Trempler Ima, Bürkner Paul-Christian, El-Sourani Nadiya, Binder Ellen, Reker Paul, Fink Gereon R, Schubotz Ricarda I
Department of Psychology, University of Muenster, 48149, Münster, Germany; Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Muenster, 48149, Münster, Germany.
Department of Psychology, University of Muenster, 48149, Münster, Germany.
Neuroimage. 2020 May 15;212:116674. doi: 10.1016/j.neuroimage.2020.116674. Epub 2020 Feb 22.
The brain's sensitivity to and accentuation of unpredicted over predicted sensory signals plays a fundamental role in learning. According to recent theoretical models of the predictive coding framework, dopamine is responsible for balancing the interplay between bottom-up input and top-down predictions by controlling the precision of surprise signals that guide learning. Using functional MRI, we investigated whether patients with Parkinson's disease (PD) show impaired learning from prediction errors requiring either adaptation or stabilisation of current predictions. Moreover, we were interested in whether deficits in learning over a specific time scale would be accompanied by altered surprise responses in dopamine-related brain structures. To this end, twenty-one PD patients tested on and off dopaminergic medication and twenty-one healthy controls performed a digit prediction paradigm. During the task, violations of sequence-based predictions either signalled the need to update or to stabilise the current prediction and, thus, to react to them or ignore them, respectively. To investigate contextual adaptation to prediction errors, the probability (or its inverse, surprise) of the violations fluctuated across the experiment. When the probability of prediction errors over a specific time scale increased, healthy controls but not PD patients off medication became more flexible, i.e., error rates at violations requiring a motor response decreased in controls but increased in patients. On the neural level, this learning deficit in patients was accompanied by reduced signalling in the substantia nigra and the caudate nucleus. In contrast, differences between the groups regarding the probabilistic modulation of behaviour and neural responses were much less pronounced at prediction errors requiring only stabilisation but no adaptation. Interestingly, dopaminergic medication could neither improve learning from prediction errors nor restore the physiological, neurotypical pattern. Our findings point to a pivotal role of dysfunctions of the substantia nigra and caudate nucleus in deficits in learning from flexibility-demanding prediction errors in PD. Moreover, the data witness poor effects of dopaminergic medication on learning in PD.
大脑对未预测到的感觉信号相较于预测到的感觉信号的敏感性及强化在学习中起着基础性作用。根据预测编码框架的最新理论模型，多巴胺通过控制引导学习的意外信号的精度，负责平衡自下而上的输入与自上而下的预测之间的相互作用。我们使用功能磁共振成像，研究帕金森病（PD）患者在需要适应或稳定当前预测的预测误差学习方面是否受损。此外，我们还关注在特定时间尺度上学习缺陷是否会伴随着多巴胺相关脑区意外反应的改变。为此，21名接受多巴胺能药物治疗和未治疗的PD患者以及21名健康对照者进行了数字预测范式实验。在任务过程中，基于序列的预测违反情况分别表明需要更新或稳定当前预测，从而分别对其做出反应或忽略它们。为了研究对预测误差的情境适应，违反情况的概率（或其倒数，意外程度）在实验过程中波动。当特定时间尺度上预测误差的概率增加时，健康对照者而非未服药的PD患者变得更加灵活，即需要运动反应的违反情况下，对照者的错误率降低，而患者的错误率增加。在神经层面，患者的这种学习缺陷伴随着黑质和尾状核信号的减少。相比之下，在仅需要稳定而非适应的预测误差方面，两组在行为和神经反应的概率调制上的差异则不太明显。有趣的是，多巴胺能药物既不能改善从预测误差中的学习，也不能恢复生理上的、神经典型的模式。我们的研究结果表明，黑质和尾状核功能障碍在PD患者从需要灵活性的预测误差中学习的缺陷中起关键作用。此外，数据表明多巴胺能药物对PD患者学习的效果不佳。
