Journal of integrative neuroscience最新文献

Cognitive impairment represents a progressive neurodegenerative condition with severity ranging from mild cognitive impairment (MCI) to dementia and exerts significant burdens on both individuals and healthcare systems. Vascular cognitive impairment (VCI) represents a heterogeneous clinical continuum, spanning a spectrum from subcortical ischemic VCI (featuring small vessel disease, white matter lesions, and lacunar infarcts) to mixed dementia, where vascular and Alzheimer's-type pathologies coexist. While traditionally linked to macro- and microvascular dysfunction, the mechanisms underlying VCI remain complex. However, contemporary research has gone beyond structural vascular damage, highlighting the neurovascular unit (NVU) as a critical mediator. Emerging evidence demonstrates that cerebral endothelial cells within the NVU not only regulate oxygen and nutrient transport but also orchestrate neuroinflammatory signaling and neurovascular coupling (NVC). Crucially, endothelial dysfunction initiates a self-perpetuating cycle of NVU dysregulation characterized by: (1) NVC impairment through diminished nitric oxide bioavailability and calcium signaling defects, (2) blood-brain barrier (BBB) breakdown via tight-junction protein degradation and pericyte detachment, and (3) neuroinflammation driven by endothelial-derived cytokine release and leukocyte infiltration. By integrating recent advances in NVU biology, we have established a framework to inform clinical strategies for early diagnosis and targeted therapies, which we outline in this review. Moreover, proactive management of vascular risk factors (e.g., hypertension, diabetes) in presymptomatic stages may mitigate the progression from vascular injury to irreversible dementia, underscoring its preventive potential. These insights reinforce the idea that preserving NVU integrity represents a pivotal approach to mitigating the global dementia burden.

Background: Emotion recognition from electroencephalography (EEG) can play a pivotal role in the advancement of brain-computer interfaces (BCIs). Recent developments in deep learning, particularly convolutional neural networks (CNNs) and hybrid models, have significantly enhanced interest in this field. However, standard convolutional layers often conflate characteristics across various brain rhythms, complicating the identification of distinctive features vital for emotion recognition. Furthermore, emotions are inherently dynamic, and neglecting their temporal variability can lead to redundant or noisy data, thus reducing recognition performance. Complicating matters further, individuals may exhibit varied emotional responses to identical stimuli due to differences in experience, culture, and background, emphasizing the necessity for subject-independent classification models.

Methods: To address these challenges, we propose a novel network model based on depthwise parallel CNNs. Power spectral densities (PSDs) from various rhythms are extracted and projected as 2D images to comprehensively encode channel, rhythm, and temporal properties. These rhythmic image representations are then processed by a newly designed network, EEG-ERnet (Emotion Recognition Network), developed to process the rhythmic images for emotion recognition.

Results: Experiments conducted on the dataset for emotion analysis using physiological signals (DEAP) using 10-fold cross-validation demonstrate that emotion-specific rhythms within 5-second time intervals can effectively support emotion classification. The model achieves average classification accuracies of 93.27 ± 3.05%, 92.16 ± 2.73%, 90.56 ± 4.44%, and 86.68 ± 5.66% for valence, arousal, dominance, and liking, respectively.

Conclusions: These findings provide valuable insights into the rhythmic characteristics of emotional EEG signals. Furthermore, the EEG-ERnet model offers a promising pathway for the development of efficient, subject-independent, and portable emotion-aware systems for real-world applications.

Background: Neurofibrillary tangles, composed of hyperphosphorylated tau, have been implicated in the cognitive impairments observed in Alzheimer's disease. While the precise mechanism remains elusive, cognitive deficits in Alzheimer's disease have been associated with disrupted brain network activity. To investigate this mechanism, researchers have developed several tau transgenic models. However, the extent of variability in cortical network alterations across different genetic backgrounds and ages is still not clearly defined.

Objective: To evaluate the oscillatory alterations in relation to animal developmental age and hyperphosphorylated tau protein accumulation, we reviewed and analyzed the published data on peak power and quantification of theta-gamma cross-frequency coupling (modulation index values).

Methods: A systematic review was conducted to locate and extract all studies published from January, 2002 to March, 2024 involving in vivo cortical local field potential recording in tau transgenic mouse models, ensuring the most current search results. Our meta-analysis was conducted following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines.

Results: The presence of hyperphosphorylated tau was associated with oscillatory alterations primarily reflected in power decreases, while modulation index values did not exhibit significant alterations.

Conclusions: In this analysis, we uncovered that neuronal oscillations in cortical networks are altered from the prodromal to late stages of pathology. Additionally, we found that hyperphosphorylated tau accumulation is strongly associated with cortical network hypoexcitability in tau transgenic models.

Background: Sodium homeostasis is crucial for physiological balance, yet the neurobiological mechanisms underlying sodium appetite remain incompletely understood. The nucleus tractus solitarii (NTS) integrates visceral signals to regulate feeding behaviors, including sodium intake. This study investigated the role of 11β-hydroxysteroid dehydrogenase type 2 (HSD2)-expressing neurons in the NTS in mediating sodium appetite under low-sodium diet (LSD) conditions and elucidated the molecular pathways involved, particularly the cyclic adenosine monophosphate (cAMP)/mitogen-activated protein kinase (MAPK) signaling cascade.

Methods: Using a murine model, sodium preference was assessed via a two-bottle choice test following LSD exposure. Previously published single-cell RNA sequencing data were re-analyzed to profile the transcriptional changes in HSD2 neurons. Pharmacological interventions employed MAPK inhibitor U0126 and cAMP inhibitor KH7 to dissect signaling contributions. Anterograde tracing and immunohistochemistry techniques were used to verify the efferent projections of HSD2 neurons. Autonomic function was evaluated by measuring blood pressure (BP), heart rate (HR), and phrenic nerve discharge (PND) parameters in anesthetized mice during HSD2 neuron activation.

Results: LSD significantly activated HSD2 neurons and increased sodium intake. scRNA-seq analysis revealed upregulation of genes in the cAMP/MAPK pathways under LSD conditions. Pharmacological blockade of these pathways abolished LSD-induced sodium appetite. Anterograde tracing confirmed three primary downstream targets: the pre-locus coeruleus (pre-LC), lateral parabrachial nucleus (PBcL), and ventral lateral bed nucleus of the stria terminalis (vlBNST). Notably, HSD2 neuron activation did not alter BP, HR, or PND parameters, indicating no direct role in autonomic regulation.

Conclusions: LSD induces the activation of HSD2 neurons, which in turn causes sodium intake, a phenomenon that is eliminated by blocking the cAMP/MAPK signaling pathway. These neurons project to key forebrain and brainstem regions implicated in motivational behavior but do not directly modulate cardiovascular/respiratory functions. By replicating and extending prior research, this study supports and expands the present understanding of this field.

Background and purpose: Ciprofol, a novel intravenous anesthetic, has been shown to exert protective effects against ischemic stroke, a leading cause of death and disability; however, its molecular mechanisms remain unclear. This study aimed to explore the molecular mechanisms underlying the neuroprotective effects of ciprofol using metabolomics.

Methods: This study used a middle cerebral artery occlusion (MCAO) rat model to simulate cerebral ischemia-reperfusion injury (CIRI). The rats were divided into ciprofol, MCAO, and sham groups. Histological and neurobehavioral testing methods were used to investigate the therapeutic effects of ciprofol in rats. Ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry was used to screen for differential metabolites and related metabolic pathways in the serum and brain of the three groups. Spectrophotometry was used to detect in vitro mitochondrial respiratory chain complex I (MRCC-I) activity.

Results: Neurological behavioral scores and cerebral infarct volumes of rats in the ciprofol group were significantly lower than those of rats in the MCAO group. Metabolomic analysis revealed 19 differential metabolites in serum samples and 31 differential metabolites in brain samples, including flavin mononucleotide (FMN). These metabolites were mainly enriched in the tricarboxylic acid cycle, respiratory electron transport chain, and amino acid and lipid metabolism. In vitro experiments demonstrated that ciprofol promoted the activity of MRCC-I during CIRI by increasing FMN levels.

Conclusion: The mechanisms of action of ciprofol during treatment of cerebral ischemia involve the tricarboxylic acid cycle, respiratory electron transport chain, and amino acid and lipid metabolism and may directly affect MRCC-I activity by regulating FMN.

There is a growing body of evidence that the interaction between various microbial organisms and the human host can affect various physical and even mental health conditions. Bidirectional communication occurs between the brain and the gut microbiome, referred to as the brain-gut-microbiome axis. During aging, changes occur to the gut microbiome due to various events and factors such as the mode of delivery at birth, exposure to medications (e.g., antibiotics), environmental exposures, diet, and host genetics. Connections to the brain-gut-microbiome axis through different systems also change during aging, leading to the development of chronic diseases. Disruption of the gut microbiome, known as dysbiosis, can lead to a reduction in beneficial bacteria and a corresponding increase in more harmful or even pathogenic bacteria. This imbalance may predispose or contribute to the development of various health conditions and illnesses. Targeted treatment of the gut microbiome and the brain-gut-microbiome axis may assist in the overall management of these various ailments. The purpose of this review is to describe the changes that occur in the gut microbiome throughout life, and to highlight the risk factors for microbial dysbiosis. We discuss the different health conditions experienced at various stages of life, and how dysbiosis may contribute to the clinical presentation of these diseases. Modulation of the gut microbiome and the brain-gut-microbiome axis may therefore be beneficial in the management of various ailments. This review also explores how various therapeutics may be used to target the gut microbiome. Gut biotics and microbial metabolites such as short chain fatty acids may serve as additional forms of treatment. Overall, the targeting of gut health may be an important strategy in the treatment of different medical conditions, with nutritional modulation of the brain-gut-microbiome axis also representing a novel strategy.

Background: Pilots often experience mental fatigue during task performance, accompanied by fluctuations in positive (e.g., joy) and negative (e.g., tension) emotions. Both mental fatigue and emotional changes significantly contribute to aviation accidents, yet few studies have considered their interplay. This study had three primary objectives. First, it examined the changes in positive and negative emotions following mental fatigue. Second, it investigated how these emotions influence the recovery from fatigue. Finally, it developed a comprehensive evaluation model integrating mental fatigue and emotional states.

Methods: Two task sets were created using the visual search paradigm, incorporating simulated flight tasks with positive and negative emotional stimuli. Data were collected from 30 participants using electroencephalogram (EEG), eye-tracking, electrocardiogram (ECG), and behavioral performance metrics.

Results: Participants showed mental fatigue after the simulated flight task, with reduced arousal for both positive and negative emotions; positive images had stronger effects. ERP showed decreased N1, P3, and LPP amplitudes. A Support Vector Machine (SVM) classifier achieved over 93% accuracy for fatigue but about 70% for emotion recognition.

Conclusions: The task effectively induced fatigue and indicated that positive stimuli may aid recovery. Multimodal features support accurate fatigue detection, though emotion classification needs improvement Clinical Trial Registration: No: ChiCTR2500104961. https://www.chictr.org.cn/showproj.html?proj=267844.

Sleep paralysis, colloquially known as "ghost pressing" is a state of momentary bodily immobilization occurring either at the onset of sleep or upon awakening. It is characterized by atonia during rapid eye movement (REM) sleep that continues into wakefulness, causing patients to become temporarily unable to talk or move but possessing full consciousness and awareness of their surroundings. Sleep paralysis is listed in the International Classification of Sleep Disorders, 3rd Edition (ICSD-3) as a parasomnia occurring during REM sleep that be classified as either isolated or narcolepsy-associated. Several brain areas, including the forebrain, hypothalamus, and brainstem, as well as several neurotransmitters and modulators, are involved in the control of REM sleep. The primary brain region responsible for inducing muscle paralysis during REM sleep is the subcoeruleus nucleus, also known as the sublaterodorsal (SLD) nucleus in rats. Sleep paralysis results from the inability to immediately restore muscle tone during the transition from sleep to wakefulness. In this article, we systematically review the neural circuit that controls REM sleep and the underlying mechanisms, predisposing factors, clinical characteristics, and treatments for sleep paralysis. We also compare isolated sleep paralysis (ISP) and narcolepsy-associated sleep paralysis and speculate upon the role of microsleep in sleep paralysis.