Publications by authors named "Mengkuan Lin"

Article Synopsis
  • The common marmoset has become increasingly popular in neuroscience research over the past 20 years, especially for studying human brain diseases, but marmoset-specific research tools are often limited and must be created within labs.
  • A team has designed and tested various imaging and measurement techniques for studying marmosets, including MRI, PET, CT, and electrophysiology, and has made these designs publicly accessible to help ease the burden on researchers.
  • They provide numerous computer-aided design (CAD) files, software, and resources, including tools for neuroimaging and experimental stimuli, through the Marmoset Brain Connectome website to support further advancements in marmoset neuroscience.
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An essential step toward understanding brain function is to establish a structural framework with cellular resolution on which multi-scale datasets spanning molecules, cells, circuits and systems can be integrated and interpreted. Here, as part of the collaborative Brain Initiative Cell Census Network (BICCN), we derive a comprehensive cell type-based anatomical description of one exemplar brain structure, the mouse primary motor cortex, upper limb area (MOp-ul). Using genetic and viral labelling, barcoded anatomy resolved by sequencing, single-neuron reconstruction, whole-brain imaging and cloud-based neuroinformatics tools, we delineated the MOp-ul in 3D and refined its sublaminar organization.

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Understanding of neuronal circuitry at cellular resolution within the brain has relied on neuron tracing methods which involve careful observation and interpretation by experienced neuroscientists. With recent developments in imaging and digitization, this approach is no longer feasible with the large scale (terabyte to petabyte range) images. Machine learning based techniques, using deep networks, provide an efficient alternative to the problem.

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Unlabelled: The assessment of swallowing function is important for the prevention of aspiration pneumonia. We developed a new swallowing monitoring system that uses respiratory flow, swallowing sound, and laryngeal motion. We applied this device to 11 healthy volunteers and 10 patients with dysphagia.

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