Research Article: Generalized lessons about sequence learning from the study of the serial reaction time task

Date Published: May 21, 2012

Publisher: University of Finance and Management in Warsaw

Author(s): Hillary Schwarb, Eric H. Schumacher.

http://doi.org/10.2478/v10053-008-0113-1

Abstract

Over the last 20 years researchers have used the serial reaction time (SRT) task
to investigate the nature of spatial sequence learning. They have used the task
to identify the locus of spatial sequence learning, identify situations that
enhance and those that impair learning, and identify the important cognitive
processes that facilitate this type of learning. Although controversies remain,
the SRT task has been integral in enhancing our understanding of implicit
sequence learning. It is important, however, to ask what, if anything, the
discoveries made using the SRT task tell us about implicit learning more
generally. This review analyzes the state of the current spatial SRT sequence
learning literature highlighting the stimulus-response rule hypothesis of
sequence learning which we believe provides a unifying account of discrepant SRT
data. It also challenges researchers to use the vast body of knowledge acquired
with the SRT task to understand other implicit learning literatures too often
ignored in the context of this particular task. This broad perspective will make
it possible to identify congruences among data acquired using various different
tasks that will allow us to generalize about the nature of implicit
learning.

Partial Text

Learning is an integral part of human experience. Throughout our lives we are
constantly presented with new information that mustbe attended, integrated, and
stored. When learning is successful, the knowledge we acquire can be applied in
future situations to improve and enhance our behaviors. Learning can occur both
consciously and outside of our awareness. This learning without awareness, or
implicit learning, has been a topic of interest and
investigation for over 40 years (e.g., Thorndike
& Rock, 1934). Many paradigms have been used to investigate implicit
learning (cf. Cleeremans, Destrebecqz, & Boyer,
1998; Clegg, DiGirolamo, & Keele,
1998; Dienes & Berry, 1997),
and one of the most popular and rigorously applied procedures is the serial reaction
time (SRT) task. The SRT task is designed specifically to address issues related to
learning of sequenced information which is central to many human behaviors (Lashley, 1951) and is the focus of this review
(cf. also Abrahamse, Jiménez, Verwey, &
Clegg, 2010).

In 1987, Nissen and Bullemer developed a
procedure for studying implicit learning that over the next two decades would become
a paradigmatic task for studying and understanding the underlying mechanisms of
spatial sequence learning: the SRT task. The goal of this seminal study was to
explore learning without awareness. In a series of experiments, Nissen and Bullemer
used the SRT task to understand the differences between single- and dual-task
sequence learning. Experiment 1tested the efficacy of their design. On each trial,
an asterisk appeared at one of four possible target locations each mapped to a
separate response button (compatible mapping). Once a response was made the asterisk
disappeared and 500 ms later the next trial began. There were two groups of
subjects. In the first group, the presentation order of targets was random with the
constraint that an asterisk could not appear in the same location on two consecutive
trials. In the second group, the presentation order of targets followed a sequence
composed of 10 target locations that repeated 10 times over the course of a block
(i.e., “4-2-3-1-3-2-4-3-2-1” with 1,
2, 3, and 4 representing the
four possible target locations). Participants performed this task for eight blocks.
Significant Block × Group interactions were observed in both the reaction time
(RT) and accuracy data with participants in the sequenced group responding more
quickly and more accurately than participants in the random group. This is the
standard sequence learning effect. Participants who are exposed to an underlying
sequence perform more quickly and more accurately on sequenced trials compared to
random trials presumably because they are able to use knowledge of the sequence to
perform more efficiently. When asked, 11 of the 12 participants reported having
noticed a sequence, thus indicating that learning did not occur outside of awareness
in this study. However, in Experiment 4 individuals with Korsakoff’s syndrome
performed the SRT task and did not notice the presence of the sequence. Data
indicated successful sequence learning even in these amnesic patents. Thus, Nissen
and Bullemer concluded that implicit sequence learning can indeed occur under
single-task conditions.

Research has suggested that implicit and explicit learning rely on different
cognitive mechanisms (N. J. Cohen & Eichenbaum,
1993; A. S. Reber, Allen, & Reber,
1999) and that these processes are distinct and mediated by different
cortical processing systems (Clegg et al.,
1998; Keele, Ivry, Mayr, Hazeltine, &
Heuer, 2003; A. S. Reber et al.,
1999). Therefore, a primary concern for many researchers using the SRT
task is to optimize the task to extinguish or minimize the contributions of explicit
learning. One aspect that seems to play an important role is the choice of sequence
type.

One last point to consider when designing an SRT experiment is how best to assess
whether or not learning has occurred. In Nissen and Bullemer’s (1987) original experiments, between-group
comparisons were used with some participants exposed to sequenced trials and others
exposed only to random trials. A more common practice today, however, is to use a
within-subject measure of sequence learning (e.g., A. Cohen et al., 1990; Keele,
Jennings, Jones, Caulton, & Cohen, 1995; Schumacher & Schwarb, 2009; Willingham, Nissen, & Bullemer, 1989). This is accomplished by
giving a participant several blocks of sequenced trials and then presenting them
with a block of alternate-sequenced trials (alternate-sequenced trials are typically
a different SOC sequence that has not been previously presented) before returning
them to a final block of sequenced trials. If participants have acquired knowledge
of the sequence, they will perform less quickly and/or less accurately on the block
of alternate-sequenced trials (when they are not aided by knowledge of the
underlying sequence) compared to the surrounding blocks of sequenced trials. This RT
relationship, known as the transfer effect, is now the standard way
to measure sequence learning in the SRT task.

There are three main hypotheses1 in
the SRT task literature concerning the locus of sequence learning: a stimulus-based
hypothesis, a stimulus-response (S-R) rule hypothesis, and a response-based
hypothesis. Each of these hypotheses maps roughly onto a different stage of
cognitive processing (cf. Donders, 1969;
Sternberg, 1969). Although cognitive
processing stages are not often emphasized in the SRT task literature, this
framework is typical in the broader human performance literature. This framework
assumes at least three processing stages: When a stimulus is presented, the
participant must encode the stimulus, select the task appropriate response, and
finally must execute that response. Many researchers have proposed that these
stimulus encoding, response selection, and response execution processes are
organized as serial and discrete stages (e.g., Donders, 1969; Meyer & Kieras,
1997; Sternberg, 1969), but other
organizations (e.g., parallel, serial, continuous, etc.) are possible (cf. Ashby, 1982; McClelland, 1979). It is possible that sequence learning can occur at
one or more of these information-processing stages. We believe that consideration of
information processing stages is critical to understanding sequence learning and the
three main accounts for it in the SRT task.

Even in the first SRT study, the effect of dividing attention (by performing a
secondary task) on sequence learning was investigated (Nissen & Bullemer, 1987). Since then, there has been an
abundance of research on dual-task sequence learning, however, the results of this
effort have been controversial with many studies reporting intact sequence learning
under dual-task conditions (e.g., Frensch et al.,
1998; Frensch & Miner, 1994;
Grafton, Hazeltine, & Ivry, 1995;
Jiménez & Vázquez, 2005;
Keele et al., 1995; McDowall, Lustig, & Parkin, 1995; Schvaneveldt & Gomez, 1998; Shanks & Channon, 2002; Stadler,
1995) and others reporting impaired learning with a secondary task (e.g.,
Heuer & Schmidtke, 1996; Nissen & Bullemer, 1987). As a result,
several hypotheses have emerged in an attempt to explain these data and provide
general principles for understanding multi-task sequence learning. These hypotheses
include the attentional resource hypothesis (Curran
& Keele, 1993; Nissen & Bullemer,
1987), the automatic learning hypothesis/suppression hypothesis (Frensch, 1998; Frensch et al., 1998, 1999; Frensch & Miner, 1994), the organizational
hypothesis (Stadler, 1995), the task
integration hypothesis (Schmidtke & Heuer,
1997), the two-system hypothesis (Keele
et al., 2003), and the parallel response selection hypothesis (Schumacher & Schwarb, 2009) of sequence
learning. While these accounts seek to characterize dual-task sequence learning
rather than identify the underlying locus of this learning, connections can still be
drawn. We propose that the parallel response selection hypothesis is not only
consistent with the S-R rule hypothesis of sequence learning discussed above, but
also most ade-quately explains the existing literature on dual-task spatial sequence
learning.

This review of the vast literature surrounding the SRT task demonstrates that the
past 20 years of research have afforded great insights into the underlying structure
of implicit sequence learning. However, the generalizability of these principles to
other implicit learning tasks has yet to be determined. The SRT task provides a
highly controlled and efficient procedure for modeling sequence learning behavior;
however, the fidelity of the underlying processes to those of real-world sequential
learning has yet to be verified (Mathews,
1997). Applying the knowledge acquired about implicit sequence learning
from the SRT task to other related implicit learning task is an important first step
in verifying the universality of these SRT-derived accounts for implicit sequence
learning.

In this review we have presented the SRT task in detail with a particular focus on
important factors to consider when designing an SRT study. We have summarized the
various hypotheses associated with identifying the locus of spatial sequence
learning and have demonstrated how the S-R rule hypothesis provides a cohesive
framework for unifying a seemingly incongruous literature. Additionally we have
reviewed various studies using the dual-SRT task and suggested that the parallel
response selection hypothesis can explain many of the discrepant findings in this
literature. The S-R rule hypothesis and the parallel response selection hypothesis
are conceptually similar and both highlight the importance of response selection
processes in successful sequence learning. We propose that taken together, the S-R
rule hypothesis and parallel response selection hypothesis not only provide a
unifying framework, but also point to response selection as the underlying critical
cognitive process for effective sequence learning.

 

Source:

http://doi.org/10.2478/v10053-008-0113-1

 

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