Neuroscience
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Face recognition is an important aspect of human non-verbal communication. Event-related potentials or magnetic fields, such as the N170/M170 component, are considered essential neural markers of face processing. Compared to upright human faces, inverted human faces and upright but not inverted animal faces cause longer latencies and larger amplitudes of these components. ⋯ Additionally, face orientation differentially modulated the anterior region of the fusiform gyrus (FG) in both face categories. These results suggest that spatiotemporal dynamics differ in face orientation regardless of category and that the FG contributes little or nothing to the M170 modulation recorded in the scalp sensor. Furthermore, we demonstrated that inverted human and animal faces are processed via different mechanisms.
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Reaching movements are essential for daily tasks and they have been widely investigated through kinematic, kinetic, and electromyographic (EMG) analyses. Recent studies have also suggested that the central nervous system simplifies movement control by using muscle synergies. An alternative approach is to investigate how EMG activity reflects at theneural level with the spinal maps representation that visualizes the spatiotemporal activity of motoneuronal pools. ⋯ The multidimensional Pearson's correlation coefficient was used to assess thesimilarity of spinal maps among repetitions of movements within subjects (intra-subject variability) and among participants (inter-subject variability). Spinal maps of tonic and total EMG showed high intra- and inter-subject similarity in all planes, while phasic spinal maps were less repeatable and more subject-specific. These results may be useful as areference for rehabilitation, clinical, and neurological evaluations, especially for longitudinal assessments.
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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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Exercise-induced fatigue (EF) is characterized by a decline in maximal voluntary muscle force following prolonged physical activity, influenced by both peripheral and central factors. Central fatigue involves complex interactions within the central nervous system (CNS), where astrocytes play a crucial role. This study explores the impact of astrocytic calcium signals on EF. ⋯ Utilizing genetic tools to either enhance or reduce astrocytic calcium signaling, we observed corresponding decreases and increases in exercise-induced fatigue time, respectively. Furthermore, modulation of astrocytic calcium signals influenced corticostriatal synaptic plasticity, with increased signals impairing and decreased signals ameliorating long-term depression (LTD). These results highlight the pivotal role of astrocytic calcium signaling in the regulation of exercise-induced fatigue and synaptic plasticity in the striatum.
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The recent emergence of updated drugs for the treatment of Alzheimer's disease (AD) has produced encouraging cognitive and clinical results in clinical trials, but there is still controversy over how to choose effective treatment options among these numerous drugs. The purpose of this network meta-analysis (NMA) is to compare and rank these drugs based on their efficacy. ⋯ Donanemab and Lecanemab showed good efficacy in ADCS-ADL and CDR-SB, respectively. GV-971 is the best choice to improve ADAS cogs and NPI.