Neuroscience
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Acceleration/deceleration forces are a common component of various causes of mild traumatic brain injury (mTBI) and result in strain and shear forces on brain tissue. A small quantifiable volume dubbed the compensatory reserve volume (CRV) permits energy transmission to brain tissue during acceleration/deceleration events. The CRV is principally regulated by cerebral blood flow (CBF) and CBF is primarily determined by the concentration of inspired carbon dioxide (CO2). ⋯ Ribonucleic acid (RNA) sequencing conducted four hpi revealed that CO2 exposure prevented mTBI-induced transcriptional alterations of several targets related to oxidative stress, immune, and inflammatory signaling. Quantitative real-time PCR analysis confirmed the prevention of mTBI-induced increases in mitogen-activated protein kinase kinase kinase 6 and metallothionein-2. These initial proof of concept studies reveal that increases in inspired CO2 mitigate the detrimental contributions of acceleration/deceleration events in mTBI and may feasibly be translated in the future to humans using a medical device seeking to prevent mTBI among high-risk groups.
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Visuospatial attention allows humans to selectively gate and prioritize visual (including salient, emotional) information for efficiently navigating natural visual environments. As emotions have been known to influence attentional performance, we asked if emotions also modulate the spatial distribution of visual attention and whether any such effect was further associated with individual differences in anxiety. Participants (n = 28) discriminated the orientation of target Gabor patches co-presented with distractors, speedily and accurately. ⋯ No correlation was observed between state - anxiety and the emotion-cued attention gradients. In sum, the results suggest that individual trait - anxiety levels influence the effect of negative and physiologically arousing emotion signals (e.g., Disgust) on the spatial distribution of visual attention. The findings could be of relevance for understanding biases in visual behaviour underlying affective states and disorders.
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Metabotropic glutamate receptor subtype 7 (mGluR7) is a member of the group III mGluRs, which localize to presynaptic active zones of the central nervous system. We previously reported that mGluR7 knockout (KO) mice exhibit ejaculatory disorders, although they have normal sexual motivation. We hypothesized that mGluR7 regulates ejaculation by potentiating the excitability of the neural circuit in the lumbosacral spinal cord, because administration of the mGluR7-selective antagonist into that region inhibits drug-induced ejaculation. ⋯ Histological examination indicated that mGluR7 controls sympathetic neurons as well as parasympathetic neurons. In view of the complexity of its synaptic regulation, mGluR7 might control ejaculation by multi-level and multi-modal mechanisms. Our study provides insight into the mechanism of ejaculation as well as a strategy for future therapies to treat ejaculatory disorders in humans.
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A growth mindset refers to an individual's beliefs about the malleable nature of intelligence. It plays an important role in motivation and achievement. However, few studies have examined the brain mechanisms involved in the growth mindset. ⋯ Whole-brain correlation analyses showed a positive relationship between growth mindset scores and regional GMV of the medial orbitofrontal cortex (mOFC) after controlling for age, sex, and total intracranial volume. This result was robust after controlling for intelligence quotient. The mOFC was primarily related to reward processing, supporting the social-cognitive theory of motivation on growth mindset.
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Parkinson's disease (PD) is one of the leading causes of neurological disability, and its prevalence is expected to increase rapidly in the following few decades. PD diagnosis heavily depends on clinical features using the patient's symptoms. Therefore, an accurate, robust, and non-invasive bio-marker is of critical clinical importance for PD. ⋯ The proposed methodology is applied to three open fMRI databases for demonstration and validation. The PD diagnosis accuracy can reach 96.4% when the proposed methodology is used. Thus, rs-fMRI and topological machine learning provide a quantifiable and verifiable bio-marker for future PD early detection and treatment evaluation.