Evidence map›Paper›PMID 34100255›Full record

ArticleCognitive, affective & behavioral neuroscience2021

Disrupted communication of the temporoparietal junction in patients with major depressive disorder.

Xiaotong Wen, Yuan Liu, Ping Zhao, Zhenghao Liu, Huanhuan Li, Wen Li, Zhiyuan Zhu, Xia Wu

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Article in Cognitive, affective & behavioral neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Targeting Affective Mood Disorders With Ketamine to Prevent Chronic Postsurgical Pain.Frontiers in pain research (Lausanne, Switzerland) · 2022
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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Xiaotong Wen *Department of Psychology, Renmin University of China, Beijing, 100872, China.
Yuan Liu *Department of Psychology, Renmin University of China, Beijing, 100872, China.
Ping ZhaoDepartment of Psychology, Renmin University of China, Beijing, 100872, China.
Zhenghao LiuDepartment of Psychology, Renmin University of China, Beijing, 100872, China.
Huanhuan LiDepartment of Psychology, Renmin University of China, Beijing, 100872, China.
Wen LiDepartment of Psychology, Renmin University of China, Beijing, 100872, China.
Zhiyuan ZhuSchool of Artificial Intelligence, Beijing Normal University, Beijing, 100875, China.
Xia WuDepartment of Psychology, Renmin University of China, Beijing, 100872, China. wuxia@bnu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Patients with major depressive disorder (MDD) suffer impairment in the transmission and integration of internal and external information sources. Accumulating evidence suggests that the temporoparietal junction (TPJ) is important for multiple cognitive and social functions and may act as a key node for the integration of internal and external information. Therefore, the TPJ's aberrant interaction mechanism may underpin MDD psychopathology. To answer this question, we conducted a comprehensive study using resting-state functional magnetic imaging data recorded from 74 patients with MDD and 69 normal controls. First, we examined whether TPJ was the most prominent region with altered functional/effective connectivity with multiple depression-related regions/networks, based on either zero-lag correlations or temporal mutual information (total interdependence and Granger causality) measurements. Accordingly, we derived a network model that depicts alterations of TPJ-connectivity in patients with MDD. Lastly, we performed a cross-approach comparison demonstrating more conducive indicators in delineating the network alteration model. Functional/effective connectivity between the TPJ and major functional networks that govern internal and external-driven information resources was attenuated in patients with MDD. TPJ acts like a key node for information-inflow and integration of multiple information streams. Therefore, dysfunctional connectivity indicators may serve as effective biomarkers for MDD. MDD is associated with the breakdown of the TPJ interaction model and its connections with the default mode network and the task-positive network.

Indexed as

Major Depressive DisorderBrainBrain MappingHumansMagnetic Resonance ImagingNeural PathwaysFunctional connectivityGranger causalityMajor depressive disorderTemporoparietal junctionTotal interdependence

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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.