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Higher-order and distributed synergistic functional interactions encode information gain in goal-directed learning

Author

Listed:
  • Etienne Combrisson

    (CNRS)

  • Ruggero Basanisi

    (CNRS
    IMT School for Advanced Studies Lucca)

  • Matteo Neri

    (CNRS)

  • Guillaume Auzias

    (CNRS)

  • Giovanni Petri

    (London
    CENTAI Institute)

  • Daniele Marinazzo

    (Faculty of Psychological and Educational Sciences)

  • Stefano Panzeri

    (University Medical Center Hamburg-Eppendorf (UKE))

  • Andrea Brovelli

    (CNRS)

Abstract

Goal-directed learning arises from distributed neural circuits including the prefrontal, posterior parietal and temporal cortices. However, the role of cortico-cortical functional interactions remains unclear. To address this question, we integrated information dynamics analysis with magnetoencephalography to investigate the encoding of learning signals through neural interactions. Our findings revealed that information gain (the reduction in uncertainty about the causal relationship between actions and outcomes) is represented over the visual, parietal, lateral prefrontal and ventromedial/orbital prefrontal cortices. Cortico-cortical interactions encoded information gain synergistically at the level of pairwise and higher-order relations, such as triplets and quadruplets. Higher-order synergistic interactions were characterized by long-range relationships centered in the ventromedial and orbitofrontal cortices, which served as key receivers in the broadcast of information gain across cortical circuits. Overall, this study provides evidence that information gain is encoded through synergistic and higher-order functional interactions and is broadcast to prefrontal reward circuits.

Suggested Citation

  • Etienne Combrisson & Ruggero Basanisi & Matteo Neri & Guillaume Auzias & Giovanni Petri & Daniele Marinazzo & Stefano Panzeri & Andrea Brovelli, 2025. "Higher-order and distributed synergistic functional interactions encode information gain in goal-directed learning," Nature Communications, Nature, vol. 16(1), pages 1-19, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-62507-1
    DOI: 10.1038/s41467-025-62507-1
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    References listed on IDEAS

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    1. Andrea Santoro & Federico Battiston & Maxime Lucas & Giovanni Petri & Enrico Amico, 2024. "Higher-order connectomics of human brain function reveals local topological signatures of task decoding, individual identification, and behavior," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    2. Jacopo Grilli & György Barabás & Matthew J. Michalska-Smith & Stefano Allesina, 2017. "Higher-order interactions stabilize dynamics in competitive network models," Nature, Nature, vol. 548(7666), pages 210-213, August.
    3. Stefano Palminteri & Mehdi Khamassi & Mateus Joffily & Giorgio Coricelli, 2015. "Contextual modulation of value signals in reward and punishment learning," Nature Communications, Nature, vol. 6(1), pages 1-14, November.
    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. Stefano Palminteri & Mehdi Khamassi & Mateus Joffily & Giorgio Coricelli, 2015. "Contextual modulation of value signals in reward and punishment learning," Post-Print halshs-01236045, HAL.
    6. J. Kael White & Ethan S. Bromberg-Martin & Sarah R. Heilbronner & Kaining Zhang & Julia Pai & Suzanne N. Haber & Ilya E. Monosov, 2019. "A neural network for information seeking," Nature Communications, Nature, vol. 10(1), pages 1-19, December.
    7. Andrei Khilkevich & Michael Lohse & Ryan Low & Ivana Orsolic & Tadej Bozic & Paige Windmill & Thomas D. Mrsic-Flogel, 2024. "Brain-wide dynamics linking sensation to action during decision-making," Nature, Nature, vol. 634(8035), pages 890-900, October.
    8. Urs Köster & Jascha Sohl-Dickstein & Charles M Gray & Bruno A Olshausen, 2014. "Modeling Higher-Order Correlations within Cortical Microcolumns," PLOS Computational Biology, Public Library of Science, vol. 10(7), pages 1-12, July.
    9. Elad Schneidman & Michael J. Berry & Ronen Segev & William Bialek, 2006. "Weak pairwise correlations imply strongly correlated network states in a neural population," Nature, Nature, vol. 440(7087), pages 1007-1012, April.
    10. Jonathan M. Levine & Jordi Bascompte & Peter B. Adler & Stefano Allesina, 2017. "Beyond pairwise mechanisms of species coexistence in complex communities," Nature, Nature, vol. 546(7656), pages 56-64, June.
    11. Sébastien Ballesta & Weikang Shi & Katherine E. Conen & Camillo Padoa-Schioppa, 2020. "Values encoded in orbitofrontal cortex are causally related to economic choices," Nature, Nature, vol. 588(7838), pages 450-453, December.
    12. Mathias Pessiglione & Ben Seymour & Guillaume Flandin & Raymond J. Dolan & Chris D. Frith, 2006. "Dopamine-dependent prediction errors underpin reward-seeking behaviour in humans," Nature, Nature, vol. 442(7106), pages 1042-1045, August.
    13. Alicia Sanchez-Gorostiaga & Djordje Bajić & Melisa L Osborne & Juan F Poyatos & Alvaro Sanchez, 2019. "High-order interactions distort the functional landscape of microbial consortia," PLOS Biology, Public Library of Science, vol. 17(12), pages 1-34, December.
    14. Christoph Kirst & Marc Timme & Demian Battaglia, 2016. "Dynamic information routing in complex networks," Nature Communications, Nature, vol. 7(1), pages 1-9, April.
    15. Elise Payzan-LeNestour & Peter Bossaerts, 2011. "Risk, Unexpected Uncertainty, and Estimation Uncertainty: Bayesian Learning in Unstable Settings," PLOS Computational Biology, Public Library of Science, vol. 7(1), pages 1-14, January.
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