Skip to main content

Beyond the blob: characterizing Prefrontal Cortex networks in prediction and motivation with simultaneous EEG-fMRI recordings

Periodic Reporting for period 1 - PreMotive (Beyond the blob: characterizing Prefrontal Cortex networks in prediction and motivation with simultaneous EEG-fMRI recordings)

Reporting period: 2016-08-01 to 2018-07-31

Life is full of surprises. It is fundamental to swiftly realize when things don’t go as planned, and come up with new plans, adapting to the unforeseen. In the human brain, these surprise signals are essential for learning, predicting future events, and select the most appropriate behaviour. Research suggests that surprise signals are continuously calculated by the prefrontal cortex (PFC). However, the precise mechanisms supporting this calculation, and how it affects the rest of the brain, was unclear. The goal of this project was to determine how different PFC regions contribute in computing surprise, and how this changes 1) the processing of sensory information, and 2) the processing of motivational information. Specifically, I tested a neurocomputational theory of PFC function using EEG-fMRI Simultaneous recordings, a cutting-edge technique that allows measuring where and when certain brain regions are active, and hence determine how they communicate. This theory emphasizes the importance of understanding network dynamics, rather than simply testing for activity in isolated regions. The results show that surprise signals are indeed encoded by a cortico-cortical network including sensory regions, medial PFC and lateral PFC. Furthermore, I tested behavioural predictions of the same model of PFC function on how motivational information (rather than sensory information) is processed. To this end, I have shown that healthy people’s decisions change depending on whether they are informed about cost or benefits first. I replicate this observation in patients with Parkinson’s Disease, opening up potential avenues for clinical translation. Overall, the results of the project provide substantial contribution to understanding PFC function, and indicate how this knowledge may be exploited to understand altered PFC activity in pathology, and to devise interventions based on the behavioural observations and computational insights.
During this period, I have accomplished the project’s goals, detailed in three work packages (WPs). WP1-2 included EEG and EEG-fMRI training, the development of a novel experimental paradigm (implementing cross-modal prediction and prediction error), the development and testing of the technical setup and empirical testing of the proposed hypotheses.
I have learned how to perform EEG data analysis and how to collect simultaneous fMRI-EEG data. I have developed a novel experimental paradigm to investigate the Prediction-Error Error Prediction hypothesis (PE-EP) outlined in the grant proposal. I developed a cross-modal cueing paradigm, where participants were exposed to two different type of stimuli: visual stimuli (colored circles on a computer screen) and somatosensory stimuli (vibrations delivered through a custom-made MR-compatible device). I have tested the novel experimental setup and paradigm with extensive pilot work, and subsequently successfully collected 46 datasets. The fMRI and EEG have been analysed as planned. I have learned to use new analysis toolboxes (Brain vision analyzer, Fieldtrip, fMRI prep, ICA AROMA, MRqc)
The goal of WP3 was to investigate how motivational information affects behaviour (decision-making and task-performance), with particular attention to timing of presentation of effort and reward information. This WP3 has been carried out in collaboration with Oxford University as planned. I investigated effects of motivational information processing (according to the discussed PFC theory) on behaviour of patients’ with Parkinson’s Disease (PD). We know PD patients have a dopamine deficits, and by testing these patients ON and OFF dopaminergic medication it was possible to directly address the hypothesis that the disease, and dopaminergic medication, would interact with PFC mapping of motivational information, thus affecting behaviour. For this project, 50 datasets have been collected (25 patients ON and OFF medication).
Dissemination has been a priority throughout the project. I have published theoretical and empirical work related to WP1-3 in 7 scientific articles (in the Journal of Cognitive Neuroscience, Frontiers in neuroscience, Neuropsychologia, Plos Computational Biology, Cognitive Affective Behavioural Neuroscience).
I have participated to international scientific conferences to spread these findings, both as symposium organizer and invited speaker. In 2017 I attended the International conference for Cognitive Neuroscience ICON, where I organized a discussion panel and delivered an invited talk, and the meeting of the Dutch association for psychonomics (NVP, 2017, symposium organizer and speaker). In 2018 I was an invited speaker at the Society for Psychophysiology (SPR) meeting. In 2019 I gave keynote lecture at the Spring School on Cognitive Control of Dresden Technical university, and a talk in a symposium at the International Convention for Psychological Science (ICPS). In 2019 I will also attend the Assciation for Psychological Science convention (APS, invited talk), and the European Society for Cognitive Psychology meeting (ESCOP, as speaker and symposium organizer).

I have also carried out outreach actions. I became Editor-in-Chief of the online magazine In-Mind (http://it.in-mind.org/) publishing several issues featuring articles written in laymen terms, describing scientific findings (from the field of Psychology and Neuroscience). All published articles are written by experts, peer-reviewed and reviewed for readability and language by the editorial team. Additionally, I have written 2 dissemination pieces, aimed at a broader audience. In one article, I describe some of the computational approaches I used. This article is published on the popular online magazine Science Trends (https://sciencetrends.com/how-the-brain-learns-to-control-itself/). In the second piece, I broadly summarize the goal of my research and research methods (http://blog.donders.ru.nl/?p=8828&lang=en).
This work has brought about substantial progress in the state of the art of computational understanding of PFC networks function (as evidenced by the project-related publications). Further, publication of the empirical results will be pursued shortly. The findings in Parkinson’s patients have additional potential to inform patient research (understanding neural mechanisms underlying behavioural deficits such as lack of motivation and apathy), as well inspire novel interventions (my data suggest that changing the way patients process information may reduce lack of motivation and effort avoidance).

In terms of broader scientific and societal impact, I have collaborated in starting up the “Women in Neuroscience Repository” (www.winrepo.org). WinRepo is an online repository where women neuroscientists can subscribe, make a profile describing their specialization and work, and hence be more visible. The purpose is to facilitate the organisation of more diverse and gender-balanced conferences and symposia (issue that is currently problematic in the field). I currently am a member of the WinRepo committee, and I am active in other activities with the purpose of raising awareness on gender bias in neuroscience. About this topic, I wrote an article together with the WinRepo committee, discussing gender bias, issues and solutions. This article has been published in the European Journal of Neuroscience in 2019.
mc-figure-final.png