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Brainlit

2020
Team Members:
  • Bijan Varjavand
  • Ryan Lu
  • Matthew Figdore
  • Alex Fiallos
  • Xi (Stanley) Wang
  • Victor Wang
  • Jenny Trieu
  • Sanika Phatak
Advisors:
  • Joshua Vogelstein, PhD
  • Thomas Athey
  • Jaewon Chung
  • Benjamin Pedigo

Abstract:

Understanding the structure of the brain can lead to advances in treating neurological disorders. Our team is developing Brainlit, a Python-based software library devoted to processing, analyzing, and conducting inference on large volumetric datasets. Research in fields such as neuroscience is trending more and more towards extremely big data. For example, recent imaging advances such as serial two-photon microscopy can image entire brains with submicron spatial resolution, sufficient to resolve and trace individual axons (Winnubst et al.). These huge terabyte-sized datasets come with myriad problems such as storage, access, and parallelization of algorithms. The Brainlit package provides easy-to-use utilities and algorithms for handling, visualizing, and analyzing large data. Brainlit is fully open-source and can be downloaded from the Python Package Index (PyPi). The documentation and all releases are available at https://github.com/neurodata/brainlit.

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