Cargando…
Load-dependent inverted U–shaped connectivity of the default mode network in schizophrenia during a working-memory task: evidence from a replication functional MRI study
BACKGROUND: Working-memory deficit is associated with aberrant degree distribution of the brain connectome in schizophrenia. However, the brain neural mechanism underlying the degree redistribution pattern in schizophrenia is still uncertain. METHODS: We examined the functional degree distribution o...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
CMA Impact Inc.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9524478/ https://www.ncbi.nlm.nih.gov/pubmed/36167413 http://dx.doi.org/10.1503/jpn.220053 |
_version_ | 1784800515447586816 |
---|---|
author | Wang, Feiwen Xi, Chang Liu, Zhening Deng, Mengjie Zhang, Wen Cao, Hengyi Yang, Jie Palaniyappan, Lena |
author_facet | Wang, Feiwen Xi, Chang Liu, Zhening Deng, Mengjie Zhang, Wen Cao, Hengyi Yang, Jie Palaniyappan, Lena |
author_sort | Wang, Feiwen |
collection | PubMed |
description | BACKGROUND: Working-memory deficit is associated with aberrant degree distribution of the brain connectome in schizophrenia. However, the brain neural mechanism underlying the degree redistribution pattern in schizophrenia is still uncertain. METHODS: We examined the functional degree distribution of the connectome in 81 patients with schizophrenia and 77 healthy controls across different working-memory loads during an n-back task. We tested the associations between altered degree distribution and clinical symptoms, and we conducted functional connectivity analyses to investigate the neural mechanism underlying altered degree distribution. We repeated these analyses in a second independent data set of 96 participants. In the second data set, we employed machine-learning analysis to study whether the degree distribution pattern of one data set could be used to discriminate between patients with schizophrenia and controls in the other data set. RESULTS: Patients with schizophrenia showed decreased centrality in the dorsal posterior cingulate cortex (dPCC) for the “2-back versus 0-back” contrast compared to healthy controls. The dPCC centrality pattern across all working-memory loads was an inverted U shape, with a left shift of this pattern in patients with schizophrenia. This reduced centrality was correlated with the severity of delusions and related to reduced functional connectivity between the dPCC and the dorsal precuneus. We replicated these results with the second data set, and the machine-learning analyses achieved an accuracy level of 71%. LIMITATIONS: We used a limited n-back paradigm that precluded the examination of higher working-memory loads. CONCLUSION: Schizophrenia is characterized by a load-dependent reduction of centrality in the dPCC, related to the severity of delusions. We suggest that restoring dPCC centrality in the presence of cognitive demands might have a therapeutic effect on persistent delusions in people with schizophrenia. |
format | Online Article Text |
id | pubmed-9524478 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | CMA Impact Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95244782022-10-14 Load-dependent inverted U–shaped connectivity of the default mode network in schizophrenia during a working-memory task: evidence from a replication functional MRI study Wang, Feiwen Xi, Chang Liu, Zhening Deng, Mengjie Zhang, Wen Cao, Hengyi Yang, Jie Palaniyappan, Lena J Psychiatry Neurosci Research Paper BACKGROUND: Working-memory deficit is associated with aberrant degree distribution of the brain connectome in schizophrenia. However, the brain neural mechanism underlying the degree redistribution pattern in schizophrenia is still uncertain. METHODS: We examined the functional degree distribution of the connectome in 81 patients with schizophrenia and 77 healthy controls across different working-memory loads during an n-back task. We tested the associations between altered degree distribution and clinical symptoms, and we conducted functional connectivity analyses to investigate the neural mechanism underlying altered degree distribution. We repeated these analyses in a second independent data set of 96 participants. In the second data set, we employed machine-learning analysis to study whether the degree distribution pattern of one data set could be used to discriminate between patients with schizophrenia and controls in the other data set. RESULTS: Patients with schizophrenia showed decreased centrality in the dorsal posterior cingulate cortex (dPCC) for the “2-back versus 0-back” contrast compared to healthy controls. The dPCC centrality pattern across all working-memory loads was an inverted U shape, with a left shift of this pattern in patients with schizophrenia. This reduced centrality was correlated with the severity of delusions and related to reduced functional connectivity between the dPCC and the dorsal precuneus. We replicated these results with the second data set, and the machine-learning analyses achieved an accuracy level of 71%. LIMITATIONS: We used a limited n-back paradigm that precluded the examination of higher working-memory loads. CONCLUSION: Schizophrenia is characterized by a load-dependent reduction of centrality in the dPCC, related to the severity of delusions. We suggest that restoring dPCC centrality in the presence of cognitive demands might have a therapeutic effect on persistent delusions in people with schizophrenia. CMA Impact Inc. 2022-09-27 /pmc/articles/PMC9524478/ /pubmed/36167413 http://dx.doi.org/10.1503/jpn.220053 Text en © 2022 CMA Impact Inc. or its licensors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY-NC-ND 4.0) licence, which permits use, distribution and reproduction in any medium, provided that the original publication is properly cited, the use is noncommercial (i.e., research or educational use), and no modifications or adaptations are made. See: https://creativecommons.org/licenses/by-nc-nd/4.0/ |
spellingShingle | Research Paper Wang, Feiwen Xi, Chang Liu, Zhening Deng, Mengjie Zhang, Wen Cao, Hengyi Yang, Jie Palaniyappan, Lena Load-dependent inverted U–shaped connectivity of the default mode network in schizophrenia during a working-memory task: evidence from a replication functional MRI study |
title | Load-dependent inverted U–shaped connectivity of the default mode network in schizophrenia during a working-memory task: evidence from a replication functional MRI study |
title_full | Load-dependent inverted U–shaped connectivity of the default mode network in schizophrenia during a working-memory task: evidence from a replication functional MRI study |
title_fullStr | Load-dependent inverted U–shaped connectivity of the default mode network in schizophrenia during a working-memory task: evidence from a replication functional MRI study |
title_full_unstemmed | Load-dependent inverted U–shaped connectivity of the default mode network in schizophrenia during a working-memory task: evidence from a replication functional MRI study |
title_short | Load-dependent inverted U–shaped connectivity of the default mode network in schizophrenia during a working-memory task: evidence from a replication functional MRI study |
title_sort | load-dependent inverted u–shaped connectivity of the default mode network in schizophrenia during a working-memory task: evidence from a replication functional mri study |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9524478/ https://www.ncbi.nlm.nih.gov/pubmed/36167413 http://dx.doi.org/10.1503/jpn.220053 |
work_keys_str_mv | AT wangfeiwen loaddependentinvertedushapedconnectivityofthedefaultmodenetworkinschizophreniaduringaworkingmemorytaskevidencefromareplicationfunctionalmristudy AT xichang loaddependentinvertedushapedconnectivityofthedefaultmodenetworkinschizophreniaduringaworkingmemorytaskevidencefromareplicationfunctionalmristudy AT liuzhening loaddependentinvertedushapedconnectivityofthedefaultmodenetworkinschizophreniaduringaworkingmemorytaskevidencefromareplicationfunctionalmristudy AT dengmengjie loaddependentinvertedushapedconnectivityofthedefaultmodenetworkinschizophreniaduringaworkingmemorytaskevidencefromareplicationfunctionalmristudy AT zhangwen loaddependentinvertedushapedconnectivityofthedefaultmodenetworkinschizophreniaduringaworkingmemorytaskevidencefromareplicationfunctionalmristudy AT caohengyi loaddependentinvertedushapedconnectivityofthedefaultmodenetworkinschizophreniaduringaworkingmemorytaskevidencefromareplicationfunctionalmristudy AT yangjie loaddependentinvertedushapedconnectivityofthedefaultmodenetworkinschizophreniaduringaworkingmemorytaskevidencefromareplicationfunctionalmristudy AT palaniyappanlena loaddependentinvertedushapedconnectivityofthedefaultmodenetworkinschizophreniaduringaworkingmemorytaskevidencefromareplicationfunctionalmristudy |