Predicting Theory of Mind in children from the infant connectome

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This study trained a computational model on infant fMRI data to identify brain connectivity patterns that predict later Theory of Mind capacity in children.

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The study trained a computational model using resting-state fMRI connectome data from 8–15-month-old infants to identify whole-brain connectivity patterns that predict joint attention, and then tested whether the same connectome also predicted later Theory of Mind (ToM) abilities. The model significantly predicted joint attention in an independent infant sample, and the identified connectivity pattern also predicted ToM capacity in children aged 2–5 years, with the default network and its interaction with the ventral attention network contributing strongly. The authors do not explicitly state a limitation in the provided text, but the key caveat is that prediction is statistical and based on specific measured connectivity patterns and developmental age windows. This paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

Our ability to reason about other people’s mental states, labeled Theory of Mind (ToM), is critical for successful human interaction. Despite its importance for human cognition, early predictors of individual ToM development are lacking. Here, we trained a computational model to identify whole-brain connectivity patterns predictive of joint attention, from resting-state fMRI data of 8-15-month-old infants, and tested whether the identified connectome would also predict ToM capacity later in development. First, the model significantly predicted joint attention scores in an independent infant sample. Crucially, the identified connectome did indeed predict ToM in children aged 2-5 years. The default network and its interaction with the ventral attention network formed dominant connections of the network, suggesting that the interplay of bottom-up attention and higher-order cognition paves the way for mature social cognition. These findings provide an early marker for individual differences in social cognitive development, with high potential for the early diagnosis of social cognitive disorders.
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Abstract Our ability to reason about other people’s mental states, labeled Theory of Mind (ToM), is critical for successful human interaction. Despite its importance for human cognition, early predictors of individual ToM development are lacking. Here, we trained a computational model to identify whole-brain connectivity patterns predictive of joint attention, from resting-state fMRI data of 8-15-month-old infants, and tested whether the identified connectome would also predict ToM capacity later in development. First, the model significantly predicted joint attention scores in an independent infant sample. Crucially, the identified connectome did indeed predict ToM in children aged 2-5 years. The default network and its interaction with the ventral attention network formed dominant connections of the network, suggesting that the interplay of bottom-up attention and higher-order cognition paves the way for mature social cognition. These findings provide an early marker for individual differences in social cognitive development, with high potential for the early diagnosis of social cognitive disorders. Competing Interest Statement The authors have declared no competing interest. Footnotes Manuscript improved to better clarify the novelty and relevance of ToM prediction

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