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Study on the hierarchy of cross-modal processing using functional MRI and Deep Learning

Research Project

Project/Area Number 19K20390
Research Category

Grant-in-Aid for Early-Career Scientists

Allocation TypeMulti-year Fund
Review Section Basic Section 61060:Kansei informatics-related
Research InstitutionNational Institute for Physiological Sciences

Principal Investigator

PHAM QUANG TRUNG  生理学研究所, システム脳科学研究領域, 特任研究員 (60837722)

Project Period (FY) 2019-04-01 – 2022-03-31
Project Status Completed (Fiscal Year 2021)
Budget Amount *help
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2021: ¥520,000 (Direct Cost: ¥400,000、Indirect Cost: ¥120,000)
Fiscal Year 2020: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2019: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Keywordscognitive science / somatosensory / haptics / perception / Cognitive Science / Somatosensory / Perception / Cognitive science / Haptics / Cross-modal / functional MRI / Deep Learning / Vision
Outline of Research at the Start

It remains unknown how the brain construct visual imagery from haptic object signal. The purpose of this research is to seek for a computational model of the brain, by which the haptic information is processed into categorical value, using a deep learning model and functional MRI.

Outline of Final Research Achievements

In this study, I proposed a hypothesis where the fragments of haptic information are integrated into visual imagery at the intraparietal sulcus (IPS) and lateral occipital cortex (LOC) before passing to the visual ventral pathway for object recognition. For examining that hypothesis, I designed an experiment where the participants try to recognize the 3x5 dot-digits (from 0 to 9) from visual and haptic stimuli. During the experiment, I captured their brain signals using an MRI scanner. Behavioral analysis revealed that most participants can recognize the dot-digit above the chance level. Their visual performance is better than haptic performance. The fMRI analysis confirmed the involvements of IPS and LOC, and the dorsolateral prefrontal cortex (dlPFC) which is related to working-memory. I performed a representational analysis and found similar representations for both haptic and visual information at the IPS and LOC.

Academic Significance and Societal Importance of the Research Achievements

The results of this study extend our current understanding of the cross-modal processing of haptic and visual information in the brain. In the future, I expected these results to become hint for building a more efficient robotics system that mimics human brain.

Report

(4 results)
  • 2021 Annual Research Report   Final Research Report ( PDF )
  • 2020 Research-status Report
  • 2019 Research-status Report
  • Research Products

    (4 results)

All 2022 2021

All Journal Article (3 results) (of which Int'l Joint Research: 3 results,  Peer Reviewed: 3 results,  Open Access: 3 results) Presentation (1 results) (of which Int'l Joint Research: 1 results)

  • [Journal Article] Counterfactual Explanation of Brain Activity Classifiers Using Image-To-Image Transfer by Generative Adversarial Network2022

    • Author(s)
      Matsui Teppei、Taki Masato、Pham Trung Quang、Chikazoe Junichi、Jimura Koji
    • Journal Title

      Frontiers in Neuroinformatics

      Volume: 15 Pages: 802938-802938

    • DOI

      10.3389/fninf.2021.802938

    • Related Report
      2021 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] On co-activation pattern analysis and non-stationarity of resting brain activity2022

    • Author(s)
      Matsui Teppei、Pham Trung Quang、Jimura Koji、Chikazoe Junichi
    • Journal Title

      NeuroImage

      Volume: 249 Pages: 118904-118904

    • DOI

      10.1016/j.neuroimage.2022.118904

    • NAID

      120007188354

    • Related Report
      2021 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Distillation of Regional Activity Reveals Hidden Content of Neural Information in Visual Processing2021

    • Author(s)
      Pham Trung Quang、Nishiyama Shota、Sadato Norihiro、Chikazoe Junichi
    • Journal Title

      Frontiers in Human Neuroscience

      Volume: 15 Pages: 1-9

    • DOI

      10.3389/fnhum.2021.777464

    • Related Report
      2021 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Presentation] Hierarchical processing of vision-to-value transformation: A combinatory study of fMRI and deep learning2021

    • Author(s)
      Pham Quang Trung
    • Organizer
      The 44th Annual Meeting of the Japan Neuroscience Society & The 1st CJK International Meeting
    • Related Report
      2021 Annual Research Report
    • Int'l Joint Research

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Published: 2019-04-18   Modified: 2023-01-30  

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