IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-022-35654-y.html
   My bibliography  Save this article

Neural mechanisms underlying the hierarchical construction of perceived aesthetic value

Author

Listed:
  • Kiyohito Iigaya

    (California Institute of Technology
    Columbia University Irving Medical Center
    Columbia University)

  • Sanghyun Yi

    (California Institute of Technology)

  • Iman A. Wahle

    (California Institute of Technology)

  • Sandy Tanwisuth

    (California Institute of Technology)

  • Logan Cross

    (California Institute of Technology
    Stanford University)

  • John P. O’Doherty

    (California Institute of Technology)

Abstract

Little is known about how the brain computes the perceived aesthetic value of complex stimuli such as visual art. Here, we used computational methods in combination with functional neuroimaging to provide evidence that the aesthetic value of a visual stimulus is computed in a hierarchical manner via a weighted integration over both low and high level stimulus features contained in early and late visual cortex, extending into parietal and lateral prefrontal cortices. Feature representations in parietal and lateral prefrontal cortex may in turn be utilized to produce an overall aesthetic value in the medial prefrontal cortex. Such brain-wide computations are not only consistent with a feature-based mechanism for value construction, but also resemble computations performed by a deep convolutional neural network. Our findings thus shed light on the existence of a general neurocomputational mechanism for rapidly and flexibly producing value judgements across an array of complex novel stimuli and situations.

Suggested Citation

  • Kiyohito Iigaya & Sanghyun Yi & Iman A. Wahle & Sandy Tanwisuth & Logan Cross & John P. O’Doherty, 2023. "Neural mechanisms underlying the hierarchical construction of perceived aesthetic value," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-022-35654-y
    DOI: 10.1038/s41467-022-35654-y
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-022-35654-y
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-022-35654-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Kiyohito Iigaya & Sanghyun Yi & Iman A. Wahle & Koranis Tanwisuth & John P. O’Doherty, 2021. "Aesthetic preference for art can be predicted from a mixture of low- and high-level visual features," Nature Human Behaviour, Nature, vol. 5(6), pages 743-755, June.
    2. Valerio Mante & David Sussillo & Krishna V. Shenoy & William T. Newsome, 2013. "Context-dependent computation by recurrent dynamics in prefrontal cortex," Nature, Nature, vol. 503(7474), pages 78-84, November.
    3. Ladan Shams & Yukiyasu Kamitani & Shinsuke Shimojo, 2000. "What you see is what you hear," Nature, Nature, vol. 408(6814), pages 788-788, December.
    4. Camillo Padoa-Schioppa & John A. Assad, 2006. "Neurons in the orbitofrontal cortex encode economic value," Nature, Nature, vol. 441(7090), pages 223-226, May.
    5. Thomas A. Stalnaker & Nisha K. Cooch & Michael A. McDannald & Tzu-Lan Liu & Heather Wied & Geoffrey Schoenbaum, 2014. "Orbitofrontal neurons infer the value and identity of predicted outcomes," Nature Communications, Nature, vol. 5(1), pages 1-13, September.
    6. Shiva Farashahi & Christopher H. Donahue & Benjamin Y. Hayden & Daeyeol Lee & Alireza Soltani, 2019. "Flexible combination of reward information across primates," Nature Human Behaviour, Nature, vol. 3(11), pages 1215-1224, November.
    7. Mattia Rigotti & Omri Barak & Melissa R. Warden & Xiao-Jing Wang & Nathaniel D. Daw & Earl K. Miller & Stefano Fusi, 2013. "The importance of mixed selectivity in complex cognitive tasks," Nature, Nature, vol. 497(7451), pages 585-590, May.
    8. Nathaniel D. Daw & John P. O'Doherty & Peter Dayan & Ben Seymour & Raymond J. Dolan, 2006. "Cortical substrates for exploratory decisions in humans," Nature, Nature, vol. 441(7095), pages 876-879, June.
    9. Kendrick N. Kay & Thomas Naselaris & Ryan J. Prenger & Jack L. Gallant, 2008. "Identifying natural images from human brain activity," Nature, Nature, vol. 452(7185), pages 352-355, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wenyi Zhang & Yang Xie & Tianming Yang, 2022. "Reward salience but not spatial attention dominates the value representation in the orbitofrontal cortex," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    2. 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.
    3. Jan Weber & Anne-Kristin Solbakk & Alejandro O. Blenkmann & Anais Llorens & Ingrid Funderud & Sabine Leske & Pål Gunnar Larsson & Jugoslav Ivanovic & Robert T. Knight & Tor Endestad & Randolph F. Helf, 2024. "Ramping dynamics and theta oscillations reflect dissociable signatures during rule-guided human behavior," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    4. Pierre O. Boucher & Tian Wang & Laura Carceroni & Gary Kane & Krishna V. Shenoy & Chandramouli Chandrasekaran, 2023. "Initial conditions combine with sensory evidence to induce decision-related dynamics in premotor cortex," Nature Communications, Nature, vol. 14(1), pages 1-28, December.
    5. Wan-Yu Shih & Hsiang-Yu Yu & Cheng-Chia Lee & Chien-Chen Chou & Chien Chen & Paul W. Glimcher & Shih-Wei Wu, 2023. "Electrophysiological population dynamics reveal context dependencies during decision making in human frontal cortex," Nature Communications, Nature, vol. 14(1), pages 1-24, December.
    6. Zhewei Zhang & Chaoqun Yin & Tianming Yang, 2022. "Evidence accumulation occurs locally in the parietal cortex," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    7. Javier G. Orlandi & Mohammad Abdolrahmani & Ryo Aoki & Dmitry R. Lyamzin & Andrea Benucci, 2023. "Distributed context-dependent choice information in mouse posterior cortex," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    8. Nir Moneta & Mona M. Garvert & Hauke R. Heekeren & Nicolas W. Schuck, 2023. "Task state representations in vmPFC mediate relevant and irrelevant value signals and their behavioral influence," Nature Communications, Nature, vol. 14(1), pages 1-21, December.
    9. Huanyuan Zhou & KongFatt Wong-Lin & Da-Hui Wang, 2018. "Parallel Excitatory and Inhibitory Neural Circuit Pathways Underlie Reward-Based Phasic Neural Responses," Complexity, Hindawi, vol. 2018, pages 1-20, April.
    10. Benjamin R Cowley & Matthew A Smith & Adam Kohn & Byron M Yu, 2016. "Stimulus-Driven Population Activity Patterns in Macaque Primary Visual Cortex," PLOS Computational Biology, Public Library of Science, vol. 12(12), pages 1-31, December.
    11. Takuya Ito & Guangyu Robert Yang & Patryk Laurent & Douglas H. Schultz & Michael W. Cole, 2022. "Constructing neural network models from brain data reveals representational transformations linked to adaptive behavior," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    12. John A Clithero & Dharol Tankersley & Scott A Huettel, 2008. "Foundations of Neuroeconomics: From Philosophy to Practice," PLOS Biology, Public Library of Science, vol. 6(11), pages 1-6, November.
    13. Nagaraj R. Mahajan & Shreesh P. Mysore, 2022. "Donut-like organization of inhibition underlies categorical neural responses in the midbrain," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    14. Daniel Durstewitz, 2017. "A state space approach for piecewise-linear recurrent neural networks for identifying computational dynamics from neural measurements," PLOS Computational Biology, Public Library of Science, vol. 13(6), pages 1-33, June.
    15. Kaushik J. Lakshminarasimhan & Eric Avila & Xaq Pitkow & Dora E. Angelaki, 2023. "Dynamical latent state computation in the male macaque posterior parietal cortex," Nature Communications, Nature, vol. 14(1), pages 1-20, December.
    16. J. L. Amengual & F. Di Bello & S. Ben Hadj Hassen & Suliann Ben Hamed, 2022. "Distractibility and impulsivity neural states are distinct from selective attention and modulate the implementation of spatial attention," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    17. Laura E. Suárez & Agoston Mihalik & Filip Milisav & Kenji Marshall & Mingze Li & Petra E. Vértes & Guillaume Lajoie & Bratislav Misic, 2024. "Connectome-based reservoir computing with the conn2res toolbox," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    18. Qianli Yang & Edgar Walker & R. James Cotton & Andreas S. Tolias & Xaq Pitkow, 2021. "Revealing nonlinear neural decoding by analyzing choices," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
    19. Shinichiro Kira & Houman Safaai & Ari S. Morcos & Stefano Panzeri & Christopher D. Harvey, 2023. "A distributed and efficient population code of mixed selectivity neurons for flexible navigation decisions," Nature Communications, Nature, vol. 14(1), pages 1-28, December.
    20. Leo Chi U Seak & Simone Ferrari-Toniolo & Ritesh Jain & Kirby Nielsen & Wolfram Schultz, 2023. "Systematic comparison of risky choices in humans and monkeys," Working Papers 202316, University of Liverpool, Department of Economics.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-022-35654-y. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.