Plasticity of large-scale neural connectivity following working memory training

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In an ageing society techniques to preserve and improve cognitive function are gaining increasing importance. Approaches such as working memory (WM) training were found to improve processing capacities. In neuroimaging studies, this improvement was associated with alterations in amplitude of regional brain signal, while changes in interaction, or connectivity, between brain regions remain unclear. Considering increasing evidence that the human brain represents a dynamic system of neural networks, there is a need for development of connectivity-based markers of neural plasticity. In the proposed study we will investigate neuronal substrates of training-induced cognitive improvement at the level of large-scale brain connectivity. Given a variety of mechanisms underlying neural plasticity, we will apply a combination of neuroimaging techniques such as fMRI, PET, and DTI in a group of middle-aged healthy participants. Using these modalities, functional, metabolic, and structural connectivity will be measured. Experimental subjects will undergo a systematic WM training, followed by a comparison with an active control group. Simultaneous acquisition of MRI and fluorodeoxyglucose PET data on a hybrid PET/MR system will take place before and after training. An extensive cognitive test battery will be administered at the same two time points, as well as at 3 and 12 months follow-up. We hypothesize an increase in connectivity indices of the default mode and central executive networks following training. However, given the distinct temporal dynamics and energy costs, different forms of training-induced neuroplasticity are expected to be differently related to cognitive gains in time. Specifically, we hypothesize that increase in network structural and metabolic connectivity predicts long-term (12 months after training) near-transfer effects with higher accuracy than does functional connectivity. Beside neurobiological relevance, results of the proposed study will contribute to the development of cognitive interventions against age- and disease-related cognitive deficits.