非表示:
キーワード:
SCANNING-ELECTRON-MICROSCOPY; MOUSE-BRAIN; 3-DIMENSIONAL STRUCTURE;
DENDRITIC SPINES; NERVOUS-SYSTEM; IMAGE DATA; DATA SETS; IN-VIVO;
DROSOPHILA; RECONSTRUCTIONNeurosciences;
要旨:
The connectivity architecture of neuronal circuits is essential to
understand how brains work, yet our knowledge about the neuronal wiring
diagrams remains limited and partial. Technical breakthroughs in
labeling and imaging methods starting more than a century ago have
advanced knowledge in the field. However, the volume of data associated
with imaging a whole brain or a significant fraction thereof, with
electron or light microscopy, has only recently become amenable to
digital storage and analysis. A mouse brain imaged at light-microscopic
resolution is about a terabyte of data, and 1 mm(3) of the brain at EM
resolution is about half a petabyte. This has given rise to a new field
of research, computational analysis of large-scale neuroanatomical data
sets, with goals that include reconstructions of the morphology of
individual neurons as well as entire circuits. The problems encountered
include large data management, segmentation and 3D reconstruction,
computational geometry and workflow management allowing for hybrid
approaches combining manual and algorithmic processing. Here we review
this growing field of neuronal data analysis with emphasis on
reconstructing neurons from EM data cubes.
