Dissociating neural learning signals in human sign- and goal-trackers.,Nature Human Behaviour

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Dissociating neural learning signals in human sign- and goal-trackers.
Nature Human Behaviour ( IF 21.4 ) Pub Date : 2019-11-11 , DOI: 10.1038/s41562-019-0765-5
Daniel J Schad _{1,

2} , Michael A Rapp ₁ , Maria Garbusow ₂ , Stephan Nebe _{3,

4} , Miriam Sebold _{1,

2} , Elisabeth Obst ₃ , Christian Sommer ₃ , Lorenz Deserno _{5,

6,

7} , Milena Rabovsky ₁ , Eva Friedel _{2,

8} , Nina Romanczuk-Seiferth ₂ , Hans-Ulrich Wittchen _{3,

9} , Ulrich S Zimmermann _{3,

10} , Henrik Walter ₂ , Philipp Sterzer ₂ , Michael N Smolka _{3,

11} , Florian Schlagenhauf _{2,

5} , Andreas Heinz ₂ , Peter Dayan _{12,

13} , Quentin J M Huys _{14,

15,

16}

Affiliation

Cognitive Sciences, University of Potsdam, Potsdam, Germany.
Department of Psychiatry and Psychotherapy, Charité Campus Mitte, Charité-Universitätsmedizin Berlin, Berlin, Germany.
Department of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany.
Department of Economics, Zurich Center for Neuroeconomics, University of Zurich, Zurich, Switzerland.
Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
Wellcome Trust Centre for Neuroimaging, University College London, London WC1N 3BG, United Kingdom.
Centre for Computational Psychiatry and Ageing Research, Max Planck University College London, London, UK.
Berlin Institute of Health, Berlin, Germany.
Institute of Clinical Psyhology & Psychotherapy, TU-Dresden und Department of Psychiatry, Ludwig-Maximalians-Universität, München, Germany.
Department of Addiction Medicine and Psychotherapy, kbo-Isar-Amper-Klinikum, Munich, Germany.
Neuroimaging Center, Technische Universität Dresden, Dresden, Germany.
Gatsby Computational Neuroscience Unit, University College London, London, UK.
Max Planck Institute for Biological Cybernetics, Tübingen, Germany.
Center for Addictive Disorders, Hospital of Psychiatry, University of Zürich, Zürich, Switzerland.
Translational Neuromodeling Unit, University of Zürich and Swiss Federal Institute of Technology, Zürich, Switzerland.
Complex Depression Anxiety and Trauma Service, Camden and Islington NHS Foundation Trust, London, UK.

Individuals differ in how they learn from experience. In Pavlovian conditioning models, where cues predict reinforcer delivery at a different goal location, some animals-called sign-trackers-come to approach the cue, whereas others, called goal-trackers, approach the goal. In sign-trackers, model-free phasic dopaminergic reward-prediction errors underlie learning, which renders stimuli 'wanted'. Goal-trackers do not rely on dopamine for learning and are thought to use model-based learning. We demonstrate this double dissociation in 129 male humans using eye-tracking, pupillometry and functional magnetic resonance imaging informed by computational models of sign- and goal-tracking. We show that sign-trackers exhibit a neural reward prediction error signal that is not detectable in goal-trackers. Model-free value only guides gaze and pupil dilation in sign-trackers. Goal-trackers instead exhibit a stronger model-based neural state prediction error signal. This model-based construct determines gaze and pupil dilation more in goal-trackers.

中文翻译：

分离人类手势和目标跟踪器中的神经学习信号。

个人从经验中学习的方式有所不同。在巴甫洛夫式条件模型中，线索会预测补给物在不同目标位置的传递，某些被称为“符号追踪器”的动物会接近该提示，而另一些被称为“目标追踪器”的动物会接近该目标。在符号跟踪器中，无模型的阶段性多巴胺能回报预测错误是学习的基础，这会使刺激“想要”。目标跟踪器不依赖多巴胺进行学习，而是被认为使用基于模型的学习。我们使用眼动追踪，瞳孔测量和功能性磁共振成像（通过信号追踪和目标追踪的计算模型来提供信息）在129名男性中证明了这种双重解离。我们显示符号跟踪器展现出在目标跟踪器中无法检测到的神经奖励预测错误信号。无模型值仅指导符号跟踪器中的注视和瞳孔扩张。相反，目标跟踪器展示了一个更强大的基于模型的神经状态预测误差信号。这种基于模型的构造在目标跟踪器中更能确定注视和瞳孔扩张。

更新日期：2019-11-13

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