Inappropriate behaviors may result from acquiring maladaptive associations between irrelevant information in the environment and important events, such as reward or punishment. Pre-exposure effects are believed to prevent the expression of irrelevant associations. For example, learned irrelevance delays the expression of associations between conditioned (CS) and unconditioned (US) stimuli following their uncorrelated presentation. The neuronal substrates of pre-exposure effects in humans are largely unknown because these effects rapidly attenuate when using traditional pre-exposure paradigms. The latter are therefore incompatible with neuroimaging approaches that require many trial repetitions. Moreover, large methodological differences between animal and human research on pre-exposure effects challenge the presumption of shared neurocognitive substrates, and question the prevalent use of pre-exposure effects in animals to model symptoms of human mental disorders. To overcome these limitations, we combined a novel learned irrelevance task with model-based fMRI. We report the results of a model that describes learned irrelevance as a dynamic process, which evolves across trials and integrates the weighting between two state-action values pertaining to 'CS-no US' associations (acquired during pre-exposure) and 'CS-US' associations (acquired during subsequent conditioning). This relative weighting correlated i) positively with the learned irrelevance effect observed in the behavioral task, ii) positively with activity in the entorhinal cortex, and iii) negatively with activity in the nucleus accumbens (NAcc). Furthermore, the model updates the relative weighting of the two state-action values via two separate prediction error (PE) signals that allow the dynamic accumulation of evidence for the CS to predict the 'US' or a 'no US' outcome. One PE signal, designed to increase the relative weight of 'CS-US' associations following 'US' outcomes, correlated with activity in the NAcc, while another PE signal, designed to increase the relative weight of 'CS-no US' associations following 'no US' outcomes, correlated with activity in the basolateral amygdala. By extending previous animal observations to humans, the present study provides a novel approach to foster translational research on pre-exposure effects.

中文翻译：

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人类学习无关性的神经计算相关性

不适当的行为可能是由于在环境中的不相关信息与重要事件（例如奖励或惩罚）之间获得了适应不良的关联。预曝光效应被认为可以防止无关关联的表达。例如，习得的不相关延迟了条件 (CS) 和无条件 (US) 刺激在不相关的呈现后之间关联的表达。人类暴露前效应的神经元底物在很大程度上是未知的，因为当使用传统的暴露前范式时，这些效应会迅速减弱。因此，后者与需要多次试验重复的神经影像学方法不相容。而且，关于暴露前效应的动物和人类研究之间的巨大方法论差异挑战了共享神经认知基础的假设，并质疑在动物中普遍使用暴露前效应来模拟人类精神障碍症状。为了克服这些限制，我们将新的学习无关任务与基于模型的 fMRI 相结合。我们报告了一个模型的结果，该模型将学习到的无关性描述为一个动态过程，该过程在试验中发展，并整合了与“CS-no US”关联（在预曝光期间获得）和“CS-”相关的两个状态行为值之间的权重。美国协会（在随后的调理期间获得）。这种相对权重 i) 与在行为任务中观察到的学习无关效应呈正相关，ii) 内嗅皮层的活性呈阳性，和 iii) 伏隔核 (NAcc) 的活性呈负向。此外，该模型通过两个独立的预测误差 (PE) 信号更新两个状态-动作值的相对权重，这些信号允许 CS 动态积累证据以预测“US”或“无 US”结果。一个 PE 信号，旨在增加“US”结果后“CS-US”关联的相对权重，与 NAcc 中的活动相关，而另一个 PE 信号，旨在增加“CS-no US”关联的相对权重。 “无美国”结果，与基底外侧杏仁核的活动相关。通过将之前的动物观察扩展到人类，