Evidence map›Paper›PMID 41082670›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2025

Neural predictors of hidden, persistent psychological states at work.

Bear M Goldstein, Shannon M Burns, Ashley L Binnquist, Macrina C Dieffenbach, Csaba Konkoly, Shira Abramowitz, Matthew D Lieberman

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Neural predictors of hidden, persistent psychological states at work.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  2. Article
  3. Article
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

7 authors.

Bear M GoldsteinDepartment of Psychology, University of California, Los Angeles, CA 90095.ORCID 0000-0002-9724-206X
Shannon M BurnsDepartment of Psychological Science and Neuroscience, Pomona College, Claremont, CA 91711.
Ashley L BinnquistDepartment of Psychology, University of California, Los Angeles, CA 90095.ORCID 0000-0001-7993-943X
Macrina C DieffenbachDepartment of Psychology, University of California, Los Angeles, CA 90095.ORCID 0000-0002-6396-7484
Csaba KonkolyHum Capital, Los Angeles, CA 90272.
Shira AbramowitzSummit Impact, Summit Series L.L.C., Cambridge, MA 02139.
Matthew D LiebermanDepartment of Psychology, University of California, Los Angeles, CA 90095.ORCID 0000-0002-4447-7359

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Common workplace challenges such as feeling overwhelmed, burned out, or disengaged often remain hidden due to fear of judgment or social norms, contributing to rising mental health crises and organizational dysfunction. This study presents a brain-based framework for predicting these hidden and persistent psychological states through noninvasive neuroimaging. We used functional near-infrared spectroscopy to record neural activity from 67 executives in the field as they watched a video about workplace attitudes. We then applied a multitimepoint pattern analysis (MTPA) approach to reduce timeseries dimensionality and successfully classify whether individuals were feeling overwhelmed (72.8% accuracy) or in need of a new or different challenge (79.1% accuracy) in their careers using the temporal parietal junction (TPJ) and dorsal medial prefrontal cortex (dmPFC), respectively. The MTPA framework also allowed us to reverse-engineer specific thematic properties of the stimulus that evoked differential neural responses linked to these predicted outcomes. Emotional content in the video (e.g., reported distress) corresponded to the selected TPJ features that predicted whether someone was overwhelmed, while socially relevant content (e.g., missing social gatherings) aligned with the selected features from the dmPFC that predicted the need for a new or different challenge. These findings demonstrate the ability of neural measures to unobtrusively identify hidden and persistent psychological states in real-world settings, enabling targeted interventions that can improve well-being and engagement.

Indexed as

WorkplaceAdultBrainBrain MappingEmotionsFemaleHumansMaleMiddle AgedParietal LobePrefrontal CortexSpectroscopy, Near-Infrareddefault mode networkfNIRSmachine learningneural synchronypsychological lenses

Identifiers

PMID41082670
PMCPMC12557504

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.