Last. Lu Lu(UTHSC: University of Tennessee Health Science Center)H-Index: 45
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Age Related Hearing Loss (ARHL) is associated with cognitive dysfunction, however the detailed mechanism remains unclear. The aim of this study is to investigate the potential underlying mechanism with a systems genetics approach. A transcriptome-wide association study was performed on aged (12-32 months) BXD mice strains. The hippocampus gene expression was obtained from 56 BXD strains, and the hearing acuity was assessed from 54 BXD strains. Further correlation analysis identified a total of 1...
Last. Nicole C Keong(NUS: National University of Singapore)H-Index: 12
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OBJECTIVE.Multimorbidity burden across disease cohorts and variations in clinico-radiographic presentations within normal pressure hydrocephalus(NPH) confound its diagnosis, and the assessment of its amenability to interventions. We hypothesized that novel imaging techniques such as 3-directional linear morphological indices could help in distinguishing between hydrocephalus vs. non-hydrocephalus and correlate with responsiveness to external lumbar drainage(CSF responsiveness) within NPH subtype...
Last. Kristin Scott(Helen Wills Neuroscience Institute)H-Index: 22
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We combine a chemically-synthesized, voltage-sensitive fluorophore with a genetically encoded, self-labeling enzyme to enable voltage imaging in Drosophila melanogaster. Previously, we showed that a rhodamine voltage reporter (RhoVR) combined with the HaloTag self-labeling enzyme could be used to monitor membrane potential changes from mammalian neurons in culture and brain slice. Here, we apply this hybrid RhoVR-Halo approach in vivo to achieve selective neuron labeling in intact fly brains. We...
Artificial neural networks (ANNs), like convolutional neural networks (CNNs) have achieved the state-of-the-art results for many machine learning tasks. However, inference with large scale full-precision CNNs must cause substantial energy consumption and memory occupation, which seriously hinders their deployment on mobile and embedded systems. Highly inspired from biological brain, spiking neural networks (SNNs) are emerging as new solutions because of natural superiority in brain-like learning...
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