Instructed knowledge shapes feedback-driven aversive learning in striatum and orbitofrontal cortex, but not the amygdala: Instruction-based expected value: Instructed Learners

<p>This corresponds to Figure 3: Figure supplement 2. We fit our modified computational model (which flexibly updates when instructed reversals are delivered) to SCR in the Instructed Group learners during our fear reversal learning task. We measured within-subject correlations with brain responses to unreinforced CS presentations (trial-by-trial). Robust regression was used to generate group results. These results are restricted to the 20 Instructed Group subjects who showed differential SCR prior to the first reversal.</p>

[](https://neurovault.org/images/60319)

### Collection description

<p>This includes all maps from Atlas et al., 2016. The experiment was an aversive reversal learning task (fear conditioning with reversals) in which participants viewed images (angry faces from the Ekman set) and one stimulus was paired with a shock on 30% of trials. There were 3 reversals across the task. One group (n = 30, Instructed Group) was informed about contingencies before learning &amp; prior to each reversal, whereas a second group (n = 40, Uninstructed Group) learned only through experience. Neuroimaging analyses focused on correlations with dynamic expected value (EV) calculated based on an adapted Rescorla-Wagner learning model with an additional parameter to measure the effects of instructed reversals (see Atlas et al). This model was fit to skin conductance from learners in either the Instructed group (n=20) or the Uninstructed Group (n = 20) to generate Instructed and Feedback-driven EV. We used the best fits from the models fit to each group to generate parametric modulators for fMRI analyses and modeled EV on unreinforced (no shock) trials in our first level analyses and compared within and across groups at second level. We also used task-based fMRI to look at trials surrounding reversal within the Instructed Group to identify regions that update immediately with instruction and those that continue to respond to previous contingencies, and how well reversals correlated with responses to instructions in the DLPFC region that showed greater activation in the Instructed Group across all trials. </p>

###Subject species

homo sapiens

###Modality

fMRI-BOLD

### Analysis level

group

### Cognitive paradigm (task)

reversal learning task

### Map type

T

<p>此描述对应图3：图补充2。我们将所改进的计算模型（该模型可根据指令反转灵活更新）拟合到指导组学习者在我们的恐惧反转学习任务中的SCR（皮肤电导反应）上。我们通过逐次试验测量了受试者大脑对未加强条件刺激呈现的响应的相关性。使用稳健回归来生成组别结果。这些结果仅限于在第一次反转前表现出差异SCR的20名指导组受试者。</p>

[](https://neurovault.org/images/60319)

### 数据集描述

<p>本数据集包括Atlas等人在2016年的所有图谱。实验是一项厌恶性反转学习任务（恐惧条件反射与反转），参与者观看图像（Ekman集的愤怒面孔），其中在一个试验中有30%的概率将刺激与电击配对。任务中进行了3次反转。一组（n=30，指导组）在学习和每次反转之前被告知相关情境，而另一组（n=40，非指导组）仅通过经验进行学习。神经影像学分析集中在基于改进的Rescorla-Wagner学习模型（额外参数用于测量指令反转的效果）计算出的动态期望值（EV）的相关性上（见Atlas等人）。此模型被拟合到指导组（n=20）或非指导组（n=20）的学习者的皮肤电导上，以生成指导驱动的和反馈驱动的EV。我们使用每个组别模型的最佳拟合来生成fMRI分析的参数调节器，并在第一级分析中模拟未加强（无电击）试验中的EV，并在第二级中比较组和组之间的差异。我们还使用基于任务的fMRI来观察指导组中反转周围的试验，以识别立即随指令更新的区域以及继续对先前情境做出反应的区域，并评估反转与DLPFC区域（在所有试验中指导组表现出更大激活）中指令响应的相关性。</p>

### 受试者物种

homo sapiens

### 模式

fMRI-BOLD

### 分析级别

组别

### 认知范式（任务）

反转学习任务

### 地图类型

T