Neuroscience
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Brain iron accumulation is a common feature shared by several neurodegenerative disorders including Parkinson's disease. However, what produces this accumulation of iron is still unknown. In this study, the 6-hydroxydopamine (6-OHDA) hemi-parkinsonian rat model was used to investigate abnormal iron accumulation in substantia nigra. ⋯ Presence of iron following dopamine cell degeneration was studied by MRI, which revealed hypointense signals in the substantia nigra. The presence of iron deposits was further validated in histological evaluations. Furthermore, iron inclusions were closely associated with active microglia and with increased levels of L-ferritin indicating a putative role for microglia and L-ferritin in brain iron accumulation and dopamine neurodegeneration.
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Recent data suggest that manipulating the muscle afferents of one arm affects both ipsilateral and contralateral perceptual estimates. Here, we used the mirror paradigm to study the bimanual integration of kinesthetic muscle afferents. The reflection of a moving hand in a mirror positioned in the sagittal plane creates an illusion of symmetrical bimanual movement. ⋯ We found that as long as the arm was still moving, the kinesthetic illusion decayed slowly after visual occlusion. These findings suggest that the mirror illusion results from the combination of visuo-proprioceptive signals from the two arms and is not purely visual in origin. Our findings also support the more general concept whereby proprioceptive afferents are integrated bilaterally for the purpose of kinesthesia during bimanual tasks.
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The fact that interference from peripheral distracting information can be reduced in high perceptual load tasks has been widely demonstrated in previous research. The modulation from the perceptual load is known as perceptual load effect (PLE). Previous functional magnetic resonance imaging (fMRI) studies on perceptual load have reported the brain areas implicated in attentional control. ⋯ DC-PLE correlation analysis revealed that PLE was positively associated with the right middle temporal visual area (MT)-one of dorsal attention network (DAN) nodes. Furthermore, the right MT functionally connected to the conventional DAN and the RSFCs between right MT and DAN nodes were also positively associated with individual difference in PLE. The results suggest an important role of attentional control in perceptual load tasks and provide novel insights into the understanding of the neural correlates underlying PLE.
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Studies have indicated that a cortical sensory system is capable of processing information from different sensory modalities. However, it still remains unclear when and how a cortical system integrates and retains information across sensory modalities during learning. Here we investigated the neural dynamics underlying crossmodal associations and memory by recording event-related potentials (ERPs) when human participants performed visuo-tactile (crossmodal) and visuo-visual (unimodal) paired-associate (PA) learning tasks. ⋯ Additional behavioral experiments suggested that these ERP components were not relevant to the participants' familiarity with stimuli per se. Further, by shortening the delay length (from 1300ms to 400ms or 200 ms) between the first and second stimulus in the crossmodal task, declines in participants' task performance were observed accordingly. Taken together, these results provide insights into the cortical plasticity (induced by PA learning) of neural networks involved in crossmodal associations in working memory.
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Primary visual cortex, the first cortical stage of visual information processing, is represented by diverse functional maps that demonstrate the selectivity for specific visual features such as spatial frequency (SF). Although the local organization of SF maps in cat area 17 (A17) has been largely investigated, the global arrangement remains elusive. ⋯ In particular, we found the highest SF preference within the global distribution concentrated around the horizontal meridian. These results significantly contribute to a more comprehensive understanding of the SF organization in visual cortex.