Reveal the informational nature of conscious self and sense of agency under the information closure theory of consciousness
| Project/Area Number |
22K20679
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| Research Category |
Grant-in-Aid for Research Activity Start-up
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| Allocation Type | Multi-year Fund |
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| Review Section |
0704:Neuroscience, brain sciences, and related fields
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| Research Institution | Rikkyo University (2023)
The University of Tokyo (2022) |
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Principal Investigator |
チャン ユーチャン 立教大学, 現代心理学部, 助教 (50831484)
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| Project Period (FY) |
2022-08-31 – 2024-03-31
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| Project Status |
Completed (Fiscal Year 2023)
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| Budget Amount *help |
¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
Fiscal Year 2023: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2022: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | consciousness / Information Closure / theory of consciousness / neuroscience / Consciousness / ICT / Mathematical Model / Neural Systems / Sense of Agency / Artificial Intelligence / Scale Problem / Simulation / information closure / Conscious Action |
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| Outline of Research at the Start |
This project investigates conscious action and the sense of agency using the framework of the Information Closure Theory of consciousness. Research aims include understanding the sense of agency via information theory and identifying conscious action and agency in neural and artificial systems.
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| Outline of Annual Research Achievements |
This project advanced our understanding of the conscious self and sense of agency through the Information Closure Theory of Consciousness (ICT). We developed mathematical foundations to measure conscious self and agency, validated ICT with neural network simulations, and confirmed its predictions. In the final phase, we extended ICT to large-scale analyses using advanced AI models, demonstrating higher levels of conscious self and agency in model-based reinforcement learning agents. These results provide new insights into consciousness, with significant implications for neuroscience and AI. Future research will focus on further empirical validation and applying these findings to neurophysiological data.
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Report
(2 results)
Research Products
(4 results)
