We still lack a detailed map of the anatomical disposition of neurons in the human brain. A complete map would be an important step for deeply understanding the brain function, providing anatomical information useful to decipher the neuronal pattern in healthy and diseased conditions. Here, we present several important advances towards this goal, obtained by combining a new clearing method, advanced Light Sheet Microscopy and automated machine-learning based image analysis. We perform volumetric imaging of large sequentially stained human brain slices, labelled for two different neuronal markers NeuN and GAD67, discriminating the inhibitory population and reconstructing the brain connectivity.

Fast volumetric mapping of human brain slices / Pesce L.; Laurino A.; Gavryusev V.; Mazzamuto G.; Sancataldo G.; Scardigli M.; Roffilli M.; Silvestri L.; Costantini I.; Pavone F.S.. - ELETTRONICO. - 11360:(2020), pp. 43-48. (Intervento presentato al convegno Neurophotonics 2020 nel 2020) [10.1117/12.2555644].

Fast volumetric mapping of human brain slices

Pesce L.;Laurino A.;Gavryusev V.;Mazzamuto G.;Sancataldo G.;Scardigli M.;Silvestri L.;Costantini I.;Pavone F. S.
2020

Abstract

We still lack a detailed map of the anatomical disposition of neurons in the human brain. A complete map would be an important step for deeply understanding the brain function, providing anatomical information useful to decipher the neuronal pattern in healthy and diseased conditions. Here, we present several important advances towards this goal, obtained by combining a new clearing method, advanced Light Sheet Microscopy and automated machine-learning based image analysis. We perform volumetric imaging of large sequentially stained human brain slices, labelled for two different neuronal markers NeuN and GAD67, discriminating the inhibitory population and reconstructing the brain connectivity.
2020
Proceedings of SPIE - The International Society for Optical Engineering
Neurophotonics 2020
2020
Goal 9: Industry, Innovation, and Infrastructure
Pesce L.; Laurino A.; Gavryusev V.; Mazzamuto G.; Sancataldo G.; Scardigli M.; Roffilli M.; Silvestri L.; Costantini I.; Pavone F.S.
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1215594
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