Expectancy learning · Enhancing expectancy formation in healthy aging through statistical and sensorimotor learning
Horizon 2020 — Marie Skłodowska-Curie Actions
- Duration
- 2016-05-01 → 2018-06-04
- EU contribution
- €165,599
- Participants
- 1
- Scheme
- MSCA-IF-EF-ST
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Results in brief
Enhancing expectancy formation in healthy aging through statistical and sensorimotor learning
To function in a dynamic environment, humans must learn which events to expect, and when to expect them. Anticipating upcoming events is particularly important for making sense of complex auditory information such as speech or music. How does learning give rise to the ability to anticipate upcoming events, and how does this ability change over the lifespan? In addition, can learning be enhanced by regularities in the environment and by linking movements with those events? These questions have remained unanswered until now, yet they are crucial to understanding how the human brain develops the ability to predict future events and how this system changes in healthy aging. This understanding provides a basis for selecting and informing interventions, therapies, technologies, and even policies that can maximize the independence and well-being of elderly individuals. The main goal of the project is to understand how individuals learn to anticipate what events will occur and when they will occur within novel series of information. The aims of the project are to reveal 1) how people learn to anticipate both particular events and higher-level structures of events, 2) how learning changes in healthy aging, 3) whether regularities in the environment and linking movements to external events can enhance learning, and 4) how subcortical brain regions are involved in these learning processes. To address these objectives we applied behavioural, electrophysiological, and neuroimaging approaches, as well as theoretical development. These approaches revealed how learning of events and event structures unfold, and results confirmed that regularities and body movement enhance learning. These approaches also revealed unexpected insights, including different ways in which movement enhances learning, individual differences in temporal structure learning, and a theoretical framework for prediction and learning in healthy aging.
Data: CORDIS, © European Union
Project 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.
Original text from CORDIS.
Participants
- UNIVERSITEIT MAASTRICHT · MaastrichtCoordinatorNetherlands
Links
- View on CORDIS
- DOI: 10.3030/707865
- https://band-lab.com/iii-the-people/iii-ii-the-people-post-docs/iii-ii-ii-the-people-post-docs-rachel-brown/
Data: CORDIS, © European Union