Summary
How does the brain use past experiences to shape future actions? Over two decades ago, research in rodents has made a remarkable discovery that may provide key answers to this fundamental question. Researchers found that while rats were sleeping, activity in their hippocampus seemingly retraced the animals’ previous trajectories in a maze, only much faster than in real time. This phenomenon, known as replay, has become a major focus of neuroscientists and even artificial intelligence researchers over the past decades. The resulting research demonstrated that replay is prevalent during wakeful resting, related to memory, planning and reward processing, and shares similarities with machine learning algorithms. These findings suggest that replay may be a fundamental mechanism behind memory consolidation and the computation of optimal behavior. Yet, despite the significance of this phenomenon, little is known about replay in the human brain. The major reason for the lack of knowledge are difficulties to measure fast neural processes non-invasively in the human hippocampus. The main goal of the proposed research is to overcome these obstacles, and to provide deeper insights into replay in humans. To achieve this, we will use a novel fMRI analysis method that tests whether the transitions between successive fMRI patterns during rest or sleep exhibit non-random relations to the temporal structure of previous experiences. Using this approach, the proposed research will provide insights into four cognitive and computational aspects of replay in the human brain: (1) the coordination of hippocampal replay with activity in other brain areas, (2) the effects of reward and planning on content and direction of replay, (3) the role of replay during sleep and its relation to sleep spindles, and (4) its role in age-related memory decline. In combination, insights gained from this research promise to greatly enhance our understanding of how memories guide adaptive behavior in humans.
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| Web resources: | https://cordis.europa.eu/project/id/852669 |
| Start date: | 01-04-2020 |
| End date: | 30-09-2026 |
| Total budget - Public funding: | 1 416 506,00 Euro - 1 416 506,00 Euro |
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Original description
How does the brain use past experiences to shape future actions? Over two decades ago, research in rodents has made a remarkable discovery that may provide key answers to this fundamental question. Researchers found that while rats were sleeping, activity in their hippocampus seemingly retraced the animals’ previous trajectories in a maze, only much faster than in real time. This phenomenon, known as replay, has become a major focus of neuroscientists and even artificial intelligence researchers over the past decades. The resulting research demonstrated that replay is prevalent during wakeful resting, related to memory, planning and reward processing, and shares similarities with machine learning algorithms. These findings suggest that replay may be a fundamental mechanism behind memory consolidation and the computation of optimal behavior. Yet, despite the significance of this phenomenon, little is known about replay in the human brain. The major reason for the lack of knowledge are difficulties to measure fast neural processes non-invasively in the human hippocampus. The main goal of the proposed research is to overcome these obstacles, and to provide deeper insights into replay in humans. To achieve this, we will use a novel fMRI analysis method that tests whether the transitions between successive fMRI patterns during rest or sleep exhibit non-random relations to the temporal structure of previous experiences. Using this approach, the proposed research will provide insights into four cognitive and computational aspects of replay in the human brain: (1) the coordination of hippocampal replay with activity in other brain areas, (2) the effects of reward and planning on content and direction of replay, (3) the role of replay during sleep and its relation to sleep spindles, and (4) its role in age-related memory decline. In combination, insights gained from this research promise to greatly enhance our understanding of how memories guide adaptive behavior in humans.Status
SIGNEDCall topic
ERC-2019-STGUpdate Date
27-04-2024
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