About the research:
The project applies tools from statistical physics to identify biomarkers of Alzheimer’s disease (AD) and aging through the analysis of large magnetoencephalography (MEG) datasets. Measures of entropy, complexity, and causality will be computed to characterize dynamic patterns of brain activity. The goal is to differentiate healthy individuals from those at early stages of the disease and, in particular, to distinguish patients with mild cognitive impairment (MCI) who progress to AD from those who remain stable. To this end, the complexity–entropy plane (CxH) will be used, which makes it possible to identify different regimes of brain activity organization. This approach is expected to contribute to the development of predictive tools for diagnosis and to more personalized intervention strategies for neurodegenerative diseases.
Awards and honors:
🏆 Highest distinction cum laude in the PhD in Physics at the Universidad de las Islas Baleares, at the Institute for Cross-Disciplinary Physics and Complex Systems (IFISC) (2014)
🏆 For Women in Science Award L’Oréal-UNESCO-ABC in Physics (2022)
🏆 1st GIRLS AND WOMEN IN SCIENCE AWARD, Federal University of Alagoas (2023)
Selected publications:
Da Paz, Ícaro Rodolfo Soares Coelho, Pedro FA Silva, Helena Bordini de Lucas, Sérgio HA Lira, Osvaldo A. Rosso, and Fernanda Selingardi Matias. “Symbolic information approach applied to human intracranial data to characterize and distinguish different cognitive processes.” Physical Review E 110, no. 2 (2024): 024403. https://journals.aps.org/pre/abstract/10.1103/PhysRevE.110.024403 arxiv: https://arxiv.org/pdf/2404.17981
Lotfi, Nastaran, Thais Feliciano, Leandro AA Aguiar, Thais Priscila Lima Silva, Tawan TA Carvalho, Osvaldo A. Rosso, Mauro Copelli, Fernanda Selingardi Matias, and Pedro V. Carelli. “Statistical complexity is maximized close to criticality in cortical dynamics.” Physical Review E 103, no. 1 (2021): 012415. https://journals.aps.org/pre/abstract/10.1103/PhysRevE.103.012415 arxiv: https://arxiv.org/pdf/2010.04123
Carlos, Francisco Leandro P., Maria Carla Navas, Ícaro Rodolfo Soares Coelho Da Paz, Helena Bordini de Lucas, Maciel-Monteiro Ubirakitan, Marcelo Cairrão Araújo Rodrigues, Moises Aguilar Domingo, Eva Herrera-Gutiérrez, Osvaldo A. Rosso, Luz Bavassi, Fernanda Selingardi Matias. “A statistical complexity measure can differentiate Go/NoGo trials during a visual-motor task using human electroencephalogram data.” Physica D: Nonlinear Phenomena (2025): 134955. https://www.sciencedirect.com/science/article/abs/pii/S0167278925004324 arxiv: https://arxiv.org/pdf/2507.16159
Matias, Fernanda Selingardi., Leonardo L. Gollo, Pedro V. Carelli, Steven L. Bressler, Mauro Copelli, and Claudio R. Mirasso. “Modeling positive Granger causality and negative phase lag between cortical areas.” NeuroImage 99 (2014): 411-418. https://www.sciencedirect.com/science/article/abs/pii/S1053811914004480 pdf: https://ifisc.uib-csic.es/documents/364/news_415_SincronitzacioAnticipadaArticuloNeuroImage22052014.pdf
Machado, Julio Nunes, and Fernanda Selingardi Matias. “Phase bistability between anticipated and delayed synchronization in neuronal populations.” Physical Review E 102, no. 3 (2020): 032412. https://journals.aps.org/pre/abstract/10.1103/PhysRevE.102.032412 https://arxiv.org/pdf/2008.11891
Matias, Fernanda S., Pedro V. Carelli, Claudio R. Mirasso, and Mauro Copelli. “Anticipated synchronization in neuronal circuits unveiled by a phase-response-curve analysis.” Physical Review E 95, no. 5 (2017): 052410. https://journals.aps.org/pre/abstract/10.1103/PhysRevE.95.052410 arxiv: https://arxiv.org/pdf/1703.03444
