Joana Cabral

  • Brain Networks
  • Computational Neuroscience
  • Brain dynamics
  • fMRI
  • Brain
  • Mental Health

Joana Cabral is interested in the fundamental principles underlying brain function. She believes that understanding the most primitive biophysical mechanisms at the genesis of coordinated brain activity – ultimately leading to our thoughts and actions – will provide new insights to fight psychiatric disorders. She is a Biomedical Engineer with a PhD in Theoretical and Computational Neuroscience. After a postdoc at the Department of Psychiatry at the University of Oxford, UK, Joana is currently Assistant Researcher at the Life and Health Sciences Research Institute as part of the STRESS.COM team. She is also a Visiting Researcher at the Center for Eudaimonia and Human Flourishing at the University of Oxford, UK, at the Shemesh lab at the Champalimaud Center for the Unknown in Lisbon, Portugal and at the Center for Music in the Brain in Aarhus University, Denmark. Joana has specialised in the development of large-scale brain models and advanced analytical tools to investigate the mechanisms behind resting-state activity in health and disease. Her field of research involves Medical Engineering, with emphasis in Computational Modelling and Neuroimaging for Psychophysiology and Psychopathology research – namely, the LEiDA algorithm (standing for Leading Eigenvector Dynamics Analysis) developed in 2017 has served to identify features in whole-brain dynamics that correlate with several cognitive and behavioural conditions. Joana has received several awards, including the 2019 L’Oréal Award for Women in Science Portugal.

Scientific Highlights

“1. Cabral J, Hugues E, Sporns O, Deco G (2011) Role of Local Network Oscillations in Resting-State Functional Connectivity. NeuroImage (57) 130-139.
2. Cabral J, Hugues E, Kringelbach ML, Deco G (2012) Modeling the outcome of structural disconnection on resting-state functional connectivity. NeuroImage (62) 1342–1353.
3. Cabral J, Luckhoo H, Woolrich M, Joensson M, Mohseni H, Baker A, Kringelbach ML, Deco G (2014) Exploring mechanisms of spontaneous MEG functional connectivity: How delayed network interactions lead to structured amplitude envelopes of band- pass filtered oscillations. NeuroImage (90) 423-435.
4. Cabral J, Kringelbach ML, Deco G. (2014) Exploring the network dynamics underlying brain activity during rest. Progress in Neurobiology (114) 102-131.
5. Cabral J, Kringelbach ML, Deco G (2017) Functional connectivity dynamically evolves on multiple time- scales over a static structural connectome: Models and mechanisms. NeuroImage, ISSN 1053-8119.
6. Cabral J, Vidaurre D, Marques P, Magalhães R, Silva Moreira P, Soares JM, Deco G, Sousa N, Kringelbach ML (2017) Cognitive performance in healthy older adults relates to spontaneous switching between states of functional connectivity during rest. Scientific Reports 2017; 7: 5135.
7. Deco G, Cruzat J, Cabral J, Knudsen GM, Carhart-Harris RL, Whybrow PC, Logothetis NK, Kringelbach ML (2018) Whole-Brain Multimodal Neuroimaging Model Using Serotonin Receptor Maps Explains Non- linear Functional Effects of LSD. Current Biology.
8. Lord LD, Expert P, Atasoy S, Roseman L, Rapuano K, Lambiotte R, Nutt DJ, Deco G, Carhart-Harris RL, Kringelbach ML, Cabral J (2019) Dynamical exploration of the repertoire of brain networks at rest is modulated by psilocybin. NeuroImage 199:127- 142
9. Deco G, Cruzat J, Cabral J, Tagliazucchi E, Laufs H, Logothetis NK, Kringelbach ML (2019) Awakening: Predicting external stimulation to force transitions between different brain states. Proceedings of the National Academy of Sciences. 3;116(36):18088-97.
10. Kringelbach ML, Cruzat J, Cabral J, Knudsen GM, Carhart-Harris R, Whybrow PC, Logothetis NK, Deco G (2020) Dynamic coupling of whole-brain neuronal and neurotransmitter systems. Proceedings of the National Academy of Sciences, 117(17), 9566-9576.
11. Shine JM, Müller EJ, Munn B, Cabral J, Moran RJ, Breakspear M. (2021) Computational models link cellular mechanisms of neuromodulation to large-scale neural dynamics. Nature neuroscience. 24(6):765- 76.”