Evaluating state-based network dynamics in anhedonia

Q4 Neuroscience
Angela Pisoni , Jeffrey Browndyke , Simon W. Davis , Moria Smoski
{"title":"Evaluating state-based network dynamics in anhedonia","authors":"Angela Pisoni ,&nbsp;Jeffrey Browndyke ,&nbsp;Simon W. Davis ,&nbsp;Moria Smoski","doi":"10.1016/j.ynirp.2024.100225","DOIUrl":null,"url":null,"abstract":"<div><div>Anhedonia is a transdiagnostic clinical syndrome associated with significant clinical impairment. In spite of this, a clear network-level characterization of anhedonia does not yet exist. The present study addressed this gap in the literature by taking a graph theoretical approach to characterizing state-based (i.e., reward anticipation, rest) network dynamics in a transdiagnostic sample of adults with clinically significant anhedonia (<em>n</em> = 77). Analyses focused on three canonical brain networks: the Salience Network (SN), the Default Mode Network (DMN) and the Central Executive Network (CEN), with hypotheses focusing on the role of saliency-mapping in anhedonia. Contrary to hypotheses, no significant relation was found between the SN and anhedonia symptom severity. Exploratory results revealed a significant association between anhedonia severity and DMN reorganization from rest to reward anticipation. Specifically, greater anhedonia severity was associated with less reward-related reorganization. This finding suggests that anhedonia severity may be associated with DMN hyposensitivity, such that individuals with more severe anhedonia may have a difficult time disengaging from their internal world in the context of potentially rewarding experiences. Although preliminary, this finding challenges the centrality of the SN in anhedonia severity and suggests the importance of the DMN. Clinical implications and future directions are explored.</div></div>","PeriodicalId":74277,"journal":{"name":"Neuroimage. Reports","volume":"4 4","pages":"Article 100225"},"PeriodicalIF":0.0000,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neuroimage. Reports","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S266695602400031X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Neuroscience","Score":null,"Total":0}
引用次数: 0

Abstract

Anhedonia is a transdiagnostic clinical syndrome associated with significant clinical impairment. In spite of this, a clear network-level characterization of anhedonia does not yet exist. The present study addressed this gap in the literature by taking a graph theoretical approach to characterizing state-based (i.e., reward anticipation, rest) network dynamics in a transdiagnostic sample of adults with clinically significant anhedonia (n = 77). Analyses focused on three canonical brain networks: the Salience Network (SN), the Default Mode Network (DMN) and the Central Executive Network (CEN), with hypotheses focusing on the role of saliency-mapping in anhedonia. Contrary to hypotheses, no significant relation was found between the SN and anhedonia symptom severity. Exploratory results revealed a significant association between anhedonia severity and DMN reorganization from rest to reward anticipation. Specifically, greater anhedonia severity was associated with less reward-related reorganization. This finding suggests that anhedonia severity may be associated with DMN hyposensitivity, such that individuals with more severe anhedonia may have a difficult time disengaging from their internal world in the context of potentially rewarding experiences. Although preliminary, this finding challenges the centrality of the SN in anhedonia severity and suggests the importance of the DMN. Clinical implications and future directions are explored.
评估失乐症中基于状态的网络动力学
失乐症是一种跨诊断的临床综合征,伴有严重的临床损害。尽管如此,关于失乐症的明确的网络层面特征描述尚不存在。本研究针对文献中的这一空白,采用图论方法描述了临床上患有明显失乐症的成人(n = 77)的跨诊断样本中基于状态(即奖赏预期、休息)的网络动力学特征。分析的重点是三个典型的大脑网络:显著性网络(SN)、默认模式网络(DMN)和中央执行网络(CEN),假设的重点是显著性映射在失乐症中的作用。与假设相反的是,SN 与失乐症症状严重程度之间没有发现明显的关系。探索性结果显示,失神症严重程度与从休息到奖赏预期的DMN重组之间存在显著关联。具体来说,失乐症严重程度越高,与奖赏相关的重组越少。这一发现表明,失乐症的严重程度可能与DMN的低敏感性有关,因此失乐症较严重的人可能很难在潜在奖赏体验的背景下脱离他们的内心世界。尽管是初步研究,但这一发现对SN在厌食症严重程度中的中心地位提出了质疑,并提示了DMN的重要性。本文探讨了这一发现对临床的影响以及未来的研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Neuroimage. Reports
Neuroimage. Reports Neuroscience (General)
CiteScore
1.90
自引率
0.00%
发文量
0
审稿时长
87 days
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信