Using GPUs to Discover Human Brain Connectivity - Neuroscience News

Summary: Researchers developed a new GPU-based machine learning algorithm to help predict the connectivity of networks within the brain. A new GPU-based machine learning algorithm developed by researchers at the Indian Institute of Science (IISc) can help scientists better understand and predict connectivity between different regions of the brain. The algorithm, called Regularized, Accelerated, Linear Fascicle Evaluation, or ReAl-LiFE, can rapidly analyse the enormous amounts of data generated from diffusion Magnetic Resonance Imaging (dMRI) scans of the human brain. Using ReAL-LiFE, the team was able to evaluate dMRI data over 150 times faster than existing state-of-the-art algorithms. "Tasks that previously took hours to days can be completed within seconds to minutes," says Devarajan Sridharan, Associate Professor at the Centre for Neuroscience (CNS), IISc, and corresponding author of the study published in the journal Nature Computational Science.