A large body of research suggests that goal-directed behavior depends on an efficient integration of neural activity to generate an appropriate action or choice. Neuroscientists have proposed that rhythms in the brain constitutes a fundamental mechanism underlying cognitive processes, which require an efficient large-scale integration of distributed neural activity to support both neural communication and plasticity. Crucially, abnormal interactions between brain functional networks in various neuropsychological conditions that are related to certain cognitive deficits, strongly suggest that these types of synchronized large-scale network interactions have a functional role. This project derives ground-breaking computational neuromodulation of cognition assays by systematically studying the causal link between large-scale network interactions and behavior via theory-driven investigations. This was carried out by an unprecedented combination of brain imaging techniques, computational modelling, and novel non-invasive causal manipulations of brain rhythms.
This project mainly focuses on gaining a deep understanding of resource limitations in the human brain generally speaking, alongside a fundamental cognitive function in almost any higher-order organism: Attention. Attention is a fundamental executive control function that is critical for survival. It refers to our ability to selectively process behaviorally relevant sensory information out of the large number of stimuli bombarding our senses (e.g. when attending to the road and avoiding distractions while driving a car). A fundamental issue that every organism faces – in both health and disease – is the limited capacity available to process information, which is referred to as “limited attention”. And this is precisely the main goal of this ERC project: To generate both theoretical and empirical knowledge about what constitutes attentional limitations in humans, by providing both correlative and causal links between brain function and the observed behaviour.
On the applied science side, there is a great need for technologies that enhance cognitive functioning or remediate the cognitive deficits of brain disorders to allow individuals to interact normally in society (e.g. psychopathologies related to cognitive deficits emerging throughout the lifespan, including during childhood, adolescence and adulthood), however, not in a data-driven manner as it is usually implemented (which are theoretically agnostic data analysis methods broadly construed including, but extending, standard statistical methods), but importantly designed using theory-driven tools that mathematically specify mechanistically interpretable relationships between brain function and behavior. Current treatments in neuropsychiatric disorders that are linked to cognitive deficits usually involve pharmacological interventions, but substantial evidence shows that individuals taking medication to normalize cognitive functioning typically experience adverse, nonspecific side effects that are not a direct result of the intended pharmacological action of the drug. In light of this evidence, it is of utmost scientific necessity that we formally understand the brain mechanisms that enable us to successfully guide goal-directed behavior in both health and disease.
This project established a long-needed neuroscientific perspective that, first, generates a formal and mechanistic understanding of the neural processes underlying distinct cognitive functions in the healthy brain and how they are affected by brain disorders, with the applied goal of developing neurocomputational assays that can detect deviant network interactions causally related to behavior. Second, based on these neurocomputational tools, this research elucidates how novel neural interventions involving low-cost and painless non-invasive brain stimulation techniques may be applied with the aim of designing potential treatments of a wide range of neuropsychological disorders associated with deficits in various cognitive functions that are in turn linked to abnormal brain function.