Impact of Response Stimulus Interval on Transfer of Non-local Dependent Rules in Implicit Learning: An ERP Investigation

Abstract

In the literature on implicit learning, controversy exists regarding whether the knowledge obtained from implicit sequence learning consists of context-bound superficial features or context-free structural rules. To explore the nature of implicit knowledge, event related potentials (ERP) recordings of participants’ performances in a non-local dependent transfer task under two response-stimulus-interval (RSI) conditions (250 and 750 ms) were obtained. In the behavioral data, a transfer effect was found in the 750 ms RSI condition but not in the 250 ms RSI condition, suggesting that a long RSI is the basis for the occurrence of non-local dependent transfer, as which might have provided enough reaction time for participants to process and capture the implicit rule. Moreover, P300 amplitude was found to be sensitive to the impact of RSI on the training process (i.e., the longer RSI elicited higher P300 amplitudes), while variations in both N200 (i.e., a significant increase) and P300 amplitudes (i.e., a significant decrease) were found to be related to the presence of a transfer effect. Our results supported the claim that implicit learning can involve abstract rule knowledge acquisition under an appropriate RSI condition, and that amplitude variation in early ERP components (i.e., N200 and P300) can be useful indexes of non-local dependent learning and transfer effects.

A Dual Simple Recurrent Network Model for Chunking and Abstract Processes in Sequence Learning

“…The relevant behavioural and simulation results demonstrated that both surface and abstract structures can be captured by this dual process model, but abstract structures can be learned only explicitly. However, this is inconsistent with recent findings that people can implicitly acquire abstract structures ( Lin and Murray, 2013 ; Tanaka and Watanabe, 2014a , b , 2015 ; Huang et al, 2017 ; Fu et al, 2018 ; Ling et al, 2018 ).…”

“…Moreover, the present findings also helped account for the inconsistent findings about abstract learning and consciousness. Although more recent studies have provided new evidence that abstract learning can occur unconsciously ( Dienes et al, 2012 ; Kemeny and Meier, 2016 ; Huang et al, 2017 ; Ling et al, 2018 ), other studies supported that abstract knowledge can only be acquired consciously ( Shanks and St John, 1994 ; Dominey et al, 1998 ; Boyer et al, 2005 ; Cleeremans and Destrebecqz, 2005 ). According to our findings, this might be because the former studies used relatively simple abstract structures while the latter studies used more complex structures.…”

“… Boyer et al (2005) also suggested that the core mechanism involved in sequence learning is statistical in nature and genuine rule-based knowledge is necessarily conscious. Nonetheless, more studies have recently provided new evidence that abstract relationships or concepts can be processed without awareness ( Gross and Greene, 2007 ; Dienes et al, 2012 ; Lin and Murray, 2013 ; Tanaka and Watanabe, 2014a , b , 2015 ; Huang et al, 2017 ; Ling et al, 2018 ).…”

Perceiving structure in unstructured stimuli: Implicitly acquired prior knowledge impacts the processing of unpredictable transitional probabilities

“…In the statistical-sequence learning literature, the implicit transfer of both the perceptual and the motor sequence was shown in a version of the ASRT task that, in the testing phase, included a novel, previously unpracticed alternating motor or perceptual sequence with the same type of stimuli (Hallgató et al, 2013; Nemeth et al, 2009). In a deterministic SRT task, the 2 nd order transitional probability structure was implicitly transferred from the training to the testing phase, where the perceptual features of the stimuli differed (i.e., 1 st order structure: locations arranged horizontally or according to a square, Huang et al, 2017). Likewise, experiments using the artificial grammar learning task found the implicit transfer of sequential dependencies to novel vocabularies (Tunney & Altmann, 2001).…”

Non-linear effects of presentation rate on sequence learning

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In this article, we explore the impact of presentation rate on the extraction of hierarchical structure by manipulating the duration of the Response-to-Stimulus Interval (RSI) in a Serial Reaction Time (SRT) task. Multiple hypotheses have been put forward in the literature to account for the influence of RSI duration on sequence learning in the SRT task (Frensch & Miner, 1994;Huang et al, 2017;Willingham et al, 1997). However, this question has never been addressed from the perspective of hierarchical structure extraction.

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