Whether to thrive or to survive, the ability to learn and acquire cognitive skills represents a fundamental aspect of human existence. However, individuals differ in their abilities to acquire new cognitive skills, with ~10% suffering from a learning disability. Others exhibit a marked decline in their cognitive skills in the wake of unfortunate events such as stroke, traumatic brain injury, or degenerative illnesses. Still others who exhibit normal cognitive functioning might be dissatisfied with their achievements, and wish to seek out means to improve their cognitive skills.
Two contemporary ways to improve cognitive abilities in healthy and atypical participants are: 1) cognitive training to affect the brain and impact behaviour; 2) brain stimulation to directly affect areas that might not function at an optimal (atypical populations) or the most optimal (typical populations) level. Recent research in my lab has successfully combined these methods to further improve skill acquisition and cognitive outcomes. Notably, our research to date has primarily focused on healthy adults, mostly with high-level cognitive abilities (university students). I aim to extend my research in several directions by: 1) optimising cognitive training and brain stimulation by combining individualised training and brain stimulation in an intervention that is inspired by the 'personalised medicine' approach; 2) uncovering the potential neurocognitive cost(s) that might be associated with neurocognitive enhancement, a point that has been almost completely neglected in the fields of brain stimulation and cognitive training; and 3) utilising neuroimaging methods to shed light on the neural mechanisms underlying the performance enhancement (and, possibly, cost) produced by cognitive training and brain stimulation. This integrative approach will allow me to take this young field a leap forward.
In this programme of research, I will adopt numerical cognition as a working model. This is motivated by theoretical reasons, because compared to more artificial training paradigms, numerical cognition is an excellent and highly realistic model for cognitive skill acquisition and complex cognitive skills, which can be easily translated to other domains (e.g., reading, attention, executive functions). Moreover, by applying cognitive training to numerical abilities this work will have high ecological validity and an increased likelihood to be translated beyond laboratory research to the public good. For practical reasons, numerical abilities represent an important cognitive asset, which affect one's level of education, career opportunities, salary, and socioeconomic status, as well as physical and mental health. Moreover, the financial and societal burden of low numeracy levels on our modern, technology-driven society further highlight the urgent need for basic and applied research on numerical cognition.
This ambitious, multidisciplinary programme will provide basic and potentially translational research implications in multiple fields, including neuroscience, psychology, and education. Therefore, this effort to study and improve human cognition by integrating both basic and applied research at the interface between neuroscience and psychology, represents a promising direction to my goal of improving education, training, and rehabilitation.