Institute for Systems Neuroscience, University Medical Center Hamburg-Eppendorf, W34, Martinistr. 52, 20246, Hamburg, Germany.
Division of Humanities and Social Sciences, Caltech, M/C 228-77, 1200 E. California Blvd, Pasadena, CA, 91125, USA.
Nat Commun. 2019 Jan 3;10(1):20. doi: 10.1038/s41467-018-07912-5.
The role of the frontal lobes in cognition and behavior has long been enigmatic. Over the past decade, computational models have provided a powerful approach to understanding cognition and decision-making. Here, we used a model-based approach to analyze data from a classical task used to assess frontal lobe function, the Wisconsin Card Sorting Test. We applied computational modeling and voxel-based lesion-symptom mapping in 328 patients with focal lesions, to uncover cognitive processes and neural correlates of test scores. Our results reveal that lesions in the right prefrontal cortex are associated with elevated perseverative errors and reductions in the model parameter of sensitivity to punishment. These findings indicate that the capacity to flexibly switch between task sets requires the detection of contingency changes, which are enabled by a sensitivity to punishment that reduces perseverative errors. We demonstrate the power of model-based approaches in understanding patterns of deficits on classical neuropsychological tasks.
额叶在认知和行为中的作用一直是个谜。在过去的十年中,计算模型为理解认知和决策提供了一种强大的方法。在这里,我们使用基于模型的方法来分析经典任务(威斯康星卡片分类测试)的数据,该任务用于评估额叶功能。我们在 328 名有局灶性病变的患者中应用计算建模和基于体素的病变-症状映射,以揭示认知过程和测试分数的神经相关物。我们的结果表明,右前额叶皮层的病变与持续错误增加和惩罚敏感性模型参数降低有关。这些发现表明,需要灵活地在任务集之间切换的能力需要检测到条件变化,这是通过对惩罚的敏感性来实现的,这种敏感性可以减少持续错误。我们展示了基于模型的方法在理解经典神经心理学任务缺陷模式方面的强大功能。