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Single neurons in prefrontal cortex encode abstract rules

Author

Listed:
  • Jonathan D. Wallis

    (Center for Learning and Memory, RIKEN-MIT Neuroscience Research Center, Massachusetts Institute of Technology)

  • Kathleen C. Anderson

    (Center for Learning and Memory, RIKEN-MIT Neuroscience Research Center, Massachusetts Institute of Technology)

  • Earl K. Miller

    (Center for Learning and Memory, RIKEN-MIT Neuroscience Research Center, Massachusetts Institute of Technology)

Abstract

The ability to abstract principles or rules from direct experience allows behaviour to extend beyond specific circumstances to general situations. For example, we learn the ‘rules’ for restaurant dining from specific experiences and can then apply them in new restaurants. The use of such rules is thought to depend on the prefrontal cortex (PFC) because its damage often results in difficulty in following rules1. Here we explore its neural basis by recording from single neurons in the PFC of monkeys trained to use two abstract rules. They were required to indicate whether two successively presented pictures were the same or different depending on which rule was currently in effect. The monkeys performed this task with new pictures, thus showing that they had learned two general principles that could be applied to stimuli that they had not yet experienced. The most prevalent neuronal activity observed in the PFC reflected the coding of these abstract rules.

Suggested Citation

  • Jonathan D. Wallis & Kathleen C. Anderson & Earl K. Miller, 2001. "Single neurons in prefrontal cortex encode abstract rules," Nature, Nature, vol. 411(6840), pages 953-956, June.
    • Handle: RePEc:nat:nature:v:411:y:2001:i:6840:d:10.1038_35082081
    DOI: 10.1038/35082081
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    Cited by:

    1. Ali Ghazizadeh & Okihide Hikosaka, 2022. "Salience memories formed by value, novelty and aversiveness jointly shape object responses in the prefrontal cortex and basal ganglia," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    2. R Becket Ebitz & Brianna J Sleezer & Hank P Jedema & Charles W Bradberry & Benjamin Y Hayden, 2019. "Tonic exploration governs both flexibility and lapses," PLOS Computational Biology, Public Library of Science, vol. 15(11), pages 1-37, November.
    3. Francesco Ceccarelli & Lorenzo Ferrucci & Fabrizio Londei & Surabhi Ramawat & Emiliano Brunamonti & Aldo Genovesio, 2023. "Static and dynamic coding in distinct cell types during associative learning in the prefrontal cortex," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    4. Bahareh Taghizadeh & Ole Fortmann & Alexander Gail, 2024. "Position- and scale-invariant object-centered spatial localization in monkey frontoparietal cortex dynamically adapts to cognitive demand," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    5. Márton Albert Hajnal & Duy Tran & Michael Einstein & Mauricio Vallejo Martelo & Karen Safaryan & Pierre-Olivier Polack & Peyman Golshani & Gergő Orbán, 2023. "Continuous multiplexed population representations of task context in the mouse primary visual cortex," Nature Communications, Nature, vol. 14(1), pages 1-20, December.
    6. Florian Raudies & Eric A Zilli & Michael E Hasselmo, 2014. "Deep Belief Networks Learn Context Dependent Behavior," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-9, March.
    7. Arno Onken & Jue Xie & Stefano Panzeri & Camillo Padoa-Schioppa, 2019. "Categorical encoding of decision variables in orbitofrontal cortex," PLOS Computational Biology, Public Library of Science, vol. 15(10), pages 1-27, October.
    8. Daigo Takeuchi & Dheeraj Roy & Shruti Muralidhar & Takashi Kawai & Andrea Bari & Chanel Lovett & Heather A. Sullivan & Ian R. Wickersham & Susumu Tonegawa, 2022. "Cingulate-motor circuits update rule representations for sequential choice decisions," Nature Communications, Nature, vol. 13(1), pages 1-19, December.

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