Evidence map›Paper›PMID 29036672›Full record

ArticleSchizophrenia bulletin2017

Convergence and Divergence of Brain Network Dysfunction in Deficit and Non-deficit Schizophrenia.

Miao Yu, Zhengjia Dai, Xiaowei Tang, Xiang Wang, Xiaobin Zhang, Weiwei Sha, Shuqiao Yao, Ni Shu, Xindi Wang, Jiaying Yang and 4 more

Abstract read
In one paragraph

Article in Schizophrenia bulletin, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

32 citing papers in PubMed.

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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

14 authors.

Miao YuDepartment of Neuropsychiatry, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China.
Zhengjia DaiDepartment of Psychology, Sun Yat-sen University, Guangzhou, China.
Xiaowei TangDepartment of Psychiatry, Wutaishan Hospital of Yangzhou, Yangzhou, China.
Xiang WangMedical Psychological Institute of the Second Xiangya Hospital, Central South University, Changsha, China.
Xiaobin ZhangDepartment of Psychiatry, Wutaishan Hospital of Yangzhou, Yangzhou, China.
Weiwei ShaDepartment of Psychiatry, Wutaishan Hospital of Yangzhou, Yangzhou, China.
Shuqiao YaoMedical Psychological Institute of the Second Xiangya Hospital, Central South University, Changsha, China.
Ni ShuState Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
Xindi WangState Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
Jiaying YangDepartment of Epidemiology and Biostatistics, School of Public Health, Southeast University, Nanjing, China.
Xiangyang ZhangMenninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX.
Xiangrong ZhangDepartment of Neuropsychiatry, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China.
Yong HeState Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
Zhijun ZhangDepartment of Neuropsychiatry, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Deficit schizophrenia (DS), characterized by primary and enduring negative symptoms, has been considered as a pathophysiologically distinct schizophrenic subgroup. Neuroimaging characteristics of DS, especially functional brain network architecture, remain largely unknown. Resting-state functional magnetic resonance imaging and graph theory approaches were employed to investigate the topological organization of whole-brain functional networks of 114 male participants including 33 DS, 41 non-deficit schizophrenia (NDS) and 40 healthy controls (HCs). At the whole-brain level, both the NDS and DS group exhibited lower local efficiency (Eloc) than the HC group, implying the reduction of local specialization of brain information processing (reduced functional segregation). The DS, but not NDS group, exhibited enhanced parallel information transfer (enhanced functional integration) as determined by smaller characteristic path length (Lp) and higher global efficiency (Eglob). The Lp and Eglob presented significant correlations with Brief Psychiatric Rating Scale (BPRS) total score in the DS group. At the nodal level, both the NDS and DS groups showed higher functional connectivity in the inferior frontal gyrus and hippocampus, and lower connectivity in the visual areas and striatum than the controls. The DS group exhibited higher nodal connectivity in the right inferior temporal gyrus than the NDS and HC group. The diminished expression of Scale for the Assessment of Negative Symptoms (SANS) subfactors negatively correlated with nodal connectivity of right putamen, while asociality/amotivation positively correlated with right hippocampus across whole patients. We highlighted the convergence and divergence of brain functional network dysfunctions in patients with DS and NDS, which provides crucial insights into pathophysiological mechanisms of the 2 schizophrenic subtypes.

Indexed as

AdultBrainConnectomeHumansMagnetic Resonance ImagingMaleMiddle AgedNerve NetSchizophreniadeficit schizophreniafunctional connectivitygraph theoryresting-state fMRIsmall-world

Identifiers

PMID29036672
PMCPMC5737538

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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.