Chronic pain is linked to a resting-state neural archetype that optimizes learning from punishments.

Francesco Scarlatti, Ludovic Dormegny-Jeanjean, Roman Schefzik, Tobias Banaschewski, Arun L W Bokde, Rüdiger Brühl, Sylvane Desrivières, Hugh Garavan, Penny Gowland, Antoine Grigis, Andreas Heinz, Jean-Luc Martinot, Marie-Laure Paillère Martinot, Eric Artiges, Dimitri Papadopoulos Orfanos, Luise Poustka, Michael N Smolka, Sarah Hohmann, Nathalie Holz, Nilakshi Vaidya, Henrik Walter, Robert Whelan, Gunter Schumann, Frauke Nees, Emanuel Schwarz, Martin Löffler, Jack R Foucher, Herta Flor
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Abstract

Chronic pain is a leading cause of disability, yet its underlying susceptibility traits remain unclear. Disorders like chronic pain may stem from extreme neural types, or archetypes, optimized for specific cognitive strategies and reflected in patterns of resting-state networks. Here, we examined a sample from the general population ( n = 892) and three clinical samples with subacute back pain ( n = 76), chronic back pain ( n = 30), and treatment-resistant depression ( n = 24). Using the sample from the general population, we found three neural archetypes that prioritize different cognitive strategies. Clinical pain samples, compared to the sample from the general population, mapped close to an archetype optimized for punishment learning (Archetype P). We replicated these results by recomputing the archetypes starting from the clinical pain samples, additionally revealing an association between Archetype P and pain severity. These findings suggest a neural-cognitive trait underlying susceptibility to chronic pain.

慢性疼痛与静息状态的神经原型有关,这种神经原型使从惩罚中学习的能力得到优化。
慢性疼痛是致残的主要原因,但其潜在的易感性特征尚不清楚。慢性疼痛等疾病可能源于极端的神经类型或原型,它们针对特定的认知策略进行了优化,并反映在静息状态网络的模式中。在这里,我们检查了来自普通人群的样本(n = 892)和三个临床样本,分别患有亚急性背痛(n = 76)、慢性背痛(n = 30)和难治性抑郁症(n = 24)。使用来自普通人群的样本,我们发现了三种优先考虑不同认知策略的神经原型。与普通人群的样本相比,临床疼痛样本更接近于惩罚学习优化的原型(原型P)。我们通过重新计算从临床疼痛样本开始的原型来复制这些结果,另外揭示了原型P与疼痛严重程度之间的关联。这些发现提示了慢性疼痛易感性的神经认知特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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