Position–item associations play a role in the acquisition of order knowledge in an implicit serial reaction time task.

Abstract

Knowledge of sequential regularities plays a key role in forms of explicit and implicit memory, such as working memory and motor skills. Despite important advances in the study of sequence knowledge in the past century, the theoretical development of implicit and explicit memory has occurred separately. Unlike the literature on implicit sequence learning, the explicit learning literature differentiates between 2 forms of representation of serial structure, chaining (C is the item following B in the sequence A-B-C-D) and ordinal position knowledge (C is the 3rd item). In 3 experiments, we demonstrate that these 2 forms of sequence knowledge can be acquired in implicit sequence learning. In Experiment 1, 2 trained sequences were recombined at transfer such that the strength of (a) associations between serial positions and sequence elements as well as (b) associations between successive sequence elements could be estimated. In Experiment 2, we compared sequence elements placed at the trained versus untrained serial position. Experiment 3 reduced cues that can be used to determine the start of a sequence within the stream of trials. Our results suggest that the discussion held in explicit memory research about different forms of representation of sequences knowledge also is relevant for implicit sequence learning.

Why should working memory be related to incidentally learned sequence structures?

“…Prominent work on the representation of sequential structure in WM (e.g., Botvinick & Plaut, 2006;Cumming, Page, & Norris, 2003;Hebb, 1961) makes use of incidental tasks, in which sequences are encoded and retrieved as a by-product of instructed task processing. This suggests that neural and cognitive processes responsible for sequential structure in explicit and implicit cognition might overlap (see Discussion in Schuck, Gaschler, Keisler, & Frensch, 2012). In line with this, Aizenstein et al (2004) found activity in prefrontal cortex, striatal, anterior cingulate cortex, and visual regions (V1, V2, and V3) during implicit and explicit learning conditions.…”

Practice and sleep form different aspects of skill

“…Learning of transitions is present in humans (who can learn transition probabilities from up to six items prior 6 ) and monkeys (who can learn transitions between consecutive items 5,9 ), but not in pigeons 9 . On the other hand, learning the ordinal position of events in four-item lists has been demonstrated in humans 8 , monkeys 3 and pigeons 7 . In a real-life setting, for an experienced pianist, familiarity with frequencies of movement-to-movement transitions within a musical key can lead to faster performance of a new song that is written in a key rather than out of key, while each new song within a key can be unique, with this uniqueness represented by the ordinal position of each of the movements.…”

“…In a real-life setting, for an experienced pianist, familiarity with frequencies of movement-to-movement transitions within a musical key can lead to faster performance of a new song that is written in a key rather than out of key, while each new song within a key can be unique, with this uniqueness represented by the ordinal position of each of the movements. Motor skills for hobbies such as these and for compulsory activities such as speaking and driving, rely in part on the human ability to form long-term memory representations of both transition and ordinal information 4–6,8,9 .…”

Working Memory and Its Relation to Deterministic Sequence Learning

“…Evidence of the latter comes from varying the transition probabilities of an item sequence based on an artificial grammar which results in gradual learning of frequently repeated trials [29], [46], [58], [59]. Schuck, Gaschler, Keisler, and Frensch [55] discuss work from the verbal learning tradition (including the Hebb effect) on the representation of serial order and models on the representation of serial order in WM in order to then test the representation of serial order in implicit sequence learning. Based on our results it might be a next step to directly test whether and how the presentations of serial order in WM determines the presentation of serial order in implicit sequence knowledge, i.e., does implicit sequence learning store the order representation held in WM?…”