Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich & Swiss Federal Institute of Technology (ETH Zurich), Wilfriedstr. 6, 8032 Zurich, Switzerland.
Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich & Swiss Federal Institute of Technology (ETH Zurich), Wilfriedstr. 6, 8032 Zurich, Switzerland; Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Switzerland.
Neuroimage. 2021 Feb 1;226:117590. doi: 10.1016/j.neuroimage.2020.117590. Epub 2020 Dec 4.
Navigating the physical world requires learning probabilistic associations between sensory events and their change in time (volatility). Bayesian accounts of this learning process rest on hierarchical prediction errors (PEs) that are weighted by estimates of uncertainty (or its inverse, precision). In a previous fMRI study we found that low-level precision-weighted PEs about visual outcomes (that update beliefs about associations) activated the putative dopaminergic midbrain; by contrast, precision-weighted PEs about cue-outcome associations (that update beliefs about volatility) activated the cholinergic basal forebrain. These findings suggested selective dopaminergic and cholinergic influences on precision-weighted PEs at different hierarchical levels. Here, we tested this hypothesis, repeating our fMRI study under pharmacological manipulations in healthy participants. Specifically, we performed two pharmacological fMRI studies with a between-subject double-blind placebo-controlled design: study 1 used antagonists of dopaminergic (amisulpride) and muscarinic (biperiden) receptors, study 2 used enhancing drugs of dopaminergic (levodopa) and cholinergic (galantamine) modulation. Pooled across all pharmacological conditions of study 1 and study 2, respectively, we found that low-level precision-weighted PEs activated the midbrain and high-level precision-weighted PEs the basal forebrain as in our previous study. However, we found pharmacological effects on brain activity associated with these computational quantities only when splitting the precision-weighted PEs into their PE and precision components: in a brainstem region putatively containing cholinergic (pedunculopontine and laterodorsal tegmental) nuclei, biperiden (compared to placebo) enhanced low-level PE responses and attenuated high-level PE activity, while amisulpride reduced high-level PE responses. Additionally, in the putative dopaminergic midbrain, galantamine compared to placebo enhanced low-level PE responses (in a body-weight dependent manner) and amisulpride enhanced high-level precision activity. Task behaviour was not affected by any of the drugs. These results do not support our hypothesis of a clear-cut dichotomy between different hierarchical inference levels and neurotransmitter systems, but suggest a more complex interaction between these neuromodulatory systems and hierarchical Bayesian quantities. However, our present results may have been affected by confounds inherent to pharmacological fMRI. We discuss these confounds and outline improved experimental tests for the future.
在物理世界中导航需要学习感官事件及其随时间变化（波动性）之间的概率关联。这种学习过程的贝叶斯解释基于分层预测误差（PE），其由不确定性（或其倒数，精度）的估计加权。在之前的 fMRI 研究中，我们发现关于视觉结果的低水平精度加权 PEs（更新有关关联的信念）激活了假定的多巴胺能中脑；相比之下，关于线索-结果关联的精度加权 PEs（更新有关波动性的信念）激活了胆碱能基底前脑。这些发现表明，多巴胺能和胆碱能对不同层次的精度加权 PEs 有选择性影响。在这里，我们在健康参与者的药理学干预下重复了我们的 fMRI 研究，以检验这一假设。具体来说，我们使用了多巴胺能（氨磺必利）和毒蕈碱（比哌立登）受体拮抗剂以及多巴胺能（左旋多巴）和胆碱能（加兰他敏）调节剂的增强药物进行了两项药理学 fMRI 研究，采用了基于受试者的双盲安慰剂对照设计：研究 1 使用了多巴胺能和毒蕈碱受体拮抗剂，研究 2 使用了多巴胺能和胆碱能增强药物。分别对研究 1 和研究 2 的所有药理学条件进行汇总，我们发现，正如我们之前的研究那样，低水平精度加权 PEs 激活中脑，高水平精度加权 PEs 激活基底前脑。然而，我们发现，只有当将精度加权 PEs 分解为其 PE 和精度分量时，才能观察到与这些计算量相关的大脑活动的药理学效应：在假定包含胆碱能（脑桥被盖核和外侧背盖核）核的脑干区域中，与安慰剂相比，比哌立登增强了低水平 PE 反应并减弱了高水平 PE 活性，而氨磺必利则降低了高水平 PE 反应。此外，在假定的多巴胺能中脑，加兰他敏与安慰剂相比增强了低水平 PE 反应（以体重依赖的方式），而氨磺必利增强了高水平精度活动。任务行为不受任何药物的影响。这些结果不支持我们关于不同层次推断水平和神经递质系统之间存在明确二分法的假设，但表明这些神经调制系统和分层贝叶斯量之间存在更复杂的相互作用。然而，我们目前的结果可能受到药理学 fMRI 固有的混杂因素的影响。我们讨论了这些混杂因素，并概述了未来改进实验测试的方法。
