UBNIN Algorithm: Iit-g Algorithm To Encode Healthy Individuals, Parkinson’s Patients | Guwahati News

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Guwahati: A novel algorithm developed by IIT Guwahati may code brain connectivity patterns of healthy individuals and Parkinson’s patients into a numerical representation. This innovative research holds immense potential in the realm of brain printing and emerges as a promising biomarker with numerical value for tracking mental illness progression over time, researchers said.
The study involved analysis of structural brain MRI scans of 180 Parkinson’s patients and 70 healthy individuals from National Institute of Mental Health and Neurosciences (NIMHANS).
“Since every human brain has a unique pattern of network connectivity, the developed Unique Brain Network Identification Number (UBNIN) algorithm may be employed for creating individual brain IDs, possibly useful for brainprinting. However, further investigation is still needed to confirm changes in UBNIN values with time and age,” IIT-Guwahati said in a statement on Thursday.
It added that this research also indicates that with age, human brain connectivity changes, as illustrated by obtained network metrics. “This could possibly be due to underlying neurological issues and hence clustering coefficient (a network metric) could be used as a biomarker,” read the statement.
PD is a neurodegenerative disorder, with clinical symptoms such as tremors, stiffness, and slow movement, which worsens with age. But neurodegeneration starts long before these symptoms appear, making early detection imperative for effective PD management, researchers said. Addressing this critical gap, they said in a first-of-its-kind study, IIT Guwahati and NIMHANS researchers used non-invasive structural MRI scans during rest.
Cota Navin Gupta, assistant professor, neural engineering lab at biosciences and bioengineering department of IIT Guwahati said, “UBNIN is a special number representing unique characteristics of each human brain from a network perspective. Interestingly, we can also reverse engineer any human’s UBNIN value to reconstruct the original brain network. This UBNIN algorithm will enable us to identify and characterise (encode-decode) brain networks of every human beings efficiently.”
“We are now looking into the possibilities of using UBNIN as a potential biomarker to distinguish healthy and Parkinson’s at group level,” Gupta added.
The findings have been published in the journal Brain Sciences and was co-authored by Tanmayee Samantaray, Utsav Gupta, Jitender Saini and Cota Navin Gupta.
The developed UBNIN algorithm makes MRI data interpretable and holds a potential to transform neurodegenerative disorder diagnosis and treatment. This may be used as a biomarker to complement other diagnostic tests recommended by neurologists.

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