with IQR of 3 cpm was determined for the binocular accommodative facility (BAF). The normative central tendency for BAF for school children aged 8-17 years ranged from 9 to 14 cpm; data were widely spread, with a minimum of 5 and a maximum of 20 cpm. A median value of 14 cpm with IQR of 4 cpm was determined for VF. The normative central tendency for VF for school children 8-17 years ranged from 10 to 18 cpm; data were widely spread, with a minimum of 6 and a maximum of 21 cpm.

Conclusion: The normative data apply only to similarly aged Ghanaian children and serve as standards for comparison to clinical data for MAF, BAF, and VF during case analysis.