脑结构的多变量模式分析预测听觉认知训练干预后的功能结果。

IF 5.7 2区 医学 Q1 PSYCHIATRY
Lana Kambeitz-Ilankovic, Sophia Vinogradov, Julian Wenzel, Melissa Fisher, Shalaila S Haas, Linda Betz, Nora Penzel, Srikantan Nagarajan, Nikolaos Koutsouleris, Karuna Subramaniam
{"title":"脑结构的多变量模式分析预测听觉认知训练干预后的功能结果。","authors":"Lana Kambeitz-Ilankovic,&nbsp;Sophia Vinogradov,&nbsp;Julian Wenzel,&nbsp;Melissa Fisher,&nbsp;Shalaila S Haas,&nbsp;Linda Betz,&nbsp;Nora Penzel,&nbsp;Srikantan Nagarajan,&nbsp;Nikolaos Koutsouleris,&nbsp;Karuna Subramaniam","doi":"10.1038/s41537-021-00165-0","DOIUrl":null,"url":null,"abstract":"<p><p>Cognitive gains following cognitive training interventions are associated with improved functioning in people with schizophrenia (SCZ). However, considerable inter-individual variability is observed. Here, we evaluate the sensitivity of brain structural features to predict functional response to auditory-based cognitive training (ABCT) at a single-subject level. We employed whole-brain multivariate pattern analysis with support vector machine (SVM) modeling to identify gray matter (GM) patterns that predicted higher vs. lower functioning after 40 h of ABCT at the single-subject level in SCZ patients. The generalization capacity of the SVM model was evaluated by applying the original model through an out-of-sample cross-validation analysis to unseen SCZ patients from an independent validation sample who underwent 50 h of ABCT. The whole-brain GM volume-based pattern classification predicted higher vs. lower functioning at follow-up with a balanced accuracy (BAC) of 69.4% (sensitivity 72.2%, specificity 66.7%) as determined by nested cross-validation. The neuroanatomical model was generalizable to an independent cohort with a BAC of 62.1% (sensitivity 90.9%, specificity 33.3%). In particular, greater baseline GM volumes in regions within superior temporal gyrus, thalamus, anterior cingulate, and cerebellum predicted improved functioning at the single-subject level following ABCT in SCZ participants. The present findings provide a structural MRI fingerprint associated with preserved GM volumes at a single baseline timepoint, which predicted improved functioning following an ABCT intervention, and serve as a model for how to facilitate precision clinical therapies for SCZ based on imaging data, operating at the single-subject level.</p>","PeriodicalId":19328,"journal":{"name":"NPJ Schizophrenia","volume":"7 1","pages":"40"},"PeriodicalIF":5.7000,"publicationDate":"2021-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1038/s41537-021-00165-0","citationCount":"4","resultStr":"{\"title\":\"Multivariate pattern analysis of brain structure predicts functional outcome after auditory-based cognitive training interventions.\",\"authors\":\"Lana Kambeitz-Ilankovic,&nbsp;Sophia Vinogradov,&nbsp;Julian Wenzel,&nbsp;Melissa Fisher,&nbsp;Shalaila S Haas,&nbsp;Linda Betz,&nbsp;Nora Penzel,&nbsp;Srikantan Nagarajan,&nbsp;Nikolaos Koutsouleris,&nbsp;Karuna Subramaniam\",\"doi\":\"10.1038/s41537-021-00165-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Cognitive gains following cognitive training interventions are associated with improved functioning in people with schizophrenia (SCZ). However, considerable inter-individual variability is observed. Here, we evaluate the sensitivity of brain structural features to predict functional response to auditory-based cognitive training (ABCT) at a single-subject level. We employed whole-brain multivariate pattern analysis with support vector machine (SVM) modeling to identify gray matter (GM) patterns that predicted higher vs. lower functioning after 40 h of ABCT at the single-subject level in SCZ patients. The generalization capacity of the SVM model was evaluated by applying the original model through an out-of-sample cross-validation analysis to unseen SCZ patients from an independent validation sample who underwent 50 h of ABCT. The whole-brain GM volume-based pattern classification predicted higher vs. lower functioning at follow-up with a balanced accuracy (BAC) of 69.4% (sensitivity 72.2%, specificity 66.7%) as determined by nested cross-validation. The neuroanatomical model was generalizable to an independent cohort with a BAC of 62.1% (sensitivity 90.9%, specificity 33.3%). In particular, greater baseline GM volumes in regions within superior temporal gyrus, thalamus, anterior cingulate, and cerebellum predicted improved functioning at the single-subject level following ABCT in SCZ participants. The present findings provide a structural MRI fingerprint associated with preserved GM volumes at a single baseline timepoint, which predicted improved functioning following an ABCT intervention, and serve as a model for how to facilitate precision clinical therapies for SCZ based on imaging data, operating at the single-subject level.</p>\",\"PeriodicalId\":19328,\"journal\":{\"name\":\"NPJ Schizophrenia\",\"volume\":\"7 1\",\"pages\":\"40\"},\"PeriodicalIF\":5.7000,\"publicationDate\":\"2021-08-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1038/s41537-021-00165-0\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"NPJ Schizophrenia\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1038/s41537-021-00165-0\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PSYCHIATRY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"NPJ Schizophrenia","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1038/s41537-021-00165-0","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHIATRY","Score":null,"Total":0}
引用次数: 4

摘要

认知训练干预后的认知收益与精神分裂症患者(SCZ)的功能改善有关。然而,观察到相当大的个体间差异。在这里,我们评估了大脑结构特征的敏感性,以预测单受试者对基于听觉的认知训练(ABCT)的功能反应。我们采用支持向量机(SVM)建模的全脑多变量模式分析来识别灰质(GM)模式,这些模式可以预测SCZ患者在单受试者水平上进行40小时ABCT后功能的提高和降低。通过对独立验证样本中未见SCZ患者进行50 h ABCT的样本外交叉验证分析,应用原始模型对SVM模型的泛化能力进行评估。通过嵌套交叉验证,基于全脑GM体积的模式分类预测随访时功能更高或更低,平衡准确度(BAC)为69.4%(敏感性72.2%,特异性66.7%)。神经解剖学模型适用于BAC为62.1%的独立队列(敏感性90.9%,特异性33.3%)。特别是,SCZ参与者在ABCT后,颞上回、丘脑、前扣带和小脑区域的基线GM体积更大,预示着单受试者水平的功能改善。目前的研究结果提供了一个与单一基线时间点保存的GM体积相关的结构性MRI指纹,预测了ABCT干预后功能的改善,并作为如何促进基于成像数据的SCZ精确临床治疗的模型,在单个受试者水平上操作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multivariate pattern analysis of brain structure predicts functional outcome after auditory-based cognitive training interventions.

Cognitive gains following cognitive training interventions are associated with improved functioning in people with schizophrenia (SCZ). However, considerable inter-individual variability is observed. Here, we evaluate the sensitivity of brain structural features to predict functional response to auditory-based cognitive training (ABCT) at a single-subject level. We employed whole-brain multivariate pattern analysis with support vector machine (SVM) modeling to identify gray matter (GM) patterns that predicted higher vs. lower functioning after 40 h of ABCT at the single-subject level in SCZ patients. The generalization capacity of the SVM model was evaluated by applying the original model through an out-of-sample cross-validation analysis to unseen SCZ patients from an independent validation sample who underwent 50 h of ABCT. The whole-brain GM volume-based pattern classification predicted higher vs. lower functioning at follow-up with a balanced accuracy (BAC) of 69.4% (sensitivity 72.2%, specificity 66.7%) as determined by nested cross-validation. The neuroanatomical model was generalizable to an independent cohort with a BAC of 62.1% (sensitivity 90.9%, specificity 33.3%). In particular, greater baseline GM volumes in regions within superior temporal gyrus, thalamus, anterior cingulate, and cerebellum predicted improved functioning at the single-subject level following ABCT in SCZ participants. The present findings provide a structural MRI fingerprint associated with preserved GM volumes at a single baseline timepoint, which predicted improved functioning following an ABCT intervention, and serve as a model for how to facilitate precision clinical therapies for SCZ based on imaging data, operating at the single-subject level.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
NPJ Schizophrenia
NPJ Schizophrenia Medicine-Psychiatry and Mental Health
CiteScore
6.30
自引率
0.00%
发文量
44
审稿时长
15 weeks
期刊介绍: npj Schizophrenia is an international, peer-reviewed journal that aims to publish high-quality original papers and review articles relevant to all aspects of schizophrenia and psychosis, from molecular and basic research through environmental or social research, to translational and treatment-related topics. npj Schizophrenia publishes papers on the broad psychosis spectrum including affective psychosis, bipolar disorder, the at-risk mental state, psychotic symptoms, and overlap between psychotic and other disorders.
×
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