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Hypervigilance during anxiety and selectiveattention during fear: Using steady-state visualevoked potentials (ssVEPs) to disentangle attention
mechanisms during predictable and unpredictable threatAnna K. Kastner-Dorn a, Marta Andreatta a, Paul Pauli a andMatthias J. Wieser a,b,*
a Department of Psychology (Biological Psychology, Clinical Psychology, and Psychotherapy), University of
Wurzburg, Wurzburg, Germanyb Department of Psychology, Education, and Child Studies, Erasmus University Rotterdam, Rotterdam, The
Netherlands
a r t i c l e i n f o
Article history:
Received 8 January 2018
Reviewed 14 February 2018
Revised 25 April 2018
Accepted 9 May 2018
Action editor Peter Kirsch
Published online 21 May 2018
Keywords:
Fear
Anxiety
Attention
Defensive responding
EEG
ssVEP
Heart rate
* Corresponding author. Erasmus UniversityE-mail address: [email protected] (M.J. W
https://doi.org/10.1016/j.cortex.2018.05.0080010-9452/© 2018 Elsevier Ltd. All rights rese
a b s t r a c t
Anxiety is induced by unpredictable threat, and presumably characterized by enhanced vig-
ilance. In contrast, fear is elicited by imminent threat, and leads to phasic responses with
selective attention. In order to investigate attention mechanisms and defensive responding
during fear and anxiety, we employed an adaptation of the NPU-threat test and measured
cortical (steady-state visual evoked potentials, ssVEPs), physiological (heart rate, HR), and
subjective responses (ratings) topredictable (fear-related) andunpredictable (anxiety-related)
threat in 42 healthy participants. An aversive unconditioned stimulus (US, loud noise) was
100% predicted by a cue (predictable P-cue) in one context (predictable P-context), but
appeared unpredictably within a different context (unpredictable U-context, U-cue), while it
was never delivered in a neutral safe context (N-cue, N- context). In response to predictable
threat (P-cue), increased ssVEP amplitudes and accelerated HR were found. Both predictable
andunpredictablecontextsyielded increasedssVEPamplitudes compared to thesafecontext.
Interestingly, in the unpredictable context participants showed longer-lasting visuocortical
activation than in the predictable context, supporting the notion of heightened vigilance
during anxiety. In parallel, HR decelerated to both threat contexts indicating fear bradycardia
to these threatening contexts as compared to the safe context. These results support the idea
of hypervigilance in anxiety-like situations reflected in a long-lasting facilitated processing of
sensory information, in contrast to increased selective attention to specific imminent threat
during fear. Thus, this study further supports the defense-cascade model with vigilance and
orienting in the post-encounter phase of threat (anxiety), while selective attention and
defensive mobilization in the circa-strike phase of threat (fear).
© 2018 Elsevier Ltd. All rights reserved.
Rotterdam, Institute of Pieser).
rved.
sychology, P.O. Box 1738, 3000 DR, Rotterdam, The Netherlands.
c o r t e x 1 0 6 ( 2 0 1 8 ) 1 2 0e1 3 1 121
1. Introduction
According to DSM-5, fear is oriented towards specific immi-
nent threat, while anxiety is defined as the anticipation of
unspecific future threat (American Psychiatric Association,
2013). In the same vein, experimental studies consider fear
as a phasic response to concrete threat that dissolves quickly
when the respective threat is removed, while anxiety is
regarded as a sustained affective response (Davis, Walker,
Miles, & Grillon, 2010; Perusini & Fanselow, 2015; Tovote,
Fadok, & Luthi, 2015). In consequence, fear is expected to
activate selective attention mechanisms towards a specific
threat stimulus, whereas anxiety should lead to a sustained
heightened vigilance, whose broadening attention aims at
detecting potential but yet to be detected threat in the
environment.
In experimental research, fear can be modeled using cue
conditioning, where a cue becomes a reliable predictable
signal of an aversive unconditioned stimulus and conse-
quently elicits fear responses. Anxiety can be modeled using
context conditioning, where the US is associated with a long-
lasting stimulus, i.e., the context, in the absence of a pre-
dictable cue. As a consequence, a sustained fear response (i.e.,
anxiety) is elicited throughout the duration of the context
(Davis et al., 2010). Thus, the predictability of the aversive
event plays a crucial role during these conditioning paradigms
(Bouton, 1994; Maren, Phan, & Liberzon, 2013). Fear responses
reflecting defensive activation such as increased startle re-
sponses, can be evoked by a cue predicting an aversive event
(Andreatta & Pauli, 2015; Bradley, Moulder, & Lang, 2005). A
context which is learned to be associated with aversive con-
sequences without predicting the exact time of their occur-
rence elicits anxiety-related responses (Andreatta, Neueder,
Glotzbach-Schoon, Muhlberger, & Pauli, 2017; Baas, Nugent,
Lissek, Pine, & Grillon, 2004; Grillon, Baas, Lissek, Smith, &
Milstein, 2004) and avoidance of this context (Glotzbach,
Ewald, Andreatta, Pauli, & Muhlberger, 2012; Grillon, Baas,
Cornwell, & Johnson, 2006).
The neuronal systems underlying phasic fear and tonic
anxiety are seen as two overlapping, but nevertheless distinct
networks (Davis et al., 2010). While the central nucleus of the
amygdala plays a central role in predictable threat (Boll,
Gamer, Gluth, Finsterbusch, & Buchel, 2013), the (bed nu-
cleus of the stria terminalis BNST) is involved in processing
unpredictable threat (Alvarez, Chen, Bodurka, Kaplan, &
Grillon, 2011). In addition, several studies reported an
increased and sustained activation of extended visual areas,
(anterior cingulate cortex ACC), insula and parietal cortex
(Alvarez et al., 2011; Andreatta et al., 2015; Hasler et al., 2007;
Maren et al., 2013). These latter areas are also part of the
attention network, and hence, these findings support the idea
of sustained anxiety being associated with enhanced
vigilance.
Fear and anxiety can also be classified according to
different stages of the defense cascade model (Blanchard,
Yudko, Rodgers, & Blanchard, 1993; Bradley, Codispoti,
Cuthbert, & Lang, 2001; Fanselow, 1994). In this model, the
proximity of the source of threat determines the type of
defensive behavior. During the pre-encounter phase, where
threat is looming, animals as well as humans show an ori-
enting response with an interplay of the parasympathetic
and sympathetic nervous system (Bradley et al., 2001;
Cacioppo & Berntson, 1994). Together with the post-
encounter phase, when threat is identified but not close,
this stage is associated with anxiety responses since the
threat has not clearly been identified yet. A shrinking dis-
tance to the source of threat, however, leads to mobilization
of the organism's resources, which is regulated by activity of
the sympathetic nervous system (Blanchard et al., 1993; L€ow,
Lang, Smith, & Bradley, 2008). This transition from post-
encounter to circa-strike phase is associated with the state
of fear, since the organism is directly threatened by the
predator. These two stages come along with different (heart
rate HR) response patterns, and thereby differentiate be-
tween fear and anxiety with a HR deceleration during the
post-encounter stage, and an HR acceleration during immi-
nent threat, i.e., circa-strike stage (Bradley et al., 2001; L€ow
et al., 2008). In addition, recent studies showed that heart
rate accelerates or decelerates not only as a function of
threat imminence but also as a function of behavioral op-
tions. For instance, it was shown that when participants
could not actively avoid the threat, stronger heart rate
deceleration was observed (L€ow, Weymar, & Hamm, 2015;
Wendt, L€ow, Weymar, Lotze, & Hamm, 2017).
In order to directly compare anxiety and fear responses,
Schmitz and Grillon developed a paradigm, which manipu-
lates the predictability of threat, the so-called NPU-threat
test (2012). The NPU-threat test includes three different
conditions (neutral, predictable, and unpredictable threat).
In each, a neutral or threat context is determined by an in-
struction presented for a long duration (>30 sec). During
these periods, a cue occurs with a relatively short duration
(i.e., 8 sec) repeatedly. In the (neutral condition N), no
aversive stimulus (e.g., electric shock) is presented, while in
the (predictable condition P) the aversive stimulus only oc-
curs during the presentation of the respective cue. In the
(unpredictable condition U), the aversive stimulus occurs
unpredictably within the context-only parts of the trial.
Startle amplitudes measured during the cue presentation
revealed a fear-potentiated startle during the cue in the P-
condition compared to all other conditions. For the context-
only parts (i.e., periods without any cue presentations),
startle amplitudes were increased during the (unpredictable
context U-context) compared to the two other conditions,
which is defined as anxiety-potentiated startle (Grillon et al.,
2004). As indicated by this startle modulation to predictable
and unpredictable threat, the motivational significance
changes for the context and cue stimuli and thereby pre-
sumably facilitates sensory processing of these stimuli
(Lang, Bradley, & Cuthbert, 1990). However, these results do
not allow any conclusions yet whether anxiety and fear
differently affect sensory processing and whether any tem-
poral dynamics in this processing can differentiate between
fear and anxiety.
The (steady-state visually evoked potential ssVEP) as an
oscillatory field potential measured by (electro-encephalo-
gram EEG), perfectly meets these requirements as
c o r t e x 1 0 6 ( 2 0 1 8 ) 1 2 0e1 3 1122
continuous measure of sensory processing (Norcia,
Appelbaum, Ales, Cotterau, & Rossion, 2015; Vialatte,
Maurice, Dauwels, & Cichocki, 2010; Wieser, Miskovic, &
Keil, 2016a). The ssVEP signal is elicited by the driving fre-
quency of a flickering stimulus and reflects activity of the
primary and extended visual cortex as well contributions of
higher order cortices (Di Russo et al., 2007; Muller, Teder, &
Hillyard, 1997; Wieser & Keil, 2011). As the frequency of the
ssVEP signal is known, it allows to obtain a time-frequency
sensitive measure of visuocortical activity in response to the
respective stimulus (Muller, Teder-Salejarvi, & Hillyard,
1998; Norcia et al., 2015). Augmented ssVEP amplitudes
reveal increased attentional resources towards a stimulus
(Keil, Gruber, & Muller, 2001). Furthermore, an increased
motivational significance of a stimulus evokes heightened
oscillatory cortical responses (e.g., Keil et al., 2010; Keil
et al., 2003; Wieser, McTeague, & Keil, 2011, 2012). Simi-
larly, a stimulus which was learned to be of significance as
during fear conditioning, elicits higher ssVEP amplitudes in
visual cortices (Miskovic & Keil, 2012, 2013b; Moratti, Keil, &
Miller, 2006; Wieser et al., 2008, 2014a, 2014b). This does not
only apply to cue-fear conditioning, but could be recently
shown in context-anxiety conditioning, with sustained
ssVEP amplitudes during contextual anxiety. Importantly,
such higher motivational attention was maintained
throughout the duration of the context (Kastner, Pauli, &
Wieser, 2015). Moreover, the ssVEP approach is perfectly
suited to address questions regarding the perception of so-
cial stimuli within contextual information (Wieser & Keil,
2014; Wieser et al., 2016a).
In a previous study, we successfully adapted the NPU-
threat test in order to compare attention processes during
predictable and unpredictable threat via ssVEPs using
simple Gabor patches and surrounding arrays of geometric
shapes (Wieser, Reicherts, Juravle, & Von Leupoldt, 2016b).
In brief, these results showed that attention and sensory
processing are selectively enhanced for the predictable cue
and the onset of the unpredictable context. The present
study aimed at extending these findings by using more
complex, photorealistic stimuli. The continuous visuocort-
ical changes in response to predictable and unpredictable
threat were assessed in order to observe the high-
resolution changes in time. It was assumed that height-
ened ssVEP amplitudes elicited by the context of the un-
predictable condition should exceed both the activation
during the neutral and predictable contexts and be main-
tained throughout the context. During the cue pre-
sentations, the predictable cue is expected to capture
attentional resources compared to the neutral and unpre-
dictable cue, as could be observed in previous studies on
cue conditioning (Miskovic & Keil, 2012, 2013b; Moratti
et al., 2006; Wieser et al., 2008, 2014a, 2014b) as well as in
our previous NPU-threat study (Wieser et al., 2016b).
Moreover, we expected that this differential response
would be also reflected in cardiovascular responses, with
HR deceleration in the unpredictable context as an index of
anxiety, and HR acceleration during the cue in the pre-
dictable condition as an index of defensive mobilization
(Bradley et al., 2001; L€ow et al., 2008).
2. Methods
2.1. Participants
Participants were 45 female students, who were recruited via
a local online platform. Exclusion criteriawere any psychiatric
or neurological disorders (self-report). Participants received 9
Euros as study reimbursement. Due to a failed differentiation
between the three contexts, three participants had to be
excluded from analysis. Resulting participants' age ranged
from 18 to 34 (M ¼ 23.14, SD ¼ 3.35). Mean trait and state
anxiety scores as measured with the Spielberger State-Trait
Anxiety Inventory were 35.19 (SD ¼ 8.49) and 33.95
(SD ¼ 7.52), respectively.
2.2. Stimulus materials and procedure
Three context stimuli and three cue stimuli were used. The
context stimuli were screenshots from virtual offices created
with the Source Engine from the Valve Corporation (Belle-
vue, USA), used in previous studies (Andreatta et al., 2015;
Glotzbach et al., 2012). The office differed in layout and
furniture, but pictures were balanced for luminance and
complexity by controlling the luminance values returned by
the Image Manipulation Program GIMP 2.8.14 (159, 160, 160,
for the context stimuli) and a quantitative measure of en-
tropy, calculated with the respective MATLAB function (6.68,
6.80 and 7.20, respectively). The cue stimuli were taken from
the (Radboud Faces database RaFD; Langner et al., 2010).
Three female faces with frontal orientation and neutral ex-
pressions were chosen (Rafd090_02, Rafd090_32, Rafd090_58).
As the RaFD pictures only depict faces, the facial stimuli and
a neutral female body (also created with the Source Engine)
were merged in order to create a more realistic situation
with a person standing in an office room (see Fig. 1a). Stimuli
subtended a horizontal visual angle of 33.38� and 2.86� and a
vertical visual angle of 23.90� and 5.32� for context stimuli
and cue stimuli, respectively. In order to evoke ssVEPs,
stimuli were presented in flickering mode at either 12 or
15 Hz. If the context-stimuli flickered at 12 Hz, the cue
stimuli were superimposed at the other frequency (i.e.,
15 Hz), and vice versa (counterbalanced across participants).
The stimuli were presented on a computer screen with a
refresh rate of 60 Hz, which was positioned at a distance of
100 cm from the participants' eyes. The combination of
context and cue stimuli and the assignment to the three
conditions was counterbalanced across participants. A loud
startle probe (white noise), presented via headphones at
95 dB for 500 msec served as aversive unconditioned stim-
ulus (US).
All stimuli were rated before and after the experimental
session for valence, arousal, and anxiety on 9-point visual
analog scales (VAS). These ranged from 1 “very unpleasant”,
“very calm” and “not threatening” to 9 “very pleasant”, “very
arousing” and “very threatening”, respectively. Context and
cue stimuli were rated separately, as well as cue-context
compounds with the cue in the foreground, similar to how
they were appearing in the experimental session.
Fig. 1 e Stimuli and design. (A): Examples of the context stimuli and cues within contexts. (B): Schematic design of the NPU-
threat test, adapted from Schmitz and Grillon (2012). (N ¼ neutral condition, P ¼ predictable condition, U ¼ unpredictable
condition). Each trial lasted for 60 sec and was followed by an inter-trial interval (ITI) between 1750 and 2500 msec. In the N
condition, no US was presented. During the P condition, an US occurred at the last 500 msec of one or two cues, and one or
two US were presented randomly in the context-only phases during U. One possible run is depicted on top, another order
started with the UNPNPNU block, followed by PNUNUNP.
c o r t e x 1 0 6 ( 2 0 1 8 ) 1 2 0e1 3 1 123
After the first ratings, participants received instructions
regarding the three different conditions. Participants were
explained that they were about to learn how to predict the
occurrence of the aversive noise and under which condition
it would not be predictable. They were informed about the
three conditions called “no noise”, “predictable noise” and
“unpredictable noise” and whether to expect the loud noise.
Then the corresponding picture of the room and the asso-
ciated person were displayed. Afterwards, participants were
asked to assign each context and cue to the right condition
in order to check their comprehension of instructions. A
similar test was performed after the experimental session.
As mentioned above, three participants had to be excluded
afterwards, as they mixed up the conditions.
The design of the study followed the procedure suggested
by Schmitz and Grillon (2012) for the NPU paradigm (Fig. 1b).
One trial comprised the presentation of one context for 60 sec
and three occurrences of the associated cue for 4 sec each,with
context-only intervals of 11e13 sec. An instruction screen
preceded each trial for 2,000 msec containing the information
about the following condition. An inter-trial interval showing a
blank screen (ITI) of 1,750e2,000 msec followed each trial. The
aversive noise occurred once or twice within each trial for the
predictable and unpredictable condition (50% 1x occurrence,
50% 2x occurrences within a trial), but was never presented in
the neutral condition. In the predictable condition, the aver-
sive noise was presented during the last 500 msec of cue pre-
sentation, with the cue and aversive noise co-terminating. In
the unpredictable condition, the aversive noise was presented
randomly in the context-only intervals. The order of trials was
determined following the protocol of Schmitz and Grillon
(2012) with blocks of trials with PNUNUNP or UNPNPNU
order. The experimental session consisted of four of these
blocks with alternating order. After half of the session, par-
ticipants had a short break. Altogether, 8 predictable, 8 un-
predictable and 12 neutral conditions were presented.
2.3. Data recording and analysis
2.3.1. Rating dataThe ratings of valence, arousal, and anxiety for the contexts,
cues, and for the cue-context compounds before and after the
task were analyzed with repeated-measures ANOVAs
including the within-subject factor condition (N, P, U) (Grillon
et al., 2004).
2.3.2. EEG dataEEG was continuously recorded with a HydroCel Geodesic
Sensor Net (Electrical Geodesics, Inc., Eugene, OR) with 128
sensors (sampling rate of 250 Hz and online band pass filter of
.1e100 Hz). The vertex electrode (Cz) served as online-
reference electrode. The impedance of each sensor was kept
below 50 kU, as recommended for the Electrical Geodesics
high-impedance amplifiers.
The raw ssVEP signal averaged across all participants and
conditions for a representative electrode (sensor 75, Oz)
together with the Fast Fourier Transformation and the
resulting frequency topographies of this ssVEP signal are
shown in Fig. 2. EEG data preprocessing was performed with
the Matlab based software emegs 2.4 (Peyk, De Cesarei, &
Jungh€ofer, 2011) for contexts and cues separately. For the
contexts, datawas low-pass filtered at 40 Hz and event-related
epochswere extracted from 600msec before until 60,600msec
after context stimulus onset. Due to the unusual long segment
length of 60 sec for the context stimuli, no artifact detection
was performed, as it would have resulted in a rejection of
more than 50% of the trials due to eye movements and eye
blinks. Thus, all 8 trials per condition were used for this
analysis. Due to the robustness of the ssVEP signal, this
approach seems feasible and has been used in other para-
digms (Rossion & Boremanse, 2011). In order to assess cortical
activation during cue processing separately, data was low-
pass filtered at 40 Hz and discrete epochs were extracted,
Fig. 2 e Grand mean ssVEP amplitudes across all participants and all conditions and the respective frequency spectra (Fast
Fourier Transformation). The ssVEP signal was averaged across all participants and all conditions for the first 4 sec of each
trial. The raw signal is shown (A) and the respective Fast Fourier Transformation of this ssVEP signal (B) for sensor 75 (Oz).
The topographies of the two driving frequencies of 12 and 15 Hz are also given (C). The electrodes used for spatial averaging
of the ssVEP amplitudes are given in (D). Dark grey are electrodes used for cue analysis, light grey are electrodes used for
context analysis.
c o r t e x 1 0 6 ( 2 0 1 8 ) 1 2 0e1 3 1124
from 600 msec before to 4,600 msec after cue onset. Artifact
detection on the preprocessed data was performed in a two-
step method as described by (Jungh€ofer, Elbert, Tucker, &
Rockstroh, 2000). All epochs were averaged separately for
every condition, and contexts and cues. A Hilbert trans-
formation using a MATLAB script (see Miskovic & Keil, 2013a,
for a detailed description) was performed on the raw signal in
order to gain time varying ssVEP amplitudes in the respective
stimulation frequencies.
Statistical analysis was performed using IBM SPSS Statis-
tics 22. For context-related responses of the whole trial length
(60 sec), a 3 � 5 repeated measures ANOVA including the
within-subject factors condition (N, P, U) and five time win-
dows (�a 12,000 msec) was calculated, using the ssVEP signal
averages across two occipito-lateral sensor clusters with 5
sensors each (Fig. 2d). The clusters were chosen according to a
previous study from our lab (Kastner et al., 2015), in which
context effects were found to be maximal. In a second step,
four segments with equal length of 7,000 msec were cut out of
the context-only interval between the cue presentations
(0e7,000, 17,000e24,000, 34,000e41,000, 51,000e58,000 msec
from context onset) to exclude any possible effects driven by
the cue presentation. A repeated-measures ANOVA including
the within-subject factors laterality (left vs right electrodes
cluster), condition (N, P, U) and time (4 segments) was
conducted.
For the cue-related responses, repeated-measures
ANOVAs including the factors condition (N, P, U) and time
window (4 time windows of 1,000 msec) were conducted for
the ssVEP signal elicited by the cue and separately for the
ssVEP signal elicited by the context during cue presentation. A
medial-occipital sensor cluster with six sensors around Oz
(Fig. 2d) was used for extracting the cue-evoked ssVEP signal
(Kastner et al., 2015; Wieser et al., 2016b).
2.3.3. Heart rate (HR)HR was assessed by recording an electrocardiogram with two
adhesive Ag/AgCl electrodes. To calculate continuous heart
rate, R-spikes in the electrocardiogram were counted semi-
automatically using VisionAnalyzer2.0 software and the
inter-beat-interval (IBI) was determined. Then, continuous HR
estimateswere determined per sampling point (sampling rate:
1000 Hz). Due to artifacts which made R-peak scoring impos-
sible, only 39 participants could be included in the analysis for
context effects and 36 regarding cue effects. Segments of 4 sec
during cue presentation were averaged for each condition as
were the segments of the first 10 sec of the trial during which
only the context was presented. We decided to analyze the
first 10 sec after context onset only, since this was the only
time where no cue was presented across all trials. Then,
change scores were calculated by subtracting a baseline of
1 sec before context or cue onset, respectively. HR response
c o r t e x 1 0 6 ( 2 0 1 8 ) 1 2 0e1 3 1 125
was scored as mean activity in consecutive 1 sec bins. A
repeated-measures ANOVA including the within-subject fac-
tors condition (N, P, U) and four time windows of 1 sec was
conducted for the cue segments, while the analysis for the
context effects included 10 time windows of 1 msec.
In all analyses, the alpha level was set at p < .05. If the
assumption of sphericity was violated, Greenhouse-Geisser
correction was applied and the Greenhouse-Geisser Epsilon
(GG-ε) is reported. Effect sizes are reported as partial eta (h2p).
3. Results
3.1. Ratings
As expected, the pre-ratings did not reveal any differences in
valence, arousal or anxiety for the context and cue stimuli (all
ps > .482). Regarding the post-ratings (Table 1), the analysis of
the contexts ratings revealed a main effect of condition [F (2,
82) ¼ 26.05, p ¼ <.001, h2p ¼ .39, GG-ε ¼ .84], with more negative
valence ratings for the predictable [t (41) ¼ 5.88, p < .001] and
unpredictable context [t (41) ¼ 5.60, p < .001] compared to the
neutral context, while they did not differ from each other
(p ¼ .348). Similarly, a main effect of condition was found for
arousal [F (2, 82) ¼ 37.67, p ¼ <.001, h2p ¼ .479] and anxiety [F (2,
82) ¼ 36.47, p ¼ <.001, h2p ¼ .47, GG-ε ¼ .87], revealing increased
arousal and anxiety ratings for the predictable [t (41) ¼ 7.37,
p < .001; t (41) ¼ 8.13, p < .001] and unpredictable context [t
(41) ¼ 6.96, p < .001; t (41) ¼ 6.65, p < .001] compared to neutral
context. Again, the predictable and unpredictable context did
not show differences in arousal (p ¼ .297) or anxiety ratings
(p ¼ .372).
Table 1 e Mean ratings (SD) Cue-Context compounds,Cues, and Contexts after the experimental session, in thethree experimental conditions (N: No Shock; P: PredictableShock; U: Unpredictable Shock).
Cue þ Context (n ¼ 42)
N P U
M SD M SD M SD
Valence 6.50 1.52 3.76 1.38 3.79 1.55
Arousal 1.90 1.34 4.64 2.30 4.64 2.30
Threat 1.50 1.13 4.07 2.30 3.83 2.37
Context only (n ¼ 42)
N P U
M SD M SD M SD
Valence 6.48 2.10 4.07 1.68 3.76 1.57
Arousal 2.02 1.33 4.50 2.07 4.83 2.21
Threat 1.52 1.23 3.83 1.96 4.12 2.14
Cue only (n ¼ 35)
N P U
M SD M SD M SD
Valence 6.17 1.52 3.76 1.37 3.79 1.55
Arousal 1.90 1.34 4.69 2.14 4.42 2.17
Threat 1.50 1.13 4.07 2.30 3.83 2.37
Note:Due to saving failure, the cue ratingswere only available for 35
participants.
Regarding the cues-in-contexts ratings, a similar pattern
evolved. A main effect of condition for the valence ratings [F
(2, 82)¼ 45.90, p < .001, h2p ¼ .53] showedmore negative valence
ratings for the predictable [t (41) ¼ 7.95, p < .001] and unpre-
dictable cue [t (41)¼ 7.88, p < .001] compared to the neutral cue
but no difference between the two former (p ¼ .936). Similarly,
amain effect for arousal [F (2, 82)¼ 38.87, p < .001, h2p ¼ .49] and
anxiety ratings [F (2, 82) ¼ 38.40, p < .001, h2p ¼ .48] revealed
increased arousal and anxiety for the predictable [arousal: t
(41) ¼ 7.33, p < .001; anxiety: t (41) ¼ 7.66, p < .001] and un-
predictable cue [arousal: t (41) ¼ 7.05, p < .001; anxiety: t
(41) ¼ 6.51, p < .001] compared to the neutral cue; the pre-
dictable and the unpredictable conditions did not differ in
arousal nor anxiety (all ps > .387).
The cue-ratings (only available from 35 participants due to
saving errors), revealed a similar pattern. A main effect of
condition for the valence ratings [F (2, 68) ¼ 27.55, p < .001,
h2p ¼ .45] showed more negative valence ratings for the pre-
dictable [t (34) ¼ 6.05, p < .001] and unpredictable cue [t
(34) ¼ 5.86, p < .001] compared to the neutral cue, but no dif-
ference between the former two (p ¼ .299). Similarly, a main
effect for arousal [F (2, 68) ¼ 27.92, p < .001, h2p ¼ .45] and
anxiety ratings [F (2, 68) ¼ 30.93, p < .001, h2p ¼ .48] revealed
increased arousal and anxiety for the predictable [arousal: t
(34) ¼ 5.90, p < .001; anxiety: t (34) ¼ 6.71, p < .001] and un-
predictable cue [arousal: t (34) ¼ 5.75, p < .001; anxiety: t
(41) ¼ 5.54, p < .001] compared to the neutral cue; again, no
difference was found between predictable and unpredictable
cues.
3.2. EEG data
3.2.1. Cortical response to contextsThe analysis of the whole 60 sec context segments (including
cue presentations) showed a main effect of condition [F (2,
82) ¼ 9.64, p < .001, h2p ¼ .42] indicating increased ssVEP am-
plitudes during the predictable [t (41) ¼ 7.02, p < .001] and
unpredictable [t (41) ¼ 5.65, p < .001] compared to the neutral
context, while there was no significant difference between
predictable and unpredictable contexts (p ¼ .633) (see Fig. 3). A
main effect of time [F (4, 164) ¼ 53.51, p < .001, h2p ¼ .566, GG-
ε ¼ .30] showed a significant decrease of the ssVEP signal from
the first (0e12 sec) to the second time window (12e24 sec)
across all three conditions [t (41) ¼ 7.49, p < .001] and to all
other following time windows (ts > 6.62, ps < .001). As later-
ality did not return any significant main effect nor interaction
(all ps > .520), this factor was disregarded in any further ana-
lyses and the two sensor clusters were combined.
The analysis of the epochs without any cue presentation
revealed a main effect of condition [F (2, 82) ¼ 23.04, p < .001,
h2p ¼ .36] and phase [F (3, 123) ¼ 54.93, p < .001, hp2 ¼ .57, GG-
ε ¼ .43] (Fig. 4). Furthermore, a significant interaction of con-
dition and time was found [F (6, 246) ¼ 2.26, p ¼ .039, h2p ¼ .05,
GG-ε ¼ .62]. The conditions did not show any differential
cortical activation in the first time interval (0e7 sec) [F (2,
82) ¼ 2.18, p ¼ .119, h2p ¼ .051], while a significant difference
between conditions was found in the second (17e24 sec) [F (2,
82) ¼ 29.53, p < .001, h2p ¼ .42] and third time interval
(34e41 sec) [F (2, 82) ¼ 22.25, p < .001, h2p ¼ .35], with increased
cortical activation for the predictable [second: t (41) ¼ 6.00,
Fig. 3 e Grand average scalp topographies of ssVEP amplitudes in response to the neutral, predicable, and unpredictable
contexts, averaged across the whole trial duration (60,000 msec).
c o r t e x 1 0 6 ( 2 0 1 8 ) 1 2 0e1 3 1126
p < .001; third: t (41) ¼ 5.88, p < .001] and the unpredictable
condition [second: t (41) ¼ 7.41, p < .001; third: t (41) ¼ 5.49,
p < .001] compared to the neutral context. The predictable and
unpredictable context did not differ from each other during
these first three time intervals (all ps > 269). Interestingly, in
the fourth time interval (51e58 sec) the main effect of condi-
tion [F (2, 82) ¼ 28.17, p < .001, h2p ¼ .407] indicated besides
significant higher cortical activity during both the predictable
[t (41) ¼ 5.26, p < .001] and unpredictable context [t (41) ¼ 6.88,
p < .001] compared to the neutral context, a heightened ssVEP
amplitude in response to the unpredictable compared to the
predictable context [t (41) ¼ 2.73, p ¼ .009].
3.2.2. Cortical response to cuesAnalysis of the cue segments (4,000msec) revealedmarginally
significant different cortical responses [F (2, 82) ¼ 2.86,
p¼ .063, h2p ¼ .065]. As thismain effect was predicted by amain
hypothesis, planned paired sampled t-tests were performed.
These showed an increased ssVEP signal elicited by the pre-
dictable compared to the neutral cue [t (41) ¼ 2.17, p ¼ .036],
while neither the comparison between neutral and unpre-
dictable cue nor between predictable and unpredictable cue
returned significant (all ps > .196).
A similar analysis was performed for the ssVEP signal eli-
cited by the contexts during cue presentation. This revealed a
main effect of condition [F (2, 82) ¼ 3.68, p ¼ .029, h2p ¼ .08].
During cue presentation, the predictable context elicited
increased ssVEP amplitudes as compared to the neutral
context [t (41) ¼ 3.21, p ¼ .003], while in the unpredictable cue
condition, the context did not show any differential cortical
activation compared to the neutral and the predictable
context (all ps > .153) (see Fig. 5).
3.3. Heart rate
3.3.1. Response to contextThe heart rate deceleration for the predictable and unpre-
dictable context compared to the neutral context is depicted
in Fig. 6A. The repeated measures ANOVA returned a signifi-
cant main effect of condition [F (2, 76) ¼ 5.62, GG-ε ¼ .91,
p ¼ .005, hp2 ¼ .13] and time [F (9, 342) ¼ 14.37, GG-ε ¼ .35,
p< .001, h2p ¼ .27], and a significant interaction condition x time
[F (18, 684) ¼ 2.80, GG-ε ¼ .36, p ¼ .010, h2p ¼ .07]. Except for the
first two time intervals, both predictable and unpredictable
contexts elicited a significantly larger HR decrease compared
to the neutral context (ts > 2.20, ps < .034). The predictable and
unpredictable contexts did not elicit any differential heart rate
in all time windows (all ps > .104).
3.3.2. Response to cuesThe repeated measures ANOVA concerning the HR changes
during cue presentation returned a significant main effect of
condition [F (2, 70) ¼ 15.01, GG-ε ¼ .78, p < .001, h2p ¼ .30] and
time [F (3, 105)¼ 26.07,GG-ε¼ .52, p < .001, h2p ¼ .427], as well as
a significant interaction between those factors [F (6,
210)¼ 10.44,GG-ε¼ .49, p< .001, h2p ¼ .23]. As seen in Fig. 6B, the
predictable cue elicited a significant HR acceleration between
1 and 4 sec compared to the neutral (ts > .2.51, ps < .017) and
the unpredictable condition (ts > .2.98, ps < .005).
4. Discussion
The present study investigated the differential influence of
predictability of threat on attention processes, with the goal to
demarcate the state of fear as a phasic response with selective
attention during imminent threat and the state of anxiety as a
sustained response with sustained vigilance. A strength of
this study is the use of steady-state visual evoked potentials
within the NPU-test allowing a continuous assessment of
attention-modulated electrocortical responses, thereby taking
into account the temporal distinctiveness between fear and
anxiety as one key characteristic differentiating between
these two affective states.
As expected and in line with previous findings (e.g.,
Grillon et al., 2004; Wieser et al., 2016b), the contexts asso-
ciated with the aversive event (i.e., P- and U-context) were
rated more arousing and anxiogenic as well as more negative
than the control context (N-context). Contrary to previous
studies, we found no differences between predictable and
unpredictable contexts (Grillon et al., 2009). A possible
explanation for this lack of differentiation may be that in our
paradigm, the participants actually had to learn and
remember in which context they were (different office
Fig. 4 e Grand average scalp topographies of ssVEP amplitudes in response to the neutral, predicable, and unpredictable
contexts. The ssVEP signal was averaged and analyzed separately for four selected time intervals (7 sec) of the trial during
which no cues were presented (0e7 sec, 17e24 sec, 34e41 sec, and 51e58 sec) after context onset.
c o r t e x 1 0 6 ( 2 0 1 8 ) 1 2 0e1 3 1 127
rooms), whereas in the studies by Grillon and colleagues
participants continuously received written information about
the specific context on the screen. Possibly, the differentia-
tion between U and P contexts in our protocol might have
been more complex, which consequently led to a less clear
discrimination between the two conditions. The ratings for
the cues embedded in the respective context revealed a
similar pattern. The cues presented in both the unpredictable
and predictable condition were rated as more unpleasant,
more arousing and more anxiogenic compared to the cue
presented in the neutral context. The same was found for the
ratings of predictable and unpredictable cues alone (Alvarez
et al., 2011; Haaker, Lonsdorf, Thanellou, & Kalisch, 2013).
Based on these ratings we conclude that all stimuli
Fig. 5 e Grand mean ssVEP amplitudes in response the cues, and in response to the contexts during cue presentation. The
upper row shows the grand mean scalp topographies of the ssVEP amplitudes elicited by the cues within each condition,
averaged across 4 sec. The lower row shows the mean ssVEP amplitudes elicited by the contexts during the cue
presentation averaged across 4 sec.
c o r t e x 1 0 6 ( 2 0 1 8 ) 1 2 0e1 3 1128
associated with the US, even when not in an explicit manner,
elicited strong negative affective responses.
During both the predictable and unpredictable condition,
increased cortical activation in visual cortex was observed
throughout the whole 60 sec of context presentation. Inter-
estingly, when only considering time windows without cue
presentation, the ssVEP amplitudes showed a differential
activation in response to the unpredictable compared to the
predictable threat. A facilitated sensory processing of the
Fig. 6 e Averaged heart rate responses for the neutral, predictabl
a -1 sec pre-stimulus baseline) for the first 10 sec of each trial d
predictable threat elicited larger HR decelerations compared to
(Asterisks indicate significant effects at p < .05, for the post-hoc
a -1sec pre-stimulus baseline) during the 4 sec of cue presenta
acceleration between 1 and 4 sec compared to the neutral and
effects at p < .05, for the post-hoc comparisons P vs N and P vs
unpredictable context only evolved in the last window of the
trial. This means that during the predictable context, sus-
tained attentional resources were reduced as the threat of an
US occurrence dissolved with the last cue presentation. In
contrast, the threat was present continuously in the unpre-
dictable context and therefore increased attentional resources
were continuously maintained. This is in contrast to our
previous study, which only found effects for the unpredictable
context restricted to the very onset of the condition (Wieser
e, and unpredictable condition. (A) Heart rate changes (from
uring context presentation; Unpredictable as well as
the neutral condition in all but the first two time intervals.
comparisons P vs N and U vs N). (B) Heart rate changes (from
tions. The predictable cue elicited a significant larger HR
the unpredictable condition (Asterisks indicate significant
U).
c o r t e x 1 0 6 ( 2 0 1 8 ) 1 2 0e1 3 1 129
et al., 2016b). Possibly, the more complex stimuli used here
required more time to be identified and hence more atten-
tional resources at a later time window as compared to the
previous study, which only used arrays of very simple
geometrical shapes as contexts. We conclude that the present
findings strongly support the notion of anxiety as a state of
sustained, longer lasting response with continuous height-
ened vigilance during unpredictable threat.
As expected, an increased cortical activation was observed
in response to the predictable cue compared to the neutral
cue, which corroborates findings of enhanced startle re-
sponses (Grillon et al., 2009) and ssVEPs (Wieser et al., 2016b)
for the cues in the predictable condition. Interestingly, the
context surrounding the predictable cue during its 4 sec pre-
sentation elicited also increased ssVEP amplitudes. It seems
that not only the cue for the aversive event, but also the sur-
rounding context gains motivational significance and threat
value. This finding corroborates results from our previous
study (Wieser et al., 2016b). Similar results were observed for
visual contexts, which contained a fearful face; the aversive
cues led to an amplification of the contexts, indicated by
enhanced ssVEP amplitudes (Wieser & Keil, 2014). Together,
these results support the notion that during specific threat,
processing of surrounding contexts is also enhanced.
Our results suggest that unpredictable and predictable
threat similarly draw attentional resources and lead to
increased electrocortical activation when no crucial cue is
present. One explanation could be that the time between cues,
when only the context is present, serves for both conditions as
a time of uncertainty about the occurrence of the aversive
event. While in the unpredictable condition, the occurrence is
not predictable in any way, even in the predicable condition
the context signals some uncertainty about when the actual
cue, and consequently the aversive event appear.
Both the predictable and unpredictable condition were
associatedwith pronounced decelerations in heart rate during
the first 10 sec of the trials, in which only the context was
present. Such HR decelerations (often labeled fear brady-
cardia) are known from the animal literature to reflect
an orienting response during the post-encounter phase of
the defense cascade model and indicate hyper-alertness
(Fanselow, 1994; L€ow et al., 2008, 2015). As soon as the cue
appeared, HR of the participants significantly increased in the
predictable condition only compared to both the neutral and
the unpredictable condition. This response resembles the
circa-strike phase, in which the threat becomes proximal and
physiological arousal increases as indicated by heart rate ac-
celeration and increased skin conductance (Fanselow, 1994;
Lang, Davis, & €Ohman, 2000; Richter et al., 2012). As soon as
the threat e that is the cue in the predictable condition e is
present, heart rate significantly increases as index for sym-
pathetic activation necessary for the defensive response.
The defense cascade model is ideally suited to explain the
similarities and differences in the electrocortical and physio-
logical activation between predictable and unpredictable
threat observed in this study. During the post-encounter
phase, a general facilitated sensory processing reflected by
increased electrocortical activation in occipital areas (unspe-
cific vigilance) has to be expected; as the anticipated threat is
not as imminent yet, the organism needs to evaluate the
situation in order to prepare any suitable responses. The
observed increased cortical responses during the unpredict-
able condition, reflecting increasedmobilization of attentional
resources, are in line with this explanation. Even during the
predictable condition, a preparation for the approaching cue
and subsequently also for the occurrence of the aversive event
has to take place, as seen with increased ssVEP amplitudes in
response to the context of the predictable condition. However,
a differentiation between these two conditions is observed
during the cue presentation. The occurrence of the predictable
cue can be classified as the circa-strike phase during defense.
The proximity of the unpleasant event leads to increased
physiological activations in order to prepare immediate re-
sponses together with selective attention for the threat-
specific cue. These processes are reflected in our findings of
increased ssVEP amplitudes aswell as a heart rateacceleration
in response to the cue in the predictable condition.
Some limitations of the present study should be
mentioned. First, due to practical reasons we only included
female participants, which naturally hampers the generaliz-
ability of our findings. Second, in order to analyze pure
context timewindows,we had to remove the cue periods from
both the P and the U condition. This asymmetrically removes
US-presentations from the P but not the U-condition. Thus,
the U-condition in that set of analyses may be contaminated
with time periods of presumably increased arousal due to the
noise burst presentations, while these periods are removed
from the P-condition. As a consequence, the comparison of N
and U in those analyses does not necessarily inform about the
difference between fear and anxiety. However, if arousal
would be the inly driving factor, we should have seen this
effect also at earlier time windows.
In sum, the present study aimed at differentiating the
attention mechanisms and defensive responding during fear
and anxiety using ssVEP, HR, and ratings data. Increased
activation in occipital areas reflecting facilitated sensory gain
was found for both predictable and unpredictable threat
conditions. Without the availability of a cue, unpredictable
and predictable threat showed similar cortical activation, but
importantly the activation was longer lasting in the unpre-
dictable threat condition, which is in line with the predictions
of the defense cascade model. Heightened vigilance during
post-encounter and selective attention during circa-strike
were disentangled using electrocortical measures and
distinctive heart rate responses. Overall, this study confirms
that anxiety and fear are indeed different affective states with
distinctive patterns of attention and physiological reactivity.
In a next step, research should consider the interplay of
cue and context conditioning, perhaps including extinction
processes, to advance our understanding of attentional
mechanisms in anxiety disorders and treatment processes.
For example, it should be interesting to see if anxiety sensi-
tivity as a potential risk factor for panic disorder is also
associated with selective enhanced visuocortical responding
during the unpredictable threat condition, which was
observed recently (Stevens, Weinberg, Nelson, Meissel, &
Shankman, 2018). In the same vein, possible plasticity of
these neurocognitive mechanisms in response to treatments
targeting unpredictability of threat (Gorka et al., 2017) may
inform us about successful treatment components. With
c o r t e x 1 0 6 ( 2 0 1 8 ) 1 2 0e1 3 1130
regard to extinction processes, it will be important to check if
participants with risk factors for anxiety disorders (e.g.,
enhanced trait anxiety, anxiety sensitivity or a risk allele such
as of the genes coding for the 5-HT transporter [5HTT] and the
NPS receptor [NPSR1] show slower extinction learning for
contexts, cues, or both (Glotzbach-Schoon et al., 2013a;
Glotzbach-Schoon et al., 2013b). Last but not least, in terms
of the RDoC initiative it may also be important to test if this
paradigm may contribute to specifically refine underlying
processes contributing to the psychopathology of anxiety and
stress-related disorders (Lang, McTeague, & Bradley, 2016;
Lonsdorf & Richter, 2017).
Acknowledgements
This workwas supported by the German Research Foundation
(SFB/TRR-58, projects B01 and B05).
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