Transition Dynamics Shape Mental State Concepts

Mark A. Thornton, Milena Rmus, Amisha D. Vyas, Diana I. Tamir

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

People have a unique ability to represent other people’s internal thoughts and feelings—their mental states. Mental state knowledge has a rich conceptual structure, organized along key dimensions, such as valence. People use this conceptual structure to guide social interactions. How do people acquire their understanding of this structure? Here we investigate an underexplored contributor to this process: observation of mental state dynamics. Mental states—including both emotions and cognitive states—are not static. Rather, the transitions from one state to another are systematic and predictable. Drawing on prior cognitive science, we hypothesize that these transition dynamics may shape the conceptual structure that people learn to apply to mental states. Across nine behavioral experiments (N = 1,439), we tested whether the transition probabilities between mental states causally shape people’s conceptual judgments of those states. In each study, we found that observing frequent transitions between mental states caused people to judge them to be conceptually similar. Computational modeling indicated that people translated mental state dynamics into concepts by embedding the states as points within a geometric space. The closer two states are within this space, the greater the likelihood of transitions between them. In three neural network experiments, we trained artificial neural networks to predict real human mental state dynamics. The networks spontaneously learned the same conceptual dimensions that people use to understand mental states. Together these results indicate that mental state dynamics— and the goal of predicting them—shape the structure of mental state concepts.

Original languageEnglish (US)
Pages (from-to)2804-2829
Number of pages26
JournalJournal of Experimental Psychology: General
Volume152
Issue number10
DOIs
StatePublished - Apr 27 2023

All Science Journal Classification (ASJC) codes

  • Experimental and Cognitive Psychology
  • Developmental Neuroscience
  • General Psychology

Keywords

  • artificial neural network
  • concepts
  • emotion
  • prediction
  • theory of mind

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