Proceedings of the Annual Meeting of the Cognitive Science Society

This paper presents a computational model of attentional requirements in sequence learning. The structure of a keypressing sequence affects subjects' abilities to learn the sequence in a dual task paradigm (Cohen, Ivry, & Keele, 1990). Sequences containing unique associations among successive positions (i.e., 1-5-4-2-3) are learned during distraction. Sequences containing repeated positions with ambiguous associations (i.e., 3-1-2-1-3-2) are not learned during distraction. Cohen, et al. proposed two fundamental operations in sequence learning. A n associative mechanism mediates learning of the unique patterns (1-5-4-2-3). These associations do not require attention to be learned. Such an associative mechanism is poorly suited for learning the sequence with repeated elements and ambiguous associations. These sequences must be parsed and organized in a hierarchical manner. This hierarchical organization requires attention. The simulations reported in this paper were run on an associative model of sequence learning developed by Jordan (1986). Sequences of differing structures were presented to the model under two conditions - unparsed, and parsed into subsequences. The simulations modeled closely the keypressing task used by Cohen, Ivry and Keele (1990). The simulations (1) replicate the empirical findings, and (2) suggest that imposing hierarchical organization on sequences with ambiguous associations significantly improves the model's ability to learn those sequences. Implications for the analysis of fundamental computations underlying a system of skilled movement are discussed.