Objective
My research examines how humans form new expectancies, or states of anticipation for future events, and how expectancy formation changes over the lifespan. Humans constantly anticipate upcoming events in order to understand those events, prepare actions, and adapt to changes. Although the neural and behavioral signatures of expectancies have been well-characterized, we do not know how they arise and how they change over the lifespan. I aim to reveal the following: 1) How new expectancies are formed during the course of learning novel information. 2) How expectancy formation differs between younger and older adults. 3) How the combination of regularities in event structure and sensorimotor integration, a phenomenon that has not been investigated, potentiates expectancy formation. 4) The role of interacting subcortical-cortical neural networks in expectancy formation. I will monitor the dynamic changes in electrophysiological brain responses, as well as overt anticipatory behaviour, over the course of learning in order to capture the changes of anticipatory responses online, and I will apply Bayesian neural network modelling to infer the neural and cognitive state changes underlying these response changes. I will also measure changes in subcortical-cortical networks that result from learning, including structural integrity, functional connectivity, and the ability to decode the learned information. This multi-methods approach will utilize my expertise in behavioural and MRI methods combined with my research group's expertise in EEG and computational modelling, as well as the state-of-the-art EEG, MRI, and laboratory facilities, on-site expertise, and support staff available at Maastricht University. This research is urgently needed so that we can finally understand the origin of expectancies, their consequences on the aging brain, and how we can enhance their formation to improve lifelong learning.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- natural sciences biological sciences neurobiology cognitive neuroscience
- natural sciences computer and information sciences artificial intelligence computational intelligence
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
MSCA-IF-EF-ST - Standard EF
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-MSCA-IF-2015
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
6200 MD Maastricht
Netherlands
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.