Neuroscience
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Individuals with mild cognitive impairment (MCI) are regarded as being at high risk of developing Alzheimer's disease (AD). The apolipoprotein E (APOE) ε4 allele is a well-established genetic risk factor for developing AD. In the present study, by using voxel-mirrored homotopic connectivity (VMHC), we aimed to explore the potential functional disruptions in MCI APOE-ε4 carriers. ⋯ The results showed that MCI APOE-ε4 carriers presented increased VMHC in the inferior frontal gyrus/insula and middle frontal gyrus/superior frontal gyrus in comparison with noncarriers. We found that MCI APOE-ε4 carriers showed increased functional connectivity between the seed regions (bilateral inferior frontal gyri/insula and bilateral middle frontal gyri/superior frontal gyri) and broad brain areas, including the frontal, temporal, parietal, and cerebellar regions. Our findings provide neuroimaging evidence for the modulation of the APOE genotype on the neurodegenerative disease phenotype and may be potentially important for monitoring disease progression in double-high-risk populations of AD.
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Myofascial pain syndrome (MPS) is a type of skeletal pain identified by myofascial trigger points (MTrPs). The formation of MTrPs is linked to muscle damage. The fibroblast growth factor receptor (FGFR1) has been found to cause pain sensitivity while repairing tissue damage. ⋯ PD173074 increased the mechanical pain threshold of the MTrPs group, and inhibited the expression of p-FGFR1, PI3K-p110γ, and p-AKT. Moreover, LY294002 increased the mechanical pain threshold of the MTrPs group. These findings suggest that FGFR1 may regulate myofascial pain in rats through the PI3K/AKT pathway.
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This study aims to investigate the difference in cortical signal characteristics between the left and right foot imaginary movements and to improve the classification accuracy of the experimental tasks. Raw signals were gathered from 64-channel scalp electroencephalograms of 11 healthy participants. Firstly, the cortical source model was defined with 62 regions of interest over the sensorimotor cortex (nine Brodmann areas). ⋯ A few of statistically significant differences in the network properties were observed between tasks in the α and β rhythm. The SMLR-SVM classification model achieved fair discrimination accuracy between imaginary movements of the two feet (maximum 75% accuracy rate in single-trial analyses). This study reveals the network mechanism of the discrimination of the left and right foot motor imagery, which can provide a novel avenue for the BCI system by unilateral lower limb motor imagery.
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The application of resting state functional MRI (RS-fMRI) in Parkinson's disease (PD) was widely performed using standard statistical tests, however, the machine learning (ML) approach has not yet been investigated in PD using RS-fMRI. In current study, we utilized the mean regional amplitude values as the features in patients with PD (n = 72) and in healthy controls (HC, n = 89). The t-test and linear support vector machine were employed to select the features and make prediction, respectively. ⋯ Similar with previous neuroimaging studies in PD, the discriminative regions were mainly included the disrupted motor system, aberrant visual cortex, dysfunction of paralimbic/limbic and basal ganglia networks. The lateral parietal lobe, such as right inferior parietal lobe (IPL) and supramarginal gyrus (SMG), was detected as the discriminative features exclusively in Slow-4. Our findings, at the first time, indicated that the ML approach is a promising choice for detecting abnormal regions in PD, and a multi-frequency scheme would provide us more specific information.
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Individuals respond faster to presentations of bisensory stimuli (e.g. audio-visual targets) than to presentations of either unisensory constituent in isolation (i.e. to the auditory-alone or visual-alone components of an audio-visual stimulus). This well-established multisensory speeding effect, termed the redundant signals effect (RSE), is not predicted by simple linear summation of the unisensory response time probability distributions. Rather, the speeding is typically faster than this prediction, leading researchers to ascribe the RSE to a so-called co-activation account. ⋯ This intermixed design requires participants to switch between sensory modalities on many task trials (e.g. from responding to a visual stimulus to an auditory stimulus). Here we show that much, if not all, of the RSE under this paradigm can be attributed to slowing of reaction times to unisensory stimuli resulting from modality switching, and is not in fact due to speeding of responses to AV stimuli. As such, the present data do not support a co-activation account, but rather suggest that switching and mixing costs akin to those observed during classic task-switching paradigms account for the observed RSE.