Mind Wandering I have attached the article that needs to be read to answer the discussion question that my professor has created. It need to be 1 page long

Mind Wandering I have attached the article that needs to be read to answer the discussion question that my professor has created. It need to be 1 page long, 12pt times new roman, 1in margins, and single spaced. I have also attached the rubric for the assignment. Research Report
Absorbed in Thought: The Effect of Mind
Wandering on the Processing of Relevant
and Irrelevant Events
Psychological Science
22(5) 596–601
© The Author(s) 2011
Reprints and permission:
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DOI: 10.1177/0956797611404083
http://pss.sagepub.com
Evelyn Barron1, Leigh M. Riby1, Joanna Greer1, and
Jonathan Smallwood2
1
Division of Psychology, Northumbria University, and 2Department of Social Neuroscience,
Max Planck Institute of Human Cognitive and Brain Sciences, Leipzig, Germany
Abstract
This study used event-related potentials to explore whether mind wandering (task-unrelated thought, or TUT) emerges through
general problems in distraction, deficits of task-relevant processing (the executive-function view), or a general reduction in
attention to external events regardless of their relevance (the decoupling hypothesis). Twenty-five participants performed
a visual oddball task, in which they were required to differentiate between a rare target stimulus (to measure task-relevant
processes), a rare novel stimulus (to measure distractor processing), and a frequent nontarget stimulus. TUT was measured
immediately following task performance using a validated retrospective measure. High levels of TUT were associated with a
reduction in cortical processing of task-relevant events and distractor stimuli. These data contradict the suggestion that mind
wandering is associated with distraction problems or specific deficits in task-relevant processes. Instead, the data are consistent
with the decoupling hypothesis: that TUT dampens the processing of sensory information irrespective of that information’s
task relevance.
Keywords
cognitive, event-related potential, attention, memory, mind wandering, P3a, P3b, P300, task-unrelated thought
Received 3/18/10; Revision accepted 1/2/11
A key challenge facing cognitive neuroscience is detailing
how thinking unfolds when unconstrained by an external task.
The initial impetus for such research came from the observation of a class of neural systems—now known as the default
network (Raichle et al., 2001)—that was unusually active during periods of rest relative to when a range of tasks were being
performed. The default mode has been linked to a wide range
of cognitive processes, such as mental-state attribution, autobiographical memory, and emotional responses (Spreng, Mar,
& Kim, 2009, for a meta-analysis), and these connections have
led to the consensus view that this network of structures
is important in unconstrained internal thought processes
(Buckner, Andrews-Hanna, & Schacter, 2008).
Since the initial observations, evidence has accumulated
that the default mode intermittently intrudes on task performance during periods of mind wandering. Periods of error or
lengthy response time have been linked to default processes
(Christoff, Gordon, Smallwood, Smith, & Schooler, 2009;
Weissman, Roberts, Visscher, & Woldorff, 2006). Similarly,
studies that have manipulated task demands to increase
task-unrelated thought (TUT; e.g., Mason et al., 2007) also
increased activity in several areas of the default network,
including the medial prefrontal cortex and the precuneus.
Finally, using experience sampling, Christoff et al. (2009)
observed that periods of TUT tended to recruit not only areas
of the default network but also areas of the executive-function
system (e.g., the anterior cingulate and the dorsolateral prefrontal cortex).
Although growing evidence suggests that mind wandering
involves an absence of attentional constraint to a task, it is
unclear how this process occurs. There are three views on this
subject. First, judging from the evidence of studies linking
mind wandering to states of distraction (e.g., ADHD; Shaw &
Giambra, 1993), it is conceivable that TUT is simply a general
failure to deal with distraction regardless of whether it arises
internally or externally. Following the distractibility hypothesis, TUT is associated with a heightened response to distractor
Corresponding Author:
Leigh M. Riby, Division of Psychology, Northumbria University,
Northumberland Building, Newcastle Upon Tyne, United Kingdom NE1 8ST
E-mail: leigh.riby@northumbria.ac.uk
597
The Effect of Mind Wandering on the P3a and P3b
events in a task. Second, it has been suggested that mind wandering is a failure in executive control (McVay & Kane, 2010);
this notion is based on the observation that TUT is associated
with errors on tasks requiring executive control (e.g., Smallwood, Baraciaia, Lowe, & Obonsawin, 2003; Smallwood
et al., 2004). In this executive-function view, TUT involves a
specific impairment in the processing of task-relevant events.
Third, mind wandering has been suggested to involve a state
of decoupled processing, in which attention becomes coupled
to an internal process and decoupled from perceptual information (Smallwood, 2010; Smallwood et al., 2003). This process
of perceptual decoupling is hypothesized to aid TUT because
it helps insulate an internal train of thought from the distracting influence of external perceptual information (see U. Frith
& Frith, 2003). Previous studies have shown that periods of
TUT do reduce the cortical processing of both task-relevant
and perceptual information (Kam et al., 2011; Smallwood,
Beach, Schooler, & Handy, 2008), and according to the decoupling hypothesis, TUT suppresses the response to external
events regardless of those events’ task relevance.
The goal of the current study was to adjudicate between the
distractibility, executive-function, and decoupling hypotheses
about the relationship between mind wandering and taskrelevant attention. We asked participants to perform an oddball task, in which a rare target stimulus (requiring a response)
was presented against a series of frequent background stimuli
to index target processing. A task-irrelevant event with the
same rare frequency as the target was also presented to index
distraction. To provide an index of ongoing attention, we measured the response that task events evoked in the brain (known
as event-related potentials, or ERPs).
In the paradigm of the oddball task, two ERP components
are generally observed. First, a large positive peak elicited at
approximately 300 ms to 500 ms over central-parietal sites and
known as the P3b is generated when participants attend to the
target stimuli. P3b amplitudes are believed to reflect the maintenance of a stimulus in working memory when the mental
representation of the stimulus context is updated (Donchin,
Kramer, & Wickens, 1986; Polich, 2003). Second, when participants process the distractor stimulus, an earlier deflection
with a more fronto-central distribution (known as the P3a) is
elicited. The P3a is thought to depend on frontal lobe functioning and reflects the capture of attention by rare distractor stimuli (Escera, Alho, Scrogher, & Winkler, 2000; Knight, 1997).
In addition to the varying scalp distributions and relation to
different task events, there are several sources of evidence that
the P3a and P3b index different but related aspects of sustained attention (see Polich, 2003, for a review). First, relative
to control subjects, the amplitude of the P3a increases and the
amplitude of the P3b decreases in participants with ADHD
(e.g., van Mourik, Oosterlaan, Heslenfeld, Konig, & Sergeant,
2007). Similarly, frontal lesions are associated with a reduction in P3a amplitude but have no effect on the magnitude of
P3b amplitude (Knight, 1984). Together, this evidence suggests that the amplitude of the P3a provides a measure of the
level of external distraction in a population. By contrast, the
amplitude of the P3b is closely linked to the allocation of
attention to a task. For example, dual-task situations often
reduce the amplitude of the P3b (for a review, see Polich,
2003), and successful memory for a stimulus is related to
increased P3b amplitude at encoding (Karis, Fabiani, &
Donchin, 1984). The amplitude of the P3b provides an index
of attention to task-relevant stimuli. It has been suggested that
the P3a and P3b reflect the separate processes of attentional
capture and task focus that in combination reflect the processes necessary for sustaining attention while performing a
task (Polich, 2003).
In the study reported here, participants completed a posttask measure of mind wandering after performing the oddball
task. Using these data, we tested the three different views of
mind wandering by exploring how individual differences in
TUT vary with the different measures of attention provided by
the ERPs. First, the hypothesis that mind wandering is simply
a general problem with distraction would suggest that TUT
involves a strong response to the rare distractors (i.e., a large
P3a amplitude). Second, the hypothesis that TUT involves
specific executive-function difficulties in maintaining task
processing (e.g., McVay & Kane, 2010) would predict a specific reduction in target processing (i.e., a reduction in P3b
amplitude). Finally, the hypothesis that TUT is simply a state
of internal focus would indicate that the ERPs to all events
decrease regardless of those events’ task relevance (i.e., a
reduction in both P3a and P3b amplitudes).
Previous studies have directly measured TUT using
experience-sampling probes; in the current study, we used a
retrospective self-report measure, the Dundee Stress State
Questionnaire (DSSQ; Matthews et al., 1999), which was
administered immediately after task completion. The DSSQ is
a validated measure of TUT experienced during a task and has
been used to reveal the relationship between mind wandering
and both mood (e.g., Smallwood, O’Connor, & Heim, 2005)
and sustained attention (Smallwood et al., 2004). There are
two advantages to measuring mind wandering in a retrospective manner: First, it ensures that participants are not aware of
the nature of the investigation while the critical data are
recorded; thus, this process provides a less biased indicator of
experience. Second, it allows the collection of time series EEG
data without the disruptions caused by experience sampling.
Method
Participants
Twenty-five right-handed adults participated in the study (16
female, 9 male; mean age = 27.84 years, SD = 8.79 years). All
had normal or corrected-to-normal vision and reported no neurological conditions that might affect performance. Ethical
approval was obtained from the Division of Psychology Ethics
Board at Northumbria University. All participants gave written informed consent.
598
Materials and procedure
The three-stimulus oddball task was presented using E-Prime
presentation software (Schneider, Eschman, & Zuccolotto,
2001) on a 17 1/2-in. monitor. Participants were instructed to
press the space bar on a standard keyboard in response to the
target stimulus and ignore all other stimuli. The target stimulus
(red circle, area = 12.6 cm2) appeared on 13% of trials, the standard stimulus (green square, area = 16 cm2) appeared on 74% of
trials, and the novel stimulus (blue square, area = 256 cm2)
appeared on 13% of trials. Participants completed a 10-trial
practice block. The testing phase consisted of 4 blocks of 150
trials each. Stimuli remained on screen for 100 ms, followed by
an interstimulus interval between 830 ms and 930 ms. (For further discussion of the oddball task, see Polich, 2003).
At the end of the testing session, participants completed the
DSSQ. Participants were asked about the type of thoughts they
experienced during the experiment. The questions were
divided into two factors that identified (a) the level of taskrelated interference (e.g., “I thought about how I should work
more carefully”) and (b) TUT (e.g., “I thought about something that happened earlier today”). Participants rated their
answers on a 5-point scale (never = 1, once = 2, a few times =
3, often = 4, very often = 5).
On the basis of their responses to the DSSQ, participants
were split into three groups: high TUT (n = 8; mean DSSQ
score = 20.5, SD = 3.93), medium TUT (n = 9; mean DSSQ
score = 15.63, SD = 0.71), and low TUT (n = 8; mean
DSSQ score = 10.88, SD = 2.23). We equated membership size
for the high- and low-TUT groups. The medium-TUT group
was created in order to be sure that participants in the high- and
low-TUT groups were only those individuals who displayed
extreme mind wandering and extreme task focus, respectively.
For that reason, no differences were expected between the
medium-TUT group and any other group.
ERP recording
EEGs were recorded from 32 channels using an electrode cap
(Biosemi, Amsterdam, The Netherlands). Electrode placement
was based on the international 10-20 system (Klem, Lüders,
Jaspers, & Elger, 1999). The montage included 4 midline sites
(Fz, Cz, Pz, Oz), 14 sites over the left hemisphere (FP1, AF3,
F3, F7, FC1, FC5, C3, T7, CP1, CP5, P3, P7, PO3, O1), and
14 sites over the right hemisphere (FP2, AF4, F4, F8,
FC2, FC6, C4, T8, CP2, CP6, P4, P8, PO4, O2). Additional
electrodes were placed on the left and right mastoid. All
EEG recordings were referenced to the linked mastoid
processes. To assess eye blink movement, we placed electrodes above and below the left eye to record the vertical
electrooculogram.
All signals were digitized at a rate of 2048 Hz, with a
recording epoch of 1,200 ms. Automatic eye blink correction,
artifact rejection (values outside the range of −75 µV to
+75 µV), and ERP averaging were carried out off-line using
Barron et al.
Neuroscan SCAN 4.3 software (Compumedics, El Paso, TX).
After eye blink correction and removal of trials with artifacts,
the remaining trials were used in the analysis of each TUT
group’s responses. For the frequent standard stimuli, there
were on average 99.9, 104.3, and 103.0 trials for the low-,
medium-, and high-TUT groups, respectively (an ANOVA
revealed a nonsignificant effect of group, p = .65). For the rare
target stimuli, there were on average 19.2, 18.4, and 18.6 trials
for the low-, medium-, and high-TUT groups, respectively
(nonsignificant effect of group, p = .65). For the rare novel
stimuli, there were on average 18.8, 18.8, and 18.7 trials for
the low-, medium-, and high-TUT groups, respectively (nonsignificant effect of group, p = .99).
Results and Discussion
As a result of the easy nature of the oddball task, hit rates demonstrated ceiling effects for all groups (> 97%). As expected,
no group difference in reaction time was found because of the
easy and repetitive nature of the task.
To confirm that the oddball task gave rise to the P3a and
P3b components central to our investigation, we plotted ERPs
across all participants for the standard stimuli, novel distractors, and target stimuli for selected Fz, Cz, and Pz electrode
sites (Fig. 1a). Figure 1b shows the scalp distributions of the
ERPs at the peak amplitudes of the P3a and P3b components
at Fz and Pz, respectively, as well as the central-frontal distribution for the P3a component and the parietal-central distribution for the P3b component. To capture these ERP components
of interest, we created narrow time windows by visually
inspecting the grand-average ERPs and considering the peak
amplitude for the P3a at Fz (374 ms) and the P3b at Pz
(398 ms). As a result, the average amplitudes were calculated
in the 330-ms to 440-ms range for the P3a and in the 360-ms to
470-ms range for the P3b. This method of defining components has been used in previous research (Roche, Garavan, Foxe,
& O’Mara, 2005). No differences across groups were observed
for latency.
To analyze ERPs, we targeted the scalp regions where previous research has shown that P3a and P3b are centered. Two
3-electrode clusters were created for each component. For
P3a, the focus was on the average of a frontal cluster (Fz, FC1,
FC2) and a central cluster (Cz, CP1, CP2). For P3b, the focus
was a central cluster (Cz, CP1, CP2) and a parietal cluster (Pz,
PO3, PO4). Because we were primarily concerned with the
effects of TUT, we entered task-related interference as a
covariate in the following analyses.
The differences in P3a amplitudes in response to novel distractor stimuli were analyzed in a 3 (TUT group: high, low) ×
2 (site: frontal, central) analysis of covariance (ANCOVA).
There was a main effect of group, F(1, 13) = 7.1, p < .05, ηp2 = .35 (low-TUT group: M = 11.8, high-TUT group: M = 5.4); the low-TUT group demonstrated greater P3a amplitude than the high-TUT group did. Figure 2 shows topographical scalp maps for P3a and P3b in the low- and high-TUT groups. 599 The Effect of Mind Wandering on the P3a and P3b a Target Frequent Novel Fz 7.5 Mean Amplitude (µV) b Stimulus Responses to Novel Distractors (P3a) P3a 0 +7.5 µV –7.5 0 250 500 750 1,000 Time (ms) Cz Mean Amplitude (µV) 7.5 Responses to Target Stimuli (P3b) 0 –7.5 0 250 500 750 0 µV 1,000 Time (ms) Pz Mean Amplitude (µV) 7.5 –7.5 µV P3b 0 –7.5 0 250 500 750 1,000 Time (ms) Fig. 1. Grand-average event-related potentials (ERPs) across all participants. Mean amplitude (a) for selected frontal (Fz), central (Cz), and parietal (Pz) electrode sites is shown as a function of stimulus type. The topographical maps (b) show the scalp distributions of the ERPs at the times of the peak P3a amplitude at Fz (374 ms) and the peak P3b amplitude at Pz (398 ms), highlighted with the arrows in (a). The difference in P3b amplitude was analyzed in a 2 (TUT group: high, low) × 2 (site: central, parietal) ANCOVA. Prior to analyses, one extreme value was removed after visual inspection of the box plots (an outlier was defined as > 1.5
box lengths below or above the box). For target stimuli, there
was a main effect of group, F(1, 12) = 9.2, p < .05, ηp2 = .43 (low-TUT group: M = 10.4, high-TUT group: M = 5.3); the low-TUT group exhibited greater P3b amplitude than the high-TUT group did. Our data revealed that TUT was associated with a reduction in orienting to and processing of both targets and distractors (a smaller P3a and P3b amplitude). It is important to note that 600 Barron et al. Low Task-Unrelated Thought High Task-Unrelated Thought Responses to Novel Distractors (P3a) +7.5 µV 0 µV Responses to Target Stimuli (P3b) –7.5 µV Fig. 2. Topographical maps showing the scalp distributions of the event-related potentials at the times of the peak P3a amplitude at Fz (374 ms) and the peak P3b amplitude at Pz (398 ms). Results are shown separately for the groups with high and low task-unrelated thought. we replicated the association between TUT and reduced P3b amplitude (Smallwood et al., 2008) using retrospective rather than experience-sampling measures. This approach provides confidence that our results are free of artifacts created by any specific method. Together, these data indicate that mind wandering suppresses the brain’s response to rare stimuli regardless of the stimuli’s task relevance. The absence of an increase in P3a amplitude associated with TUT rules out the possibility that mind wandering is simply a state of distraction, and the absence of a decrease only in the P3b amplitude is inconsistent with the executive-function view. Instead, these data are consistent with the decoupling hypothesis, which suggests that the suppression of processing of external stimuli helps to keep internal thought separate from the competing influence of the external world (e.g., U. Frith & Frith, 2003; Smilek, Carriere, & Cheyene, 2010). In addition to accounting for the current data, the decoupling hypothesis explains why spontaneous thought (an undeniably adaptive process) often leads to error. In order for the mind to focus in detail on the mental simulations inherent to TUT, attention must shift from the monitoring of the external environment. Although this decoupling process inevitably impairs concurrent external task processing (e.g., Smallwood & Schooler, 2006), it also helps shield an internal train of thought from the distractio... Purchase answer to see full attachment