IIT Guwahati develops algorithm to decode brain networks; early parkinson’s detection

NEW DELHI: Indian Institute of Technology (IIT) Guwahati’s researchers have made a breakthrough in understanding brain networks. They have developed an algorithm called the Unique Brain Network Identification Number (UBNIN) that encodes the intricate brain networks of healthy and Parkinson’s disease humans. The findings have been published in the Brain Sciences journal.

According to the official press release, the IITG team, in collaboration with the National Institute of Mental Health and Neurosciences (NIMHANS), conducted a study using UBNIN. They analysed brain scans from 180 Parkinson’s disease patients across different age groups and 70 healthy individuals. The results showed that UBNIN could potentially be used to identify early signs of brain network disruptions associated with Parkinson’s disease.

As per the institute, the algorithm can serve as a biomarker to supplement other diagnostic tests recommended by neurologists. The applications of the UBNIN algorithm span from brain printing to enhancing storage efficiency for structural MRI brain networks.

Also readIIT Madras develops electric standing wheelchair, to be commercialised by NeoMotion

The institute said that UBNIN's algorithm could also be extended to other neuroimaging modalities like electroencephalogram (EEG), functional MRI (both resting and task-based), etc. It can also be applied to other neurological conditions like Schizophrenia, Alzheimer’s, Depression, etc. Furthermore, it may be implemented on various datasets such as protein, social and traffic networks, making it a versatile tool for understanding complex system dynamics.

Explaining the research findings, assistant professor of IIT Guwahati, Cota Navin Gupta, said, “UBNIN is a special number representing unique characteristics of each human brain from a network perspective. This UBNIN algorithm will enable us to identify and characterize (encode-decode) brain networks of every human being efficiently.”