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首页> 外文期刊>NeuroImage >Distinct contributions of lateral orbito-frontal cortex, striatum, and fronto-parietal network regions for rule encoding and control of memory-based implementation during instructed reversal learning
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Distinct contributions of lateral orbito-frontal cortex, striatum, and fronto-parietal network regions for rule encoding and control of memory-based implementation during instructed reversal learning

机译:外侧眼眶额叶皮层,纹状体和额顶叶网区在指令逆向学习过程中对规则编码和基于记忆的实施控制的不同贡献

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A key element of behavioral flexibility is to quickly learn to modify or reverse previously acquired stimulus-response associations. Such reversal learning (RL) can either be driven by feedback or by explicit instruction, informing either retrospectively or prospectively about the changed response requirements. Neuroimaging studies have thus far exclusively focused either on feedback-driven RL or on instructed initial learning of novel rules. The present study examined the neural basis of instructed RL as compared to instructed initial learning, separately assessing reversal-related instruction-based encoding processes and reversal-related control processes required for implementing reversed rules under competition from the initially learned rules. We found that instructed RL is partly supported by similar regions as feedback-driven RL, including lateral orbitofrontal cortex (lOFC) and anterior dorsal caudate. Encoding-related activation in both regions determined resilience against response competition during subsequent memory-based reversal implementation. Different from feedback-driven RL, instruction-based RL relied heavily on the generic fronto-parietal cognitive control network - not for encoding but for reversal-related control processes during memory-based implementation. These findings are consistent with a model of partly decoupled, yet interacting, systems of (i) symbolic rule representations that are instantaneously updated upon instruction and (ii) pragmatic representations of reward-associated S-R links mediating the enduring competition from initially learned rules. (C) 2015 Elsevier Inc. All rights reserved.
机译:行为灵活性的关键要素是快速学习以修改或逆转先前获得的刺激反应关联。这种逆向学习(RL)可以通过反馈来驱动,也可以通过明确的指令来驱动,回顾性或前瞻性地告知已更改的响应要求。迄今为止,神经影像学研究仅专注于反馈驱动的RL或新规则的指导性初始学习。本研究检查了与指令初始学习相比的指令RL的神经基础,分别评估了与反向学习相关的基于指令的编码过程和与反向学习相关的控制过程,这些过程是在与最初学习的规则竞争下实施反向规则所必需的。我们发现,指导性RL由与反馈驱动的RL相似的区域部分支持,包括侧眼眶额叶皮层(10FC)和前背尾状。两个区域中与编码相关的激活确定了在随后的基于内存的反转实现过程中对响应竞争的恢复能力。与反馈驱动的RL不同,基于指令的RL在很大程度上依赖于通用的额顶认知控制网络-在基于内存的实现过程中,不是用于编码,而是用于与反向相关的控制过程。这些发现与(i)符号规则表示的部分解耦但相互作用的系统模型相一致,该符号规则表示根据指示即刻更新,并且(ii)奖励相关的S-R链接的实用表示将持久的竞争与最初学习的规则进行了调和。 (C)2015 Elsevier Inc.保留所有权利。

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