A5101662403- Cell Image Analysis Techniques
- Functional Brain Connectivity Studies
- Neural dynamics and brain function
- Topological and Geometric Data Analysis
- Advanced MRI Techniques and Applications
- EEG and Brain-Computer Interfaces
- Scientific Computing and Data Management
- Epilepsy research and treatment
San Diego Supercomputer Center
2022-2024
University of California, San Diego
2023-2024
Abstract To preserve scientific data created by publicly and/or philanthropically funded research projects and to make it ready for exploitation using recent ongoing advances in advanced large-scale computational modeling methods, available must use common, now-evolving standards formatting, identifying annotating should share data. The OpenNeuro.org archive, built first as a repository magnetic resonance imaging based on the Brain Imaging Data Structure formatting standards, aims house all...
Abstract When the scientific dataset evolves or is reused in workflows creating derived datasets, integrity of with its metadata information, including provenance, needs to be securely preserved while providing assurances that they are not accidentally maliciously altered during process. Providing a secure method efficiently share and verify data as well essential for reuse data. The National Science Foundation (NSF) funded Open Chain (OSC) utilizes consortium blockchain provide...
Abstract Topological data analysis (TDA) is a powerful approach for investigating complex relationships in brain networks; however, its application requires substantial domain knowledge programming, mathematics, and science, especially the context of data-driven approaches like machine learning (ML). To address this educational barrier, we introduce MaTiLDA, graphical user interface that enables exploration common representations TDA features their efficacy various classical models. This...
The rapid adoption of machine learning (ML) algorithms in a wide range biomedical applications has highlighted issues trust and the lack understanding regarding results generated by ML algorithms. Recent studies have focused on developing interpretable models establish guidelines for transparency ethical use, ensuring responsible integration healthcare. In this study, we demonstrate effectiveness interpretability methods to provide important insights into dynamics brain network interactions...