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Towards a neuroscience of active sampling and curiosity

Nature Reviews Neurosciencevolume 19pages758770 (2018) | Download Citation


In natural behaviour, animals actively interrogate their environments using endogenously generated ‘question-and-answer’ strategies. However, in laboratory settings participants typically engage with externally imposed stimuli and tasks, and the mechanisms of active sampling remain poorly understood. We review a nascent neuroscientific literature that examines active-sampling policies and their relation to attention and curiosity. We distinguish between information sampling, in which organisms reduce uncertainty relevant to a familiar task, and information search, in which they investigate in an open-ended fashion to discover new tasks. We review evidence that both sampling and search depend on individual preferences over cognitive states, including attitudes towards uncertainty, learning progress and types of information. We propose that, although these preferences are non-instrumental and can on occasion interfere with external goals, they are important heuristics that allow organisms to cope with the high complexity of both sampling and search, and generate curiosity-driven investigations in large, open environments in which rewards are sparse and ex ante unknown.

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The authors acknowledge support from the Human Frontiers Science Program (Collaborative Research Grant RGP0018/2016 to J.G. and P.-Y.O.), an Inria Neurocuriosity grant (to J.G. and P.-Y.O.), the National Eye Institute (RO1 grant to J.G.) and the National Institute of Mental Health (RO1 grant to J.G.).

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Nature Reviews Neuroscience thanks V. Stuphorn and the other anonymous reviewers for their contribution to the peer review of this work.

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  1. Department of Neuroscience, Columbia University, New York, NY, USA

    • Jacqueline Gottlieb
  2. Kavli Institute for Brain Science, Columbia University, New York, NY, USA

    • Jacqueline Gottlieb
  3. Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA

    • Jacqueline Gottlieb
  4. Inria, Bordeaux, France

    • Pierre-Yves Oudeyer
  5. Ensta ParisTech, Paris, France

    • Pierre-Yves Oudeyer


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The authors both researched data for the article, provided substantial contributions to discussion of content, wrote the article, and reviewed and edited the manuscript before submission.

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The authors declare no competing interests.

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Correspondence to Jacqueline Gottlieb.



Any entities that are capable of learning and decision-making, including humans, other animals and artificial intelligence applications such as robots and self-driving cars.

Instrumental context

A context in which agents are motivated by the desire to obtain a known goal, which is operationalized in the laboratory as maximizing a material reward (such as money, points, food or safety).

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