Max Planck University College London Centre for Computational Psychiatry and Ageing Research and the Wellcome Centre for Human Neuroimaging, University College London, London, UK.
Department of Psychology, Stanford University, 450 Jane Stanford Way, Stanford, CA, 94305, USA.
Mem Cognit. 2022 Feb;50(2):312-324. doi: 10.3758/s13421-021-01233-7. Epub 2021 Sep 14.
Neuroscience research has illuminated the mechanisms supporting learning from reward feedback, demonstrating a critical role for the striatum and midbrain dopamine system. However, in humans, short-term working memory that is dependent on frontal and parietal cortices can also play an important role, particularly in commonly used paradigms in which learning is relatively condensed in time. Given the growing use of reward-based learning tasks in translational studies in computational psychiatry, it is important to understand the extent of the influence of working memory and also how core gradual learning mechanisms can be better isolated. In our experiments, we manipulated the spacing between repetitions along with a post-learning delay preceding a test phase. We found that learning was slower for stimuli repeated after a long delay (spaced-trained) compared to those repeated immediately (massed-trained), likely reflecting the remaining contribution of feedback learning mechanisms when working memory is not available. For massed learning, brief interruptions led to drops in subsequent performance, and individual differences in working memory capacity positively correlated with overall performance. Interestingly, when tested after a delay period but not immediately, relative preferences decayed in the massed condition and increased in the spaced condition. Our results provide additional support for a large role of working memory in reward-based learning in temporally condensed designs. We suggest that spacing training within or between sessions is a promising approach to better isolate and understand mechanisms supporting gradual reward-based learning, with particular importance for understanding potential learning dysfunctions in addiction and psychiatric disorders.
神经科学研究阐明了支持从奖励反馈中学习的机制,表明纹状体和中脑多巴胺系统起着关键作用。然而,在人类中,依赖于额叶和顶叶皮层的短期工作记忆也可以发挥重要作用,特别是在通常使用的学习时间相对集中的范式中。鉴于基于奖励的学习任务在计算精神病学的转化研究中越来越多地被使用,了解工作记忆的影响程度以及如何更好地分离核心渐进学习机制非常重要。在我们的实验中,我们操纵了重复之间的间隔以及学习阶段之前的后学习延迟。我们发现,对于长时间延迟后重复的刺激(间隔训练)与立即重复的刺激(集中训练)相比,学习速度较慢,这可能反映了当工作记忆不可用时反馈学习机制的剩余贡献。对于集中学习,短暂的中断会导致后续表现下降,工作记忆能力的个体差异与整体表现呈正相关。有趣的是,当在延迟期后而不是立即测试时,集中条件下的相对偏好减弱,而间隔条件下的相对偏好增加。我们的结果为工作记忆在时间集中设计中的奖励学习中起着重要作用提供了额外的支持。我们建议在会话内或会话之间进行间隔训练是一种有前途的方法,可以更好地隔离和理解支持渐进式基于奖励的学习的机制,对于理解成瘾和精神障碍中的潜在学习障碍具有特别重要的意义。