Periodic Reporting for period 1 - BrainBehaviourModel (Understanding decision making by linking brain and behaviour)
Periodo di rendicontazione: 2018-06-01 al 2020-05-31
The second data set was obtained to further apply the novel modelling approach to other aspects of decision-making, in particular the effect of urgency by imposing a strict deadline on the decision time. This revealed a more rapid build-up of the centroparietal EEG-ERP component when participants were required to respond before an imposed deadline compared to when they could decide freely. The application of the modelling approach to this data is currently still ongoing and expected to be finalized and prepared for submission to a scientific journal within the next year.
A biologically-detailed computational model of cortico-basal ganglia networks was implemented in a commonly used open-source software program. Using this model, we demonstrated that the effect of dopaminergic medication on abnormal neural oscillations in Parkinson’s disease can be explained by wide-spread alterations in coupling strength between regions of the network. This study was published in a peer-reviewed scientific journal.
Using simultaneous recordings from deep brain stimulation electrodes and MEG, we demonstrated that separate functional networks between the cortex and subthalamic nucleus project to different parts of the subthalamic nucleus but with large spatial overlap. This suggests that it might be very difficult to entirely avoid neurocognitive side effects during deep brain stimulation treatment of Parkinson’s disease. This study is currently under review for publication in a peer-reviewed scientific journal.
We wrote a comprehensive review on the anatomy and functional organization of the subthalamic nucleus, the primary target for implantation of deep brain stimulation electrodes for treatment of Parkinson’s disease. This knowledge is important for unravelling the role of the subthalamic nucleus in controlling limbic, cognitive, and motor functions, and for understanding whether these functions can be seen as clearly independent of one another. The review was published in a peer-reviewed scientific journal.
Throughout the timeline of the Fellowship, project plans and results have been communicated to other researchers at international conferences (Cosyne 2019, HBM 2019), institutional seminars (Amsterdam, Moscow), and lab meetings (Amsterdam, London, Shanghai). In addition, two book chapters were written for a lay audience on the principles behind EEG and neural oscillations in motor control and decision-making.
The EEG studies in this project are the first to combine mathematical modelling of behavioural responses with computational modelling of EEG responses. This is a crucial step towards a full integration of cognition and neurobiology in a single model, which would be the ultimate goal for explaining how the brain controls the decisions we make. Although cognitive models of behavioural responses and neural models of EEG responses are both established methods in their respective disciplines, it is their combination that brings novel insights. Importantly, the novel modelling approach hols the potential for bringing abstract theories in psychology a step closer towards their neurobiological implementation. The approach can be readily extended to more complex decision-making processes that involve, e.g. strategic choices, values and emotions, and social factors, and to other research domains in (cognitive) neuroscience such as memory, perception, and language. It is therefore expected to find wider research applications in the next years.
Atypical decision-making behaviour in the form of systematic impulsive actions or choices may become problematic in ADHD, obsessive-compulsive disorder, gambling and drug addictions. Unravelling how our decisions are rooted in neurobiological mechanisms helps us to understand the factors that influence our behaviour, and inter-individual differences in behaviour. In the long-term, the novel modelling approach might significantly contribute to predicting effects of pharmacological interventions, stimulation protocols, and lesions on decision-making behaviour.