This research study utilizes
topological data analysis (TDA) to examine how brain functional connectivity changes during
healthy aging and in individuals with
autism spectrum disorder (ASD). By applying a method called
persistent homology, researchers developed a new metric known as
node persistence to identify specific brain regions linked to these conditions at global and local scales. The findings reveal that age-related and ASD-related changes are concentrated in networks responsible for
movement, social cognition, and memory. Significantly, many of the regions pinpointed by this mathematical tool overlap with areas targeted in
non-invasive brain stimulation therapies to improve cognitive or motor functions. This approach provides a
scalable and efficient way to map the brain's complex architecture, potentially guiding more effective
clinical interventions. In summary, the study bridges advanced geometry and neuroscience to better understand the
topological signatures of neurodevelopmental and age-related shifts.
References:
- Madhumita Mondal, Yasharth Yadav, Jürgen Jost, Areejit Samal. Node persistence from topological data analysis reveals changes in brain functional connectivity. Patterns. 2025.