It may seem quite menial, but even a simple action like reaching for a cup of coffee requires complex, yet instantaneous computations by the brain. In addition to variables like how full the cup is or the shape of the cup, there are many other factors that can affect these computations. Changes in cognition, such as memories of using similar cups in the past, and in mental health, affecting how much we value drinking this coffee – can all determine how we will reach for and grasp this cup of coffee. My research aims to improve our understanding of the links between cognition, mental health and action both in health and disease. We combine clinical and basic neuroscience methods for our research.
Changes in motivation are common in many neurological and psychiatric conditions, such as dementia and depression, but also in healthy individuals and in normal ageing. We attempt to understand whether there is a core mechanism explaining differences in motivation, and if so what it is. A related set of questions refers to how different types of motivational deficits differ across conditions, and whether this can inform us as to the specific treatment at an individual level.
We investigate the processes underlying the cluster of symptoms termed 'negative symptoms' in schizophrenia. These symptoms include reduced motivation or 'apathy' and reduced emotional expressivity. Although they tend to be overlooked and far less studied than symptoms of hallucinations and delusions, negative symptoms determine long-term clinical outcome in patients.
In this project, we ask what leads to apathy in patients, and how this can be potentially treated. To investigate this, we use computerised tasks that ask participants to decide whether and which actions to perform under different experimental conditions.
We look at individual differences in learning mechanisms in older adults and test whether certain mechanisms can put older adults at risks. Recent research has shown that even simple motor learning tasks involve a combination of learning mechanisms, such as explicit and implicit learning, feedforward and feedback adaptation, and model-free and model-based learning strategies. Our research aims to identify which mechanisms place older adults at age-related risks to their wellbeing, such as frailty and falls.