Frontiers in Neuroscience最新文献

Objective: To investigate the optimal stimulation intensity and reference range of the unilateral centrifugation subjective visual vertical (UC-SVV) test and to fill the technical gap in otolithic function evaluation in patients with peripheral vestibular diseases.

Method: Forty healthy subjects (median age 28 years) underwent a UC-SVV test at rotation speeds of 60, 120, 180, and 240 deg./s using the Neuro Kinetics Inc. (NKI) I-Portal 6.0 NOTC rotating chair system. The deviation angles of the UC-SVV line in the centre and left/right positions at each rotation speed were recorded and analysed.

Results: Forty healthy subjects completed the test. The deviation angle of the UC-SVV line differed according to the rotation speed (60, 120, 180, and 240 deg./s). At each rotation speed, the position of the rotation axis (left/centre/right position) affected the deviation angle and direction of the UC-SVV line. At each position of the rotation axis, the rotation speed also affected the deviation angle. When the rotation chair was translated to the left and right positions, the UC-SVV line deviated to the right and left sides, respectively, and the deviation angle increased with increasing rotation speed. The deviation angle at 60 deg./s was significantly less than that at 180 and 240 deg./s (p < 0.001). When the rotation axis was in the centre position, the absolute value of the SVV deviation was less than 0.3, and there was no statistically significant difference at any rotation speed.

Conclusion: This study preliminarily discussed the deviation direction and angle of the UC-SVV line under different stimulation intensities in a range of healthy middle-aged subjects. The optimal stimulation intensity for the UC-SVV test is suggested to be 180 or 240 deg./s. Specifically, the peak rotation speed could be 180 deg./s if the subject is unable to tolerate high-speed rotation. This study provides support for improving this technology for evaluation of otolith function and its diagnostic significance in peripheral vestibular diseases.

Night shift is a prevalent workstyle in medical hospitals, demanding continuous health monitoring and rapid decision making of medical professionals. Night shifts may cause serious health problems to medical staff, including cognitive impairments, poor sleep, and inflammatory responses, leading to the altered gut-brain axis. However, how night shifts impact gut-brain axis and how long the impact lasts remain to be studied. Hence, we investigated the dynamic changes of brain-microbiota relations following night shifts and subsequent recovery days among medical shift workers. Young medical staffs were recruited for the 3-session assessments over the scheduled night shifts (pre-shift, post-shift, and recovery) by measuring (a) sleep metrics, (b) brain functions, (c) gut bacteriome compositions, and (d) cognitive assessments. Participants experienced partial sleep deprivation only during the 5-day night shifts but rapidly returned to baseline after the 4-day recovery, so as the elevated brain fluctuations in the superior frontal gyrus after night shifts. Meanwhile, the night shifts caused elongated connectivity changes of default-mode and dorsal attention networks without recovery. Nevertheless, we did not find prevailing night-shift effects on cognition and gut bacteriome compositions, except the Gemellaceae concentration and the multi-task performance. Collectively, night shifts may induce prolonged alterations on brain connectivity without impacts on gut bacteriome, suggesting the vulnerable brain functions and the resilient gut bacteriome to the short-term night shifts among medical shift workers.

Premenstrual syndrome (PMS) is characterized by emotional or physical discomfort that occurs specifically during the luteal phase. However, women with PMS typically do not exhibit abnormalities in serum sex hormone levels or structural anomalies, making it challenging to identify distinct pathological findings unique to PMS. Instead, they may exhibit hypersensitivity to fluctuations in sex hormone levels within the normal range. This study involved experiments conducted in the late luteal phase. The pre-stress baseline state evaluated the effects of PMS on interoception using the Heartbeat Counting Task (HCT) and the Multidimensional Assessment of Interoceptive Awareness (MAIA), and the effects on emotional states using a questionnaire assessing subjective emotions in the late luteal phase. The results indicated that the "PMS group" scored higher on the HCT compared to the "without PMS group," while their MAIA scores were lower. Additionally, the PMS group reported experiencing more negative and stressful states. The findings suggest that women with PMS demonstrate high accuracy in but lower awareness of interoception. This mismatch between "accuracy" and "awareness" may indicate a maladaptive state regarding mental health. The stress-related analysis examined whether the effects of stress on exacerbating PMS include impacts on interoception and the autonomic nervous system (ANS). States before baseline, immediately after, and during stress recovery were evaluated. The results revealed that women in the PMS group exhibited more pronounced negative and stressful states; they showed higher scores on the HCT, with scores progressively increasing as the task was repeated. Regarding ANS indices, no main effect of group was observed, but parasympathetic activity increased during the recovery period compared to the pre-stress baseline. In the degree of changes in parasympathetic activity from the baseline to post-stress and recovery periods, a group-by-time interaction effect was observed. These findings suggest that the PMS group may experience a prolonged rebound effect during the recovery phase following induced stress. In conclusion, women with PMS exhibit a discrepancy between high interoceptive accuracy and low awareness of their sensations. This may contribute to heightened discomfort and suggest that vulnerability to stress, mediated by the parasympathetic nervous system, exacerbates factor for PMS symptoms.

[This corrects the article DOI: 10.3389/fnins.2019.00254.].

Introduction: In most mammals, paternal care is not mandatory for raising offspring. In house mice, experience with pups governs the extent and quality of paternal care. First-time fathers undergo a dramatic transition from ignoring or killing pups to caring for pups. The behavioral shift occurs together with changes in brain estrogen signaling as indicated by changes in estrogen receptor presence and distribution in multiple areas regulating olfaction, emotion, and motivation.

Methods: We measured changes in the expression of aromatase, the enzyme converting testosterone into estrogen, as an indirect measure of estrogen synthesis, in various areas of the limbic system in mice with increasing paternal experience.

Results: The amount of paternal experience (5 or 27 days) was associated with increased numbers of immunocytochemically-identified aromatase expressing cells in the medial and cortical amygdala, posterior piriform cortex, and ventromedial hypothalamus. Functionally, these changes can be related to the disappearance of aggression or neglect towards pups when first-time fathers or, even more, well-experienced fathers are handling their own pups. In the lateral septum, the anterior piriform cortex and to some extent in the medial preoptic area, parental experience increased the number of aromatase-positive cells only in fathers with 27 days of experience, and only in the right hemisphere. This represents a novel case of brain-functional lateralization triggered by experience. Nuclei/areas associated with maternal care (medial preoptic area, bed nucleus of stria terminalis, nucleus accumbens) exhibited a left-hemisphere advantage in aromatase expressing cells, both in pup-naïve and pup-experienced males. This newly found lateralization may contribute to the left-hemisphere dominant processing and perception of pup calls to release parental behavior.

Conclusion: In general, the experience-dependent changes in aromatase expression we observed in most brain areas did not mirror the previously reported changes in estrogen receptors (ERα) when pup-naïve males became pup-caring fathers. Hence, paternal behavior may depend, in a brain area-specific way, on the differential action of estrogen through its receptors and/or direct local modulation of neural processing.

The brain-gut axis (BGA) is emerging as a critical mediator in chronic pain, involving bidirectional communication between the central nervous system and the gastrointestinal system. The "Pain Matrix" is associated with microbial dysbiosis, vagus nerve dysfunction, and hypothalamic-pituitary-adrenal (HPA) axis dysregulation, driving neuroinflammation and central sensitization. Key mechanisms include microbial diversity loss, leaky gut, and altered neuroactive signaling via short-chain fatty acids (SCFAs) and vagal pathways. This narrative review explores the intricate interplay between BGA mechanisms and chronic pain, highlighting therapeutic opportunities such as restoring dysbiosis, modulating vagus nerve activity, and regulating endocrine pathways. These interventions target inflammation, autonomic balance, and stress/reward pathway modulation, offering a promising path toward integrative pain management. Further research is required to validate these strategies and improve patient outcomes.

Background and objective: Autophagy is a natural process regulated by autophagy-related genes in eukaryotic cells that involves the degradation of cytoplasmic proteins and old or damaged organelles via the lysosomal pathway to help maintain cell homeostasis. Previous studies have suggested a potential association between autophagy and migraine, while the underlying mechanisms remain unclear. This review seeks to evaluate the possible involvement of autophagy in the pathophysiology of migraine, aiming to clarify its role and implications for future research and therapeutic strategies.

Methods: A search in PubMed was conducted for English-language articles until December 5, 2024. Key terms of "autophagy," "migraine," "microglia," "neurogenic inflammation," "central sensitization," "mitophagy" and "neuropathic pain" in different combinations.

Results: In the context of migraine, the activation of the phosphoinositide 3-kinase (PI3K)/protein kinase B (PKB/Akt) signaling pathway exerts a direct influence on the mammalian target of rapamycin (mTOR), leading to a reduction in autophagy levels. Moreover, the stimulation of purinergic ligand-gated ion channel type 7 receptor (P2X7R) in microglia can hinder autophagy by interfering with the fusion of autophagosomes and lysosomes, which impedes the degradation of substrates within the autophagolysosome. Increased levels of calcitonin gene-related peptide (CGRP) may also modulate autophagy through the Akt/mTOR or protein kinase A (PKA)/mTOR signaling pathways. Additionally, research indicates that mitophagy may be partially impaired in individuals suffering from migraine. Furthermore, autophagy could contribute to the dysregulation of synaptic plasticity by influencing the processes of long-term potentiation (LTP) and long-term depression (LTD), both of which are associated with central sensitization in chronic migraine.

Conclusion: These findings suggest that autophagy may play an important role in the pathophysiology of migraine, particularly in its development and central sensitization. Research on autophagy modulators related to migraine will provide valuable insights for treatment strategies.

With Moore's law nearing its end due to the physical scaling limitations of CMOS technology, alternative computing approaches have gained considerable attention as ways to improve computing performance. Here, we evaluate performance prospects of a new approach based on disordered superconducting loops with Josephson-junctions for energy efficient neuromorphic computing. Synaptic weights can be stored as internal trapped fluxon states of three superconducting loops connected with multiple Josephson-junctions (JJ) and modulated by input signals applied in the form of discrete fluxons (quantized flux) in a controlled manner. The stable trapped fluxon state directs the incoming flux through different pathways with the flow statistics representing different synaptic weights. We explore implementation of matrix-vector-multiplication (MVM) operations using arrays of these fluxon synapse devices. We investigate the energy efficiency of online-learning of MNIST dataset. Our results suggest that the fluxon synapse array can provide ~100× reduction in energy consumption compared to other state-of-the-art synaptic devices. This work presents a proof-of-concept that will pave the way for development of high-speed and highly energy efficient neuromorphic computing systems based on superconducting materials.

Background: Understanding how artificial intelligence (AI) is employed to predict, diagnose, and perform relevant analyses in Alzheimer's disease research is a rapidly evolving field. This study integrated and analyzed the relevant literature from the Science Citation Index (SCI) and Social Science Citation Index (SSCI) on the application of AI in Alzheimer's disease (AD), covering publications from 2004 to 2023.

Objective: This study aims to identify the key research hotspots and trends of the application of AI in AD over the past 20 years through a bibliometric analysis.

Methods: Using the Web of Science Core Collection database, we conducted a comprehensive visual analysis of literature on AI and AD published between January 1, 2004, and December 31, 2023. The study utilized Excel, Scimago Graphica, VOSviewer, and CiteSpace software to visualize trends in annual publications and the distribution of research by countries, institutions, journals, references, authors, and keywords related to this topic.

Results: A total of 2,316 papers were obtained through the research process, with a significant increase in publications observed since 2018, signaling notable growth in this field. The United States, China, and the United Kingdom made notable contributions to this research area. The University of London led in institutional productivity with 80 publications, followed by the University of California System with 74 publications. Regarding total publications, the Journal of Alzheimer's Disease was the most prolific while Neuroimage ranked as the most cited journal. Shen Dinggang was the top author in both total publications and average citations. Analysis of reference and keyword highlighted research hotspots, including the identification of various stages of AD, early diagnostic screening, risk prediction, and prediction of disease progression. The "task analysis" keyword emerged as a research frontier from 2021 to 2023.

Conclusion: Research on AI applications in AD holds significant potential for practical advancements, attracting increasing attention from scholars. Deep learning (DL) techniques have emerged as a key research focus for AD diagnosis. Future research will explore AI methods, particularly task analysis, emphasizing integrating multimodal data and utilizing deep neural networks. These approaches aim to identify emerging risk factors, such as environmental influences on AD onset, predict disease progression with high accuracy, and support the development of prevention strategies. Ultimately, AI-driven innovations will transform AD management from a progressive, incurable state to a more manageable and potentially reversible condition, thereby improving healthcare, rehabilitation, and long-term care solutions.