Pereg Maayan, Harpaz Danielle, Sabah Katrina, Ben-Shachar Mattan S, Amir Inbar, Dreisbach Gesine, Meiran Nachshon
Department of Psychology and Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva, Israel, 8410501.
Department of Psychology, University of Regensburg, Regensburg, Germany.
J Cogn. 2021 Jul 7;4(1):31. doi: 10.5334/joc.176. eCollection 2021.
The ability to learn abstract generalized structures of tasks is crucial for humans to adapt to changing environments and novel tasks. In a series of five experiments, we investigated this ability using a Rapid Instructed Task Learning paradigm (RITL) comprising short miniblocks, each involving two novel stimulus-response rules. Each miniblock included (a) instructions for the novel stimulus-response rules, (b) a NEXT phase involving a constant (familiar) intervening task (0-5 trials), (c) execution of the newly instructed rules (2 trials). The results show that including a NEXT phase (and hence, a prospective memory demand) led to relatively more robust abstract learning as indicated by increasingly faster responses with experiment progress. Multilevel modeling suggests that the prospective memory demand was just another aspect of the abstract task structure which has been learned.
学习任务的抽象通用结构的能力对于人类适应不断变化的环境和新任务至关重要。在一系列五个实验中，我们使用一种快速指导任务学习范式（RITL）来研究这种能力，该范式由短的迷你块组成，每个迷你块涉及两个新的刺激-反应规则。每个迷你块包括：（a）新刺激-反应规则的说明；（b）一个“下一个”阶段，涉及一个固定的（熟悉的）中间任务（0至5次试验）；（c）执行新指导的规则（2次试验）。结果表明，包含一个“下一个”阶段（因此，有一个前瞻性记忆需求）会导致相对更稳健的抽象学习，这表现为随着实验进展反应越来越快。多层次建模表明，前瞻性记忆需求只是已学习的抽象任务结构的另一个方面。
