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Joana Cabral

Computational neuroscience 

Hedonia: Translational Research Group, Department of Psychiatry, University of Oxford, Oxford, United Kingdom
Life and Health Sciences Research Institute, University of Minho, Braga, Portugal




Joana Cabral did her PhD in Computational Neuroscience with Gustavo Deco in Barcelona, Spain after completing her master degree in Biomedical Engineering in Portugal. She is currently a postdoc researcher at the Department of Psychiatry at the University of Oxford, UK and at the Life and Health Sciences Research Institute at the University of Minho, Portugal.

Joana specialised in the development of whole-brain network models to investigate the mechanisms underlying long-range functional connectivity and its breakdown in psychiatric diseases linked to pathological connectivity.


Investigating brain function using computational network models

Composed of nearly 100 billion neurons, the human brain is one of the most complex networks in nature, exhibiting non-trivial spatiotemporal patterns with evident behavioural and cognitive correlates, spanning several orders of magnitude. To explore the principles governing brain dynamics at the system level, computational neuroscience has developed analytic and numerical methods to reduce the dimensionality of large neuronal ensembles and explore their interactive dynamics when embedded in the complex network formed by long-range white matter fibers: the structural connectome. Computational simulations have shown that interactions between neural masses (modelled with different degrees of reduction) in the structural connectome reveal self-organizing macroscopic patterns similar to the ones detected with fMRI. Yet, how these patterns evolve in time and their relation with M/EEG oscillatory rhythms remains controversial. In my talk, I will present the state-of-the-art in brain network models with an eye on current challenges and discuss their future potential to provide insights regarding cognitive processing at the system level and their disruption in psychiatric disorders.