(Numbers refer to inputs in my list of Journal publications)

My research uses neuropsychology [13,16-19], in addition to different structural [1,2,3,7,8,11,12] and functional [6,9,10,14,15] neuroimaging techniques to uncover the mechanisms by which the brain supports different aspects of cognition. Using funding provided by the EU and Basque Government, I studied bilingualism across the lifespan, (including children, young and elderly adults) and its association with cognitive, functional, and structural brain measures [2-7]. One of the most important contributions of this research was a new approximation for exploring the neural basis of bilingualism by using complex network analysis [2,3,6,7]. I found that early bilingualism modifies the structural configuration of the brain by developing specialized subnetworks in response to the burden of processing two languages, but that this outcome decreases the efficiency of the whole-brain connectivity [7]. This is a striking example of how the brain copes with increased processing demands. I also observed an opposite pattern in elderly lifelong bilinguals: increased efficiency of the whole-brain and no specialized subnetworks [2]. These studies revealed that the effects of bilingualism on brain structure are not permanent, and that lifetime experience of active bilingualism might help the brain become more efficient. These results helped to arbitrate between alternative models of bilingualism and to inform novel accounts of brain plasticity [see 4,5]. I have also been involved in researching the neural bases of Dravet Syndrome [8] and Parkinson’s disease (in preparation). During my time at Diego Portales University (2009) and the Cuban Neuroscience Center (2003 – 2008), I was involved in identifying the underlying cognitive deficits in schizophrenia [14], as well as the neural basis of emotional [9,10,15,19] and attentional [13,16,18] processing in healthy and pathological populations, such as prosopagnosia [10], dyslexia [17], autism [19], and psychopathy. My work at UTSC was focused on the neural basis of visual imagery and perception of words with the aid of machine learning methodology as applied to fMRI data. This project has revealed a network of cortical regions supporting word identification and has shed light on the visual-orthographic content of neural representations supported by this network (in preparation). Currently, in my MSCA Fellowship, I aim to map the interface between the semantic representational and control networks by estimating the dynamical networks underlying ongoing resting-state fMRI. This also includes determining the structural connectivity (based on DW-MRI). I compare data from healthy controls and semantic patients to draw inferences about the brain from whole networks (complex-level topology) to individual nodes (low-level topology) and edges (connectivity-level) in order to model how the brain reorganises after damage and ultimately to have a better understanding of how the semantic subnetworks recruit each other to give rise semantic behaviour.