Evidence map›Paper›PMID 42301939›Full record

ArticleSocial cognitive and affective neuroscience2026

Hierarchical systems in the default mode network when reasoning about self and other mental states.

Isaac R Christian, Samuel A Nastase

Abstract read
In one paragraph

Article in Social cognitive and affective neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Isaac R ChristianDepartment of Psychology, Princeton University, Princeton, NJ 08544, United States.ORCID 0000-0003-0446-3072
Samuel A NastaseDepartment of Psychology and Center for Computational Language Sciences, University of Southern California, Los Angeles, CA 90089, United States.

Funding

1Princeton Neuroscience Institute Innovation Fund 24400E2349FA010AE Studios 24400B1459FA010
6 · The paper itself

Abstract

Humans spend considerable time contemplating the minds of others. But this ability is not limited to external agents-we also turn the lens for reading minds inward, reflecting on our own thoughts, emotions, and sense of self. Some processes involved in reasoning about minds may rely on shared mechanisms, while others may be specific to the agent under consideration. We developed a paradigm where participants performed either a mental state inference task or a control task targeting either another person presented onscreen or their own mind. Using functional MRI and multi-voxel pattern analysis, we replicate a well-established self-other gradient along the medial prefrontal wall: ventral regions encoded mental state inference patterns for self, but not other, whereas more dorsal regions encoded mental state inference for both self and other, compared to control conditions. Posterior cingulate cortex, on the other hand, differentiated the target of mental state inference. Using a cross-classification analysis, we also found that patterns in the dorsomedial prefrontal cortex, ventromedial prefrontal cortex, and right temporoparietal junction were sensitive to mental state reasoning, regardless of the target agent. Our findings reveal a functional hierarchy for mental state reasoning where certain areas support agent-specific reasoning and others support more abstract, agent-general reasoning.

Indexed as

BrainDefault Mode NetworkSelf ConceptTheory of MindThinkingAdultBrain MappingFemaleHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleYoung Adultdefault mode networkfMRImetacognitionmulti-voxel pattern analysisself-othersocial reasoningtheory of mind

Identifiers

PMID42301939
PMCPMC13431780

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.