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Probing research fronts identification unfailingly delivers interesting results in any field due to its decisive nature. Citation analysis is an acclaimed method used in this process among which more successful results backing Author Co-citation Analysis (ACA) and Author Bibliographic Coupling Analysis (ABCA). The current study opted to combine author bibliographic coupling network analysis and author keywords to explore and display a graphical representation of prominent research areas’ evolution over the study period in Indian Neuroscience research domain. Application of hierarchical clustering to author bibliographic coupling networks for all non-overlapping consecutive years included in the study period were performed and analysed in VOSviewer mapping software. The powerful Lin/log modularity normalization was chosen for determining distance based similarity while clustering the network units. Results of the study unfolded ten prominent research subfields with more emphasis on Epilepsy’ and ‘Parkinson’s disease’ research. Depression was identified as one of the upcoming prominent area in recent years. Apart from its cruciality in framing national level mental health policies, the study will also prove ABCA to be an effective method in identifying prominent research areas.