Conflict Adaptation
pm eastern standard
OBSERVATION
Unconscious Conflict Adaptation Without Feature-Repetitions and Response Time Carry-Over
Christoph Huber-Huber and Ulrich Ansorge University of Vienna
Leading theories of cognition linked executive control to consciousness or awareness. Evidence from masked priming experiments questioned this link, but without addressing possible confounds. Respond- ing to a target after a masked prime, participants are slower if prime and target present conflicting (incongruent) than nonconflicting (congruent) information. Crucially, congruence in the previous trial modulates this congruence effect, presenting a congruence-sequence effect. This has been interpreted as conflict adaptation by executive control processes, but alternative explanations through trial-to-trial feature-repetitions and response-time (RT) carry-over are possible. Here, we ruled out these alternative explanations by a mixed-model analysis of trials without trial-to-trial feature-repetitions and still found a congruence-sequence effect—that is, evidence for conflict adaptation, in the absence of conflict awareness. There was also no evidence that the participants’ awareness of their RTs played a role. These findings suggest that executive control can indeed operate in an awareness-independent fashion.
Public Significance Statement The demarcation line between conscious and unconscious cognitive processes is a central topic in theories of the human mind. This study shows that unconscious cognition exhibits conflict adaptation strategies (related to executive function and human will) that have previously been attributed mainly to conscious cognition. The present findings, therefore, challenge the widely accepted link between executive control in the form of conflict adaptation and consciousness or awareness.
Keywords: conflict adaptation, unconscious perception, response-time carry-over, priming, consciousness
Supplemental materials: http://dx.doi.org/10.1037/xhp0000450.supp
Humans flexibly adapt their behavior to challenges in their environment (Botvinick, Braver, Barch, Carter, & Cohen, 2001; Gratton, Coles, & Donchin, 1992), but the role of consciousness or awareness for adaptation is debated. In particular, masked priming provides controversial evidence (Ansorge, Fuchs, Khalid, & Kunde, 2011; Desender, Van Lierde, & Van den Bussche, 2013; Greenwald, Draine, & Abrams, 1996; Kunde, 2003; van Gaal, Lamme, & Ridderinkhof, 2010). Therefore, in the current study, we tested if adaptation can be elicited in an awareness-independent fashion, free of potentially confounding influences.
In priming experiments, participants categorize targets into al- ternative categories (e.g., different words as denoting either spa- tially elevated or lowered positions; Ansorge et al., 2011). In incongruent trials, the prime and its target are from alternative categories (e.g., down before above) and categorization responses are slower than in congruent trials, in which target and prime are from the same category (e.g., down before below; Greenwald et al., 1996). This congruence effect in response times (RTs) measures prime-target conflict and potentially poses a challenge that re- quires adaptation by the participant. In line with this possibility, with visible primes, the strength of the congruence effect in the current trialn depends on the previous trialn-1 (Ansorge et al., 2011; Gratton et al., 1992; Greenwald et al., 1996; Kunde, 2003). If trialn-1 was congruent, the congruence effect in trialn is larger than if trialn-1 was incongruent (Ansorge et al., 2011; Gratton et al., 1992). This congruence-sequence effect is often interpreted as adaptation to conflict (Botvinick et al., 2001): If incongruent prime and target presented a conflict in trialn-1, cognitive control down- regulates the influence of the prime, which decreases the congru- ence effect in trialn. In contrast, if prime and target signaled less conflict in trialn-1, the influence of the prime is not down-regulated and the congruence effect in trialn is stronger (Gratton et al., 1992).
Christoph Huber-Huber and Ulrich Ansorge, Department of Basic Psy- chological Research and Research Methods, University of Vienna.
Christoph Huber-Huber is now at Centre for Mind/Brain Sciences (CIMeC), University of Trento.
We thank Miriam Matysik and Adriana Negrea for assistance in data collection.
Correspondence concerning this article should be addressed to Christoph Huber-Huber, Centre for Mind/Brain Sciences (CIMeC), University of Trento, Corso Bettini 31, 38068 Rovereto (TN), Italy. E-mail: christoph [email protected]
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an Ps
yc ho
lo gi
ca l
A ss
oc ia
tio n
or on
e of
its al
lie d
pu bl
is he
rs .
T hi
s ar
tic le
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
Journal of Experimental Psychology: Human Perception and Performance
© 2018 American Psychological Association
2018, Vol. 44, No. 2, 169–175 0096-1523/18/$12.00 http://dx.doi.org/10.1037/xhp0000450
169
Concerning the possibility of conflict adaptation to stimuli of which the participants are unaware, however, the findings are less clear-cut. It is known that masking a prime can eliminate the participants’ awareness of the prime and of prime-target conflict, and that yet masked primes can elicit a congruence effect (Breit- meyer, 2007). However, the decisive finding of an awareness- independent congruence-sequence effect in masked priming ex- periments (Desender et al., 2013; Desender, Van Opstal, & Van den Bussche, 2014; van Gaal et al., 2010) is not necessarily evidence for conflict adaptation. Instead, trial-to-trial repetitions or priming of the target and the prime stimulus or RT carry-over could also lead to congruence-sequence effects, without requiring cognitive control, as will be explained next.
First, congruence-sequence effects may result from trial-to-trial repetitions or priming (Hazeltine, Lightman, Schwarb, & Schum- acher, 2011; Mayr, Awh, & Laurey, 2003). If only two stimuli (e.g., a left- and a right-pointing arrow) are used for congruent and incongruent conditions, the perceptual trial-to-trial transitions from a congruent to a congruent (CC) and from an incongruent to an incongruent (II) trial are on average smaller than from a congruent to an incongruent (CI) and from an incongruent to a congruent (IC) trial because half of all CC and II transitions are complete trial- to-trial prime- and target-repetitions, whereas neither CI nor IC transitions contain complete prime- and target-repetitions. Because trial-to-trial prime and target repetitions can prime responses in trialn, congruent trialsn-1 are followed by larger congruence effectsn–that is, RT[CI] minus RT[CC]–compared with incongruent trials n-1–that is, RT[II] minus RT[IC]. The result is a congruence-sequence effect driven by trial-to-trial feature-repetitions (Mayr et al., 2003).
To test awareness-independent conflict adaptation in the present study, we reduced trial-to-trial feature-repetitions by using four words per response category. In addition, we conducted our anal- yses twice, once on all trials (with-feature-repetitions analysis) and once on only those trials in which neither prime nor target repeated from trialn-1 to trialn (no-feature-repetition analysis).
Second, in addition to trial-to-trial feature-repetitions, RTn-1 also contributes to congruence-sequence effects independently from conflict adaptation (RT carry-over; Huber-Huber & Ansorge, 2017). As demonstrated by computational modeling (Yeung, Co- hen, & Botvinick, 2011) and experiments (Kinoshita, Mozer, & Forster, 2011; Schmidt & Weissman, 2015), compared with slower responses in trialn-1, faster responses in trialn-1 entail larger con- gruence effects in trialn, suggesting that participants adapt their response criteria to their own RTs. After a slow and, therefore, conflict-rich trialn-1 (Yeung et al., 2011) participants reduce the influence of the prime leading to smaller congruence effects in trialn. Even more critical, participants might be aware of their response speed, allowing them an awareness-dependent form of conflict adaptation, even with masked primes. To measure conflict adaptation independently of RT carry-over, we controlled for RTn-1 in a mixed-model analysis (see Method). In addition, we measured response-speed awareness: Participants categorized whether they thought they had responded fast or slow relative to all previous responses. From these reports, we computed sensitivities d= for response-speed awareness.
To ensure unawareness of prime-target conflict, in separate blocks, participants categorized the prime-target relation (whether congruent or incongruent). As for the response-speed reports, we
computed sensitivities d= for conflict awareness (Stanislaw & Todorov, 1999).
Materials and Method
Participants
Based on previous studies, we intended to include at least 26 participants (Huber-Huber & Ansorge, 2017). Because of conver- gence problems, which render any inference on model parameters impossible and do, therefore, not allow any conclusions about the significance or nonsignificance of effects, we ran a few additional participants. Because more data could easily be collected, we preferred this option compared with constraining model parame- ters (cf. Barr, Levy, Scheepers, & Tily, 2013). The second con- vergence check with 33 psychology students (19 female, two left-handed) was successful. Participants’ mean age was 22 years (range: 18 to 48 years). All participants were treated in accordance with the Declaration of Helsinki, provided written informed con- sent, had normal or corrected to normal vision, and received course credit in return.
Apparatus
Stimuli were presented on a 15-inch color Video Graphics Array (VGA) monitor. Viewing distance was 57 cm. The response device was a USB keyboard. The experiment was programmed using the Psychophysics toolbox (Brainard, 1997).
Stimuli
German words served as primes and targets. Each word denoted a spatially elevated or lower position (or an upward or downward direction). Words of the up category were: “oben” (on top), “darueber” (above), “hinauf” (upward), and “hoch” (high); the words of the down category were: “unten” (down), “darunter” (below), “hinab” (downward), and “tief” (deep). In congruent trials (50% of all trials), a prime was combined with a different target of the same spatial category (e.g., hoch as prime with oben as target). In incongruent trials a prime was combined with a target of the alternative category (e.g., hoch as prime before unten as target). In one trial, prime and target were never the same word to prevent within-trial stimulus repetitions (Forster, 1998). Congruent and incongruent trials were equally likely and presented in a random order.
Each word subtended a visual angle of 1.5° to 3.2° horizontally, and up to 0.5° vertically. Words were presented white on a black background (18 pt lowercase Courier New). In each trial, forward and backward masks consisted of 10 uppercase letters, randomly sampled from a uniform distribution. Masks subtended an angle of 4° horizontally and 0.5° vertically.
Procedure
To initiate a trial, participants pressed the #5 key on the numeric keypad. First, a fixation dot appeared for 1,800 to 2,200 ms. Then, a forward mask (200 ms), the prime (34 ms), a backward mask (34 ms), and the target (200 ms) immediately followed one another (see Figure 1). Stimuli were presented at screen center.
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an Ps
yc ho
lo gi
ca l
A ss
oc ia
tio n
or on
e of
its al
lie d
pu bl
is he
rs .
T hi
s ar
tic le
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
170 HUBER-HUBER AND ANSORGE
There were two tasks in each trial (Huber-Huber & Ansorge, 2017). First, participants categorized the target quickly and accu- rately by pressing the #8 key (above the #5 key) for up targets and the #2 key (below the #5 key) for down targets with their right index fingers. After each target response, in speed-awareness blocks, participants reported whether they thought they had re- sponded fast or slow compared with all their previous responses by pressing the keys D and F with the left hand. In prime-awareness blocks, participants judged the congruence of prime and target with the same keys D and F. The mapping of response options to keys was counterbalanced across participants. Participants were instructed to take the time they needed in the speed or prime- awareness task.
Whenever participants confused response hands, they received feedback about their key mapping; for instance, when they had pressed either key D or F without having responded to a target. Such error trials were repeated later in the experiment. Other errors, like pressing #2 when #8 would have been correct, were not repeated. If responses were too slow (more than 1,250 ms), a text message prompted faster responses.
The experiment had two parts. The first part covered five blocks of target-categorization plus speed-awareness task; the second part contained four blocks of target-categorization plus prime- awareness task. Each block encompassed 64 trials. Instructions were provided at the start of each part. The primes were not mentioned until the prime-awareness tests in Block 6. The block order with speed-awareness before conflict-awareness task pre- vented underestimating participants’ awareness of prime-target conflict by lacking adaptation to the luminance (Holender, 1986).
Awareness of Prime-Target Conflict
After each trial’s target response, participants judged if the current trial had been congruent or incongruent. Thus, we tested awareness of exactly that characteristic that was responsible for the congruence effect. For the sensitivity measure, incongruent trials counted as signals and congruent trials as noise, so that partici- pants’ reports of conflict in incongruent trials were Hits and reports of conflict in congruent trials were False Alarms (FAs). By subtraction of individual z-transformed FA rates from z-transformed Hit rates, d= was calculated, separately for each participant. In case of low conflict awareness, average d= was expected to be close to zero. Because frequentist t tests cannot provide evidence in favor of the null hypothesis (Dienes, 2011; Wagenmakers, 2007), we computed a Bayesian one-sample t test against zero with the ttestBF function of the BayesFactor package (Rouder, Morey, Speckman, & Province, 2012) in R. We consider Bayes factors smaller than 1/3 as negative and larger than 3 as positive evidence, and values between 1/3 and 3 as inconclusive or weak evidence (Raftery, 1995).
Linear Mixed Effects Model (LMM) Analysis
We conducted a linear mixed model analysis in R (version 3.2.1) with the lme4 package (version 1.1–8). Details are provided in the supplemental material (section Supplementary Method).
We excluded trials with incorrect target categorizations (errors) or mistakes in the task order (invalid trials) as well as trials after such errors, which implies that RTn-1 were correct RTs only. This procedure also limited the analysis to trials in which the task was
above
below
prime 34 ms
target 200 ms
QUEJYMVLRP
RJSLWOERNV
target discrimination task
backward mask 34 ms
forward mask 200 ms
blocks 1 to 5: speed-awareness task blocks 6 to 9: prime-visibility task
Figure 1. Example of an incongruent trial. Prime and target denote opposite spatial directions. Immediately after having given a response to the target (target discrimination task), participants judged their own response speed in Blocks 1 to 5, or the congruence of the prime-target relation in Blocks 6 to 9.
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an Ps
yc ho
lo gi
ca l
A ss
oc ia
tio n
or on
e of
its al
lie d
pu bl
is he
rs .
T hi
s ar
tic le
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
171UNCONSCIOUS CONFLICT ADAPTATION
very likely performed as intended, and it guaranteed that errors could not have contributed to conflict awareness. Outliers were determined by inspection of quantile-quantile (Q-Q) plots of trans- formed RT data, and removed before model fitting (Kinoshita et al., 2011).
We defined a random factor for participant-by-target combi- nations. Considering the target stimuli, the random effects structure ensured that varying difficulty across targets—for instance, easier processing of the German words oben, unten, and tief because of their unique initial letters—was treated as random variation and modeled separately from congruence ef- fects.
Fixed effects comprised the factors task (contrast: speed- awareness minus prime-awareness), congruence in trialn (congruencen; contrast: incongruent minus congruent), congru- ence in trialn-1 (congruencen-1; contrast: incongruent minus congruent), RT in trialn-1 as continuous predictor (RTn-1; also called RT carry-over), speed-awareness in trialn-1 (speed- awaren-1; contrast: unaware minus aware), and prime-awareness in trialn-1 (prime-awaren-1; contrast: unaware minus aware). If the 95% confidence interval (CI) for a fixed effect parameter, obtained from bootstrapping with 5,000 simulations, did not include zero, the corresponding fixed effect was considered to be significant. This approach avoids hypothesis testing that, in the context of mixed models, relies on approximations to p values (Baayen, Davidson, & Bates, 2008, p. 396). In addition, it perfectly matches recommendations of using parameter esti- mation and CIs (Cumming, 2014).
Results and Discussion
We found evidence for conflict adaptation and for a lack of the participants’ awareness of conflict. More important, only trials with- out trial-to-trial feature-repetitions showed this pattern (no-feature- repetitions): The congruence-sequence effect was significant, ! ” #0.034, SE ” 0.011, t ” #3.041, 95% CI [#0.057, #0.013] (Figure 2D). There was no evidence that RT carry-over modulated the congruence effect, ! ” #0.008, SE ” 0.006, t ” #1.372, 95% CI [#0.018, 0.003] (Figure 2E), and the participants were not aware of conflict as indicated by a Bayes factor of BF01 ” 4.50 (Figure 2F).
In contrast, an analysis of all trials, including trial-to-trial feature-repetitions, showed no evidence of a congruence-sequence effect, Congruencen $ Congruencen-1, ! ” #0.010, SE ” 0.008, t ” #1.300, 95% CI [#0.025, 0.005] (Figure 2A). Instead, RT carry-over led to larger congruence effects in trial n following fast compared with slow responses in trial n-1, ! ” #0.016, SE ” 0.004, t ” #3.626, 95% CI [#0.024, #0.007] (Figure 2B), and the Bayes factor for conflict awareness was inconclusive, BF01 ” 1.26 (Figure 2C). Thus, there was less evidence for a congruence- sequence effect, more evidence for contributions by RT carry- over, and higher prime awareness in an analysis of all trials than in the no-feature-repetitions analysis. An upshot of these findings is that evidence for conflict adaptation can be overlooked in studies that do not control for trial-to-trial repetitions (e.g., Ansorge et al., 2011).
How can the different results of the analyses with versus without feature-repetitions be explained? Repeating the prime or the target probably altered the effective prime-target interval in trialn. For
instance, the effective interval would increase, if the prime but not the target in trialn was primed by trialn-1. Perhaps because both congruence effects and participants’ awareness of the prime crit- ically depend on prime-target intervals (Breitmeyer, Hoar, Ran- dall, & Conte, 1984; Eimer & Schlaghecken, 2003), feature- repetitions have increased prime awareness, and strengthened the influence of RT carry-over on the congruencen effect.
1
Intriguingly, we found evidence for conflict adaptation—that is, a congruence-sequence effect, only in trials without trial-to-trial feature-repetitions. It is, therefore, impossible that trial-to-trial feature-repetitions accounted for the congruence-sequence effect.
The present congruence-sequence effect was also not driven by RTn-1. Although participants were aware of their response speed, as measured in Blocks 1–5, range of d= ” 0.14 to 1.70, and mean d= ” 0.97, t(32) ” 16.46, p % .001 (Bayesian t test, BF10 & 1014), this type of awareness cannot account for congruence-sequence effects because there was no evidence that RT carry-over modu- lated the congruence effect in the absence of trial-to-trial feature- repetitions (Figure 2E) in the first place. In addition, trial-to-trial fluctuations of speed-awareness did not modulate the congruence effect either (see supplementary material, section Supplementary Results). Thus, there is no evidence that the congruence-sequence effect was driven by RT carry-over.
As trial-to-trial feature-repetitions and RT carry-over were ruled out, the remaining explanation for the congruence-sequence effect is conflict adaptation. Moreover, participants were unaware of prime-target conflict (Figure 2C, 2F). In addition, in Blocks 6–9, in which conflict awareness was measured in each trial, conflict- report in trialn-1 (here called prime-awaren-1, levels: aware vs. unaware) did neither show effects in the analyses of all trials nor in the analysis of no trial-to-trial feature-repetitions (see supple- mentary material, section Supplementary Results). This is addi- tional support for awareness-independent conflict adaptation.
A possible complication that was not completely ruled out are contingency learning effects (Schmidt, 2013). In our experiment, each specific prime preceded any congruent target more often than any one incongruent target because congruent prime and target were never identical. Participants might have learned these con- tingencies. However, contingencies were small and hitherto it is unclear if learning contingencies of unconsciously perceived in- formation is possible at all (Schmidt, 2013).
Given that participants were unaware of conflict in conditions without feature-repetitions, but nevertheless adapted processing of the prime to the amount of prime-target conflict in trialn-1, the present conflict-adaptation effects are at variance with existing theories linking executive control to conscious awareness (De- haene & Naccache, 2001; Jack & Shallice, 2001). Because trial- to-trial visual feature-repetitions (Mayr et al., 2003) and RT carry- over (Huber-Huber & Ansorge, 2017) were excluded, the present results support the possibility that cognitive control could be triggered by stimuli outside of the participants’ awareness.
1 To further support this hypothesis, we analyzed prime awareness in only those trials in which at least one word from trialn-1 had been repeated in trialn. As expected, prime awareness was slightly but evidently above chance in these trials, mean d= ” 0.14, range #0.33 to 0.88, BF01 ” 0.31. A direct comparison of prime awareness d= values in trials with and trials without feature-repetitions was, however, inconclusive, BF10 ” 0.96.
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an Ps
yc ho
lo gi
ca l
A ss
oc ia
tio n
or on
e of
its al
lie d
pu bl
is he
rs .
T hi
s ar
tic le
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
172 HUBER-HUBER AND ANSORGE
One possible reason for the link between cognitive control and unconscious stimuli could be that unconscious processing and cognitive control were based on partly shared neural cor- relates (Boy, Husain, & Sumner, 2010, in particular Figure 4). This possibility also makes sense considering that conscious (volitional) processes might have evolved from automatic, reflex-like, and unconscious processes. Despite the prevalent distinction between automatic and volitional processes (Shiffrin
& Schneider, 1984), a line of evidence suggests that systems of volitional (conscious) control are inseparable extensions of evolutionary older automatic (unconscious) systems (Harrison, Freeman, & Sumner, 2014).
In summary, our findings corroborate the view that awareness- independent processing contributes to forms of human executive control that have hitherto been attributed to consciousness (Hassin, 2013; Hommel, 2007).
625
650
675
500
750
1000
−0.4
0.0
0.4
0.8
Congruent Incongruent
500 750 1000
Congruence in trial n−1
Response time in trial n−1 [ms]
R es po ns e tim e tri al n [m s]
R es po ns e tim e in tri al n [m s]
C on fli ct −d et ec tio n d’
625
650
675
500
750
1000
−0.4
0.0
0.4
0.8
Congruent Incongruent
500 750 1000
Congruence in trial n−1
Response time in trial n−1 [ms]
R es po ns e tim e tri al n [m s]
R es po ns e tim e in tri al n [m s]
C on fli ct −d et ec tio n d’
Congruence in trial n
Congruent Incongruent
All trials (with trial-to-trial feature repetitions) feature repetitionsA
B
C
D
E
F
Congruence effects following
fast responses
following slow
responses
Congruence effects following
fast responses
following slow
responses
No trial-to-trial
Figure 2. Results of the mixed-model analysis of response times (RTs) for all trials, including trial-to-trial feature-repetitions (on the left), and for only the trials without trial-to-trial feature-repetitions (on the right). There was no evidence for conflict adaptation in the analysis of all trials (Panel A, Model 14), but in the subset of trials where no word from the previous trial was repeated in the current trial (no-feature-repetitions, Panel D, Model 31). RT in the previous trial (RT carry-over) modulated the congruence effect for all trials (Panel B, Model 13), but not in the no-feature-repetitions analysis (Panel E, Model 31). Panels C and F show box plots of individual subjects’ prime-target conflict awareness measure (d=). Error bars in Panels A and D represent 95% Wald-type confidence interval. Dots in Panels B and E represent a random subsample of a fifth of all individual trials.
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an Ps
yc ho
lo gi
ca l
A ss
oc ia
tio n
or on
e of
its al
lie d
pu bl
is he
rs .
T hi
s ar
tic le
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
173UNCONSCIOUS CONFLICT ADAPTATION
References
Ansorge, U., Fuchs, I., Khalid, S., & Kunde, W. (2011). No conflict control in the absence of awareness. Psychological Research, 75, 351–365. http://dx.doi.org/10.1007/s00426-010-0313-4
Baayen, H., Bates, D., Kliegl, R., & Vasishth, S. (2015). RePsychLing: Data sets from psychology and linguistics experiments. Retrieved from https://github.com/dmbates/RePsychLing
Baayen, R. H., Davidson, D. J., & Bates, D. M. (2008). Mixed-effects modeling with crossed random effects for subjects and items. Journal of Memory and Language, 59, 390–412. http://dx.doi.org/10.1016/j.jml .2007.12.005
Barr, D. J., Levy, R., Scheepers, C., & Tily, H. J. (2013). Random effects structure for confirmatory hypothesis testing: Keep it maximal. Journal of Memory and Language, 68, 255–278. http://dx.doi.org/10.1016/j.jml .2012.11.001
Bates, D., Kliegl, R., Vasishth, S., & Baayen, H. (2015). Parsimonious mixed models. arXiv Preprint. Retrieved from http://arxiv.org/abs/1506. 04967
Bates, D. M., Maechler, M., Bolker, B., & Walker, S. (2013). lme4: Linear mixed-effects models using Eigen and S4 (version 1.1–8) [Software, R package]. Retrieved from https://cran.r-project.org/package”lme4
Botvinick, M. M., Braver, T. S., Barch, D. M., Carter, C. S., & Cohen, J. D. (2001). Conflict monitoring and cognitive control. Psychological Re- view, 108, 624–652. http://dx.doi.org/10.1037/0033-295X.108.3.624
Boy, F., Husain, M., & Sumner, P. (2010). Unconscious inhibition sepa- rates two forms of cognitive control. Proceedings of the National Acad- emy of Sciences of the United States of America, 107, 11134–11139. http://dx.doi.org/10.1073/pnas.1001925107
Brainard, D. H. (1997). The psychophysics toolbox. Spatial Vision, 10, 433– 436. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/ 9176952; http://dx.doi.org/10.1163/156856897X00357
Breitmeyer, B. G. (2007). Visual masking: Past accomplishments, present status, future developments. Advances in Cognitive Psychology, 3, 9–20. http://dx.doi.org/10.2478/v10053-008-0010-7
Breitmeyer, B. G., Hoar, W. S., Randall, D. J., & Conte, F. P. (1984). Visual masking: An integrative approach. Oxford: Oxford University Press.
Burnham, K. P., & Anderson, D. R. (2002). Model selection and multi- model inference: A practical information-theoretic approach. New York, NY: Springer.
Canty, A., & Ripley, B. (2013). boot: Bootstrap R (S-Plus) functions. R package (version 1.3–16) [Computer software]. Retrieved from https:// cran.r-project.org/package”boot
Crainiceanu, C. M., & Ruppert, D. (2004). Likelihood ratio tests in linear mixed models with one variance component. Journal of the Royal Statistical Society, Series B: Statistical Methodology, 66, 165–185. http://dx.doi.org/10.1111/j.1467-9868.2004.00438.x
Cumming, G. (2014). The new statistics: Why and how. Psychological Science, 25, 7–29. http://dx.doi.org/10.1177/0956797613504966
Davison, A. C., & Hinkley, D. V. (1997). Bootstrap methods and their applications. Cambridge: Cambridge University Press. http://dx.doi.org/ 10.1017/CBO9780511802843
Dehaene, S., & Naccache, L. (2001). Towards a cognitive neuroscience of consciousness: Basic evidence and a workspace framework. Cognition, 79, 1–37. http://dx.doi.org/10.1016/S0010-0277(00)00123-2
Desender, K., Van Lierde, E., & Van den Bussche, E. (2013). Comparing conscious and unconscious conflict adaptation. PLoS ONE, 8, e55976. http://dx.doi.org/10.1371/journal.pone.0055976
Desender, K., Van Opstal, F., & Van den Bussche, E. (2014). Feeling the conflict: The crucial role of conflict experience in adaptation. Psychological Science, 25, 675–683. http://dx.doi.org/10.1177/0956797613511468
Dienes, Z. (2011). Bayesian versus orthodox statistics: Which side are you on? Perspectives on Psychological Science, 6, 274–290. http://dx.doi .org/10.1177/1745691611406920
Eimer, M., & Schlaghecken, F. (2003). Response facilitation and inhibition in subliminal priming. Biological Psychology, 64, 7–26. http://dx.doi .org/10.1016/S0301-0511(03)00100-5
Forster, K. I. (1998). The pros and cons of masked priming. Journal of Psycholinguistic Research, 27, 203–233. Retrieved from http://www. ncbi.nlm.nih.gov/pubmed/9561785; http://dx.doi.org/10.1023/A: 1023202116609
Gratton, G., Coles, M. G. H., & Donchin, E. (1992). Optimizing the use of information: Strategic control of activation of responses. Journal of Experimental Psychology: General, 121, 480–506. http://dx.doi.org/10 .1037/0096-3445.121.4.480
Greenwald, A. G., Draine, S. C., & Abrams, R. L. (1996). Three cognitive markers of unconscious semantic activation. Science, 273, 1699–1702. http://dx.doi.org/10.1126/science.273.5282.1699
Greven, S., Crainiceanu, C. M., Küchenhoff, H., & Peters, A. (2008). Restricted likelihood ratio testing for zero variance components in linear mixed models. Journal of Computational and Graphical Statistics, 17, 870–891. http://dx.doi.org/10.1198/106186008X386599
Harrison, J. J., Freeman, T. C. A., & Sumner, P. (2014). Saccade-like behavior in the fast-phases of optokinetic nystagmus: An illustration of the emergence of volitional actions from automatic reflexes. Journal of Experimental Psychology: General, 143, 1923–1938. http://dx.doi.org/ 10.1037/a0037021
Hassin, R. R. (2013). Yes it can: On the functional abilities of the human unconscious. Perspectives on Psychological Science, 8, 195–207. http:// dx.doi.org/10.1177/1745691612460684
Hazeltine, E., Lightman, E., Schwarb, H., & Schumacher, E. H. (2011). The boundaries of sequential modulations: Evidence for set-level con- trol. Journal of Experimental Psychology: Human Perception and Per- formance, 37, 1898–1914. http://dx.doi.org/10.1037/a0024662
Hlavac, M. (2014). stargazer: LaTeX/HTML code and ASCII text for well-formatted regression and summary statistics tables (version 5.2) [Software, R package]. Retrieved from http://cran.r-project.org/ package”stargazer
Holender, D. (1986). Semantic activation without conscious identification in dichotic listening, parafoveal vision, and visual masking: A survey and appraisal. Behavioral and Brain Sciences, 9, 1–66. http://dx.doi.org/ 10.1017/S0140525X00021269
Hommel, B. (2007). Consciousness and control. Not identical twins. Jour- nal of Consciousness Studies, 14, 155–176.
Huber-Huber, C., & Ansorge, U. (2017). The role of RT carry-over for congruence sequence effects in masked priming. Journal of Experimen- tal Psychology: Learning, Memory, and Cognition, 43, 757–780.
Jack, A. I., & Shallice, T. (2001). Introspective physicalism as an approach to the science of consciousness. Cognition, 79, 161–196. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/11164027; http://dx.doi.org/10 .1016/S0010-0277(00)00128-1
Kinoshita, S., Mozer, M. C., & Forster, K. I. (2011). Dynamic adaptation to history of trial difficulty explains the effect of congruency proportion on masked priming. Journal of Experimental Psychology: General, 140, 622–636. http://dx.doi.org/10.1037/a0024230
Kunde, W. (2003). Sequential modulations of stimulus-response corre- spondence effects depend on awareness of response conflict. Psycho- nomic Bulletin & Review, 10, 198 –205. http://dx.doi.org/10.3758/ BF03196485
Mayr, U., Awh, E., & Laurey, P. (2003). Conflict adaptation effects in the absence of executive control. Nature Neuroscience, 6, 450–452.
Raftery, A. E. (1995). Bayesian model selection in social research. Soci- ological Methodology, 25, 111–163. http://dx.doi.org/10.2307/271063
R Core Team. (2013). R: A language and environment for statistical computing (version 3.2.1) [software]. R Foundation for Statistical Com- puting. Retrieved from http://www.r-project.org
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an Ps
yc ho
lo gi
ca l
A ss
oc ia
tio n
or on
e of
its al
lie d
pu bl
is he
rs .
T hi
s ar
tic le
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
174 HUBER-HUBER AND ANSORGE
Rouder, J. N., Morey, R. D., Speckman, P. L., & Province, J. M. (2012). Default Bayes factors for ANOVA designs. Journal of Mathematical Psychology, 56, 356–374. http://dx.doi.org/10.1016/j.jmp.2012.08.001
Scheipl, F., & Bolker, B. (2014). RLRsim. Exact (restricted) likelihood ratio tests for mixed and additive models (version 3.1–2) [Software, R package]. Retrieved from https://cran.r-project.org/package”RLRsim
Scheipl, F., Greven, S., & Küchenhoff, H. (2008). Size and power of tests for a zero random effect variance or polynomial regression in additive and linear mixed models. Computational Statistics & Data Analysis, 52, 3283–3299. http://dx.doi.org/10.1016/j.csda.2007.10.022
Schmidt, J. R. (2013). Questioning conflict adaptation: Proportion congru- ent and Gratton effects reconsidered. Psychonomic Bulletin & Review, 20, 615–630. http://dx.doi.org/10.3758/s13423-012-0373-0
Schmidt, J. R., & Weissman, D. H. (2015). Congruency sequence effects and previous response times: Conflict adaptation or temporal learning? Psychological Research, 80, 590 – 607. http://dx.doi.org/10.1007/ s00426-015-0681-x
Shiffrin, R. M., & Schneider, W. (1984). Automatic and controlled pro- cessing revisited. Psychological Review, 91, 269–276. http://dx.doi.org/ 10.1037/0033-295X.91.2.269
Stanislaw, H., & Todorov, N. (1999). Calculation of signal detection theory measures. Behavior Research Methods, Instruments, & Computers, 31, 137–149. http://dx.doi.org/10.3758/BF03207704
van Gaal, S., Lamme, V. A. F., & Ridderinkhof, K. R. (2010). Uncon- sciously triggered conflict adaptation. PLoS ONE, 5, e11508. http://dx .doi.org/10.1371/journal.pone.0011508
Wagenmakers, E.-J. (2007). A practical solution to the pervasive problems of p values. Psychonomic Bulletin & Review, 14, 779–804. http://dx.doi .org/10.3758/BF03194105
Yeung, N., Cohen, J. D., & Botvinick, M. M. (2011). Errors of interpre- tation and modeling: A reply to Grinband et al. NeuroImage, 57, 316– 319. http://dx.doi.org/10.1016/j.neuroimage.2011.04.029
Received January 25, 2017 Revision received March 28, 2017
Accepted April 20, 2017 !
Members of Underrepresented Groups: Reviewers for Journal Manuscripts Wanted
If you are interested in reviewing manuscripts for APA journals, the APA Publications and Communications Board would like to invite your participation. Manuscript reviewers are vital to the publications process. As a reviewer, you would gain valuable experience in publishing. The P&C Board is particularly interested in encouraging members of underrepresented groups to participate more in this process.
If you are interested in reviewing manuscripts, please write APA Journals at [email protected]. Please note the following important points:
• To be selected as a reviewer, you must have published articles in peer-reviewed journals. The experience of publishing provides a reviewer with the basis for preparing a thorough, objective review.
• To be selected, it is critical to be a regular reader of the five to six empirical journals that are most central to the area or journal for which you would like to review. Current knowledge of recently published research provides a reviewer with the knowledge base to evaluate a new submission within the context of existing research.
• To select the appropriate reviewers for each manuscript, the editor needs detailed information. Please include with your letter your vita. In the letter, please identify which APA journal(s) you are interested in, and describe your area of expertise. Be as specific as possible. For example, “social psychology” is not sufficient—you would need to specify “social cognition” or “attitude change” as well.
• Reviewing a manuscript takes time (1–4 hours per manuscript reviewed). If you are selected to review a manuscript, be prepared to invest the necessary time to evaluate the manuscript thoroughly.
APA now has an online video course that provides guidance in reviewing manuscripts. To learn more about the course and to access the video, visit http://www.apa.org/pubs/authors/review- manuscript-ce-video.aspx.
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an Ps
yc ho
lo gi
ca l
A ss
oc ia
tio n
or on
e of
its al
lie d
pu bl
is he
rs .
T hi
s ar
tic le
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
175UNCONSCIOUS CONFLICT ADAPTATION
Blog ArchiveCopyright © 2019 HomeworkMarket.com Read More
Applied SciencesArchitecture and DesignBiologyBusiness & FinanceChemistryComputer ScienceGeographyGeologyEducationEngineeringEnglishEnvironmental scienceSpanishGovernmentHistoryHuman Resource ManagementInformation SystemsLawLiteratureMathematicsNursingPhysicsPolitical SciencePsychologyReadingScienceSocial Science