Evidence map›Paper›PMID 32715898›Full record

ArticleCognitive neuroscience

Sex-related differences in brain dynamism at rest as neural correlates of positive and negative valence system constructs.

Nina de Lacy, J Nathan Kutz, Vince D Calhoun

Open access · greenAbstract read
In one paragraph

Article in Cognitive neuroscience. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 26% of its field
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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Review
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

3 authors at 3 institutions in 1 country.

Nina de LacyDepartment of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA.ORCID 0000-0002-4574-3604
J Nathan KutzDepartment of Applied Mathematics, University of Washington, Seattle, WA, USA.
Vince D CalhounTri-institutional Center for Translational Research in Neuroimaging and Data Science (Trends), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA.
Georgia Institute of Technology · USUniversity of Washington · USUniversity of Washington Applied Physics Laboratory · US

Funding

Transcranial Direct Current Stimulation for Treatment of Auditory Verbal HalluciP20GM103472 · NIGMS · THE MIND RESEARCH NETWORK · PI CALHOUN, VINCE D · 2012 to 2017
$14.3M
Multivariate methods for identifying multitask/multimodal brain imaging biomarkersR01EB006841 · NIBIB · THE MIND RESEARCH NETWORK · PI VINCE D CALHOUN, Sergey Plis · 2007 to 2026
$9.8M
Pilot Project Program (PPP)P30GM122734 · NIGMS · THE MIND RESEARCH NETWORK · PI MAYER, ANDREW ROBERT · 2018 to 2022
$7.0M
Informed Data-Driven Fusion of Behavior, Brain Function, and GenesR01EB005846 · NIBIB · THE MIND RESEARCH NETWORK · PI CALHOUN, VINCE D · 2005 to 2016
$5.5M
Male/Female differences in psychosis and mood disorders:Dynamic imaging-genomic models for characterizing and predicting psychosis and mood dR01MH118695 · NIMH · GEORGIA STATE UNIVERSITY · PI ADALI, TULAY, CALHOUN, VINCE D · 2019 to 2023
$3.8M
Data-driven solutions for temporal, spatial, and spatiotemporal dynamic functional connectivityR01MH123610 · NIMH · GEORGIA STATE UNIVERSITY · PI ADALI, TULAY, CALHOUN, VINCE D · 2021 to 2025
$3.1M
Unified multivariate data-driven solutions for static and dynamic brain connectivityR01EB020407 · NIBIB · THE MIND RESEARCH NETWORK · PI ADALI, TULAY, CALHOUN, VINCE D · 2015 to 2018
$2.7M
Deep machine learning to delineate trajectories of vulnerability and transition to mental illness in youthK99MH118359 · NIMH · UNIVERSITY OF WASHINGTON · PI DE LACY, NINA · 2019 to 2020
$314k
NIBIB NIH HHS R01 EB005846NIBIB NIH HHS R01 EB006841NIBIB NIH HHS R01 EB020407NIGMS NIH HHS P20 GM103472NIGMS NIH HHS P30 GM122734NIMH NIH HHS K99 MH118359NIMH NIH HHS R01 MH118695NIMH NIH HHS R01 MH123610
6 · The paper itself

Abstract

Clinical anxiety and depression are the most prevalent mental illnesses, likely representing maladaptive expressions of negative valence systems concerned with conditioned responses to fear, threat, loss, and frustrative nonreward. These conditions exhibit similar, striking sex/gender-related differences in onset, incidence, and severity for which the neural correlates are not yet established. In alarge sample of neurotypical young adults, we demonstrate that intrinsic brain dynamism metrics derived from sex-sensitive models of whole-brain network function are significantly associated with valence system traits. Surprisingly, we found that greater brain dynamism is strongly positively correlated to anxiety and depression traits in males, but almost wholly decoupled from traits for important cognitive control and reappraisal strategies associated with positive valence. Conversely, intrinsic brain dynamism is strongly positively coupled to drive, novelty-seeking and self-control in females with only rare or non-significant directional negative correlation with anxiety and depression traits. Our results suggest that the dynamic neural correlates of traits for valence, anxiety and depression are significantly different in males/men and females/women. These findings may relate to the known sex/gender-related differences in cognitive reappraisal of emotional experiences and clinical presentations of anxiety and depression, with potential relevance to gold standard therapies based on enhancing cognitive control strategies.

Indexed as

BrainSex CharacteristicsAnxietyEmotionsFearFemaleHumansMaleYoung Adultanxietybrain networksdepressiondynamismnegative valencepositive valenceSex/gender

Identifiers

PMID32715898
PMCPMC7881523
OpenAlexW3043930082

What OpenQuestion holds

Textmetadata
LicenceTDM
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.