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Enhancing brain function and cognition via artificial entrainment of neural oscillations

Periodic Reporting for period 2 - ENTRAINER (Enhancing brain function and cognition via artificial entrainment of neural oscillations)

Reporting period: 2019-08-01 to 2021-01-31

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 (e.g. attention deficit hyperactivity disorder; ADHD) that are related to certain cognitive deficits, strongly suggest that these types of synchronized large-scale network interactions have a functional role. However, and critically, there is virtually no theory-driven mechanistic approach that generates insights into how neural oscillations are linked to human behavior. Moreover, we have currently no validated tools to modulate large-scale network interactions in the intact human brain. This project will be essential to derive 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 will be carried out by an unprecedented combination of brain imaging techniques, computational modelling, and novel non-invasive causal manipulations of brain rhythms.

This project will mainly focus on gaining a deep understanding of 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 the 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.

We expect to generate mechanistically interpretable neuro-computational assays for the characterization of “limited attention”. 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 such as ADHD 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. Moreover, the disappointing results of extensive clinical trials in various psychopathologies such as ADHD desperately call for the development of non-invasive interventions other than pharmacology. 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. A systematic and mechanistic understanding of the link between neurophysiological signatures and behavior would allow us to consider non-pharmacological and non-invasive interventions that are completely different from current treatments.

Thus, in this project, I aim to establish a long-needed neuroscientific perspective that, first, will generate 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 will elucidate 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.
1) Creation Decision Neuroscience Lab at ETH Zurich ( Thanks to the ERC starting grant awarded to the PI, just about 2.5 years ago it was possible to create from scratch the Decision Neuroscience Lab, where the support ETH has been fundamental for the successful kick-off of our lab. Since then and based on ERC funding, the lab welcomed three enthusiastic PhD students to the team. Two other PhD students have been hired thanks to further third party funding support. After 1 year of creation, we obtained the required ethical approvals and the lab was equipped with all necessary devices to be able to conduct the planned research work.

2) Development of attention limitation theories for the study of human behavior: The brain is a metabolically expensive inference machine. Therefore, it has been suggested that evolutionary pressure has driven it to make productive use of its limited resources by exploiting statistical regularities in a given context or environment. In the first part of our research program, we have developed behavioral theories allowing taking into consideration attentional resource limitations in human cognition by trying to solve the following fundamental question: What determines the degree of imprecisions and biases in human decisions? We propose a new theory that solves this problem and when tested against real human data, we in fact demonstrate that humans optimally make use of their limited resources for processing incoming information and exploit environmental regularities to guide decision behavior. The results of our work may have far-reaching implications not only in neuroscience, but also in psychology and economics. Such models offer the prospect of explanations for seemingly irrational aspects of choice behavior, grounded in the need to represent the world with only finite precision. This supports our emphasis on the desirability of developing models of decision-making that account simultaneously for the organisms’s goals, its environment, and its biological constraints.
Development of novel non-invasive technologies for control modulation of selective attention: Selective attention is the act of focusing one’s conscious awareness towards the stimuli most important for goal-directed behavior and away from distractors. This is paramount for survival, since at any moment in time organisms are bombarded with far more information than they can physically process. Understanding attention is important because there are disorders linked to attention deficits such as attention deficit hyperactivity disorder (ADHD). Additionally the modulation of attentional control has possible applications in the treatment of post-traumatic stress disorder and dieting. In our lab, we have recently designed a novel non-invasive brain stimulation protocol based on a closed loop stimulation technique using weak transcranial electrical currents, which allows to selectively, dynamically and rapidly up or down regulate top-down attentional control. We are currently in the process of validating this innovative methodology via various control measurements and neurocomputational characterizations. If this project is successful, this work will ultimately result in novel, low-cost, and painless non-invasive neural interventions for a wide range of neuropsychological disorders tied to abnormal attentional control.