Abstract: Explainable artificial intelligence and single cell genomics to understand the cellular complexity of human brain

Author(s):  
Richard H.Scheuermann
BIOspektrum ◽  
2021 ◽  
Vol 27 (3) ◽  
pp. 274-276
Author(s):  
Morgan S. Sobol ◽  
Anne-Kristin Kaster

AbstractSingle cell genomics (SCG) can provide reliable context for assembled genome fragments on the level of individual prokaryotic genomes and has rapidly emerged as an essential complement to cultivation-based and metagenomics research approaches. Targeted cell sorting approaches, which enable the selection of specific taxa by fluorescent labeling, compatible with subsequent single cell genomics offers an opportunity to access genetic information from rare biosphere members which would have otherwise stayed hidden as microbial dark matter.


Polymers ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 312
Author(s):  
Naruki Hagiwara ◽  
Shoma Sekizaki ◽  
Yuji Kuwahara ◽  
Tetsuya Asai ◽  
Megumi Akai-Kasaya

Networks in the human brain are extremely complex and sophisticated. The abstract model of the human brain has been used in software development, specifically in artificial intelligence. Despite the remarkable outcomes achieved using artificial intelligence, the approach consumes a huge amount of computational resources. A possible solution to this issue is the development of processing circuits that physically resemble an artificial brain, which can offer low-energy loss and high-speed processing. This study demonstrated the synaptic functions of conductive polymer wires linking arbitrary electrodes in solution. By controlling the conductance of the wires, synaptic functions such as long-term potentiation and short-term plasticity were achieved, which are similar to the manner in which a synapse changes the strength of its connections. This novel organic artificial synapse can be used to construct information-processing circuits by wiring from scratch and learning efficiently in response to external stimuli.


Author(s):  
Ugomma C. Eze ◽  
Aparna Bhaduri ◽  
Maximilian Haeussler ◽  
Tomasz J. Nowakowski ◽  
Arnold R. Kriegstein

AbstractThe human cortex comprises diverse cell types that emerge from an initially uniform neuroepithelium that gives rise to radial glia, the neural stem cells of the cortex. To characterize the earliest stages of human brain development, we performed single-cell RNA-sequencing across regions of the developing human brain, including the telencephalon, diencephalon, midbrain, hindbrain and cerebellum. We identify nine progenitor populations physically proximal to the telencephalon, suggesting more heterogeneity than previously described, including a highly prevalent mesenchymal-like population that disappears once neurogenesis begins. Comparison of human and mouse progenitor populations at corresponding stages identifies two progenitor clusters that are enriched in the early stages of human cortical development. We also find that organoid systems display low fidelity to neuroepithelial and early radial glia cell types, but improve as neurogenesis progresses. Overall, we provide a comprehensive molecular and spatial atlas of early stages of human brain and cortical development.


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