More than meets the heart: Systolic amplification of different emotional faces is task dependent

Abstract

Interoceptive processes emanating from baroreceptor signals support emotional functioning. Previous research suggests a unique link to fear: fearful faces, presented in synchrony with systolic baroreceptor firing draw more attention and are rated as more intense than those presented at diastole. This study examines whether this effect is unique to fearful faces or can be observed in other emotional faces.
Participants (n = 71) completed an emotional visual search task (VST) in which fearful, happy, disgust and sad faces were presented during systolic and diastolic phases of the cardiac cycle. Visual search accuracy and emotion detection accuracy and latency were recorded, followed by a subjective intensity task.
A series of interactions between emotion and cardiac phase were observed. Visual search accuracy for happy and disgust faces was greater at systole than diastole; the opposite was found for fearful faces. Fearful and happy faces were perceived as more intense at systole.
Previous research proposed that cardiac signalling has specific effects on the attention and intensity ratings for fearful faces. Results from the present tasks suggest these effects are more generalised and raise the possibility that interoceptive signals amplify emotional superiority effects dependent on the task employed.

Full text

More than meets the heart: Systolic amplification of different
emotional faces is task dependent
Leganes-Fonteneau, M.12*, Buckman, J.F.12, Suzuki, K.3, Pawlak, A.12, Bates,
M.E.12*
1Department of Kinesiology and Health, Rutgers University – New Brunswick, NJ, USA
2 Cardiac Neuroscience Laboratory, Center of Alcohol Studies, Rutgers University – New Brunswick, NJ,
USA
3Sackler Centre for Consciousness Science, University of Sussex - Brighton, Brighton and Hove, UK
*Corresponding authors:
Mateo Leganes-Fonteneau – mateo.leganes@rutgers.edu - Phone: +1 848-445-2301 Fax: N/A
Marsha Bates – mebates@smithers.rutgers.edu - Phone: +1 848-445-3559
Keywords: Emotion, Interoception, Visual Search Task, Face detection
The data that support the findings of this study are openly available in OSF at
http://DOI 10.17605/OSF.IO/S2EW9.

Abstract:
Interoceptive processes emanating from baroreceptor signals support emotional functioning. Previous
research suggests a unique link to fear: fearful faces, presented in synchrony with systolic baroreceptor
firing draw more attention and are rated as more intense than those presented at diastole. This study
examines whether this effect is unique to fearful faces or can be observed in other emotional faces.
Participants (n=71) completed an emotional visual search task (VST) in which fearful, happy, disgust and
sad faces were presented during systolic and diastolic phases of the cardiac cycle. Visual search accuracy
and emotion detection accuracy and latency were recorded, followed by a subjective intensity task.
A series of interactions between emotion and cardiac phase were observed. Visual search accuracy for
happy and disgust faces was greater at systole than diastole; the opposite was found for fearful faces.
Fearful and happy faces were perceived as more intense at systole.
Previous research proposed that cardiac signaling has specific effects on the attention and intensity
ratings for fearful faces. Results from the present tasks suggest these effects are more generalized and
raise the possibility that interoceptive signals amplify emotional superiority effects dependent on the
task employed.

Introduction:
Interoception is the integration of afferent physiological signals with higher order neural signals to
generate adaptive responses, particularly in emotional domains (Craig 2003; Critchley & Garfinkel 2017).
Memories for emotional words (Garfinkel et al. 2013), the mapping of physiology onto memory for
appetitive picture stimuli (Leganes‐Fonteneau et al. 2020), and the integration of subjective and neural
responses towards emotional picture stimuli (Pollatos et al. 2007) are all mediated via interoceptive
mechanisms.
There is strong evidence that cardiovascular mechanisms play a central role in interception. Cardiac
interoception is multidimensional, but specific attention has been paid to phasic cardiac signals
triggered by baroreceptors, which can affect emotional and cognitive processing (Critchley & Garfinkel
2017). Arterial baroreceptors are stretch sensitive mechanoreceptors triggered when each systolic
cardiac contraction pumps blood out of the heart. The baroreceptors relay information about the timing
and strength of each individual heartbeat to the brain, which uses it to coordinate sympathetic and
parasympathetic neural responses. Thus, baroreceptor firing provides a structured temporal framework
for deconstructing the role of phasic cardiac interoceptive signaling on cognitive and emotional
processing. Interoceptive studies use this framework to compare cognitive-emotional responses to
stimuli presented in synchrony with the R-wave (upward deflection of the QRS complex of the
electrocardiogram) which occurs at the end of the diastolic cardiac phase when baroreceptors are silent,
with stimuli presented 300ms after the R-wave, during the systolic phase and when baroreceptor firing
is estimated to be maximal (Gray et al. 2010).
The presentation of emotional stimuli in synchrony with baroreceptor firing has been examined using a
variety of tasks, and allows inferring the role of interoceptive signals in emotional processing. For
example, fearful faces presented during systole compared to diastole result in greater subjective ratings
of intensity (Garfinkel et al. 2014). More objective measures, such as an emotional attentional blink, also
show that fearful faces presented at systole are also more easily detected, as opposed to happy, disgust
and neutral faces (Garfinkel et al. 2014). Similar results were found using a spatial cueing task (Azevedo
et al. 2018); although in this case only responses for fearful and neural faces were compared. Taken
together, results from these studies highlight the role of cardiac signals in attentional engagement
towards salient stimuli and the automatic processing of cues. They also emphasize the role of
interoception on fear processing, and have been used to suggest that baroreceptor signaling selectively
increases the perception of fearful faces because of their relevance as a marker of threat (Garfinkel &
Critchley 2016), reflecting a distinct neural mechanism that underpins fear processing. This latter point is
supported by the fact that some experiments also investigated responses to disgust and happy faces
without finding a significant effect of cardiac phase (Garfinkel et al. 2014; Pfeifer et al. 2017), in line with
the hypothesis that different physiological signals support specific emotional processes (Friedman 2010).
The finding that interoceptive signals increase the perception of fearful faces parallels the so-called
threat advantage effect observed in multiple instances of emotional face research. This effect posits that
attentional responses towards aversive or threatening stimuli are higher than towards positive or
neutral stimuli (i.e. Öhman et al. 2001). However, threat advantage has proven to be highly task-
dependent (Lundqvist et al. 2014). In fact, superiority effects have been observed for happy rather than
fearful faces using emotional visual search tasks (i.e. Williams et al. 2005). Such visual search tasks are
unique in allowing insight into different factors underlying emotional face detection (Calvo &

Nummenmaa 2008) such as the perceptual salience and physical features of the faces. Moreover, a
visual search task, as opposed to other attentional paradigms, allows capturing attentional processes
more representative of the naturalistic scanning of faces in a crowd (Calvo & Nummenmaa 2008).
The evidence for the effects of baroreceptor signaling in fear processing is strong, but limited. Likewise,
definitive evidence of the specificity of cardiac interoception for fear processing is lacking and it seems
necessary to further investigate this topic using other paradigms. To test whether interoceptive signals
can amplify other emotional faces, we adapted a visual search task to study automatic attention
allocation towards emotional faces (fear, sad, happy and disgust) when stimuli were presented at
different phases of the cardiac cycle. Moreover, we administered an emotional intensity task (Garfinkel
et al. 2014) seeking to replicate previous results. We expected an interaction between cardiac cycle and
emotional cue on face detection and subjective intensity ratings. Based on previous literature, increased
responses at systole should be found for fearful faces. The emotional VST may also reveal effects for
happy faces, according to previous findings using this task, while the other emotional stimuli served as
exploratory controls.
Methods:
Participants:
A power analysis performed using results from Garfinkel et al. (2014), ηp²=0.33, revealed that a sample
of 45 participants would be sufficient to generate power = 0.95. Considering that these tasks were part
of a more extensive protocol, we decided to increase sample size by 50%.
A sample of 71 young adults (mean age=20.31, SD=2.74, 22 men) was recruited from undergraduate
students at the Rutgers University, New Jersey (USA). Participants were eligible if they had normal or
corrected-to-normal vision and reported not having any serious health issue, cardiac abnormalities, or
mental disorders in the past two years. Participants under pharmacological treatment (except birth
control) were excluded to avoid any interactions with the experiment. This study was approved by the
university Institutional Review Board for the Protection of Human Subjects Involved in Research.
Participants received compensation, either as $7/hour or course credits.
Tasks
Emotional Visual Search Task
This task assessed participants’ ability to detect emotional faces within a visual array (Williams et al.
2005). The visual array consisted of 6 faces organized in a circular pattern around the center of the
screen. Within a given trial, all faces belonged to the same actor, but one face expressed a ‘full-blown’
emotion (fear, sad, disgust or happy); the other 5 faces were emotionally neutral and served as
distractors. In total, participants completed 200 trials (50 per emotion) that used faces from 50 different
actors (28 females) extracted from the The Karolinska Directed Emotional Faces data base (Lundqvist et
al. 1998). All faces were presented in black and white and cropped around the facial oval, (Figure 1A).
Each trial started with the presentation of a red fixation point that remained on screen until the stimulus
array began. On 50% of the trials, the stimulus array appeared in synchrony with the participant’s R-
wave (diastolic trials). On the other 50% of trials, the array appeared 300ms after the R-wave to

approximate the systole (systolic trials). Trial presentation was fully randomized across emotion and
cardiac synchrony.
R-waves were detected using a Nonin 8000SM Finger Pulse Oximeter processed through a C# script that
then relayed information via UDP to Matlab for stimulus presentation. R-waves were predicted from the
mean of the 4 previous RRI intervals. The script accounted for 250ms for pulse transit time, including
25ms for delays in signal processing (Suzuki et al. 2013).
The stimulus array appeared for 100ms, followed by a black screen for 20ms. An objective response
array, which consisted of 6 white ovals at the location of the previously presented faces, then appeared.
Participants were asked to select the oval in which the emotional face had appeared as quickly and
accurately as possible using a computer mouse. Finally, participants saw a subjective response array,
consisting on 4 words in a row: Fear, Disgust, Sad, Happy. Participants were instructed to select the
emotional word that had been presented by using the mouse. Response arrays remained on screen until
a response was detected. The cursor location was reset to the center of the screen (fixation point) at the
end of each trial.
Pilot studies showed strong individual differences in objective emotional detection dependent on the
distance between the stimuli and the center of the screen. A too high visual search accuracy could
generate ceiling effects and blur the effect of cardiac phase. To control for these differences,
participants first completed a practice block, in which stimuli (the same ones used in the main task)
were not timed to cardiac signals, to calibrate accuracy in relation to the location of the faces. The
distance between stimuli and the center of the screen increased from 110px to 155px across 60 trials
using 15px intervals every 12 trials (3 trials per emotion). Accuracy scores were computed for each
interval and the largest interval at which accuracy was nearest to < 55% (chance level =1/6) was selected
for the main task. That average distance was 135px (SD<15).
Emotional Intensity task:
Participants were presented with one face at a time in the center of the screen for 150ms each. Faces
were synchronized with participants’ systole (50% trials) or diastole (50% trials). Participants were asked
to rate the intensity of each face using a visual analog scale, from “not at all intense” (0) to “very
intense” (100) (Figure 1B). Stimuli and trial schedule (i.e. number of stimuli per condition) were identical
to the Emotional VST.

Figure 1 A- Emotional Visual Search Task, B-Emotional Intensity Task: In the Emotional Visual Search
Task (A), participants saw a target emotional face on the screen (Fear, Happy, Sad or Disgust)
surrounded by 5 neutral distractors. In half of the trials, stimulus presentation was synchronized with
cardiac Diastolic phase and on the other half with the Systolic phase. Participants were asked to indicate
the location of the target emotional face (Objective response-Visual search accuracy) and indicate which
kind of emotion they saw on the screen (Subjective response-Emotion detection accuracy). In the
Emotional Intensity Task, participants were presented with a single emotional face at Systole or Diastole
and were asked to rate its intensity level on a visual analog scale.
Procedure
Participants were screened for eligibility using an online survey before completing one experimental
session in the laboratory. Upon arrival at the laboratory, participants provided written informed consent
and completed questionnaires (described in the Appendix section). Participants sat comfortably ~60cm
in front of a 19” computer screen. ECG sensors (Thought Technology Ltd, Montreal, Quebec) were
attached to participants and their physiological state was measured as part of the larger experimental
design during a 5-minute baseline task (usable data for 52 subjects, mean heart rate (HR) = 78.80).
Participants also completed two tasks measuring baseline individual differences in interoceptive
awareness (data not shown). Finally, participants performed the Emotional VST and Emotional Intensity
tasks, in that order.
Data extraction and analysis:

All data were extracted and averaged separately by emotion type and cardiac phase (systole vs.
diastole). Visual search accuracy was measured from the objective response array as the proportion of
correctly detected emotional face locations in the stimulus array. Emotion detection accuracy was
measured from the subjective response array as the proportion of correctly detected emotional
categories. Latencies for objective and subjective responses were computed as reaction times for
accurate responses (min single trial latency for objective =0.305ms (disgust face) and subjective=
0.202ms (fearful face) responses). For the Emotional Intensity task, intensity ratings were computed
from 0 to 100. Accuracy and intensity scores were transformed using arcsine square root.
A series of 2-way mixed model ANOVAs examined the interaction between emotion type and cardiac
timing on accuracies and latencies for visual search and emotion detection. An equivalent analysis was
performed on intensity ratings. Significant interactions were followed by post-hoc paired samples t-tests
assessing the effect of cardiac synchrony on each emotion.
An exploratory covariate analysis with questionnaire scores and cardiovascular indices is presented in
the Appendix.
Results:
Visual search accuracy:
We found a significant main effect of emotion type, F(3,490)=143.750, p<.001, ηp2=.47, and a significant
interaction between emotion type and cardiac synchrony, F(3,490)=11.880, p<.001, ηp2=.068, on visual
search accuracy scores. There was no significant main effect of cardiac synchrony, F(1,490)=1.270,
p=.261. Post-hoc paired samples t-tests compared accuracy scores between systole/diastole for each
emotion type. We found that visual search accuracy in systole trials was significantly higher than in
diastole trials for disgust, t(490)=-2.010, p=.0453, and happy faces, t(490)=-4.400, p<.001. Conversely,
we found that visual search accuracy in diastole trials was significantly higher than in systole trials for
fearful faces, t(490)=3.040, p=.0025. There was no significant effect of cardiac phase for sad faces,
t(490)=1.000, p=.319, see Figure 2A.
The analysis of differences in latencies by cardiac synchrony identified a main effect of synchrony, with
latencies being lower at diastole than systole, F(1, 490) = 14.00, p<.001, ηp2=.028; and emotion, F(3,
490) = 17.63, p<.001, ηp2=.097, but no significant interaction between emotion and synchrony,
F(3,490)=1.75, p=.156. See Table A1 in the Appendix for descriptive statistics.
Emotion detection Accuracy:
We found a significant main effect of emotion, F(3,490)=113.290, p<.001, ηp2=.41, and cardiac phase,
F(1,490)=10.990, p=.001, ηp2=.022, on emotion detection accuracy. There was also a significant
interaction between emotion and cardiac phase, F(3,490)=6.090, p<.001, ηp2=.036. Post-hoc paired
samples t-tests compared accuracy scores between systole/diastole for each emotion type. We found
that emotion detection accuracy in diastole trials was significantly higher than in systole trials for fear,
t(490)=3.670, p<.001, and sad, t(490)=2.790, p=.006, faces . There was no significant effect of cardiac
phase for disgust, t(490)=-1.280, p=.201, and happy, t(490)=0.840, p=.4, faces. See Figure 2B.

The analysis of differences in latencies found a main effect of emotion, F(3,490)=32.35, p<.001, ηp2=.17,
but no significant main effect of synchrony, F(1,490)=1.36, p=.245 or interaction between emotion and
synchrony, F(3,490)=2.01, p=.112. See Table A2 in Appendix for descriptive statistics.
Intensity Ratings:
We found a significant main effect of emotion, F(3,469)=102.000, p<.001, ηp2=.39, and cardiac phase,
F(1,469)=7.610, p=.006, ηp2=.016, on intensity ratings. There was also a significant interaction between
emotion and cardiac phase, F(3,469)=19.040, p<.001, ηp2=.039.
Post-hoc paired samples t-tests compared intensity between systole/diastole for each emotion type. We
found that intensity ratings in systole trials were significantly higher than in diastole trials for fear,
t(469)=3.720, p=.0002, and happy, t(469)=3.950, p<.001, faces. Conversely, we found that intensity
ratings in diastole trials were significantly higher than in systole trials for disgust faces, t(469)=3.770,
p=.0002. There was no significant effect of cardiac phase for sad faces, t(469)=01.010, p=.314. See Figure
2C.

Figure 2 A – Visual Search accuracy, B – Emotion Detection accuracy, C – Intensity ratings: Task scores
as a function of emotion and cardiac synchrony. Accuracy scores were computed as the mean
proportion of correct responses. Error bars represent SE.
Discussion:
The purpose of this study was to expand previous research on the role of cardiac signals in the detection
of emotional faces. By adapting an Emo-VST to present emotional faces in synchrony with baroreceptor
signals, we attempted to provide new insight into the interoceptive correlates of emotion. We included
four emotional face sets (happy, fear, sad, disgust) and found that cardiac interoceptive signals
contributed to cognitive-emotional processing beyond fear. The results did not uniformly support our

hypotheses, but rather suggest that afferent baroreceptor signaling supports emotional processing
depending on the experimental paradigm employed.
Specifically, participants showed poorer visual search and emotion detection accuracy for fearful faces,
but greater intensity ratings when stimuli were presented at systole versus diastole. While the intensity
finding replicates Garfinkel el al. (2014), the poorer accuracy does not support the role of interoceptive
signals exclusively for fearful faces. This could be due to the fact that previous experimental paradigms
were based on tasks for which aversive stimuli show a superiority effect. For example, the emotional
attentional blink task used by Garfinkel et al. (2014) has repeatedly been shown to capture enhanced
interference by aversive stimuli (Leganes-Fonteneau et al. 2018). Similarly, spatial cueing tasks, such as
the one used by Azevedo and colleagues (2018) are more sensitive to threatening stimuli (Cisler &
Olatunji 2010).
The Emotional VST on the other hand typically elicits superiority effects for happy faces and an inhibition
of fearful faces (Williams et al. 2005). This is consistent with our findings that participants showed
greater visual search accuracy for happy faces when stimuli were presented at systole versus diastole.
Accuracy for emotion detection of happy faces did not differ as ceiling effects may have blurred the
effect of systolic amplification. Finding that happy faces also are perceived as more intense at systole
extends previous results obtained by Garfinkel el al. (2014), confirming that interoceptive signals do not
exclusively amplify the subjective perception of fearful faces. We also found an increase in visual search
accuracy for disgust faces presented at systole, although the effect was lesser than for happy faces, in
line again with previous results in an emotional VST showing higher responsiveness for happy and
disgust faces over fearful ones (Calvo & Nummenmaa 2008).
The inhibition at systole of visual search and emotion detection accuracy for fearful faces we observed
can be interpreted according to Williams et al. (2005), who proposed that fearful faces were less
detectable on a VST because they would signal imminent threat, directing subjects’ attention towards
the surrounding faces. That same rationale could be applied to our results, and systolic presentation of
fearful faces could have increased their ability to signal threat, directing attention towards the other
faces in the stimulus array more effectively and decreasing visual search and emotion detection
accuracy. The discussion of the attentional mechanisms supporting superiority effects for one or
another emotion are beyond the scope of this brief report, but they could be attributed to the
perceptual characteristics of the different faces and their salience (Calvo & Nummenmaa 2008;
Lundqvist et al. 2015). In this experiment, beyond prior observations with fear faces and the expected
superiority effects of happy faces, we observed the effect of cardiac signaling on disgust faces (greater
visual search accuracy at systole) and sad faces (poorer accuracy of emotion detection at systole).
Importantly, the flexibility of the emotional VST to incorporate different combinations of stimuli as
targets or distractors, different instructions, or experimental techniques (i.e. eye tracking) can play a
useful role in clarifying the interaction between emotional processing and cardiac signaling.
Importantly, we were not able to characterize the reliability of the R-wave prediction, but replication of
previous findings (Garfinkel et al. 2014) supports the methodology we used. Future studies should
include replication using more advanced and precise cardiac timing procedures.
Conclusions

Interoceptive deficits are proposed as a source of emotional impairment in a variety of psychiatric
disorders (i.e. anxiety, autism spectrum disorders, depression; reviewed in Khalsa et al., (2017)).
Individuals with the most prevalent psychiatric disorders often exhibit critical deficits in processing
happy and sad stimuli (Joormann & Gotlib 2007), yet the few existing studies have suggested specificity
of cardiac interoceptive signaling for fearful stimuli.
This study suggests that the specificity of interoception for fearful stimuli may be a task-based artifact,
as other emotions (happy, disgust) were amplified by cardiac signals. Although this goes against current
perspectives on the autonomic specificity of emotion (Friedman 2010), our results are consistent with
cardiac outputs as an undifferentiated interoceptive signal of general arousal feeding into evaluative
cognitive operations (Cacioppo et al. 2000). Clearly, more research is needed, but it is possible that our
novel emotional VST task may allow a broader assessment of the interoceptive correlates of emotional
processing in clinical populations. Future research aimed directly at disentangling the relationship
between interoceptive signals and the cognitive and attentional factors driving emotional processing
(Galvez-Pol et al. 2020) is needed.
Furthermore, based on evidence that baroreceptor signaling can be modulated through resonance
paced breathing to possibly increase interoceptive awareness (Leganes-Fonteneau et al. In press), the
emotional VST could be used to examine whether resonance breathing can tighten the link between
interoceptive signals and emotional face detection as a prospective clinical tool.

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