Research reportThe differential consolidation of perceptual and motor learning in skill acquisition
Introduction
Implicit skill learning occurs when information is acquired from an environment of complex stimuli without conscious access either to what was learned or to the fact that learning occurred (Reber, 1993). In everyday life, this learning mechanism is crucial for adapting to the environment and evaluating events. Implicit skill learning underlies not only motor but cognitive and social skills as well, it is therefore an important aspect of life from infancy to old age. Skill learning does not occur only during practice, in the so-called online periods, but also between practice periods, during the so-called offline periods. The process that occurs during the offline periods is referred to as consolidation which means stabilization of a memory trace after the initial acquisition. This process can result in increased resistance to interference or even improvement in performance following an offline period (Krakauer and Shadmehr, 2006, Nemeth et al., 2010b, Robertson, 2009, Song, 2009).
Most models of skill learning (Dennis and Cabeza, 2011, Doyon et al., 2009a, Hikosaka et al., 1999, Hikosaka et al., 2002, Keele et al., 2003, Kincses et al., 2008) highlight the role of the basal ganglia and the cerebellum. One of the main debates in the field of skill learning is whether we rely on “our hands” or on “our eyes” (Deroost and Soetens, 2006, Keele et al., 2003, Mayr, 1996, Nemeth et al., 2009, Song et al., 2008, Ziessler and Nattkemper, 2001)? The goal of the present study is to determine if an offline period modifies the contribution of motor and perceptual components to implicit sequence learning. This issue is of particular interest because it deals with the question of whether sequence learning and consolidation are mediated by perceptual or by motor brain networks primarily (Deroost and Soetens, 2006, Goschke, 1998).
One of the most popular implicit learning tasks is the Serial Reaction Time (SRT) Task (Nissen and Bullemer, 1987) and its modification, the Alternating Serial Reaction Time (ASRT) Task (Howard and Howard, 1997, Nemeth et al., 2010b). In the original version a stimulus appears at one of four possible locations on the screen, and subjects have to press the button corresponding to that location. Unbeknownst to them, the sequence of subsequent locations (and correspondingly, the sequence of the responses) follows a predetermined order. Without becoming aware of the sequence, subjects learn the regularity – and as they learn, they produce faster and more accurate responses. When the sequence is changed to a random series of stimuli, subjects become slower and less accurate in responding. In this paradigm, however, it is not clear what exactly the subjects learn: they might learn the sequence of the stimuli (perceptual learning), the sequence of their own eye movements (oculomotor learning), the sequence of response locations (response-based learning) or the sequence of given fingers’ movements (effector-based learning) ( Cohen et al., 1990; Remillard, 2003; Willingham, 1999).
In a SRT study Willingham (1999) used two conditions to examine the perceptual and the motor factors of learning. In one condition the stimulus–response mapping was changed in the transfer (test) phase that followed the learning phase, so that half of the subjects had to press the same sequence of keys as in the learning phase but saw new stimuli, whereas the other half had to press a different sequence of keys as in the learning phase but saw the same stimuli as before. Willingham (1999) found that transfer was shown only when the motor sequence was kept constant, but not when the perceptual sequence was constant. In a previous study, Nemeth et al. (2009) compared the magnitude of perceptual and motor implicit sequence learning using a modification of the ASRT-task in a similar design. This task (ASRT-Race) contains second-order probabilistic sequences compared to classical SRT tasks that use deterministic sequences. ASRT-Race allows measuring “pure” sequence learning separate from general skill improvements, where sequence learning is reflected in the difference between the reaction times to more predictable events as opposed to less predictable ones. In addition, this task eliminates the possibility of oculomotor learning as stimuli always appear in the same central position on the screen. In contrast to Willingham’s findings, Nemeth et al. (2009) demonstrated that not only motor, but perceptual learning of second-order probabilistic sequences is possible. Furthermore, Nemeth et al. (2009) showed that the two types of learning do not differ significantly in magnitude. The weakness of the above mentioned perceptual-motor studies (Deroost and Soetens, 2006, Mayr, 1996, Nemeth et al., 2009, Remillard, 2003, Remillard, 2009, Song et al., 2008, Willingham, 1999) is that experiments were conducted in one session. Using only one session for measuring skill learning relates to short-term performance changes in behavior and not to more permanent changes associated with learning. Consequently, it is important to address the question of the role of offline periods in perceptual and motor skill learning.
Recent reviews indicate that whether offline improvements occur at all, and whether they are sleep-dependent, varies with factors such as awareness, the formation of contextual associations and type of information to be learned (Debas et al., 2010, Doyon et al., 2009b, Nemeth et al., 2010b, Robertson, 2009, Robertson et al., 2004, Siengsukon and Boyd, 2008, Song, 2009, Song et al., 2007). For example, Robertson (2009) argues that the consolidation of explicit (goal-directed) and implicit (movement-based) learning is differentially affected by sleep and wakefulness. In implicit learning when there is no declarative knowledge about the task, consolidation may occur during both wakefulness and sleep. In line with the predictions of this theory, recent SRT studies found similar consolidation of implicit skills during both sleep and wakefulness (Nemeth et al., 2010b, Robertson et al., 2004, Song et al., 2007).
Although many researches have investigated the perceptual and motor components of “online skill learning”, to our knowledge, the effect of consolidation on perceptual and motor characteristics of skill acquisition has not been investigated so far (Deroost and Soetens, 2006, Mayr, 1996, Nemeth et al., 2009, Remillard, 2003, Remillard, 2009, Song et al., 2008). In our study we used the ASRT-Race task (Nemeth et al., 2009) to examine the possible difference in the magnitude of motor and perceptual learning after a 12-h and a 24-h retention period. In addition, we also aimed at exploring the role of sleep in offline consolidation of these two factors of skill learning. Therefore a 12-h delay was administered between the Learning Phase and Transfer Phase of the experiment, during which participants either had a sleep (night group) or they were awake (day group). If both groups acquire the same level of skill in the Learning Phase, any difference between them in the Transfer Phase will answer the question whether the perceptual or the motor component stabilizes more effectively during the offline period. In order to avoid a time-of-day effect we also administered a 24-h delay condition.
Section snippets
Participants
There were 102 individuals (students attending the University of Szeged) in the experiment (mean age = 22.34, standard deviation (SD) = 3.82; 44 males, 58 females). None of them suffered from any developmental, psychiatric or neurological disorders. Participants were randomly assigned to the perceptual group or to the motor group. The perceptual and motor groups were further divided by the length of delay (12- or 24-h delay) and by the daytime (morning-first, AM–PM/AM–AM and evening-first,
Learning in Session 1
To be able to investigate the effect of transfer after 12- and 24-h delay, the learning in Session 1 must be similar in the groups. From this point of view, the end of Session 1 is crucial (Nemeth and Janacsek, 2011, Nemeth et al., 2010b, Press et al., 2005, Song et al., 2007). Therefore, we analyzed the SLE of the last five blocks of the Learning Phase for every group. Univariate analysis of variance (ANOVA) was conducted with CONDITION (perceptual vs motor), DAYTIME (morning-first vs
Discussion
Our study investigated the role of 12-h and 24-h delay on perceptual and motor components of implicit skill learning, while eliminating oculomotor learning. In this way we connect two debates together: (1) one on the relative importance of perceptual and motor learning (2) the other on the effect of sleep on skill acquisition. We used the same method as Nemeth et al.’s study (2009), except that in our research there was a 12-h (during which participants either had sleep or they were awake) or a
Acknowledgments
Thanks to our mentors: Darlene V. Howard and James H. Howard, Jr. from Georgetown University. This research was supported by Bolyai Scholarship Program (D. N.) and OTKA K 82068. Thanks to Ágnes Szokolszky and Szabolcs Kéri helping us with the final version of the manuscript.
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2021, NeuropsychologiaCitation Excerpt :For each participant and period, separately for pattern high-probability and random low-probability triplets, median RT was calculated for those correct responses that also followed correct responses. Independent of triplet types, general skill improvements (faster RTs) reflecting more efficient visuomotor and motor-motor coordination due to practice were also considered (cf. Hallgató et al., 2013; Juhasz et al., 2019). The mean accuracy of responding for each triplet type and period are provided in Table 1; otherwise, the paper focuses on the RT analysis (cf. Kóbor et al., 2019; Kóbor et al., 2018).
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All authors contributed equally to this work.