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2023 Fiscal Year Annual Research Report

Metacognitive control of the neural signals that shape behaviour changes

Planned Research

Project AreaDeciphering and Manipulating Brain Dynamics for Emergence of Behaviour Change in Multidimensional Biology
Project/Area Number 22H05156
Research InstitutionAdvanced Telecommunications Research Institute International

Principal Investigator

CORTESE Aurelio  株式会社国際電気通信基礎技術研究所, 脳情報通信総合研究所, 研究室長 (60842028)

Co-Investigator(Kenkyū-buntansha) 川人 光男  株式会社国際電気通信基礎技術研究所, 脳情報通信総合研究所, 所長 (10144445)
Project Period (FY) 2022-06-16 – 2027-03-31
Keywordsreinforcement learning / metacognition / neural dynamics / cerebellum / decision-making / prefrontal cortex / neuroimaging / decoded neurofeedback
Outline of Annual Research Achievements

Research stream 1 (Hoang, Toyama, Kawato, Cortese): Our research has advanced our understanding of Go/No-go data by incorporating a reinforcement learning model (Hoang et al.2023, eLife). Our findings suggest collaboration between the cerebellum, basal ganglia, and cortex in forming a modular reinforcement learning system. This system involves distinct cerebellar modules receiving reward-prediction errors via climbing fibre inputs, enabling the generation of precise motor commands for Go and No-go cues (Hoang et al. 2023, bioRxiv). Additionally, we have refined a method to detect hundreds of individual climbing fibres across various two-photon recording sessions while learning Go/No-go tasks. These dual achievements provide valuable insights and resources for constructing a sophisticated model of the cerebellum.
Research stream 2 (Okamoto, Six, Taylor, Ovadia, Oka, Gutierrez, Lobaskin, Cortese): We collected data with novel behaviour tasks to test behaviour change through various measures. All tasks shared a common structure, in which participants updated their behaviour to sudden hidden changes in task conditions. We collected participants' subjective confidence ratings along multiple dimensions (perceptual, rule confidence) as well as reaction time data. Our analysis (Taylor, Ovadia, Oka, Lobaskin, Cortese) shows we can obtain reliable behavioural measures with confidence in predicting subsequent behaviour and decision-making. The results were presented at international conferences. In addition, we published an influential opinion paper (De Martino and Cortese 2024, TICS).

Current Status of Research Progress
Current Status of Research Progress

2: Research has progressed on the whole more than it was originally planned.

Reason

Research stream 1 (Hoang, Toyama, Kawato, Cortese): Our current focus lies in developing a model of the cerebellum, which is strongly informed by our recent findings. In our model, these modules are equipped with bidirectional plasticity at the parallel fibre-Purkinje cell synapses. This means climbing fibre inputs convey reward-prediction errors to enhance or decrease Purkinje cell activity, depending on the specific learning objectives. Our preliminary results are promising. The model has successfully replicated the firing activity of climbing fibres observed in the two cerebellar modules, as well as the licking behaviour of mice in Go/No-go tasks. This suggests that our model accurately captures key cerebellar function and behaviour aspects, laying a strong foundation for further exploration and refinement.
Research stream 2 (Okamoto, Six, Taylor, Ovadia, Oka, Gutierrez, Lobaskin, Cortese): Our current focus is characterising multidimensional confidence representations at behaviour, computational, and neural levels. We are writing two manuscripts, which we expect to publish within the current fiscal year, reporting on (i) our study linking learning, behaviour adaptation, and metacognition (Okamoto et al., in prep), and on the neural correlates of metacognitive evaluation (Six et al., in prep). In parallel, we are analysing behaviour and neuroimaging data (fMRI, ECoG, MEG, by Ovadia, Six, Taylor, Lobaskin).

Strategy for Future Research Activity

Research stream 1 (Hoang, Toyama, Kawato, Cortese): We will construct a large-scale spiking neuron network that includes various neuron types found within the cerebellum. This model will have a modular structure to reflect the organisational principles observed in the cerebellar cortex. The primary focus will be investigating the role of positive feedback loops and Purkinje cells, cerebellar nucleus neurons, and inferior olive neurons in generating self-organising network dynamics. In parallel, we will begin preparation with the Matsuzaki lab on the mouse DecNef project. We will define the target cortical regions and neural population coverage, the decoding approach, and the behaviour dimensions to be modified through neurofeedback.
Research stream 2 (Okamoto, Six, Taylor, Ovadia, Oka, Gutierrez, Lobaskin, Kasahara, Cortese): We will analyse and apply computational models such as reinforcement learning and hierarchical models, to study different confidence signals (perceptual, rule confidence) and their contributions to behaviour strategies. Importantly, we comprehensively evaluate low-dimensional metacognitive representations in time and space across neuroimaging modalities (fMRI, MEG, ECoG). Next, we will collect eye-tracking data to evaluate physiological confidence correlates. We will design and pilot the neurofeedback experiment in the fiscal year's second half.
Finally, we plan to present our findings from both research streams at reputed international conferences.

  • Research Products

    (19 results)

All 2024 2023 Other

All Journal Article (2 results) (of which Peer Reviewed: 2 results,  Open Access: 2 results) Presentation (12 results) (of which Int'l Joint Research: 8 results,  Invited: 4 results) Remarks (5 results)

  • [Journal Article] The cognitive reality monitoring network and theories of consciousness2024

    • Author(s)
      Aurelio CORTESE, Mitsuo KAWATO
    • Journal Title

      Neuroscience Research

      Volume: 201 Pages: 31-38

    • DOI

      10.1016/j.neures.2024.01.007

    • Peer Reviewed / Open Access
  • [Journal Article] Dynamic organization of cerebellar climbing fiber response and synchrony in multiple functional components reduces dimensions for reinforcement learning2023

    • Author(s)
      Huu Hoang, Shinichiro Tsutsumi, Masanori Matsuzaki, Masanobu Kano, Mitsuo Kawato, Kazuo Kitamura, Keisuke Toyama
    • Journal Title

      eLife

      Volume: 12:e86340 Pages: -

    • DOI

      10.7554/eLife.86340

    • Peer Reviewed / Open Access
  • [Presentation] Metacognition as the detection of internal signals2024

    • Author(s)
      Aurelio CORTESE
    • Organizer
      QB3:Qualia, Brain, Body, Behavior
    • Invited
  • [Presentation] Human action-outcome inference through weighted evidence accumulation with subjective uncertainty2024

    • Author(s)
      Naoyuki OKAMOTO
    • Organizer
      Computational and Systems Neuroscience (COSYNE) 2024
    • Int'l Joint Research
  • [Presentation] Multiple metacognitive information in different time intervals contributes to the arbitration of credit assignment in a goal-driven task2023

    • Author(s)
      Takuya ANZAI
    • Organizer
      The Machine Learning Summer School in Okinawa 2024
  • [Presentation] Negative reward-prediction errors of climbing fiber inputs for cerebellar reinforcement learning algorithm2023

    • Author(s)
      Huu HOANG
    • Organizer
      第46回日本神経科学大会(Neuro2023)
    • Int'l Joint Research
  • [Presentation] Dynamic organization of cerebellar climbing fiber response and synchrony in multiple functional modules reduces dimensions for reinforcement learning2023

    • Author(s)
      Huu HOANG
    • Organizer
      2023 Cerebellum Gordon Research Conference
    • Int'l Joint Research
  • [Presentation] Metacognition as a mechanism for concurrent monitoring and updating of internal representations2023

    • Author(s)
      Aurelio CORTESE
    • Organizer
      第46回日本神経科学大会(Neuro2023)
    • Int'l Joint Research
  • [Presentation] Cross-species mechanisms of learning and adaptive behaviour2023

    • Author(s)
      Aurelio CORTESE
    • Organizer
      第46回日本神経科学大会(Neuro2023)
    • Int'l Joint Research
  • [Presentation] How can we assess subjective experiences and internal representations in the brain?2023

    • Author(s)
      Aurelio CORTESE
    • Organizer
      The Organization for Human Brain Mapping (OHBM2023)
    • Int'l Joint Research
  • [Presentation] Metacognition of nonconscious neural representations2023

    • Author(s)
      Aurelio CORTESE
    • Organizer
      The Organization for Human Brain Mapping (OHBM2023)
    • Int'l Joint Research
  • [Presentation] Metacognition for monitoring and updating of internal abstract representations2023

    • Author(s)
      Aurelio CORTESE
    • Organizer
      Seminar at Ecole normale superieure
    • Invited
  • [Presentation] Confidence, abstractions and reinforcement learning in humans and machines2023

    • Author(s)
      Aurelio CORTESE
    • Organizer
      the 26th annual meeting of the Korean Society for Brain and Neural Sciences (KSBNS2023)
    • Int'l Joint Research / Invited
  • [Presentation] Confidence, abstractions and reinforcement learning in humans and machines2023

    • Author(s)
      Aurelio CORTESE
    • Organizer
      Seminar at Korea Advanced Institute of Science and Technology (KAIST)
    • Invited
  • [Remarks] ATR行動変容研究室研究成果

    • URL

      https://bicr.atr.jp/decnef/publications/

  • [Remarks] ATR行動変容研究室Publications

    • URL

      https://bicr.atr.jp/decnef/en/publications-2/

  • [Remarks] ATR計算脳イメージング研究室出版物

    • URL

      https://bicr.atr.jp/cbi/publications/

  • [Remarks] ATR計算脳イメージング研究室Publications

    • URL

      https://bicr.atr.jp/cbi/publications/?lang=en

  • [Remarks] Mitsuo Kawato Publication List English Paper

    • URL

      https://bicr.atr.jp/~kawato/pubep.html

URL: 

Published: 2024-12-25  

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