Activities
Sebastian Seung
The Computational Challenges of Connectomics
Because of emerging technological advances, it is becoming possible to construct maps of the brain that are more detailed than ever before. These maps, called connectomes, describe the structure of the brain's neural networks at the level of individual neurons and synapses. Connectomes are determined by imaging a specimen of brain tissue in three dimensions at nanoscale resolution, and then using computational methods to extract information about neural connectivity from the images. The computational challenges are daunting, since brain volumes as modest in size as a cubic millimeter can yield terabyte or petabyte datasets. I will describe how my laboratory creates image analysis algorithms for connectomics using a modern approach based on machine learning.