Neuroscience最新文献

Routine behaviours can become habitual, persisting even when task goals have changed. Thus, it is important that we understand how these behaviours, and their underlying neurophysiological mechanisms, can be modulated. In the current experiment, participants were trained across multiple sessions to associate specific stimuli on a computer monitor with a key-press response. This learned action tendency, developed through repeated stimulus-response pairings, was then reduced using an extinction procedure in which the stimulus was repeatedly presented but no response was to be made. The underlying neurophysiological mechanisms of the learned response and its subsequent extinction were investigated using motor-evoked potentials (MEP) elicited by transcranial magnetic stimulation (TMS) delivered to the primary motor cortex (M1). We observed that exposure to the conditioned stimulus increased corticospinal excitability in M1, and this effect was modulated by the extinction procedure. We also found evidence that stimulation of M1 using TMS can trigger the release of a cued motor response that may have otherwise been withheld. This novel finding supports the notion that an associated motor plan is generated automatically in M1 when perceiving a conditioned stimulus associated with responding. Implications of these results in the context of conditioned action tendencies are discussed.

Engineered exosomes are modified extracellular vesicles designed to enhance targeting and cargo delivery, and they have been proposed as a therapeutic strategy for Alzheimer's disease. We systematically reviewed preclinical animal studies evaluating engineered exosomes, synthesized evidence from comparisons with disease models and with natural exosomes, and reported the study in accordance with the PRISMA 2020 checklist. Outcomes included spatial learning and memory assessed by the Morris water maze, amyloid beta pathology, tau phosphorylation, and neuroinflammatory markers. Random effects meta-analyses suggested that engineered exosomes improved Morris water maze performance and reduced amyloid beta burden and pro-inflammatory cytokines compared with natural exosomes, whereas evidence regarding tau phosphorylation was limited and largely qualitative, and the overall certainty of evidence was low to very low. These findings support further investigation of engineered exosomes, but conclusions should be interpreted cautiously until confirmed by rigorously designed and blinded preclinical studies and clinical trials with standardized protocols.

Stress is frequently reported as a trigger for binge episodes, yet it remains unclear how subjective and physiological stress responses interact with cognitive and affective mechanisms to increase binge eating risk. The present study investigated the effects of acute psychosocial stress on binge urges, focusing on the role of state- and trait-level vulnerabilities. Twenty-eight individuals with BED were randomized to either a Stress condition (n = 14) or No-Stress condition (n = 14). Following an acute psychosocial stressor, participants completed the Stop-Signal Task to behaviourally assess inhibitory control. Self-reported mood, binge urge ratings and saliva samples for stress biomarker detection were collected at three timepoints throughout the experimental session. Results demonstrated that acute psychosocial stress elicited marked increases in total mood disturbance, without corresponding physiological stress responses and significantly impaired inhibitory control. Notably, only subjective stress responses were associated with greater binge urges, whereas physiological stress responses were not. This dissociation highlights subjective stress reactivity as a clinically meaningful mechanism of risk in BED, underscoring the potential value of interventions that target stress perception and regulation to reduce binge eating vulnerability.

Whole-brain segmentation constitutes a fundamental task in medical image analysis, providing quantitative assessment of fine-grained brain regions and serving as a cornerstone for both clinical practice and neuroscience research. Despite its importance, the task is inherently challenging given the numerous brain regions, pronounced inter-class heterogeneity, and sophisticated inter-class spatial dependencies. Accurate whole-brain segmentation requires not only precise delineation of local features but also comprehensive modeling of long-range dependencies and global contextual information. To tackle these challenges, we propose the Multi-Scale Channel-Mixing Hybrid Network (MSCMH-Net), a CNN-MLP hybrid framework integrating convolutional and MLP modules at multiple hierarchical levels. The framework leverages the strengths of CNNs to capture local features and spatial structures, while employing MLPs to model long-range dependencies and global contextual information. For integrating global and local information, a channel-mixing module incorporating an exponential moving average (EMA) fusion strategy is employed. A composite dataset of 106 brain MR scans was used, including 36 from MICCAI-2012, 30 from ADNI and 40 from OASIS. Ground truth labels were annotated and double-checked by experts. Comprehensive experiments conducted on the composite dataset validate that MSCMH-Net achieves competitive results relative to existing approaches.