Department of Psychology, National University of Singapore, Singapore, Singapore.
Department of Psychology, National University of Singapore, Singapore, Singapore; NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore, Singapore.
Neurosci Biobehav Rev. 2019 Jul;102:85-94. doi: 10.1016/j.neubiorev.2019.04.006. Epub 2019 Apr 18.
In constantly changing environments, individuals need to overcome old habitual behaviors in order to learn new associations. Neuroimaging studies have focused on prediction errors, reversal errors and reversal switching in the reversal learning paradigm. Due to the inconsistencies of brain functioning across studies, we attempt to shed light on the concordant activity by performing meta-analyses on different components of reversal learning. While all contrasts yielded anterior cingulate and bilateral insulae, specifically prediction errors yielded more concordant activity within the striatum and amygdala, reversal errors yielded more concordant bilateral frontal-parietal activity, and more concordant inferior frontal cortical occurred from reversal switching. These findings suggest that reversal learning is supported by a core saliency network in all aspects of reversal learning as well as other reward and control related regions in distinct stages of this cognitively complex task. Our meta-analyses results provide stereotaxic maps that can be used for further neuroimaging work on adaptive learning.
在不断变化的环境中,个体需要克服旧的习惯行为,以学习新的联想。神经影像学研究集中在反转学习范式中的预测误差、反转错误和反转切换上。由于研究中大脑功能的不一致性,我们试图通过对反转学习的不同成分进行荟萃分析来阐明一致的活动。虽然所有对比都产生了前扣带和双侧岛叶,但具体来说,预测误差在纹状体和杏仁核内产生了更一致的活动,反转错误在双侧额顶叶产生了更一致的活动,而反转切换则产生了更一致的下额叶皮质活动。这些发现表明,反转学习在反转学习的各个方面以及在这个认知复杂任务的不同阶段与其他奖励和控制相关的区域都由一个核心显著网络支持。我们的荟萃分析结果提供了立体定向图谱,可以用于进一步的神经影像学自适应学习研究。