2 citations · 2 across the 13 of their papers we have counts for
14 papers
DWI Connectome-based Sex Classification in Young using Supervised Variational Autoencoder
Aditya Kothapalli, Aaryan Gera, Sathvik Reddy +3
During adolescence, significant changes in brain development are influenced by hormonal changes that impact both the body and the brain. This study presents sex classification in 7…
EEG Interpretation Across Chant Listening: A Single-Subject Pilot Investigation Using Spectral and Functional Connectivity Analysis
Prerna Singh, Aishwarya Ghosh, Neelam Sinha +1
This technical report presents an EEG-based investigation of neural activity across five auditory conditions: Resting State (RS), Shiv Tandav Stotra (STS), Mahasudarshan Mantra (MM…
Sex-based Network-Specific Differences in Connectomes: A Krakencoder-Based Analysis
Vibhashree S H, Debanjali Bhattacharya, Vamshi Krishna Kancharla +1
This study examines how deficiencies in one brain connectome modality propagate to the other, using the Krakencoder as a simulation framework. Structural and functional connectomes…
sMRI-based Brain Age Estimation in MCI using Persistent Homology
Debanjali Bhattacharya, Neelam Sinha
In this study, we propose the use of persistent homology -- specifically Betti curves for brain age prediction and for distinguishing between healthy and pathological aging. The pr…
Persistent Homology for MCI Classification: A Comparative Analysis between Graph and Vietoris-Rips Filtrations
Debanjali Bhattacharya, Rajneet Kaur, Ninad Aithal +2
Mild cognitive impairment (MCI), often linked to early neurodegeneration, is characterized by subtle cognitive declines and disruptions in brain connectivity. The present study off…
Leveraging Persistent Homology for Differential Diagnosis of Mild Cognitive Impairment
Ninad Aithal, Debanjali Bhattacharya, Neelam Sinha +1
Mild cognitive impairment (MCI) is characterized by subtle changes in cognitive functions, often associated with disruptions in brain connectivity. The present study introduces a n…
Bayesian Network Modeling of Causal Influence within Cognitive Domains and Clinical Dementia Severity Ratings for Western and Indian Cohorts
Wupadrasta Santosh Kumar, Sayali Rajendra Bhutare, Neelam Sinha +1
This study investigates the causal relationships between Clinical Dementia Ratings (CDR) and its six domain scores across two distinct aging datasets: the Alzheimer's Disease Neuro…
Non-linear Analysis Based ECG Classification of Cardiovascular Disorders
Suraj Kumar Behera, Debanjali Bhattacharya, Ninad Aithal +1
Multi-channel ECG-based cardiac disorders detection has an impact on cardiac care and treatment. Limitations of existing methods included variation in ECG waveforms due to the loca…
Analyzing Brain Tumor Connectomics using Graphs and Persistent Homology
Debanjali Bhattacharya, Ninad Aithal, Manish Jayswal +1
Recent advances in molecular and genetic research have identified a diverse range of brain tumor sub-types, shedding light on differences in their molecular mechanisms, heterogenei…
Towards understanding the nature of direct functional connectivity in visual brain network
Debanjali Bhattacharya, Neelam Sinha
Recent advances in neuroimaging have enabled studies in functional connectivity (FC) of human brain, alongside investigation of the neuronal basis of cognition. One important FC st…
Multi-scale fMRI time series analysis for understanding neurodegeneration in MCI
Ammu R., Debanjali Bhattacharya, Ameiy Acharya +2
In this study, we present a technique that spans multi-scale views (global scale -- meaning brain network-level and local scale -- examining each individual ROI that constitutes th…
Image complexity based fMRI-BOLD visual network categorization across visual datasets using topological descriptors and deep-hybrid learning
Debanjali Bhattacharya, Neelam Sinha, Yashwanth R. +1
This study proposes a new approach that investigates differences in topological characteristics of visual networks, which are constructed using fMRI BOLD time-series corresponding…
Investigating the changes in BOLD responses during viewing of images with varied complexity: An fMRI time-series based analysis on human vision
Naveen Kanigiri, Manohar Suggula, Debanjali Bhattacharya +1
Functional MRI (fMRI) is widely used to examine brain functionality by detecting alteration in oxygenated blood flow that arises with brain activity. This work aims to investigate…
Spatial encoding of BOLD fMRI time series for categorizing static images across visual datasets: A pilot study on human vision
Vamshi K. Kancharala, Debanjali Bhattacharya, Neelam Sinha
Functional MRI (fMRI) is widely used to examine brain functionality by detecting alteration in oxygenated blood flow that arises with brain activity. In this study, complexity spec…