Joana Cabral

Research interests:

My research focuses on understanding large-scale brain dynamics through the integration of computational modeling, neuroimaging, and physics-based approaches. I develop and apply novel analytical methods to investigate how spatiotemporal patterns of brain activity emerge and relate to cognition, mental states, and neuropsychiatric disorders.

Key areas of investigation include:

• Whole-brain computational modeling of brain dynamics

• Development of neuroimaging analysis methods, particularly the Leading Eigenvector Dynamics Analysis (LEiDA), Metastable Oscillatory Modes (MOMs), Wave mechanics and Resonance phenomena, challenging traditional connectivity-based interpretations

• Modulation of brain dynamics through stimulation, using computational models and phantom experiments to predict responses to perturbation.

• Clinical applications in neurological conditions and psychiatric syndromes, including psychosis, depression, and anxiety.

Bio sketch:

Joana Cabral graduated in Biomedical Engineering in 2007 from Universidade Nova de Lisboa and completed her PhD in Theoretical and Computational Neuroscience at Universitat Pompeu Fabra in Barcelona (2008-2012) under Professor Gustavo Deco, developing expertise in whole-brain dynamical modeling and neural oscillations.

As a postdoctoral researcher at Oxford's Department of Psychiatry (2014-2017), she developed the Leading Eigenvector Dynamics Analysis (LEiDA) methodology—a novel approach to capturing rapid network reconfigurations in functional MRI data, now adopted by over 50 research groups worldwide. From 2017 to 2025 at the University of Minho's Life and Health Sciences Research Institute, she held a LaCaixa Foundation Junior Leader fellowship (2022-2025) focusing on computational models for predicting brain network modulation through stimulation.

In October 2025, Joana joined IST as Assistant Professor and Principal Researcher at LaSEEB (ISR-Lisboa/LARSyS), establishing a research line that challenges traditional interpretations of brain function through wave mechanics and fluid dynamics frameworks. She maintains active international collaborations and is committed to mentoring early-career scientists, having received a L'Oréal-UNESCO award for Women in Science in 2019.

Research grants (as PI or Co-PI):

• BrainStimPredict: Developing computational tools for predicting brain stimulation responses (Arqus Research Alliance, 2025-2026)

• SPIRIT: SuperPosition of Ionic gRadienTs (FCT Mobility, 2025)

• BRAINSTIM: Predicting brain stimulation strategies to rebalance functional networks (LaCaixa Foundation Junior Leader Fellowship, 2022-2025)

• PATHOCONNECTOMICS: Targeting disrupted functional networks (FCT, 2019-2022)

PhD Students:

• Vânia Miguel Bento (2026-) DYNAMIND: Predicting Cognitive Decline Through Ultra-Fast fMRI and AI-Driven Network Analysis, Co-supervision with Prof. Patrícia Figueiredo and Francisco Calisto, Instituto Superior Técnico, University of Lisbon

• Inês Bem-Haja (2026-) Mapping Cerebrospinal Fluid Dynamics in Cognitive Decline, Instituto Superior Técnico, University of Lisbon, Portugal

• Haeun Sun (2025-) A new strategy for Temporal Interference Stimulation on Brain-Fluid models, Instituto Superior Técnico, University of Lisbon, Portugal

• Afonso Fernandes  (2025-) Brain Dynamical Complexity in Early Psychosis: Toward Biomarkers of Clinical Outcome, Co-supervision with Prof. Dr. Pedro Morgado, Life and Health Sciences Research Institute, University of Minho, Portugal

• Marta Xavier (2021-) Advances in Computational Modeling of Resting-State Brain Activity: Predicting EEG-fMRI Dynamics, Co-supervision with Prof. Patrícia Figueiredo and Prof. Gustavo Deco, Instituto Superior Técnico, University of Lisbon, Portugal and Universitat Pompeu Fabra, Barcelona, Spain

• Fran Hancock (2020-2024) Dynamical complexity of resting state networks, Co-supervision with Prof. Federico Turkheimer, King's College London, United Kingdom

Course teaching:

• 2nd Cycle Integrated Project in Biomedical Engineering (2024/2025 - )