[pu037] SUSTAIN captures category learning, recognition, and hippocampal activation in a unidimensional vs information-integration task

There is a growing interest in alternative explanations to the dual-system account of how people learn category structures varying in their optimal decision bounds (unidimensional and information-integration structures). Recognition memory performance and hippocampal activation patterns in these tasks are two interesting findings, which have not been formally explained. Here, we carry out a formal simulation with SUSTAIN (Love, Medin, & Gureckis, 2004), an adaptive model of category learning, which had great success in accounting for recognition memory performance and fMRI activity patterns. We show, for the first time, that a formal single-system model of category learning can accommodate recognition performance after learning and is consistent with fMRI data obtained while participants learned these structures.

对人类学习范畴结构双重系统理论（其最佳决策边界存在一维与信息整合结构之分）的替代性解释逐渐引起了广泛关注。在这些任务中，识别记忆表现及海马体激活模式是两个引人注目的发现，但目前尚未得到正式的解释。在本研究中，我们运用SUSTAIN模型（Love, Medin, & Gureckis, 2004）——一种范畴学习自适应模型，该模型在解释识别记忆表现及功能性磁共振成像（fMRI）活动模式方面取得了显著成就——进行了正式的模拟实验。我们首次证明了，一种正式的单系统范畴学习模型能够在学习后适应识别表现，并且与参与者学习这些结构期间获得的fMRI数据保持一致。