Researchers at Washington State University (WSU) say they have developed an algorithm that can map brain neural networks with close to human-level accuracy.
As part of a 2013 Massachusetts Institute of Technology competition, the WSU team devised a computational model that absorbs an image as input and then processes it in a multilayer network before reaching a decision. Their algorithm incorporates an artificial neural network that mimics humans' organic neural networks.
The team still faces the formidable challenge of training computers to develop complete and precise neural maps.
WSU professor Shuiwang Ji says the networks are still highly error-prone, and a gold standard for comparing human and computational outcomes currently is lacking.
Nevertheless, Ji believes the work could accelerate the image-analysis process used for understanding brain circuitry, and improvements in computational techniques will definitely lead to reduced manual proofreading.
From WSU News
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