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Attention Bias Modification (ABM) aims to modulate attentional biases, but questions remain about its efficacy and there may be new variants yet to explore. The current study tested effects of a novel version of ABM, predictive ABM (predABM), using visually neutral cues predicting the locations of future threatening and neutral stimuli that had a chance of appearing after a delay. Such effects could also help understand anticipatory attentional biases measured using cued Visual Probe Tasks. 102 participants completed the experiment online. We tested whether training Towards Threat versus Away from Threat contingencies on the predABM would cause subsequent attentional biases towards versus away from threat versus neutral stimuli, respectively. Participants were randomly assigned and compared on attentional bias measured via a post-training Dot-Probe task. A significant difference was found between the attentional bias in the Towards Threat versus Away from Threat group. The training contingencies induced effects on bias in the expected direction, although the bias in each group separately did not reach significance. Stronger effects may require multiple training sessions. Nevertheless, the primary test confirmed the hypothesis, showing that the predABM is a potentially interesting variant of ABM. Theoretically, the results show that automatization may involve the process of selecting the outcome of a cognitive response, rather than a simple stimulus-response association. Training based on contingencies involving predicted stimuli affect subsequent attentional measures and could be of interest in future clinical studies.
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Running head: Predictive ABM 1
In press at Europe’s Journal of Psychology.
Predictive Attentional Bias Modification Induces Stimulus-Evoked Attentional Bias for Threat
Thomas E. Gladwin a*, Martin Möbius b, Eni S. Becker b
a. Department of Psychology & Counselling, University of Chichester, Chichester, United
Kingdom
b. Behavioural Science Institute, Radboud University Nijmegen, Nijmegen, The Netherlands
* Corresponding author: Thomas E. Gladwin, Address: Department of Psychology &
Counselling, University of Chichester, College Lane, PO19 6LE Chichester, United Kingdom.
Tel.: +44 (0)1243 816222; fax: +44 (0)1243 816080. Email: thomas.gladwin@gmail.com.
Predictive ABM 2
Attention Bias Modification (ABM) aims to modulate attentional biases, but questions remain
about its efficacy and there may be new variants yet to explore. The current study tested effects
of a novel version of ABM, predictive ABM (predABM), using visually neutral cues predicting
the locations of future threatening and neutral stimuli that had a chance of appearing after a
delay. Such effects could also help understand anticipatory attentional biases measured using
cued Visual Probe Tasks. 102 participants completed the experiment online. We tested whether
training Towards Threat versus Away from Threat contingencies on the predABM would cause
subsequent attentional biases towards versus away from threat versus neutral stimuli,
respectively. Participants were randomly assigned and compared on attentional bias measured
via a post-training Dot-Probe task. A significant difference was found between the attentional
bias in the Towards Threat versus Away from Threat group. The training contingencies induced
effects on bias in the expected direction, although the bias in each group separately did not reach
significance. Stronger effects may require multiple training sessions. Nevertheless, the primary
test confirmed the hypothesis, showing that the predABM is a potentially interesting variant of
ABM. Theoretically, the results show that automatization may involve the process of selecting
the outcome of a cognitive response, rather than a simple stimulus-response association. Training
based on contingencies involving predicted stimuli affect subsequent attentional measures and
could be of interest in future clinical studies.
Keywords: Attentional Bias Modification; Attention; Threat; Predictive cues; attention bias
Predictive ABM 3
Attentional biases are automatic processes that influence the selection of information for further
processing (Cisler & Koster, 2010; Kane & Engle, 2003). Spatial attentional biases, involving
the direction of attention to the location of salient cues, can be measured via dot-probe or visual
probe tasks (VPTs) (MacLeod, Mathews, & Tata, 1986). Faster responses to probe stimuli
appearing at the location of certain cue categories provides an implicit measure of bias (Cisler &
Koster, 2010; Mogg & Bradley, 2016; Notebaert, Crombez, Van Damme, De Houwer, &
Theeuwes, 2011). An interesting application of research into attentional biases is their use in
training paradigms, termed Attentional Bias Modification, ABM (MacLeod & Mathews, 2012).
ABM aims to reverse a putatively harmful attentional bias in order to change associated behavior
or symptoms, such as spider phobia (Luo et al., 2015), depression (Ferrari, Möbius, van Opdorp,
Becker, & Rinck, 2016; Wells & Beevers, 2010), addiction (Schoenmakers et al., 2010) and
PTSD (Kuckertz et al., 2014). Opinions are strongly divided, however, on the efficacy of ABM,
and it appears that, at the least, its efficacy is conditional on moderating factors (Clarke,
Notebaert, & MacLeod, 2014; Cristea, Kok, & Cuijpers, 2015; Gladwin, Wiers, & Wiers, 2016).
Some recent studies have raised interesting possibilities potentially relevant to ABM. First, cued
Visual Probe Tasks (cVPTs) have been developed to the aim of studying outcome-related
attentional biases (Gladwin, 2016). In the cVPT, instead of presenting salient cues and
determining how they affect attention, visually neutral predictive cues are used. The predictive
value is caused by Picture trials, in which the predictive cues are replaced by an actual exemplar
from the category associated with them, e.g., threat versus neutral. Assessment of the bias is
based on Probe trials, on which instead of the exemplar a probe stimulus requiring a response is
presented. Thus, performance is not dependent on a given trial’s specific exemplars, but on the
predicted categories of stimuli that could have been presented. Possibly partly due to this
Predictive ABM 4
removal of a source of variability, the cVPT has been found to have good reliability (Gladwin,
2018; Gladwin, Möbius, Mcloughlin, & Tyndall, 2018). A theoretical question is what is causing
the bias. The task design implies that the cues serve as predictive stimuli for possible outcomes,
or as a kind of prime (Kristjánsson & Ásgeirsson, 2019), due to some form of learning process
(Failing & Theeuwes, 2018). However, it is conceivable that the visual features of the cues
themselves acquire salience, as opposed to the theoretically motivating idea that predictive
mechanisms determining the outcome of attentional shifting would result in the bias (Gladwin &
Figner, 2014; Gladwin, Figner, Crone, & Wiers, 2011). Using a cVPT as an ABM task could
provide evidence to help address this issue: if using a cVPT to train participants’ attention
towards or away from an outcome indeed results in a bias involving the stimulus categories,
rather than the specific cues used during training, this would suggest that the cVPT involves
outcome-related processes rather than cue-specific learning.
Second, positive effects have been reported of what would usually be considered control
conditions of ABM, in which no specific bias was induced but probes had a random relationship
with emotional cues (Badura-Brack et al., 2015; Gladwin, 2017; Khanna et al., 2015). It has been
suggested that whether a training variant makes emotional cues relevant or irrelevant to the
training task may be an important factor in ABM (Gladwin, 2017). In usual sham conditions,
emotional cues are irrelevant to the task and thus participants could be learning to ignore such
stimuli when confronted by them. For instance, in a control condition of a training based on the
Dot-Probe task, the location of emotional cues is non-predictive of the location of probe stimuli.
In active training conditions, while the aim is to affect the direction of attentional biases, it is
also usually the case that emotional information is relevant. In the Dot-Probe example, if probe
locations are contingent on the location of emotional cues, then that makes those cues relevant.
Predictive ABM 5
This could induce a “salience side-effect” in some designs: Participants may be learning to pay
attention to the location of task-relevant emotional stimuli, even if the direction of attentional
shifting is away from them. This could add noise and complexity to results, with different
processes being affected in uncontrolled ways during training. In line with the idea that salience
is an important factor in training, Approach-Avoidance Retraining for alcohol addiction reduced
amygdala reactivity to alcohol stimuli (Wiers et al., 2015), which was interpreted as a neural
signature of salience reduction.
The goal of the current study was to explore a novel form of ABM hypothesized to avoid this
salience side-effect, which simultaneously may help understand the nature of the anticipatory
spatial attentional bias. A training version of the cued Visual Probe Task was used, in which the
probability of the location of probes relative to the outcome of cues is manipulated. This was
termed predictive Attentional Bias Modification (predABM). To test whether this kind of
predictive-cue training would affect attentional bias towards or away from actually presented
emotional stimuli, a Towards Threat training condition and an Away from Threat training
condition were compared using a normal Dot-Probe task post-training. As the delay between
emotional cues and probe stimuli in Dot-Probe tasks is known to be potentially time-dependent
(Mogg & Bradley, 2006; Noël et al., 2006), multiple cue-stimulus intervals were used. Note that
due to the experimentally controlled random allocation of participants to groups, this post-only
design allows valid statistical inference to be done: Statistically significant differences between
groups on the post-test measures can be interpreted as an effect of training, with only the usual
possibility of a false positive (which would also be present when analyzing difference scores).
Beyond this basic point on the validity of randomized post-only designs, there are advantages
and disadvantages to using a post-only versus pre-post design discussed further in the Discussion
Predictive ABM 6
section. We hypothesized that training to shift attention towards versus away from the location of
predicted upcoming threatening facial stimuli would affect attentional bias towards or away from
such stimuli on the post-test stimulus-evoked attentional bias.
Methods
Participants
Participants were recruited from a student population and received study credits for completing
the study. Participants gave informed consent and the study was approved by the local ethics
review board. The study was performed online. 102 participants completed the experiment (88%
female, 22 % male; mean age 20, SD = 0.29). The study was performed fully online.
Materials
Questionnaires
The following questionnaires were used as the set of covariates to reduce training-unrelated
variance on the post-test Dot-Probe task. The aim was to use a range of questionnaires
concerning individual differences, which could affect attentional biases involving threat:
Anxiety, post-traumatic stress disorder, depression, and aggression. The questionnaire on
depression was unfortunately lost due to a technical error. Note that because the between-subject
factor of training was randomly assigned it was stochastically independent from the covariates,
providing an appropriate situation for the use of analysis of covariance.
The TSQ (Brewin et al., 2002) was used to estimate the presence of post-traumatic stress
symptoms. Participants were asked to indicate for each of the 10 items, whether they experienced
the described symptom (at least twice) in the past week or not. The total score ranges between 0
and 10, while higher scores represent the presence of more PTSD symptoms.
Predictive ABM 7
To assess an individual’s disposition to aggressive behavior we used the Buss-Perry Aggression
Questionnaire (Buss & Perry, 1992). This questionnaire consists of four subscales; I) physical
aggression, II) verbal aggression, III) anger, IV) hostility. On 29 items, participants had to
indicate how characteristic each of the described behaviors was in describing them (1 = totally
uncharacteristic, 5 = totally characteristic), with higher scores reflecting greater disposition for
aggressive behavior.
The short version of the STAI, STAI-6 (Marteau & Bekker, 1992) was used to measure changes
in individual state anxiety. This scale comprises 6 statements to be rated on a 4-point Likert scale
(1 = not at all, 4 = very much). We calculated a weighted sum score in which responses on the
three items involving positive feelings were multiplied by -1. Higher sum scores represent higher
state anxiety levels.
The predABM Training Task
The predABM task was administered to modify attentional processing to threatening stimuli. The
faces of 16 characters, each with an angry and a neutral expression, from the BESST (Thoma,
Soria Bauser, & Suchan, 2013) were used. The task consisted of 24 blocks of 24 trials each. All
trials started with a fixation cross (300, 400, or 500 ms) followed by the appearance of two
initially neutral cues one above the other, each of which consisted of a horizontal row of five
differently colored typographical symbols (e.g., 5 blue crosses). After every 8 blocks, a different
pair of cues was used. The aim of this was to reduce the chance that participants would only
learn a contingency involving a particular pair of cue-stimuli, rather than the outcome-
contingency which was consistent over the varying cue pairs. The cues were presented for a CSI
of 200 or 1200 ms, with equal probability, so as not to induce CSI-related differences with the
dot-probe assessment. The essential feature of the task is that there were two trial-types, which
Predictive ABM 8
were presented with equal probability; On half of the trials (“picture trials”), one of the cues
(randomized per subject) was replaced by a picture of an angry face, and the other by a picture of
a neutral face. On the other half of the trials (“probe trials”), the trial continued as in a normal
dot-probe task, with the probe-distractor pair replacing the cues. The probe stimulus was an
arrow-like symbol pointing to the left < or right >. The distractor stimulus was a /\ or \/. The
distractors were used to make it more difficult to respond without focusing attention on the
correct location, since they were visually similar to the probe stimuli. Participants were
instructed to press the corresponding left or right key (F or J on the keyboard) within 800 ms.
Correct answers were followed by the word “Good” (“Goed”, in Dutch) in green, while incorrect
answers were followed by the word “Wrong” (“Fout”, in Dutch) in red. When no response was
registered the term “Too late” (“Te laat”, in Dutch) was presented in red. This feedback
remained on the screen for 500 ms. Essentially, the picture trials were designed to train an
association between cues and the possible appearance of angry versus neutral pictures at their
location, and the probe trials provided an assessment of effects of that association.
In both groups, cues consistently predicted the locations of threat and neutral stimuli. They only
differed in their relationship to where probe stimuli would appear. In the Towards Threat group,
90% of probes appeared at the location where an angry face was predicted to appear. In the
Away from Threat group, 90% of probes appeared at the location where a neutral face was
predicted to appear.
Dot-probe Task
For the dot-probe task a subset of 16 faces from the BESST was used, different from the subset
used during training. The task consisted of 4 blocks of 24 trials. Each trial started with a fixation
cross (300, 400, or 500 ms) followed by the presentation of an angry and a neutral face, one
Predictive ABM 9
above the other, for 200 or 1200 ms, with equal probability. Trials then continued precisely as in
the probe trials in the predABM task described above: a probe-distractor pair replaced the cues,
to which participants had 800 ms to respond, followed by feedback.
Procedure
Individuals who chose to participate were guided to the web page for the experiment via a Sona
Systems participant pool. They viewed a page with participant information and gave informed
consent via a button to continue. The next page briefly repeated the most essential information
and gave tips for correct performance of the tasks, e.g., turning off phones, maximizing the
browser window, and closing other programs and browser tabs. Participants filled in
questionnaires and then performed the predABM and Dot-Probe task. Participants were assigned
to a training condition at random. In the same session, participants also completed questionnaires
and tasks unrelated to the current study.
Statistical Analyses
First, within-subject repeated measures ANOVAs were performed per training group to
determine whether each training condition had the expected effects on behavior during training.
For each training condition (Towards Threat condition and Away from Threat) it was tested
whether the respective bias was induced during the training (within-subject factors Probe
Location and CSI), although of course these tests do not indicate whether such biases involved
the predicted outcome as opposed to the initially visually neutral cues. Probe Location refers to
whether the probe appeared at the location of the Threat or Neutral cue. Dependent variables
were median RT (the median was used to reduce the impact of outliers, without needing to
specify an arbitrary cut-off for outliers as would be necessary with the mean) and mean accuracy,
Predictive ABM 10
calculated for all probe trials. The questionnaire data (i.e., age, sex, Buss-Perry subscale scores,
TSQ and STAI-6) were included as covariates.
Second, and most essentially, effects of the attentional manipulation on the Dot-Probe task were
tested using mixed design ANCOVAs, with within-subject factors Probe Location (Neutral,
Threat) and CSI (200 ms, 1200 ms) and between-subject factor Training condition. The
questionnaire scores were included as covariates. It was tested whether the training conditions
(Toward Threat versus Away from Threat) induced reversed attentional biases on the Dot-Probe
task. Dependent variables were median reaction time and mean accuracy.
Results
Table 1 shows descriptive statistics for the questionnaire data. 54 participants were assigned to
the Away from Threat group and 48 to the Towards Threat group.
Predictive ABM 11
Table 1. Demographics and Questionnaire Data
Score
Away from
Threat
Towards
Threat
Sex
78%
92%
Age
19.8 (2.06)
19.5 (1.44)
BP - Physical
Aggression
19.6 (5.66)
16.6 (4.99)
BP - Verbal
Aggression
17.4 (3.76)
15.6 (2.82)
BP - Anger
16.9 (5.45)
16.9 (6.38)
BP - Hostility
20.1 (8.15)
17.9 (8.1)
Trauma Screening
Questionnaire
3.02 (2.94)
3.04 (2.8)
STAI, pre-training
-4.11 (2.93)
-3.83 (3.3)
STAI, post-training
-3.15 (3.11)
-3.21 (3.05)
Note. The values are percentages (for Sex, percentage female) and mean values, with standard
deviations in parentheses. BP represents the Buss-Perry questionnaire. The STAI scores were
calculated as the sum of negative minus the sum of positive items.
Predictive ABM 12
Performance Data on the predABM During Training Conditions
Table 2 shows descriptive statistics for the predABM. In the Away From Threat group, responses
to probes on Threat locations were slower than responses to probes on Neutral locations (F(1,
53) = 5.67, p = .021, ηp2 = .097). An effect of CSI was found (F(1, 53) = 66.53, p < .001, ηp2 =
.56) due to slower responses at the long (1200 ms) versus short (200 ms) CSI. In the Towards
Threat group, responses to probes on Threat locations were faster than responses to probes on
Neutral locations (F(1, 47) = 4.55, p = .038, ηp2 = .09). An effect of CSI was found (F(1, 47) =
24.68, p < .001, ηp2 = .34) due to slower responses at the long versus short CSI.
Table 2. Performance Data on the predABM
Measure
Probe location
CSI
Towards Threat
Reaction time [ms]
Neutral
200 ms
536 (77)
1200 ms
553 (58)
Angry
200 ms
521 (52)
1200 ms
551 (58)
Accuracy
Neutral
200 ms
0.96 (0.066)
1200 ms
0.97 (0.045)
Angry
200 ms
0.98 (0.017)
1200 ms
0.98 (0.016)
Note. Means and standard deviations for reaction time and accuracy on the predABM task.
Measure refers to performance measure, i.e., reaction time and accuracy. Probe location refers to
the location where the probe stimulus appeared: The location of the cue where Neutral faces
Predictive ABM 13
versus the cue where Angry faces would appear on non-probe trials. CSI refers to Cue-Stimulus
Interval, the delay between cue presentation and probe presentation.
Training effects on the Dot-Probe Task
Descriptive statistics for the Dot-Probe Task are shown in Table 3.
Table 3. Performance Data on the Dot-Probe task
Measure
Probe location
CSI
Towards Threat
Reaction time [ms]
Neutral
200 ms
502 (55)
1200 ms
511 (50)
Angry
200 ms
497 (53)
1200 ms
511 (52)
Accuracy
Neutral
200 ms
0.95 (0.047)
1200 ms
0.96 (0.042)
Angry
200 ms
0.97 (0.045)
1200 ms
0.97 (0.04)
1200 ms
97 (48.1)
Note. Means and standard deviations for reaction time and accuracy on the Dot-Probe task.
Measure refers to the performance measures reaction time and accuracy. Probe location refers to
the location where the probe stimulus appeared: The location of the cue where Neutral faces
versus the cue where Angry faces would appear on non-probe trials. CSI refers to Cue-Stimulus
Interval, the delay between cue presentation and probe presentation. Away from Threat and
Toward Threat refer to the training conditions.
Predictive ABM 14
On RT, the hypothesized effect was found of Group x Probe Location (F(1, 91) = 4.75, p = .033,
ηp2 = .05), shown in Figure 1. The Towards Threat group had a bias towards threat relative to the
Away from Threat group. The direction of the effect of Probe Location was reversed as expected
between the groups, with shorter RTs on the Neutral than on the Threat location in the Away
from Threat group, and shorter RTs on the Threat than on the Neutral location in the Towards
Threat group. We do note that the magnitudes of the biases were small however, and the main
effect of Probe Location did not reach significance in either group separately, despite the
significant Group x Probe Location interaction. Further, an effect of CSI was found (F(1, 91) =
7.95, p = .0060, ηp2 = .08) due to slower responses at the long versus short CSI. No effects on
accuracy were found.
Figure 1. Post-training RT Bias per Training Group
Predictive ABM 15
Note. The Figure shows the attentional bias, RT for Angry minus RT for Neutral, following the
Towards Threat and Away from Threat training. The groups showed a relative shift in bias as
expected.
Discussion
The aim of the current study was to provide a first test of the effects of predABM, a novel
version of ABM using predictive cues. Rather than being trained to direct attention towards or
away from threatening stimuli, participants were trained to direct attention towards or away from
locations based on cues predicting where a threatening stimulus could appear. Thus, the training
did not involve a direct stimulus-response association between stimuli in the threat category and
attentional shifting, a feature of usual training tasks that could result in unexpected effects
involving salience. The question was whether training using predictive cues would be able to
affect stimulus-evoked attentional bias.
Performance data during training blocks showed that participants responded to the outcome-
based task contingencies as expected. Responses were faster to probes appearing at the trained
location. Note that this could reflect either an association involving the specific predictive cues
or an association involving the stimulus category predicted by the cues initial cVPT studies
(Gladwin, 2016; Gladwin et al., 2018; Gladwin & Vink, 2018) were not able to distinguish
between such possibilities concerning underlying mechanisms. Whether the latter, outcome-
focused kind of association occurred was tested by the post-training generalization to the Dot-
Probe task described below. Training effects were in fact found on the Dot-Probe task presented
after the training. The Towards Threat group and Away from Threat group showed the expected
relative decrease and increase, respectively, in reaction time for probes on Angry versus Neutral
locations. Thus, the attentional response to emotional stimuli was changed via the stimulus
Predictive ABM 16
categories of the outcomes of the predictive cues during training. Essentially, therefore, it was
not the case that participants only learned to shift attention towards or away from the specific
predictive cues. The results show that training involved the stimulus categories that were
predicted by the initially visually neutral cues, even though the emotional stimuli never appeared
on the same trial as the probe stimuli.
The results thus provide first support for the potential use of predABM. Although concern for
salience side-effects in ABM, due to the informativeness of emotional cues, is as yet a recent
development, the predABM provides a method that appears to be able to address this potential
problem. However, we note that the potential training value of using an anticipatory attentional
bias based on upcoming emotional stimuli, rather than responses to already-presented emotional
stimuli, does not only depend on the salience side-effect. Anticipatory or preparatory processes
related to emotional stimuli could be an interesting target for training in themselves, as this may
have different effects from ABM involving stimulus-evoked processes. Further, a feature of
predictive cues is that a wide range of possible stimuli can be associated with single conditioned
cue. An interesting direction for future research is whether this may improve generalization to
other stimuli, since attention is directed towards an abstract category rather than a specific set of
stimuli.
A limitation of the current study is that only a single session was used, while effects of multiple
sessions are likely most relevant for potential clinical applications and could provide larger effect
sizes. However, the current results provide a proof-of-principle that the outcome-focused cued
training task was able to change attentional processes related to the predicted stimulus category.
A further limitation is that the population involved a sample of students. Patient groups are
clearly an important target population, and it remains to be determined whether non-student
Predictive ABM 17
samples respond to the training contingencies in the same way. A concern with training methods,
especially for future use in clinical populations, is their impact on patients. The current study was
also limited in its use of computer-generated angry faces as emotional stimuli: It cannot be
assumed that the effects will generalize to other stimulus categories. Different results might be
obtained in future research with, for example, stimuli representing physical threat, or verbal
stimuli designed to evoke shame or guilt. Concerning the design, only a post-training assessment
task for attentional bias was used, similarly to analyses involving post-training effects in
previous studies (e.g., Gladwin et al., 2015). We note that, while pre-post designs have the
advantage of providing a pre-training measurement, the logic of a post-training experimental
design, with random assignment, is equally valid statistically: The chance of the groups having
training-independent differences in attentional bias at post-test at random is the same as the
chance of groups having training-independent changes in attentional bias from pre- to post-test at
random. Further, a post-test design avoids test-retest effects, which could be a source of noise.
There may also be theoretical reasons to expect effects to be caused on post-test states, rather
than on pre-post shifts. Thus, while arguments can be made for either design, there is no reason
to consider the lack of a pre-test a particular threat to the validity of conclusions drawn from the
results. Finally, more work is needed to further explore the nature of training effects.
Psychophysiology or neuroimaging methods could help test hypotheses on which underlying
processes are affected, such as cue reactivity measures indicating changes in salience (Wiers et
al., 2015) or attentional control (Eldar & Bar-Haim, 2010).
In conclusion, training to shift their attention based on the expected stimulus-locations induces
changes in attentional biases. The use of predictive cues in training may open interesting
directions for further study.
Predictive ABM 18
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of control and motivation. Developmental Cognitive Neuroscience, 1(4), 364376.
https://doi.org/10.1016/j.dcn.2011.06.008
Gladwin, T. E., Möbius, M., Mcloughlin, S., & Tyndall, I. (2018). Anticipatory versus reactive spatial
attentional bias to threat. British Journal of Psychology. https://doi.org/10.1111/bjop.12309
Gladwin, T. E., Rinck, M., Eberl, C., Becker, E. S., Lindenmeyer, J., & Wiers, R. W. (2015). Mediation of
Cognitive Bias Modification for alcohol addiction via stimulus-specific alcohol avoidance
association. Alcoholism, Clinical and Experimental Research, 39(1), 101107.
https://doi.org/10.1111/acer.12602
Gladwin, T. E., & Vink, M. (2018). Alcohol-related attentional bias variability and conflicting automatic
associations. Journal of Experimental Psychopathology, 9(2). https://doi.org/10.5127/jep.062317
Gladwin, T. E., Wiers, C. E., & Wiers, R. W. (2016). Cognitive neuroscience of cognitive retraining for
addiction medicine: From mediating mechanisms to questions of efficacy. In Progress in Brain
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contributions of goal neglect, response competition, and task set to Stroop interference. Journal of
Experimental Psychology. General, 132(1), 4770. Retrieved from
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Wilson, T. W. (2015). Attention training normalises combat-related post-traumatic stress disorder
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fearful individuals. Behaviour Research and Therapy, 44(9), 12411250.
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Time course of attention for alcohol cues in abstinent alcoholic patients: the role of initial
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Schoenmakers, T. M., de Bruin, M., Lux, I. F. M., Goertz, A. G., Van Kerkhof, D. H. A. T., & Wiers, R. W.
(2010). Clinical effectiveness of attentional bias modification training in abstinent alcoholic
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Predictive ABM 21
Author bio statements
Dr. Thomas E. Gladwin is an experimental psychologist who studies the cognitive and neural processes
underlying motivation, emotion, and self-regulation. He works from (and on) the broad theoretical
perspective of dual-process models and uses a variety of behavioral and cognitive neuroscience methods.
This research is ultimately aimed at clinical applications using computerized Cognitive Bias Modification
training methods.
Dr. Martin Möbius researches the application of cognitive neuroscience methods to experimental forms of
mental health therapy, for instance using eye tracking or Transcranial Magnetic Stimulation to affect
attentional biases. He also has an interest in implicit measures and their conversion to intervention variants,
such as Interpretation Bias Modification.
Prof. Eni S. Becker investigates the development and treatment of anxiety disorders, such as specific
phobias, social phobia, panic- and obsessive-compulsive disorder. She mainly focuses on cognitive processes
(memory, attention, interpretation), considering these appear to play an important role in the development
of anxiety disorders. She is very much interested in approach and avoidance tendencies, studying them in
different disorders and contexts. One of her recent research interest is the change of cognitive biases, the
training of automatic tendencies. She is doing research on Approach-Avoidance trainings (for Anxiety but
also depression and substance abuse) as well as attention trainings.
Acknowledgments
None.
... Essentially, any bias on such trials is not stimulus-driven in the sense of being evoked by actually presented salient stimuli; rather, the predictive value of the cues produces an "anticipatory" attentional bias. Support for an interpretation in terms of predictive processes, rather than merely the acquisition of salience by visual features of the cues, has thus far been provided for threat stimuli (Gladwin, Möbius, & Becker, 2019). The anticipatory attentional bias towards alcohol has been shown to be correlated with risky drinking in two previous studies (Gladwin, 2019;Gladwin & Vink, 2018). ...
... This suggests that processes related to risky drinking are reflected in one particular cue acquiring salience due to its prediction of alcohol-related stimuli. Alcohol-related anticipatory attentional bias thus appears to involve different processes than threatrelated anticipatory attentional bias, which does appear to reflect processing related to the predicted outcomes rather than the acquisition of salience by a particular cue (Gladwin, Figner, et al., 2019;Gladwin, Möbius, et al., 2019). ...
Article
Temporary free access: https://authors.elsevier.com/a/1aDWt_6zzLsDQX Previous studies suggest that cues predicting the outcome of attentional shifts provide a measure of anticipatory alcohol-related attentional bias that is correlated with risky drinking and has high reliability. However, this is complicated by potential contributions of visual features of cues to reliability, unrelated to their predictive value. Further, little is known of the sensitivity of the bias to variations in cue-outcome mapping manipulations, limiting our theoretical and methodological knowledge: Does the bias robustly follow varying cue-outcome mappings, or are there automatic cue-related associative processes involved? The current studies aimed to address these issues. Participants performed variations of the cued Visual Probe Task (cVPT) in which cues were non-predictive; in which there were multiple cue pairs, used simultaneously and serially; and in which the cue-outcome mapping was reversed. The major findings were, first, that previously found reliability cannot be attributed to aspects of the cues not related to outcome-prediction; second, that reliability of the bias does not survive deviations from a simple, consistent cue-outcome mapping; third, that all predictive versions of the task showed a bias towards alcohol; fourth, that the bias did not simply follow awareness of the cue-outcome mapping; and finally, that only in the case of simultaneous multiple cue pairs, an association with risky drinking was replicated. The results provide support for the reliability of the anticipatory attentional bias for alcohol, suggest that relatively persistent associative processes underlie the bias in the alcohol context, and provide a foundation for future work using the cVPT.
... Study showed that smiles can express not only relaxation and pleasure, but also amity and acceptance to large extent and even willingness to interact. On the other hand, angry face represents more information of being rejected and negation, standing for a threat [11]. ...
... Besides, the Cyberball task could not cause variance between positive emotions (t (1, 49) � 1.53, p � 0.13, cohen's d � 0.428) and negative emotions (t (1, 49) � -1.57, p � 0.12, cohend's � −0.440). [11], data which was under 200 ms and above 2000 ms and extreme data which was above ± standard deviation were eliminated. Using the trait thwarting need for relatedness as covariate, the analysis of covariance with 2 (group of state relatedness need thwarting, control group) ×2 (happy; neutral face pairs, anger; neutral face pairs) with slope homogeneity test resulted in that interaction effects among all variables and the trait thwarting need for relatedness were not significant. ...
Article
Full-text available
The present study aimed to examine attentional biases’ components and processes toward the interpersonal evaluation information among athletes after state thwarting need for relatedness. 51 athletes completed a visual dot-probe task while their eye-movements were tracking. Results indicated athletes showed different attentional bias pattern. Acceptance information is early orientation (directional bias); early acceleration detection; sustained to late attention maintenance (difficulty in disengaging). Rejection information is early orientation (directional bias); early accelerated detection; continuous attention to maintenance (attention avoidance); late attention to maintenance (difficulty in disengaging). That is to say, they had motivation to seek acceptance toward the accepted interpersonal evaluation information and to avoid rejection information toward the rejected one. Therefore, it is suggested that the coaches provide more interpersonal communicating opportunities, so as to help them to restore their demands toward interpersonal communication, and provide the customized attentional bias trainings to improve their coping response after state thwarted need for relatedness.
... Accordingly, a few authors have suggested that sham training actively trains equal attention to substance-relevant and neutral stimuli and thereby may affect control over attention for substance-related stimuli (e.g., Schoenmakers et al., 2010;Badura-Brack et al., 2015;Khanna et al., 2016). Others have suggested that sham training serves to train participants to ignore emotional stimuli when confronted with them (Gladwin, 2017;Gladwin et al., 2019). In line with these ideas, the sham training protocol has sometimes been reconceptualized and renamed as "attentional control training, " and viewed as a more top-down goal-directed process (Gladwin, 2017). ...
... Further studies addressed the concern that systematic between-subject variance associated with individual differences related to the visual characteristics of the predictive cues might account for the high reliability (Gladwin, Banic, Figner, & Vink, 2020;). An attentional bias modification training study using a training variant of the predVPT supported the interpretation that the bias involved anticipatory processes rather than merely conditioning of the initially neutral cues (Gladwin, Möbius, & Becker, 2019). ...
Preprint
Full-text available
Concerns have been raised about the low reliability of measurements of spatial attentional bias via RT differences in dot-probe tasks. The anticipatory form of the bias, directed towards predicted future stimuli, appears to have relatively good reliability, reaching around .70. However, studies thus far have not attempted to experimentally control task-related influence on bias, which could further improve reliability. Evoking top-down versus bottom-up conflict may furthermore reveal associations with individual differences related to mental health. In the current study, a sample of 143 participants performed a predictive Visual Probe Task (predVPT) with angry and neutral face stimuli online. In this task, an automatic bias is induced via visually neutral cues that predict the location of an upcoming angry face. A task-relevant bias was induced via blockwise shifts in the likely location of target stimuli. The bias score resulting from these factors was calculated as RTs to target stimuli at locations of predicted but not actually presented angry versus neutral faces. Correlations were tested with anxiety, depression, self-esteem and aggression scales. An overall bias towards threat was found with a split-half reliability of.90, and .89 after outlier removal. Avoidance of threat in blocks with a task-relevant bias away from threat was correlated with anxiety, with correction for multiple testing. The same relationship was nominally significant for depression and low self-esteem. In conclusion, we showed high reliability of spatial attentional bias that was related to anxiety.
... This may be due to use of multiple cue-probe intervals in previous work, reducing the number of trials per interval and possibly introducing a source of noise. Finally, in a training study (Gladwin, Möbius, & Becker, 2019), it was found that performing a cVPT that was designed to train attention towards versus away from the predicted threat category induced a stimulus-evoked bias in the trained direction. This suggests that the cVPT for threat indeed involves outcome-focused processes; otherwise, the training would merely have affected responses to the particular predictive cues used during training, and would not have affected biases involving the predicted stimulus categories. ...
Article
Cues that predict the future location of emotional stimuli may evoke an anticipatory form of automatic attentional bias. The reliability of this bias towards threat is uncertain: experimental design may need to be optimized or individual differences may simply be relatively noisy in the general population. The current study therefore aimed to determine the split-half reliability of the bias, in a design with fewer factors and more trials than in previous work. A sample of 63 participants was used for analysis, who performed the cued Visual Probe Task online, which aims to measure an anticipatory attentional bias. The overall bias towards threat was tested and split-half reliability was calculated over even and odd blocks. Results showed a significant bias towards threat and a reliability of around 0.7. The results support systematic individual differences in anticipatory attentional bias and demonstrate that RT-based bias scores, with online data collection, can be reliable.
... responses such as attentional shifts. Evidence that this outcome-focused automatic process does indeed underlie the anticipatory bias was provided by a training study: training participants to direct attention towards versus away from a cued salient stimulus category, using a predictive form of Attentional Bias Modification, was found to result in a subsequent stimulus-evoked bias (Gladwin, Möbius, & Becker, 2019). That is, performing a training version of the cVPT affected processes related to the predicted stimulus categories, and not just the conditioned cues. ...
Article
Concerns have been raised about the reliability of dot-probe tasks. The cued Visual Probe Task (cVPT) uses cues predicting locations of emotional stimuli, which appears to improve reliability. However, cVPT reliability could be affected by individual differences involving cue features. Here, we assessed specifically anticipatory reliability. Further, trial-to-trial carryover effects, previously found for stimulus-evoked biases, were tested. 82 participants were analysed, who performed an online procedure including a reversal of the cue mapping. Predicted stimulus categories were neutral and angry faces. Cue-Stimulus Intervals of 400 and 1000 ms were used. An overall anticipatory attentional bias, in terms of RT difference scores, towards threat was found. Reliability was around .4, similar to previous results despite the mapping reversal procedure. Carryover effects were found with a similar pattern as for non-cued threat-evoked bias. The results confirm a reasonably reliable outcome-focused bias towards threat, showing similar carryover effects as found for stimulus-evoked bias.
... Thus, performance on probes is never influenced by the direct presentation of an emotional stimulus, only by the location of visually neutral cues predicting stimulus categories. Further, it has been found that performing a training version of the cVPT induces an attentional bias to stimuli belonging to the trained predicted categories [24]. This supports the interpretation of effects on the cVPT being due to anticipatory processes. ...
Article
Full-text available
In: Alcoholism and Drug Addiction, 32 (1): 63-70. Background Although risky drinking and alcohol dependence have been associated with spatial attentional biases, concerns have been raised about the reliability of the frequently-used dot-probe task. A form of anticipatory bias related to predictive cues has been found to be related to alcohol-related processes, and to have high reliability in the context of threat stimuli. It remains to be determined whether this anticipatory attentional bias also has good reliability for alcohol stimuli. Further, correlations with drinking-related individual differences need to be replicated. Methods 83 healthy adult participants were included, who completed the task and questionnaires on risky drinking (AUDIT-C), drinking motives (DMQ-R), reasons to abstain from drinking (RALD), and alcohol craving (ACQ). The task used a 400 ms Cue-Stimulus Interval, based on previous work. The Spearman-Brown split-half reliability of reaction time-based bias scores was calculated. The within-subject effect of probe location (predicted-alcohol versus predicted-non-alcohol) was tested using a paired-sample t-test. Correlations were calculated between bias scores and questionnaire scales; tests were one-sided for predicted effects and two-sided for exploratory effects. Results A good reliability of .81 was found. There was no overall bias. A predicted correlation between risky drinking and anticipatory bias towards alcohol was found, but no other predicted or exploratory effects. Conclusions The anticipatory attentional bias for alcohol is a reliably measurable individual difference, with some evidence that it is associated with risky drinking. Implicit measure of spatial attentional bias can achieve high reliability. Further study of attentional biases using predictive cues would appear to be promising.
... Thus, performance on probes is never influenced by the direct presentation of an emotional stimulus, only by the location of visually neutral cues predicting stimulus categories. Further, it has been found that performing a training version of the cVPT induces an attentional bias to stimuli belonging to the trained predicted categories [24]. This supports the interpretation of effects on the cVPT being due to anticipatory processes. ...
Preprint
Background Although risky drinking and alcohol dependence have been associated with spatial attentional biases, concerns have been raised about the reliability of the frequently-used dot-probe task. A form of anticipatory bias related to predictive cues has been found to be related to alcohol-related processes, and to have high reliability in the context of threat stimuli. It remains to be determined whether this anticipatory attentional bias also has good reliability for alcohol stimuli. Further, correlations with drinking-related individual differences need to be replicated.Methods83 healthy adult participants were included, who completed the task and questionnaires on risky drinking (AUDIT-C), drinking motives (DMQ-R), reasons to abstain from drinking (RALD), and alcohol craving (ACQ). The task used a 400 ms Cue-Stimulus Interval, based on previous work. The Spearman-Brown split-half reliability of reaction time-based bias scores was calculated. The within-subject effect of probe location (predicted-alcohol versus predicted-non-alcohol) was tested using a paired-sample t-test. Correlations were calculated between bias scores and questionnaire scales; tests were one-sided for predicted effects and two-sided for exploratory effects.ResultsA good reliability of .81 was found. There was no overall bias. A predicted correlation between risky drinking and anticipatory bias towards alcohol was found, but no other predicted or exploratory effects.Conclusions The anticipatory attentional bias for alcohol is a reliably measurable individual difference, with some evidence that it is associated with risky drinking. Implicit measure of spatial attentional bias can achieve high reliability. Further study of attentional biases using predictive cues would appear to be promising.
Article
Full-text available
Concerns have been raised about the low reliability of measurements of spatial attentional bias via RT differences in dot-probe tasks. The anticipatory form of the bias, directed towards predicted future stimuli, appears to have relatively good reliability, reaching around 0.70. However, studies thus far have not attempted to experimentally control task-related influence on bias, which could further improve reliability. Evoking top-down versus bottom-up conflict may furthermore reveal associations with individual differences related to mental health. In the current study, a sample of 143 participants performed a predictive Visual Probe Task (predVPT) with angry and neutral face stimuli online. In this task, an automatic bias is induced via visually neutral cues that predict the location of an upcoming angry face. A task-relevant bias was induced via blockwise shifts in the likely location of target stimuli. The bias score resulting from these factors was calculated as RTs to target stimuli at locations of predicted but not actually presented angry versus neutral faces. Correlations were tested with anxiety, depression , self-esteem and aggression scales. An overall bias towards threat was found with a split-half reliability of 0.90, and 0.89 after outlier removal. Avoidance of threat in blocks with a task-relevant bias away from threat was correlated with anxiety, with correction for multiple testing. The same relationship was nominally significant for depression and low self-esteem. In conclusion, we showed high reliability of spatial attentional bias that was related to anxiety.
Article
Full-text available
In: Alcoholism and Drug Addiction, 32 (1): 63-70. Background Although risky drinking and alcohol dependence have been associated with spatial attentional biases, concerns have been raised about the reliability of the frequently-used dot-probe task. A form of anticipatory bias related to predictive cues has been found to be related to alcohol-related processes, and to have high reliability in the context of threat stimuli. It remains to be determined whether this anticipatory attentional bias also has good reliability for alcohol stimuli. Further, correlations with drinking-related individual differences need to be replicated. Methods 83 healthy adult participants were included, who completed the task and questionnaires on risky drinking (AUDIT-C), drinking motives (DMQ-R), reasons to abstain from drinking (RALD), and alcohol craving (ACQ). The task used a 400 ms Cue-Stimulus Interval, based on previous work. The Spearman-Brown split-half reliability of reaction time-based bias scores was calculated. The within-subject effect of probe location (predicted-alcohol versus predicted-non-alcohol) was tested using a paired-sample t-test. Correlations were calculated between bias scores and questionnaire scales; tests were one-sided for predicted effects and two-sided for exploratory effects. Results A good reliability of .81 was found. There was no overall bias. A predicted correlation between risky drinking and anticipatory bias towards alcohol was found, but no other predicted or exploratory effects. Conclusions The anticipatory attentional bias for alcohol is a reliably measurable individual difference, with some evidence that it is associated with risky drinking. Implicit measure of spatial attentional bias can achieve high reliability. Further study of attentional biases using predictive cues would appear to be promising.
Article
Full-text available
Visual attention enables us to selectively prioritize or suppress information in the environment. Prominent models concerned with the control of visual attention differentiate between goal-directed, top-down and stimulus-driven, bottom-up control, with the former determined by current selection goals and the latter determined by physical salience. In the current review, we discuss recent studies that demonstrate that attentional selection does not need to be the result of top-down or bottom-up processing but, instead, is often driven by lingering biases due to the "history" of former attention deployments. This review mainly focuses on reward-based history effects; yet other types of history effects such as (intertrial) priming, statistical learning and affective conditioning are also discussed. We argue that evidence from behavioral, eye-movement and neuroimaging studies supports the idea that selection history modulates the topographical landscape of spatial "priority" maps, such that attention is biased toward locations having the highest activation on this map.
Article
Full-text available
Attentional bias variability may be related to alcohol abuse. Of potential use for studying variability is the anticipatory attentional bias: Bias due to the locations of predictively-cued rather than already-presented stimuli. The hypothesis was tested that conflicting automatic associations are related to attentional bias variability. Further, relationships were explored between anticipatory biases and individual differences related to alcohol use. 74 social drinkers performed a cued Visual Probe Task and univalent Single-Target Implicit Associations Tasks. Questionnaires were completed on risky drinking, craving, and motivations to drink or refrain from drinking. Conflict was related to attentional bias variability at the 800 ms Cue-Stimulus Interval. Further, a bias related to craving and risky drinking was found at the 400 ms Cue-Stimulus Interval. Thus, the selection of attentional responses was biased by predicted locations of expected salient stimuli. The results support a role of conflicting associations in attentional bias variability.
Article
Full-text available
Attentional Bias Modification (ABM) usually aims to induce automatic biases directed toward or away from certain stimulus categories. An alternative approach, termed Attention Control Training (ACT), uses a similar paradigm but aims to train the ability to exert top-down control over attention and downregulate bottom-up interference. The current study tested a novel Alternating Bias training aimed at training attention control rather than a bias. The training involved switching contingencies, so that the optimal attentional set alternated per block. Assessment and training tasks used neutral and angry faces as emotional stimuli. Results indicated that, rather than improving attention control, the Alternating Bias condition led to increased sensitivity to emotional stimuli, as measured via self-reported emotional reactivity and an Emotional Speeded Choice task. This was interpreted as an effect of enhanced salience: in the Alternating Bias condition, as with usual active ABM conditions, the emotional content of cues is task-relevant and this may increase its salience. This salience side-effect may be relevant to ABM methods. While ACT remains a potentially important avenue for research and treatment, the current results provide a warning that undesirable side effects may occur. Future methods may be able to selectively train flexibility without inducing an increase in salience.
Article
Full-text available
Anxiety disorders are common and difficult to treat. Some cognitive models of anxiety propose that attention bias to threat causes and maintains anxiety. This view led to the development of a computer-delivered treatment: attention bias modification (ABM) which predominantly trains attention avoidance of threat. However, meta-analyses indicate disappointing effectiveness of ABM-threat-avoidance training in reducing anxiety. This article considers how ABM may be improved, based on a review of key ideas from models of anxiety, attention and cognitive control. These are combined into an integrative framework of cognitive functions which support automatic threat evaluation/detection and goal-directed thought and action, which reciprocally influence each other. It considers roles of bottom-up and top-down processes involved in threat-evaluation, orienting and inhibitory control in different manifestations of attention bias (initial orienting, attention maintenance, threat avoidance, threat-distractor interference) and different ABM methods (e.g., ABM-threat-avoidance, ABM-positive-search). The framework has implications for computer-delivered treatments for anxiety. ABM methods which encourage active goal-focused attention-search for positive/nonthreat information and flexible cognitive control across multiple processes (particularly inhibitory control, which supports a positive goal-engagement mode over processing of minor threat cues) may prove more effective in reducing anxiety than ABM-threat-avoidance training which targets a specific bias in spatial orienting to threat.
Chapter
Full-text available
Models distinguishing two types of different processes or "systems" are prominent and widespread in many fields of psychological science. However, they recently have been substantially criticized and challenged. In this chapter, we focus on so-called dual-process or dual -system models that differentiate between more automatic (often "hot" emotional-affective) versus more controlled (often "cold" cognitive -deliberative) processes. We start out with an attempt to describe and clarify different terminologies, including a clarification of the temperature metaphor of "hotness versus coldness." We then propose to ground and decompose the notion of "hot ness" in emotion-relevant basic biological processes of the autonomic nervous system and incentive salience. Extending the scope, we then focus on two types of dual-process or dual-system models, discussing both their strengths as well as shortcomings. Finally, we suggest a diagnosis of the current state of affairs and propose possibly more fruitful directions for future research and theory-forming. As part of this, we briefly describe our R3 model, a novel model of reflectivity that here serves as a proof-of-principle thought-experiment to address several shortcomings of existing dual -process and dual-system models.
Article
Humans possess a primitive memory system for attention deployments that allows quick reorientation of visual attention to stimuli that are relevant to behavior at any given moment. We review recent evidence regarding such attentional priming effects from a number of different perspectives. We discuss recent findings on the time course and duration of such effects, the potential interaction of priming and top-down attentional guidance; how priming can be used to probe the nature of visual representations and attentional templates; findings on the basic nature of priming effects and recent relevant findings on so-called serial dependencies that share many characteristics with attentional priming. Our discussion shows that priming effects are strong and occur on many levels of perceptual processing, and that these effects cannot and should not be thought of as reflecting the operation of any single type of mechanism. Additionally, our overview shows the utility of these paradigms in answering questions about how we represent statistical regularities of stimuli in our environment.
Article
Dot‐probe or visual probe tasks (VPTs) are used extensively to measure attentional biases. A novel variant termed the cued VPT (cVPT) was developed to focus on the anticipatory component of attentional bias. This study aimed to establish an anticipatory attentional bias to threat using the cVPT and compare its split‐half reliability with a typical dot‐probe task. A total of 120 students performed the cVPT task and dot‐probe tasks. Essentially, the cVPT uses cues that predict the location of pictorial threatening stimuli, but on trials on which probe stimuli are presented the pictures do not appear. Hence, actual presentation of emotional stimuli did not affect responses. The reliability of the cVPT was higher at most cue–stimulus intervals and was .56 overall. A clear anticipatory attentional bias was found. In conclusion, the cVPT may be of methodological and theoretical interest. Using visually neutral predictive cues may remove sources of noise that negatively impact reliability. Predictive cues are able to bias response selection, suggesting a role of predicted outcomes in automatic processes.
Article
Alcohol use is associated with attentional biases for alcohol-related stimuli, as it has been measured via effects on mean performance measures in dot-probe tasks. However, the variability of attentional biases may contain essential information related to behavior and symptoms. Bias variability refers to short-time scale fluctuation in bias to and from salient stimuli, measurable within the duration of a task. The first aim of the current study was to relate attentional bias variability for alcohol cues to risky drinking behavior. The second aim was to explore a conditioned-cue version of the dot probe in which arbitrary cues signaled the location of subsequent alcoholic or nonalcoholic pictorial cues, which was designed to avoid sources of interference that could play a role in the normal dot probe. Results showed strong associations between measures of attentional bias variability and drinking behavior. Effects in the conditioned cues version of the task were weaker and appeared to require a longer training period. Nevertheless, heavier drinkers tended to respond too late to probes appearing at locations of cues predicting the appearance of nonalcohol stimuli. This suggests that predictive cues can capture an aspect of attentional processes related to alcohol use. The results indicate that attentional bias variability is worth studying further. It may be fruitful for theory and future research to focus on fluctuations in attention rather than consistent tendencies toward or away from alcohol. The potential use of predictive cues remains uncertain. Such designs may require relatively long training periods but could prove methodologically and theoretically useful.
Chapter
Cognitive retraining or cognitive bias modification (CBM) involves having subjects repeatedly perform a computerized task designed to reduce the impact of automatic processes that lead to harmful behavior. We first discuss the theory underlying CBM and provide a brief overview of important research progress in its application to addiction. We then focus on cognitive- and neural-mediating mechanisms. We consider recent criticism of both CBM and its theoretical foundations. Evaluations of CBM could benefit from considering theory-driven factors that may determine variations in efficacy, such as motivation. Concerning theory, while there is certainly room for fundamental advances in current models, we argue that the basic view of impulsive behavior and its control remains a useful and productive heuristic. Finally, we briefly discuss some interesting new directions for CBM research: enhancement of training via transcranial direct current stimulation, online training, and gamification, i.e., the use of gameplay elements to increase motivation.