Dissociable processes for learning the surface structure and abstract structure of sensorimotor sequences

A sensorimotor sequence may contain information structure at several differ ent levels. In this study, we investigated the hypothesis that two dissocia ble processes are required for the learning of surface structure and abstra ct structure, respectively, of sensorimotor sequences. Surface structure is the simple serial order of the sequence elements, whereas abstract structu re is defined by relationships between repeating sequence elements. Thus, s equences ABCBAC and DEFEDF have different surface structures but share a co mmon abstract structure, 123213, and are therefore isomorphic. Our simulati ons of sequence learning performance in serial reaction time (SRT) tasks de monstrated that (1) an existing model of the primate fronto-striatal system is capable of learning surface structure but fails to learn abstract struc ture, which requires an additional capability, (2) surface and abstract str ucture can be learned independently by these independent processes, and (3) only abstract structure transfers to isomorphic sequences. We tested these predictions in human subjects. For a sequence with predictable surface and abstract structure, subjects in either explicit or implicit conditions lea rn the surface structure, but only explicit subjects learn and transfer the abstract structure. For sequences with only abstract structure, learning a nd transfer of this structure occurs only in the explicit group. These resu lts are parallel to those from the simulations and support our dissociable process hypothesis. Based on the synthesis of the current simulation and em pirical results with our previous neuropsychological findings, we propose a neurophysiological basis for these dissociable processes: Surface structur e can be learned by processes that operate under implicit conditions and re ly on the fronto-striatal system, whereas learning abstract structure requi res a more explicit activation of dissociable processes that rely on a dist ributed network that includes the left anterior cortex.