Sampling motion trajectories during hippocampal theta sequences

Efficient planning in complex environments requires that uncertainty associated with current inferences and possible consequences of forthcoming actions is represented. Representation of uncertainty has been established in sensory systems during simple perceptual decision making tasks but it remains...

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Bibliographic Details
Published in:eLife 2022-11, Vol.11
Main Authors: Ujfalussy, Balazs B, Orbán, Gergő
Format: Article
Language:English
Subjects:
Animals
Cognitive ability
Decision making
Hippocampus
Hippocampus - physiology
navigation
neural coding
Neurons
Neuroscience
planning
probabilistic representations
Probability
Probability distribution
Rats
Sampling
Sensory systems
Theta Rhythm - physiology
Theta rhythms
Uncertainty
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Summary:Efficient planning in complex environments requires that uncertainty associated with current inferences and possible consequences of forthcoming actions is represented. Representation of uncertainty has been established in sensory systems during simple perceptual decision making tasks but it remains unclear if complex cognitive computations such as planning and navigation are also supported by probabilistic neural representations. Here, we capitalized on gradually changing uncertainty along planned motion trajectories during hippocampal theta sequences to capture signatures of uncertainty representation in population responses. In contrast with prominent theories, we found no evidence of encoding parameters of probability distributions in the momentary population activity recorded in an open-field navigation task in rats. Instead, uncertainty was encoded sequentially by sampling motion trajectories randomly and efficiently in subsequent theta cycles from the distribution of potential trajectories. Our analysis is the first to demonstrate that the hippocampus is well equipped to contribute to optimal planning by representing uncertainty.
ISSN:2050-084X
2050-084X
DOI:10.7554/eLife.74058