A multistudy analysis reveals that evoked pain intensity representation is distributed across brain systems.
A multistudy analysis reveals that evoked pain intensity representation is distributed across brain systems.
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DOI：
10.1371/journal.pbio.3001620
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发表时间：
2022-05
期刊：
影响因子：
9.8
通讯作者：
Wager, Tor D.
中科院分区：
文献类型：
--
作者：
Petre, Bogdan;Kragel, Philip;Atlas, Lauren Y.;Geuter, Stephan;Jepma, Marieke;Koban, Leonie;Krishnan, Anjali;Lopez-Sola, Marina;Losin, Elizabeth A. Reynolds;Roy, Mathieu;Woo, Choong-Wan;Wager, Tor D.
信息在大脑中以多种解剖尺度编码：局部，跨区域和网络分布，以及全球。对于疼痛，表征的规模尚未得到正式测试，并且缺乏跨区域和网络的疼痛表征的定量比较。在这项对11项研究中的376名参与者进行的多研究分析中，我们比较了多变量预测模型，以研究诱发性热痛强度表征的空间尺度和位置。我们比较了基于以下模型的模型：（a）单个最能预测疼痛的区域或静息状态网络;（B）从先前文献中开发的疼痛相关皮质-皮质下系统（“多系统模型”）;以及（c）跨越整个大脑的模型。我们使用留一研究交叉验证（CV; 7项研究）估计模型准确性，随后在4项独立的保留研究中进行验证。所有的空间尺度都传达了关于疼痛强度的信息，但分布式多系统模型预测疼痛的准确性比任何单个区域或网络高20%，并且更适用于多模式疼痛（热，内脏和机械）和特定疼痛。全脑模型显示，与多系统模型相比，没有预测优势。这些发现表明，需要多个皮层和皮层下系统来解码疼痛强度，特别是热痛，并且疼痛体验的表示可能不受任何基本区域或规范网络的限制。最后，我们采用的学习者泛化方法为评估其他领域的信息空间尺度提供了一个蓝图。疼痛是由一个单一的大脑区域或网络代表，跨越多个系统或分布在整个大脑？fMRI大脑解码在一个大型的多研究数据集表明，需要多个皮层和皮层下系统解码疼痛强度，该方法是新颖的，可以表征不同的大脑过程的代表性的规模。
Information is coded in the brain at multiple anatomical scales: locally, distributed across regions and networks, and globally. For pain, the scale of representation has not been formally tested, and quantitative comparisons of pain representations across regions and networks are lacking. In this multistudy analysis of 376 participants across 11 studies, we compared multivariate predictive models to investigate the spatial scale and location of evoked heat pain intensity representation. We compared models based on (a) a single most pain-predictive region or resting-state network; (b) pain-associated cortical–subcortical systems developed from prior literature (“multisystem models”); and (c) a model spanning the full brain. We estimated model accuracy using leave-one-study-out cross-validation (CV; 7 studies) and subsequently validated in 4 independent holdout studies. All spatial scales conveyed information about pain intensity, but distributed, multisystem models predicted pain 20% more accurately than any individual region or network and were more generalizable to multimodal pain (thermal, visceral, and mechanical) and specific to pain. Full brain models showed no predictive advantage over multisystem models. These findings show that multiple cortical and subcortical systems are needed to decode pain intensity, especially heat pain, and that representation of pain experience may not be circumscribed by any elementary region or canonical network. Finally, the learner generalization methods we employ provide a blueprint for evaluating the spatial scale of information in other domains. Is pain represented by a single brain area or network, spanning multiple systems or distributed throughout the brain? fMRI brain decoding in a large multi-study dataset shows that multiple cortical and subcortical systems are needed to decode pain intensity; the approach is novel and can characterize scale of representation across diverse brain processes.
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影响因子：
3.7
作者：
Brown JE;Chatterjee N;Younger J;Mackey S
通讯作者：
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作者：
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DOI：
10.1073/pnas.0505210102
发表时间：
2005-12-20
影响因子：
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通讯作者：
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通讯作者：
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