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Neuroimaging investigation of learning mechanisms in the human brain: new methodological approaches

The nervous system is constantly changing over the lifespan as a result of development and learning. Such plasticity-related changes occur at multiple levels of neural organization, from molecules and synapses to cortical maps and large-scale networks. Neuroimaging research over the past two decades has already contributed an extensive amount of information on how many sensory and cognitive functions are associated with particular brain structures. Increasing interest in the characterization of plasticity mechanisms in the human brain has posited new challenges to neuroimaging techniques, both of conceptual and methodological nature. In particular, it is thought that great insights will be possible through the conjoint analysis of activity within specific brain regions and functional connectivity between those regions.
In this Project, we propose to address this issue through the development and implementation of the following neuroimaging methodological approaches. Firstly, state-of-the-art acquisition methods for functional magnetic resonance imaging (fMRI) will be implemented in a 1.5 Tesla system in order to allow more quantitative and reliable assessment of learning-related brain activity changes. Secondly, different techniques for the analysis of brain connectivity will be developed and integrated, based on the combination of fMRI with electroencephalography (EEG) measurements for the assessment of both low and high frequency behavior.
Although conventional fMRI techniques using blood oxygenation level dependent (BOLD) contrast have already proved useful in the study of plasticity-related brain activity changes, they present severe constraints when the learning process of interest occurs over minutes or even hours, or when longitudinal designs are chosen to investigate effects over longer periods of time. Arterial spin labelling (ASL) perfusion imaging methods provide a more stable and quantitative measure of brain activity that constitutes an interesting complement to BOLD contrast. Moreover, a recently developed diffusion-weighted imaging (DWI) technique seems to provide an independent, quantitative measure of activation, therefore offering additional information. Protocols for the combined acquisition of BOLD, ASL and DWI fMRI will be implemented and validated using robust visual stimulation paradigms.
Synchronization of neural responses is thought to be modified as a function of learning and represents a possible plasticity mechanism. Functional connectivity investigations of fMRI data provide a way of assessing synchronization between brain regions. Protocols for both model- and data-driven analysis methods of connectivity will be implemented, in order to combine the complementary strengths of each strategy. Correlation-type exploratory approaches will be used to determine networks of functionally connected brain areas and specific causal models will then be tested, based on these networks and available neurophysiological information. Neural synchronization can also be assessed through coherence measures of EEG recordings. The high temporal resolution of this technique allows the investigation of functional connectivity at various frequency oscillation bands, which have previously been hypothesized to have differential cognitive significance. Time-series analysis methods will be implemented and validated for the measurement of phase coherence between EEG channels. Time-frequency decomposition techniques will be employed in order to explicitly access specific frequency bands of interest. Additionally, protocols for the simultaneous EEG and fMRI acquisition will be implemented and appropriate analysis methods developed for the integration of the multimodal data. By combining EEG with fMRI, we hope to enable the investigation of functional connectivity changes during learning over a broad range of frequencies.
Finally, the contextual cueing paradigm used for the study of implicit learning mechanisms will be investigated with the methods developed within this Project. Combined BOLD-ASL fMRI will first be used to determine brain activity changes related to the learning processes under study, testing hypotheses concerning the involvement of specific brain structures, namely the hippocampus and caudate nucleus. Functional connectivity analysis will also be conducted, in order to investigate the interactions between the participating brain regions. Finally, simultaneous EEG-fMRI measures will be used to investigate learning induced neuronal synchronization at different frequency bands.
In summary, with this Project we hope to contribute to the development and validation of valuable acquisition and analysis tools for the investigation of brain mechanisms of learning using neuroimaging techniques. Moreover, we expect that this Project will enable the cooperation between young scientists with expertise in the fields of Biomedical Engineering and Neuroscience, in the context of the National Network for Functional Brain Imaging recently approved by FCT.
Principal Investigator: Patrícia Figueiredo (IST)