Anxiety and affective processing under load 1
Running head: ANXIETY AND AFFECTIVE PROCESSING UNDER LOAD
Anxiety moderates the interplay between cognitive and affective processing
Jeremy D. Dvorak-Bertsch, John J. Curtin, Tal J. Rubinstein
& Joseph P. Newman
University of Wisconsin – Madison
Jeremy D. Dvorak-Bertsch
University of Wisconsin-Madison
Department of Psychology
1202 West Johnson
Madison, Wi 53706-1696
Total word count: 3875
Anxiety and affective processing under load 2
Evidence suggests that focus of attention and cognitive load may each affect emotional
processing and that individual differences in anxiety moderate such effects. We examined (1)
fear-potentiated startle (FPS) under threat-focused (TF), low-load/alternative set (LL/AS), and
high-load/alternative set (HL/AS) conditions and (2) the moderating effect of trait anxiety on
FPS across these conditions. As predicted, attentional focus and cognitive load manipulations
reduced FPS. However, the moderating effects of anxiety were specific to the LL/AS condition.
Whereas the groups displayed comparable FPS in the TF and HL/AS conditions, high-anxious
participants displayed significantly greater FPS than low-anxious participants in the LL/AS
condition. These results suggest that affective processing requires attentional resources and that
exaggerated threat processing in anxious individuals relates to direction of attention rather than
emotional reactivity per se.
Anxiety and affective processing under load 3
It has long been recognized that processing of emotional stimuli can occur in the absence
of selective attention to these stimuli (Esteves & Ohman, 1993). Indeed, a large corpus of
evidence demonstrates that emotional stimuli can invoke fast, involuntary autonomic responses
(Globisch et al. 1999) that take place outside of conscious awareness (Esteves & Ohman, 1993;
Maxwell & Davidson, 2004) and guide decision making processes (Bechara et al., 2000;
Damasio, Tranel & Damasio, 1991). However, neuroscience has also demonstrated that the
subcortical neural systems responsible for the establishment and maintenance of emotional
responses do not operate in isolation, but interact with higher order brain regions (Lang, 1995;
Curtin et al., 2001) and require some degree of cognitive resources (Pessoa et al., 2002). Indeed,
researchers (Simpson et al., 2001; Pessoa et al., 2002) have argued that attenuation of an
emotional response during increasing levels of cognitive load provides a compelling illustration
of this point.
The amygdala appears to play a critical role in the processing of emotional information
(Ledoux, 1995; Davis & Whalen, 2001). In particular, compelling evidence demonstrates that
the amygdala is involved in the recognition of cues predicting threat, as well as the conditioning
of stimulus-reinforcement contingencies (LeDoux, 1996). Moreover, research using Positron
Emission Tomography (PET imaging) shows that higher levels of dispositional negative affect
are associated with greater metabolic rate in the right amygdala (Abercrombie et al., 1998). With
regard to the automaticity of emotion, Whalen et al (1998) reported that amygdala activation to
emotional stimuli may occur without conscious awareness.
Amygdala activation in the absence of conscious awareness does not negate the
possibility that amygdala activation can be moderated by higher-order cognitive processes. In
fact, research demonstrates deactivation or suppression of the amygdala in tasks that involve
Anxiety and affective processing under load 4
higher order cognitive processing (Drevets & Raichle, 1995). Research also suggests that
amygdala-mediated emotional processes may be regulated by higher-order processes such as
effortful evaluation and appraisal (Hariri, et al., 2003), and eliminated when attention is directed
to another task (Pessoa et al., 2002). Such findings highlight the importance of understanding
the interaction between cognitive and affective processes.
Though evidence suggests that cognitive processes may interfere with or diminish
emotion processing, the necessary and sufficient conditions for observing such effects are
unclear. Two relevant considerations involve direction of attention and cognitive load. For
example, Pessoa et al. (2002, 2005) employed an experimental manipulation that focused both
spatial and object-based attention away from negative affective stimuli and observed
significantly reduced amygdala responding. However, other studies that have manipulated
spatial (e.g., Vuilleumier et al., 2001) or object-based (Anderson et al., 2003) attention failed to
alter amygdala activation significantly. Such findings raise the possibility that task difficulty or
cognitive load as opposed to direction of attention alone is the crucial variable that constrains
processing of peripheral affective stimuli. Indeed, there is compelling evidence that
experimental manipulations that tax cognitive resources effectively reduce amygdala activation
(Pessoa et al., 2005; Drevets & Raichle, 1995). Thus, the first goal of this study was to clarify
whether an experimental manipulation that alters direction of attention without taxing cognitive
resources is sufficient to diminish emotion processing or whether such effects depend upon the
extent to which a task diminishes cognitive resources.
Much of the research on the cognitive modulation of emotional responding has focused
on amygdala activation as the primary dependent measure. While this research has demonstrated
cognitive/attentional modulation of amygdalar activation evoked by emotional/threatening cues,
Anxiety and affective processing under load 5
it has not demonstrated that such cognitive modulation actually leads to changes in affective
response. Substantial evidence indicates that fear potentiated startle (FPS) is a sensitive and
specific index of fear responding (Lang, 1995). For example, the startle response in humans is
potentiated when viewing negatively valent photographic images (Vrana, Spence, and Lang,
1988), during negative emotional imagery (Cook et al., 1988), and during the anticipation of
electric shock (Grillon et al., 1993, Curtin et al., 2001). Moreover, FPS is reduced in both
animals and humans by anxiolytic drugs (Curtin et al., 1998, 2001; Patrick, Berthot, & Moore,
1996) and enhanced by anxiogenics (Davis, Walker, & Lee, 1999). Finally, FPS during
processing of threat cues is mediated by the amygdala (Davis et al., 1999), which provides an
attractive connection to the research reviewed above. Given the evidence demonstrating
cognitive/attentional moderation of amygdala activation and the established link between the
amygdala and FPS, it may be assumed that cognitive/attentional load will also moderate FPS.
This study will provide a test of this assumption and potentially bridge the literature involving
cognitive/attentional moderation of amygdala activation to other relevant research using FPS to
more directly index affective responding.
The second goal of this study was to evaluate the role of individual differences in the
predicted cognitive-affective interaction. Specifically, this study was designed to examine the
effects of trait anxiety on the cognitive/attentional moderation of FPS. The magnitude of FPS
appears to vary as a function of trait-fearfulness (Cook et al., 1991, 1992), yet research
investigating the relationship between trait anxiety and fear-potentiated startle has failed to find
anxiety-related differences (Cook et al., 1991; Grillon et al., 1993; Nitschke et al., 2002). Of
potential importance, however, these studies did not investigate FPS response to threat cues as a
function of cognitive task demands. Consequently, the absence of group differences in FPS may
Anxiety and affective processing under load 6
reflect the fact that all participants allocate sufficient attention to the processing of threat when
no additional demands are placed on attentional or cognitive resources. In contrast, some
investigators have posited an association between trait anxiety and sustained vigilance for threat
processing (Calvo & Eysenck, 2000). If individual differences in anxiety affect the maintenance
or persistence of threat processing under cognitive/attentional constraints, these individual
differences may only be observed in the laboratory by explicitly manipulating cognitive task
demands. Specifically, high-anxious individuals may persist in processing of threat cues longer
than low anxious participants as attention and/or cognitive demands increase. The second goal
of this experiment was to evaluate this prediction.
The present experiment assessed participants’ fear response as a function of trait anxiety
and cognitive/attentional demands under three conditions: 1) threat focus (TF), where
participants’ task explicitly required attention to the threat cues, 2) low-load/alternative set
(LL/AS), where participants’ task required the focus of attention on threat-irrelevant information
but placed minimal demands on working memory resources, and 3) high-load/alternative set
(HL/AS), where participants’ task again required the focus of attention on threat-irrelevant
information, but also involved a working memory task to instantiate a high cognitive load
(Jonides et al., 1997). FPS indexed fear response in all three conditions.
With respect to the first goal of this experiment, if increased cognitive (working memory)
load is necessary to modulate emotion responding, FPS should be reduced only during the high
load condition (HL/AS) relative to the other two low load conditions (LL/AS & TF). However,
if manipulating direction of attention is sufficient to modulate emotional responding, FPS should
be reduced during the low LL/AS set condition as well. With respect to the second goal of this
experiment, we predict that trait anxiety will moderate the effects of load on emotional
Anxiety and affective processing under load 7
processing. Specifically, if individual differences in trait anxiety exert their influence only when
demands are placed on attention and/or working memory resources, then trait anxiety effects on
FPS will be observed in HL/AS and LL/AS conditions but not TF condition (i.e., a trait anxiety x
Participants were 39 right-handed undergraduates (17 female) between the ages of 17 and
21. Participants were divided into high- and low-anxiety groups using a median split on the
Welsh Anxiety Scale (α=0.86; median=10; range=0-33; Welsh, 1956) 1. All procedures were
compliant with human subjects guidelines.
During the task, participants viewed a series of letter cues, each presented for 500ms with
a variable inter-trial interval of 3-4s. Letter cues were either upper or lower case and colored red
or green. Participants were instructed that in all three conditions, electric shocks would be
administered on some trials following letter cues colored in red (CUE+), but that no shocks
would follow green letters (CUE-). In fact, 200ms duration electric shocks were administered to
adjacent fingers on the participant’s left hand at 1750s post-cue onset on 20% of CUE+ trials in
each condition, for a total of 30 shocks (10 shocks per condition). Given the results from
previous research demonstrating no effects of stimulus color representing CUE+ trials on the
intensity of FPS (see Curtin et al., 1998), the color connoting shock was not counterbalanced.
Prior to the start of the experimental task, electrodes were attached to the participants left hand
and participants performed a shock sensitivity task in which they were instructed to rate a
number of shocks that linearly increased in severity using a 0 to 100 scale. Shock intensity of
the experimental task was calibrated to 75% of the participant’s shock tolerance threshold which
Anxiety and affective processing under load 8
was determined as the midpoint between the ratings of 50 (uncomfortable) and 100 (maximum
tolerable threshold) on the shock sensitivity task2.
Letter cues were grouped into six task blocks of 50 trials. Task instructions for these
blocks varied across three conditions: Threat focused (TF), Low load/Alternative set (LL/AS),
and High load/Alternative set (HL/AS). For TF, participants were instructed to attend to the
color of the letter cue and press one of two buttons using their right hand to indicate letter color.
Given that responses were always made with the right hand, button presses were not
counterbalanced across condition. To ensure sufficient motivation to perform the task,
participants were informed that speed and accuracy would influence the amount of shocks they
received. This condition was designed to focus participants on the feature of the letter cue (i.e.,
color) that connoted threat of shock. For LL/AS, participants were instructed to attend to the
case of the letter cue and press one of the two buttons to indicate if the letter cue was in upper or
lower case. Thus, letter color was no longer part of the task-relevant feature set needed to
perform this simple letter case identification condition3. For HL/AS, participants were instructed
to attend to the letter identity (i.e., f vs. c vs. r, etc) of each letter cue in the series and press one
of the two buttons to indicate if the identity of the current letter matched the identity of the letter
presented 2 trials back in the series. As in the LL/AS condition, letter color was not part of the
task-relevant feature set necessary to perform this “2-back” task. Moreover, other research with
this 2-back task has confirmed that it places substantially increased demand on working memory
and its neurobiological substrates relative to simpler identification tasks such as used the LL/AS
condition (Jonides et al., 1997). As in the TF condition, participants were reminded in both the
LL/AS and HL/AS conditions, that electric shocks would be administered on some trials
following letter cues colored in red, but that no shocks would follow green letters. Participants
Anxiety and affective processing under load 9
performed two consecutive blocks of each of these three tasks and task order was
counterbalanced across participants. In order to ensure sufficient motivation in condition LL/AS
and HL/AS, participants were informed that speed and accuracy would influence their likelihood
of receiving a reward (i.e. one of three prizes).
Forty-eight startle-eliciting noise probes (50ms, 102dB white noise burst with near
instantaneous rise time) were presented 1750ms post cue onset. The noise probes were equally
distributed across CUE+/CUE- trials in all three task conditions so that each participant
experienced 16 startles (8 CUE+ and 8 CUE-) per condition. The average time between startles
in each condition was 27 seconds, with a minimum of 14 seconds and a maximum of 61 seconds.
In addition, probes never occurred on the same trial as shock administration. Startle eyeblink
electromyogram activity was sampled from electrodes under the right eye at 2000Hz, bandpass
filtered (30-500Hz; 24dB/octave roll-off), smoothed (rectified then lowpass filtered at 30Hz;
24dB/octave) and baseline corrected. Startle blink magnitude was scored as the peak response
between 20-120ms post-probe onset. Fear response to threat cues was indexed by fear-
potentiated startle (FPS), defined as the difference in blink-response magnitude to probes
following CUE+ versus CUE- letters in each of the three task conditions.
Following the completion of the experimental task, shock electrodes and measurement
sensors were removed, and participants completed a battery of electronically administered
Fear potentiated startle
FPS was analyzed with a Trait Anxiety (low vs. high) x Condition (TF vs. LL/AS vs.
HL/AS) multivariate repeated measures analysis of variance4. With respect to the first study
Anxiety and affective processing under load 10
goal, a main effect of Condition was observed, F(2,36)=11.61, p<.001 (p-rep = .9951), effect size
= 0.39, indicating that FPS was linearly reduced from TF to LL/AS to HL/AS. Consistent with
this effect, orthogonal contrasts indicated that FPS was significantly lower in the LL/AS relative
to the TF condition, F(1,37) = 9.65, p= .004 (p-rep = .9711), and that FPS was again significantly
lower in HL/AS relative to the LL/AS condition, F(1,37) = 8.21, p = .007 (p-rep = .9594).
Furthermore, one-sample t-tests revealed that FPS was significantly different from 0 for the TF
(p<.001, p-rep = .9999) and LL/AS (p<.001, p-rep = .9988) conditions, but not the HL/AS
condition (p=.073, p-rep = .8484).
With respect to the second study goal, the main effect of Condition was significantly
moderated by Trait Anxiety, F(1,36)=3.45, p=.043 (p-pre = .8876), effect size = 0.16 (Fig. 1).
Simple effect tests revealed no significant effects of Trait Anxiety in the TF (p=.898, p-rep =
.1845) or HL/AS (p=.403, prep = .5689) conditions. In contrast, a significant simple effect of
Trait Anxiety was observed in LL/AS (p=.034, p-rep = .9016), with high anxious participants
displaying greater FPS than low anxious participants.
To examine further the impact of individual differences in trait anxiety on fear
responding, raw Welsh anxiety scores were correlated with the difference in FPS from TF to
LL/AS conditions. Welsh anxiety scores were negatively correlated (r=-0.43, p =.007, p-rep =
.9588; Fig. 2) with this decrease in FPS from TF to LL/AS, indicating that as trait anxiety
increased, participants displayed less reduction in FPS when focused on task-relevant but threat-
irrelevant features (i.e. upper/lower case) of the letter cues. In contrast, no significant correlation
was observed between Welsh anxiety and the decrease in FPS between TF and HL/AS (r= .09,
p= .583, p-rep = .4411).
Anxiety and affective processing under load 11
Task response time and accuracy
Task response time and accuracy were analyzed separately with a Trait
Anxiety (low vs. high) x Condition (TF vs. LL/AS vs. HL/AS) x CUE type (CUE+ vs. CUE-)
multivariate repeated measures analysis of variance. For response time, a main effect of
Condition was observed, F(2,37)=126.49, p< .001 (p-rep = .9999), effect size = 0.87, indicating
that response time increased from TF (M=531.9, SD=12.94) to LL/AS (M=613.2, SD=15.5) to
HL/AS (M=843.27, SD=32.95). A main effect of CUE type was also observed, F(1,38)=12.22,
p<.001 (p-rep = .9839), effect size = 0.24, indicating that participants were quicker to respond to
CUE+ trials (M=654.8, SD=18.42) than CUE- trials (M=670.78, SD=18.28). No main effect or
interactions involving Trait anxiety were observed.
For accuracy, a main effect of Condition was observed, F(2,38)=23.59, p< .001 (p-rep =
.9998), effect size = 0.55, indicating that errors increased from TF (M=2.85, SD=1.14) to LL/AS
(M=2.51, SD=1.963) to HL/AS (M=10.69, SD=1.279). A main effect of CUE type was also
observed, F(1,39)=7.7, p=.008 (p-rep = .9557), effect size = 0.17, indicating that participants
made more errors in CUE- trials (M=5.67, SD=.66) than CUE+ trials (M=5.01, SD=.63). As
with Response Time, no main effect or interactions involving Trait Anxiety were observed.
To our knowledge, this experiment provides the first direct demonstration that FPS to
threat cues is moderated independently by working memory load and focus of attention.
Specifically, the load manipulations used in this study significantly attenuated FPS in Condition
LL/AS relative to TFC, and in the HL/AS condition relative to LL/AS and TFC conditions.
Anxiety and affective processing under load 12
Consistent with previous studies, this finding suggests that amygdala-mediated affective
processing is not completely automatic and requires attentional resources (Pessoa et al., 2002).
As reviewed earlier, a shift in attentional focus with substantial cognitive load effectively
reduced differential amygdala activation to emotional stimuli (Pessoa et al., 2002). Furthermore,
research demonstrates that amygdala activation varies as a function of cognitive load (Pessoa et
al., 2005). Our study is consistent with these results and demonstrates that changes in attentional
focus and cognitive load shown to impact amygdala activation are paralleled by changes in
emotional (i.e. fear) responses. However, other work that manipulated attentional focus, without
inducing substantial cognitive load has failed to observe these reductions in amygdala activation
(e.g., Vuilleumier et al., 2001; Anderson et al., 2003). In contrast, our manipulation of
attentional focus was sufficient to reduce emotional responding without substantial cognitive
load. Given the interaction between our attentional focus manipulation and trait anxiety, it is
possible that these discrepant findings reflect differences in sample composition, particularly
those related to anxiety. Alternatively, it is possible that previous studies encouraged
participants to divide attention and maintain processing of the affective stimuli.
Despite an intuitive connection between threat processing and trait anxiety, past research
provides little or no support for this association (Cook et al., 1991; Grillon et al., 1993; Nitschke
et al., 2002). To the extent that previous investigations of threat sensitivity in trait anxious
individuals resemble our threat focused condition as appears to be the case, their failure to find
significant associations is no longer surprising. The association between trait anxiety and FPS
was found only in an experimental condition that both directed attention away from threat cues
and did not exhaust cognitive capacity. Hence, this study has also served to clarify the
Anxiety and affective processing under load 13
conditions under which trait anxiety and threat processing are related and, thus, the nature of trait
Regarding the implications of our findings for trait anxiety several interpretations are
possible. First, high-anxious individuals may have a deliberate attentional bias to process threat
information and thus persist in processing threat cues even when task demands require a
redirection of attentional focus. To the extent that high-anxious participants in Condition LL/AS
were more likely to divide attention between task-relevant stimulus features (letter case) and
task-irrelevant threat information (letter color), they would continue to display more robust fear
responses. However, the relatively high working memory load in Condition HL/AS would
interfere with this strategy of dividing attention and thus limit threat processing in high-anxious
as well as low-anxious participants.
Alternatively, high anxiety may increase threat reactivity which, in effect, makes threat
stimuli more salient. To the extent that threat stimuli are more salient for high-anxious
individuals, they would be more difficult to ignore and, so, may continue to influence emotion
processing unless cognitive capacity is essentially exhausted. This heightened reactivity
interpretation, however, is substantially undermined by the fact that high trait anxious individuals
did not show exaggerated fear responses in the threat focused condition. Moreover, to the extent
that threat cues are more salient for high anxious individuals, it follows that they would display
stronger fear responses than low-anxious individuals even in the HL/AS condition but they did
not. Although proponents of a heightened reactivity interpretation might suggest that the
absence of group differences in the HL/AS condition reflects a floor effect, such an interpretation
is undermined by the fact that comparable variability in FPS was observed across all three
Anxiety and affective processing under load 14
A final possibility relates to flexibility of attention as opposed to attentional bias or threat
reactivity per se. According to Gray and McNaughton (2000), high-anxiety reflects the strength
of a physiological system that monitors the environment for potentially relevant information
(e.g., threat cues) when people are engaged in goal-direct behavior and facilitates a redirection of
attention in response to such cues. According to Newman and colleagues, the calls for attention
that initiate such reorienting are relatively automatic, but answering calls for processing relies on
capacity-limited resources (Patterson & Newman, 1993, Newman, MacCoon, et al., in press).
According to this view, then, the significant group differences observed in the LL/AS condition
may reflect the fact that high-anxious individuals are predisposed to reorient attention to
potential threat cues more strongly than low-anxious individuals, although the consequences of
this difference would be difficult to observe in the HL/AS condition because high working
memory load precludes answering the call for processing.
Given the emphasis that Gray and McNaughton (2000) place on goal-directed behavior as
a necessary condition for revealing anxiety-related differences in threat processing, it is
noteworthy that we deliberately reinforced the focus of goal-directed behavior in the LL/AS and
HL/AS conditions by informing participants that the “amount of reward that you earn depends on
the speed and accuracy of your responses”. The fact that our alternative set manipulation was
paralleled by this instructional manipulation may, therefore, also be important for understanding
the significance of the alternative set manipulation used in this study as well as its interaction
with trait anxiety.
In summary, this experiment advanced our understanding of cognitive-emotional
interactions in three important ways. First, it clearly demonstrates that both redirection of
attentional focus and working memory load can reduce fear response. Second, this experiment
Anxiety and affective processing under load 15
substantiates the claim that cognitive-emotional interactions are moderated by individual
differences. Whereas redirection of attention was sufficient to curtail threat processing in low-
anxious individuals, it appears that high trait anxiety was associated with the persistence of threat
processing unless working memory resources were exhausted. Finally, the use of FPS rather
than amygdala activation as the primary index of fear responding strengthens confidence that
these recent demonstrations of cognitive moderation effects (e.g., Drevits & Raichle, 1995;
Pessoa et al., 2002, 2005) are directly relevant to emotional responding rather than other
functions of the amygdala. More generally, these findings clarify the circumstances which the
processing of emotion stimuli is privileged (Davis & Whalen, 2001).
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Anxiety and affective processing under load 21
Research described in this manuscript was supported by a grant from the National
Institute of Mental Health (MH53041). We greatly appreciate Alex Shackman’s insightful
contributions to the preparation of this manuscript. We also thank Josh Zeier, Samantha Glass,
Kristina Hiatt, and Donal MacCoon for their feedback and suggestions regarding the manuscript.
Address correspondence to Jeremy D. Bertsch, Department of Psychology, University of
Wisconsin-Madison, 1202 West Johnson Street, Madison, Wi 53706; email: firstname.lastname@example.org
Anxiety and affective processing under load 22
Anxiety and affective processing under load 23
FPS Difference (TF vs LL/AS)
r = .43
Anxiety and affective processing under load 24
1 Spielberger trait anxiety scores were also available for a subset of participants (N= 30). These
scores were significantly and strongly correlated with Welsh anxiety scores (r=0.74, p< .001).
When analyses were conducted using Spielberger instead of Welsh anxiety scores, results were
comparable though not significant, owing to the reduced number of participants and associated
loss of power.
2 Shock intensity levels were recorded on a 255 (8bit) intensity scale. Analyses of shock
intensity levels across groups revealed that there were no group differences, F(1,39)=.075,
3 In the low-load/alternative set condition, our intention was to simply direct attention away from
the threat cues. However, we recognize that this may also entail a low level of cognitive load;
therefore, we labeled this condition LL/AS.
4 Preliminary analysis of the startle response (rather than FPS) revealed no significant effects for
condition on the overall startle response, indicating that the average startle magnitude was
comparable across all three conditions. Initial analysis also revealed no significant effect for
counterbalanced order on FPS. In addition, initial analysis of gender revealed no significant
differences between men and women on FPS. Therefore, neither order nor gender was included
as a factor in the reported analyses.
Anxiety and affective processing under load 25 Download full-text
Figure 1: Fear potentiated startle by Trait Anxiety group in the threat focused (TF), low-
load/alternative set (LL/AS), and high-load/alternative set (HL/AS) conditions.
Figure 2: Association between Welsh anxiety scores and change in fear potentiated startle (FPS)
from the threat focused (TF) to the low-load/alternative set (LL/AS) condition (i.e., [FPS (TF)] –