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Learning task-state representations

Nature Neuroscience volume 22, pages 1544–1553 (2019)Cite this article

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Abstract

Arguably, the most difficult part of learning is deciding what to learn about. Should I associate the positive outcome of safely completing a street-crossing with the situation ‘the car approaching the crosswalk was red’ or with ‘the approaching car was slowing down’? In this Perspective, we summarize our recent research into the computational and neural underpinnings of ‘representation learning’—how humans (and other animals) construct task representations that allow efficient learning and decision-making. We first discuss the problem of learning what to ignore when confronted with too much information, so that experience can properly generalize across situations. We then turn to the problem of augmenting perceptual information with inferred latent causes that embody unobservable task-relevant information, such as contextual knowledge. Finally, we discuss recent findings regarding the neural substrates of task representations that suggest the orbitofrontal cortex represents ‘task states’, deploying them for decision-making and learning elsewhere in the brain.

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Fig. 1: Task representations.
Fig. 2: The Dimensions Task.
Fig. 3: Latent-cause inference in representation learning suggests a mechanism for altering fear memories.
Fig. 4: Humans spontaneously use similarity to infer the latent structure of task.
Fig. 5: The orbitofrontal cortex represents the current state of the task.

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Acknowledgements

I am grateful to my lab members, past and present, for their creative, methodical and incredibly revealing work on representation learning in the brain. I thank A. Langdon, N. Rouhani, and J. Zarate for helpful comments on a previous draft. This work was funded by grant W911NF-14-1-0101 from the Army Research Office and grant R01DA042065 from the National Institute on Drug Abuse.

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    Yael Niv

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Niv, Y. Learning task-state representations. Nat Neurosci 22, 1544–1553 (2019). https://doi.org/10.1038/s41593-019-0470-8

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