IIT Guwahati makes huge breakthrough in decoding human brain: See details here

Guwahati: Researchers at Indian Institute of Technology, Guwahati seem to have developed a novel algorithm, Unique Brain Network Identification Number (UBNIN), designed to encode the intricate brain networks of healthy humans and patients with Parkinson’s disease (PD). This study involved the analysis of structural brain MRI scans of 180 PD patients and 70 healthy individuals from the National Institute of Mental Health and Neurosciences (NIMHANS), India. The researchers adopted a network perspective, representing different brain regions as nodes and establishing connection values of the network based on regional grey matter volume. Further, connection values for every node were weighted to capture the significance of each link by following a series of algorithmic steps. The hence obtained numerical representation (UBNIN) was observed to be distinct for each brain network, and also applicable to other neuroimaging brain modalities. This innovative research holds immense potential in the realm of brain printing and emerges as a promising biomarker with a numerical value for tracking mental illness progression over time.

Also, Parkinson’s disease, a neurodegenerative disorder, with clinical symptoms such as tremors, stiffness, and slow movement, worsens with age. However, neurodegeneration begins long before these symptoms appear, making early detection imperative for effective PD management. Addressing this critical gap, in a first-of-its-kind study, IIT Guwahati and NIMHANS researchers used non-invasive structural MRI scans during rest. Categorizing PD patients into five age groups (A: ≤32 years, B: 33–42 years, C: 43–52 years, D: 53–62 years, and E: ≥63 years), this study delved into how age impacts the brain connectivity over varying sparsities. For each age cohort, the clustering coefficient presented a decreasing trend with increasing sparsity.

Explaining the research findings, Dr. Cota Navin Gupta, Assistant Professor, Neural Engineering Lab, Department of Biosciences and Bioengineering, IIT Guwahati said, “UBNIN is a special number representing unique characteristics of the 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 characterize(encode-decode) brain networks of every human being efficiently.”

Ph.D. Scholar Tanmayee Samantaray further added, “Applying UBNIN algorithm on longitudinal neuroimaging data (i.e. over time) holds promise for elucidating the dynamics of brain plasticity (i.e. changes in the human brain). This insight is crucial to understand how the human brain degenerates, and copes with damage due to underlying neurological diseases.”

The developed UBNIN algorithm makes MRI data interpretable and holds the potential to transform neurodegenerative disorder diagnosis and treatment. This may be used as a biomarker to complement other diagnostic tests recommended by neurologists. UBNIN’s applications range from brainprinting to optimizing storage for structural MRI brain networks. This could open avenues for low-bandwidth, high-speed information transfer of human brain networks for Telemedicine and related applications. UBNIN’s adaptability could also be extended to other neuroimaging modalities like an 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.

Further, Dr. Gupta added, “We are now looking into the possibilities of using UBNIN as a potential biomarker to distinguish healthy and Parkinson’s at the group level.”

The current findings have been published in the journal Brain Sciences and were co-authored by Tanmayee Samantaray, Utsav Gupta, Dr Jitender Saini, and Dr Cota Navin Gupta.

This research has been funded by the Ministry of Education (MoE) doctoral scholarship, Govt of India, and supported by the Scheme for Promotion of Academic and Research Collaboration (SPARC Grant), Govt of India.

Indian Institute of Technology Guwahati, established in 1994, completed 25 years of glorious existence in 2019. At present, the Institute has eleven departments, nine interdisciplinary academic centers, and five schools covering all the major engineering, science, healthcare, management, and humanities disciplines, offering BTech, BDes, BSc(Hons), MA, MDes, MTech, MSc, MS(R), MBA and PhD programs. The institute offers a residential campus to 439 faculty members and more than 8,600 students at present.

IIT Guwahati has retained the 7th position among the best engineering institutions in the country and the 9th position in both ‘Overall’ and ‘Research’ Categories in the ‘India Rankings 2023’ declared by the National Institutional Ranking Framework (NIRF) of the Union Ministry of Education.

IIT Guwahati has achieved rank 6 in the SDG 7 (Affordable and clean energy) globally in the Times Higher Education (THE) Impact Rankings 2023 and is the only academic institution in India that occupied a place among the top 100 world universities – under 50 years of age – ranked by London-based Times Higher Education (THE) in 2014 and continues to maintain its superior position even today in various International Rankings. IIT Guwahati gained the rank of 32 globally in the ‘Research Citations per Faculty’ category and an overall 364 rank in the QS World University Rankings 2024.

Among other frontier areas of research and innovation, IIT Guwahati is working towards augmenting critical science research initiatives in Genomics, Developmental Biology, Health Care Bioinformatics, and Flexible Electronics, among numerous other areas.

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