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ReAl – LiFE

Context: Researchers at the Indian Institute of Science (IISc.) have developed a new graphic processing unit (GPU) based machine learning algorithm called Regularised, Accelerated, Linear Fascicle Evaluation (ReAl – LiFE).

 

Key Points:

  • ReAl – LiFE will help to obtain a better understanding and predict connectivity between different regions of the human brain. This algorithm helps scientists study the connectivity in the brain at a speed which is 150 times higher than a regular desktop computer. This can help analyse extensive data generated from diffusion Magnetic Resonance Imaging (dMRI) scans. 
  • With the study, researchers tried to study the wiring of different brain parts, which helps perform various computations. Through it, scientists can track the movement of molecules to create a comprehensive map of the connectome, which is a network of fibres across the brain. For the accurate identification of information networks, conventional algorithms matched the predicted dMRI signals from the inferred connectome with the observed dMRI signal.
  • A similar algorithm called LiFE (Linear Fascicle Evaluation) was developed earlier to carry out optimisation, but since it worked on traditional CPUs, the computation was time-consuming. ReAl – LiFE will have various applications in the health field, including disease diagnosis and behavioural studies.

Significance: Understanding brain connectivity is critical to uncovering brain-behaviour relationships at scale. While certain patterns of brain connectivity can explain the inter-individual differences in the attention test scores, which help determine behaviours, a previous version of the same algorithm can also help distinguish between Alzheimer’s patients and healthy age-matched controls by measuring brain connectivity. 

 

Context: Dak Karmayogi was launched by Shri Ashwini Vaishnaw on June 28, 2022.

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