neuroscience

topology of brain activity

Brain activity often involves complex patterns that can be difficult to capture with traditional tools. Topological data analysis (TDA) offers a way to study the shape of these patterns, revealing structures in brain signals that might otherwise be missed.

In my work, I use TDA to explore how brain dynamics change across different conditions, such as epilepsy in fish or altered states in humans. This approach helps highlight collective features of neural activity and offers new perspectives on how the brain organizes its activity over time.

References

  1. Topological analysis of brain dynamical signals indicates signatures of seizure susceptibility, 2025 in press at Physical Review Research — M. Lucas, D. Francois, L. Mombaerts, C. Donato, A. Skupin, and D. Proverbio
    | preprint | Code |
  2. On the state-nonstate theory of hypnosis: Network and topological EEG findings, Cerebral Cortex, 2025 — M. Lucas*, N. Aime*, A. Callara, L. Fontanelli, L. Sebastiani, L. Santarcangelo, and G. Petri
    | PAPER |
  3. Higher-order connectomics of human brain function reveals local topological signatures of task decoding, individual identification, and behavior, Nature Communications, 2024 — A. Santoro, F. Battiston, M. Lucas, G. Petri, and E. Amico
    | PAPER | preprint | Code |