Neuroscience
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With the increased availability and sophistication of digital devices in the last decade, young people have become mainstream mobile phone users. Heavy mobile phone dependence causes affective problems (depression, anxiety) and loss of attention on current activities, leading to more cluttered thoughts. Problematic mobile phone use has been found to increase the occurrence of mind wandering, but the neural mechanism underlying this relationship remains unclear. ⋯ FC between the frontoparietal and motor networks, between the default mode network and cerebellar network, and within the cerebellar network mediated the relationship between mobile phone addiction and mind wandering. The findings confirm that mobile phone addiction is a risk factor for increased mind wandering and reveal that FC in several brain networks underlies this relationship. They contribute to research on behavioral addiction, education, and mental health among young adults.
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Cellular senescence is involved in the progression of neurodegenerative diseases. Motor neurons exhibit senescence-like alterations in ALS. BRD7, identified as a regulatory factor associated with cellular senescence, its function in ALS remains unclear. ⋯ Knockdown of BRD7 inhibited p53 mitochondrial translocation, leading to reduced apoptosis. Our results suggest that BRD7 plays an important role in the survival of ALS motor neurons. BRD7 knockdown can reduce cellular senescence and apoptosis by inhibiting p21 and p53 mitochondrial translocation.
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Previous research has shown that visual impairment results in reduced audio, tactile and proprioceptive ability. One hypothesis is that these issues arise from inaccurate body representations. Few studies have investigated metric body representations in a visually impaired population. ⋯ Our results showed thatblind participants overestimated their hands and feetto a similar degree. Sighted controls overestimated their hands significantly more than their feet. Taken together, our results partially support our hypothesis and suggest that visual deprivation, even for short periods result in hand size overestimation.
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Essential tremor with resting tremor (rET) and tremor-dominant Parkinson's disease (tPD) share many similar clinical symptoms, leading to frequent misdiagnoses. Functional connectivity (FC) matrix analysis derived from resting-state functional MRI (Rs-fMRI) offers a promising approach for early diagnosis and for exploring FC network pathogenesis in rET and tPD. However, methods relying solely on a single connection pattern may overlook the complementary roles of different connectivity patterns, resulting in reduced diagnostic differentiation. ⋯ Compared with single-pattern GCN, our proposed MCGCN model demonstrated superior classification accuracy, underscoring the advantages of integrating multiple connectivity modes. Specifically, the model achieved an average accuracy of 88.0% for distinguishing rET from HC, 88.8% for rET from tPD, and 89.6% for tPD from HC. Our findings indicate that combining graph convolutional networks with multi-connection patterns can not only effectively discriminate between tPD, rET, and HC but also enhance our understanding of the functional network mechanisms underlying rET and tPD.
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A common anatomical core has been described for psychiatric disorders, consisting of the dorsal anterior cingulate cortex (dACC) and anterior insula, processing uncertainty. A common neurophysiological core has been described for other brain related disorders, called thalamocortical dysrhythmia (TCD), consisting of persistent cross-frequency coupling between low and high frequencies. And a common genetic core has been described for yet another set of hypodopaminergic pathologies called reward deficiency syndromes (RDS). ⋯ TCD and RDS share a common anatomical and neurophysiological core, consisting of beta activity in the dACC and theta activity in dACC extending into precuneus and dorsolateral prefrontal cortex. TCD and RDS differ in pgACC/vmPFC activity and demonstrate an opposite balance between pgACC/vmPFC and dACC. Based on the Bayesian brain model TCD and RDS can be defined as uncertainty disorders in which the pgACC/vmPFC and dACC have an opposite balance, possibly explained by an inverted-U curve profile of both pgACC/vmPFC and dACC.