CT-3.1

A computational shortcut to coordination: common knowledge and neural alignment

Cong Wang, Lusha Zhu, Peking University, China

Session:
Contributed Talks 3 Lecture

Track:
Cognitive science

Location:
South Schools / East Schools

Presentation Time:
Sun, 27 Aug, 10:30 - 10:45 United Kingdom Time

Abstract:
Coordinating actions for common goals is ubiquitous among social animals. Game theory and multi-agent AI research proposes that coordination in the absence of communication often involves complex, recursive reasoning about the mental states of other agents. Such decision-making processes are widely considered to be prohibitively difficult and error-prone, raising questions regarding how social animals achieve effective, flexible everyday coordination in a seemingly effortless manner. Building on a long-standing conjecture of focal point and common knowledge, we provide to our knowledge the first neural evidence for a computational shortcut to coordination. Using fMRI, we show that the alignment of activity in the posterior cingulate cortex (PCC) in one group of subjects can reliably and specifically predict coordination in novel, one-shot contexts in a separate, large online sample. This suggests that coordination may be supported by shared world knowledge commonly coded in the PCC across individuals, which can be flexibly assembled and compared in service of social behavior.

Manuscript:
License:
Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 Unported License.
DOI:
10.32470/CCN.2023.1456-0
Publication:
2023 Conference on Cognitive Computational Neuroscience
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Session CT-3
CT-3.1: A computational shortcut to coordination: common knowledge and neural alignment
Cong Wang, Lusha Zhu, Peking University, China
CT-3.2: Neural network modeling reveals diverse human exploration behaviors via state space analysis
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CT-3.3: Reward morphs non-spatial cognitive maps in humans
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