Respiratory modulation of startle eye blink: A new approach to assess afferent signals from the respiratory system

Abstract

Current approaches to assess interoception of respiratory functions cannot differentiate between the physiological basis of interoception, i.e. visceral-afferent signal processing, and the psychological process of attention focusing. Furthermore, they typically involve invasive procedures, e.g. induction of respiratory occlusions or the inhalation of CO 2 -enriched air. The aim of this study was to test the capacity of startle methodology to reflect respiratory-related afferent signal processing, independent of invasive procedures. Forty-two healthy participants were tested in a spontaneous breathing and in a 0.25 Hz paced breathing condition. Acoustic startle noises of 105 dB(A) intensity (50 ms white noise) were presented with identical trial frequency at peak and on-going inspiration and expiration, based on a new pattern detection method, involving the online processing of the respiratory belt signal. The results show the highest startle magnitudes during on-going expiration compared with any other measurement points during the respiratory cycle, independent of whether breathing was spontaneous or paced. Afferent signals from slow adapting phasic pulmonary stretch receptors may be responsible for this effect. This study is the first to demonstrate startle modulation by respiration. These results offer the potential to apply startle methodology in the non-invasive testing of interoception-related aspects in respiratory psychophysiology.
This article is part of the themed issue ‘Interoception beyond homeostasis: affect, cognition and mental health’.

Full text

rstb.royalsocietypublishing.org
Research
Cite this article: Schulz A, Schilling TM,
Vo
¨gele C, Larra MF, Scha
¨chinger H. 2016
Respiratory modulation of startle eye blink:
a new approach to assess afferent signals from
the respiratory system. Phil. Trans. R. Soc. B
371: 20160019.
http://dx.doi.org/10.1098/rstb.2016.0019
Accepted: 21 June 2016
One contribution of 16 to a theme issue
‘Interoception beyond homeostasis: affect,
cognition and mental health’.
Subject Areas:
behaviour, physiology, neuroscience
Keywords:
interoception, pattern detection, respiration,
startle modification, symptom perception,
visceral-afferent signal transmission
Author for correspondence:
Andre
´Schulz
e-mail: andre.schulz@uni.lu
Electronic supplementary material is available
online at https://dx.doi.org/10.6084/m9.
figshare.c.3464874.
Respiratory modulation of startle eye
blink: a new approach to assess afferent
signals from the respiratory system
Andre
´Schulz1,2, Thomas M. Schilling2, Claus Vo
¨gele1, Mauro F. Larra2
and Hartmut Scha
¨chinger2
1
Institute for Health and Behaviour, Research Unit INSIDE, University of Luxembourg, 11, Porte des Sciences,
4366 Esch-sur-Alzette, Luxembourg
2
Division of Clinical Psychophysiology, Institute of Psychobiology, University of Trier, Johanniterufer 15,
54290 Trier, Germany
AS, 0000-0002-9381-2651; MFL, 0000-0001-5721-0920; HS, 0000-0003-0690-8864
Current approaches to assess interoception of respiratory functions cannot
differentiate between the physiological basis of interoception, i.e. visceral-
afferent signal processing, and the psychological process of attention focusing.
Furthermore, they typically involve invasive procedures, e.g. induction of
respiratory occlusions or the inhalation of CO
2
-enriched air. The aim of this
study was to test the capacity of startle methodology to reflect respiratory-
related afferent signal processing, independent of invasive procedures.
Forty-two healthy participants were tested in a spontaneous breathing and
in a 0.25 Hz paced breathing condition. Acoustic startle noises of 105 dB(A)
intensity (50 ms white noise) were presented with identical trial frequency
at peak and on-going inspiration and expiration, based on a new pattern
detection method, involving the online processing of the respiratory belt
signal. The results show the highest startle magnitudes during on-going
expiration compared with any other measurement points during the respi-
ratory cycle, independent of whether breathing was spontaneous or paced.
Afferent signals from slow adapting phasic pulmonary stretch receptors
may be responsible for this effect. This study is the first to demonstrate startle
modulation by respiration. These results offer the potential to apply startle
methodology in the non-invasive testing of interoception-related aspects in
respiratory psychophysiology.
This article is part of the themed issue ‘Interoception beyond homeostasis:
affect, cognition and mental health’.
1. Introduction
Interoception, the perception of bodily processes, plays an important role in
health and disease. For example, accurate interoception is associated with
factors that contribute to mental health, such as emotional experience [1],
emotion regulation [2] or empathy [3]. The majority of experimental paradigms
to assess interoceptive processes focuses on the perception of cardiac sen-
sations, such as the silent counting of heartbeats [4], or the discrimination of
heartbeats and exteroceptive stimuli [5], which are considered proxies for car-
diac interoceptive accuracy. Organ activation, the stimulation of interoceptors
and the afferent neural signal transmission provide the physiological basis for
visceral sensations. Interoception occurs when attention is directed towards
physical sensations [6,7]. ‘Conventional’ methods to assess interoceptive accu-
racy, however, may have several shortcomings: (i) they cannot differentiate
between the physiological basis of interoception and the psychological process
of attention focusing and (ii) they rely on subjective reports, which are expected
to be affected by various psychological states, e.g. motivation, affect and atten-
tion. The differentiation between actual afferent signals from the body and their
perception is of particular relevance for the investigation of interoception in
&2016 The Author(s) Published by the Royal Society. All rights reserved.
on October 10, 2016http://rstb.royalsocietypublishing.org/Downloaded from

mental disorders, as they (e.g. panic or somatoform disorders)
may be associated with selective disturbances in one or both of
these processes.
An alternative to interoceptive tasks, which confound
visceral sensations and their perception, is provided by the
cardiac modulation of startle (CMS) [8– 13]. CMS assesses
afferent neural traffic originating from the cardiovascular
system independent of the conscious perception of visceral
sensations [9]. More specifically, startle responses to acoustic
noise stimuli have repeatedly been demonstrated to be lower
during the early cardiac cycle phase (R-wave þ230 ms), when
the arterial pulse wave is expected to stimulate arterial baro-
receptors in large blood vessels, compared with the late
cardiac cycle phase (R þ530 ms) [8 –10,12,13]. Because this
CMS effect was largely diminished in individuals with a
degeneration of autonomic afferent nerves [9], this approach
could serve as an indirect method to reflect baro-afferent
neural signals. Neural traffic from arterial baroreceptors is
considered one important source for interoceptive neural
traffic from the cardiovascular system [14].
Afferent signals from other sources than the cardiovascular
system may be required to better understand the role of
adequate processing of bodily signals for health and disease.
Disorders of the respiratory system, such as asthma [15–18]
or chronic obstructive pulmonary disease [19– 21], are associ-
ated with altered interoceptive signal processing from the
respiratory system, which may contribute to the development
of panic disorder in those patients [22– 24]. Furthermore,
alterations in breathing can be both a cause for (e.g. respiratory
resistance, CO
2
-enriched air) and a consequence of anxiety, and
respiratory interoception could thus be a useful target for the
treatment of anxiety disorders [25]. A range of methods for
the assessment of respiratory interoception are available, how-
ever with certain limitations. Some techniques assess subjects’
sensitivity to detect changes in respiratory resistance, thus
relying on subjective reports [15,16,26,27]. Other methods
involve invasive procedures, e.g. the inhalation of CO
2
-
enriched air [28,29], or voluntary hyperventilation [30– 32] to
induce interoceptive fear. Respiratory-related evoked poten-
tials are considered psychophysiological indicators of the
cortical processing of afferent respiratory signals and thus rep-
resent an alternative to behavioural indicators of respiratory
interoception; however, their determination is also based on
respiratory occlusion events [33–35]. A common characteristic
of these approaches is that their assessment provokes a highly
uncommon and in many cases uncomfortable situation, thus
limiting the ecological validity of findings.
To address these limitations, the aim of this study was to
test the capacity of startle methodology to reflect the proces-
sing of afferent signals originating from the respiratory
system. The respiratory cycle phase may affect the central
processing of exteroceptive stimuli, and thus affect psycho-
motor reaction times. In line with this hypothesis, some
studies have reported faster reaction times during inspiration
[36–39]. In contrast, others have reported faster reaction
times [40,41], increased signal detection [42] and higher
visual event-related potentials during expiration [43]. In
anaesthetized cats, discharges in limb and lower intercostal
nerves as indicators for startle responses have been shown
to be lower during inspiration than during expiration [44].
It could be argued that these effects are due to afferent signals
from the respiratory system, presumably transmitted over
pulmonary stretch receptors.
In this study, we tested the capacity of a new method
to assess interoception of respiratory processes. This new
approach is based on the quantification of startle reflex modu-
lation. Reflexive eye blinks were measured in response to
startling acoustic noise stimuli, presented at four different
time points within the respiratory cycle: (i) at peak expiration,
(ii) on-going inspiration (maximum slope), (iii) peak inspi-
ration, and (iv) on-going expiration (maximum slope of
inversed respiratory belt signal). Blood pressure is affected
by respiratory-induced blood volume shifts within the
pulmonary circulation and central control mechanisms inte-
grating neural activity of pressure/stretch receptors located
in the lung, the heart and large proximal vasculature. As a
result, blood pressure oscillations follow the respiratory cycle
with a time lag depending on respiratory frequency. As part
of this study, we conducted a pilot study demonstrating that
respiratory frequency of 0.25 Hz is associated with similar
blood pressure levels at the two time points of ‘on-going inspi-
ration’ and ‘on-going expiration’. This ensures that potential
differences in startle responsiveness between these time
points are unaffected by differences in blood pressure levels.
2. Methods
(a) Participants
Forty-seven healthy, undergraduate students participated in the
study and received monetary compensation of E20. Owing to a
technical malfunction during data assessment, data of five par-
ticipants were lost, resulting in a final sample of 42 (30 females;
mean age: 23.8 [s.d. ¼3.0] years; BMI: 22.5 [5.1] kg m
22
). Self-
reported physical health status was assessed by customized
interview. Exclusion criteria were hearing impairments and tinni-
tus, regular use of contact lenses, any acute or chronic physical or
mental health problems and regular use of medication. All par-
ticipants provided written informed consent and were made
aware of their right to discontinue participation in the study at
any time.
(b) Procedure
Participants were seated in front of an LCD computer display in a
comfortable chair. Participants were asked to remove their glasses
if applicable, and electromyography (EMG) electrodes and the
breathing belt were attached. Headphones (Sennheiser Electronic
GmbH & Co. KG, Wedemark, Germany) were placed, and partici-
pants were informed about the experimental procedures on the
computer display. They were asked to relax, to neither speak nor
move, avoid longer periods of eye closure and listen carefully to
all acoustic stimuli. Before the beginning of the main study pro-
cedure, participants were instructed to inhale a volume of 1, 2 and
3 l of air from customized cylindrical containers. These trials were
intendedto serve as ‘standardization trials’ for a latertransformation
of the raw respiratory belt data from arbitrary units into millilitres.
All participants were tested in two experimental breathing
conditions: (i) during spontaneous breathing and (ii) during a
condition with a 0.25 Hz paced breathing rhythm (inspiration–
expiration ratio of 2 : 3). A respiratory frequency of 0.25 Hz was
chosen based on results from a pilot study reported at the end
of the Methods section. The order of appearance of experimental
conditions was counterbalanced across participants. In both con-
ditions, acoustic startle stimuli were presented at one defined
time point during each of the four different phases within the res-
piratory cycle (figure 1): (i) at peak expiration, (ii) at midpoint
during on-going inspiration, (iii) at peak inspiration and, (iv) at
midpoint during on-going expiration. During each of these
rstb.royalsocietypublishing.org Phil. Trans. R. Soc. B 371: 20160019
2
on October 10, 2016http://rstb.royalsocietypublishing.org/Downloaded from

four respiratory phases, 10 startle stimuli were presented, result-
ing in 40 stimuli per breathing condition and 80 stimuli in total.
The order of respiratory phases in which startle stimuli were
presented was also counterbalanced within participants.
During the spontaneous breathing condition, participants
focused on a fixation cross on the LCD screen. Startle stimuli
were presented with a jittering interstimulus interval of 8 – 12 s.
In the paced breathing condition, computer-controlled verbal
instructions to inhale (‘in’) and exhale (‘out’) were given over the
headphones. During startle stimulation, this auditory stimulation
had to be interrupted without affecting a participant’s breathing
rhythm, because the auditory instructions could otherwise act as
pre-pulses to the processing of the startle stimulus [45]. The
paced breathing condition was, therefore, subdivided into trials
consisting of five respiratory cycles each. During the first three
cycles, participants were verbally instructed to breath, while they
saw a green light on the LCD screen. During cycles four and
five, they were asked to continue breathing in the paced rhythm
without verbal instructions. This part of the trial was indicated
by a blue light on the screen. All startle stimuli appeared during
the fifth respiratory cycle if the respective respiratory event
was detected, whereas in 20% of those trials, there was no startle
stimulus at all (figure 2).
(c) Respiratory pattern detection
For the elicitation of startle stimuli at the defined time points
during the four phases within the respiratory cycle, an online
analysis of the respiratory signal is required, which was con-
ducted by a DASYLAB 8.0-based algorithm developed at the
Division of Clinical Psychophysiology, University of Trier. For
each subject and each of the four respiratory time points, an indi-
vidual reference template pattern was defined from a sequence of
individual breathing cycles. Depending on the breathing phase
startle stimulus
startle stimulus
startle stimulus
startle stimulus
reference template
(ca 1000–1500 ms)
reference template
(ca 1000–1500 ms)
reference template
(ca 1000–1500 ms)
reference template
(ca 1000–1500 ms)
on-going inspiration
on-going expiration
maximal inspiration
maximal expiration
(a)(b)
(c)(d)
Figure 1. Startle stimuli were presented at four respiratory phases: on-going inspiration, peak inspiration, on-going expiration and peak expiration. Reference tem-
plate patterns of 1000– 1500 ms duration were defined for each individual to predict the exact time point of startle stimulation. For ‘on-going inspiration’ (a), a
section including the post-expiratory break and the first half of the increasing slope was defined as reference template. For ‘maximum inspiration’ (b), a section
including the entire increasing slope until the local maximum was used. The reference template for ‘on-going expiration’ (c) included the inspiratory plateau and the
first half of the decreasing slope, whereas the entire decreasing slope until the local minimum was defined as reference template for ‘maximum expiration’ (d).
1.
048121620
(105 dB startle)
(blue)(green)
breathing
cycle no.
respiratory
raw signal
stimulation
visual:
(continuous)
auditory:
(0.25 Hz)
time
'in' 'out' 'in' 'out' 'in' 'out'
(s)
2. 3. 4. 5.
Figure 2. Experimental set-up for the paced breathing condition. During three consecutive respiratory cycles, participants received auditory breathing instructions
and saw a green light. When presenting a blue light, breathing instructions stopped and participants kept the same breathing rhythm. If a trial contained a startle
stimulation, then it always appeared during the fifth breathing cycle. (Online version in colour.)
rstb.royalsocietypublishing.org Phil. Trans. R. Soc. B 371: 20160019
3
on October 10, 2016http://rstb.royalsocietypublishing.org/Downloaded from

and individual differences in respiratory parameters (e.g. breath-
ing frequency, depth, etc.), this reference template pattern had a
length of 1000–1500 ms and ended with the exact time point at
which the startle elicitation was triggered (figure 1). For example,
a section of 1000–1500 ms duration including the post-expiratory
break and the first half of the increasing slope serve as template
for ‘on-going inspiration’ (figure 1a), whereas the entire increas-
ing slope of the signal until the local maximum serves as
template for ‘maximal inspiration’ (figure 1b). Thereafter, the
individual respiratory signal was continuously processed and
compared with the reference template according to a pattern
detection procedure using the following formula
D¼ÐT
0½s0ðtÞ p0ðtÞ2dt
T,
where Dis the difference between the current signal and the
reference pattern; s(t) is the signal value at time index t; p(t)is
the reference pattern value at time index t; s0(t)/p0(t) is the first
derivation of s/pand Tis the pattern length.
When the difference between the current respiratory signal
and the reference template pattern crosses a fixed threshold
and a local minimum of this function occurs, the pattern is con-
sidered as ‘detected’. In a pattern calibration phase prior to each
of the breathing conditions (spontaneous/paced), the reference
template pattern and the threshold were defined individually
for each participant. The threshold criterion was adjusted to
achieve a sensitivity of at least 90% (nine out of 10 detected pat-
terns in subsequent respiratory cycles) and a specificity of 100%.
Offline evaluation showed that 13.8% (s.d. ¼10.0%) of the
breathing patterns in the spontaneous breathing condition and
6.3% (s.d. ¼5.6%) of those in the paced breathing condition
were not accurately detected, leading to an omission of startle
stimulation in the respective trial. In this case, the stimulus was
presented in the next trial, in which the pattern was detected
(usually the subsequent trial).
(d) Technical parameters
EMG electrodes (Tyco Healthcare H124SG), which have a sensor
diameter of 10 mm as recommended by Blumenthal et al.[46],
were attached below the left eye with an interelectrode distance
of 1.5 cm to assess the activity of the orbicularis oculi muscle. Startle
stimuli consisted of acoustic white noise probes (105 dB, 50 ms
duration, instantaneous rise time, binaural stimulation). Psycho-
physiological data were recorded on hard disk with a Biopac
MP150 amplifier system (Biopac Systems, Inc., Goleta, CA) at
16-bit resolution and 1 kHz sampling rate. Hardware band-pass
filter settings were 10–500 Hz, followed by a 28 Hz software
high-pass filter [47]. The raw signal was rectified and integrated
online with a time constant of 10 ms [48]. Respiratory activity
was measured via a thoracic respiratory belt (James Long Com-
pany, Inc., Caroga Lake, NY) placed between the fifth and eighth
ribs. The signal was band-pass filtered (0.05– 10 Hz) before it was
digitized. Electrocardiography (ECG) electrodes (Tyco Healthcare
H34SG, Ag/AgCl) were placed according to the Einthoven lead
II configuration. The ECG signal was high-pass filtered (0.5 Hz).
(e) Psychophysiological data analysis
A customized Cþþ-based semi-automated PC program was used
on a WinXP platform to analyse EMG responses offline. The algor-
ithm identified response peaks in the rectified and integrated
signal in the time interval of 20– 150 ms after the startle probe
onset. The baseline period was defined by a 50 ms interval
prior to acoustic stimulation. All response data were manually
inspected. Signals with electrical and physiological artefacts,
such as coinciding blinks or excessive noise from other facial mus-
cular activity, were rejected from analysis and defined as missing.
If a participant’s responses were not visible in their individual
response latency range, the response amplitude was set to zero.
Zero response data were included in the averaging procedure,
with startle response magnitude as the final output measure [46].
Averaging was carried out per subject separately for each respi-
ratory phase and breathing instruction condition. Within each
participant, startle response magnitudes were T-scored over all
four respiratory phases and both breathing instruction conditions.
Respiratory cycles were automatically detected with WinCPRS
software (Absolute Aliens Oy, Turku, Finland) and manually
confirmed, from which breathing frequency data were derived.
Arbitrary units as results of the raw respiratory belt signal were lin-
early transformed into millilitres based on individual values in
standardization trials at the beginning of each session. Tidal
volume as derived from these transformed values is denoted as
‘adjusted’ tidal volume.
(f ) Distribution of startle stimuli across the cardiac cycle
(control analyses)
In previous studies, we observed lower startle responses during
the early when compared with the late cardiac cycle phase (i.e.
CMS) [8– 13]. To rule out that this CMS effect may have affected
the hypothesized respiratory modulation of startle, we investi-
gated in separate analyses any interaction effects of cardiac cycle
and respiratory cycle phase on startle responses. While in earlier
studies on CMS precise time points relative to the cardiac R-
wave (e.g. 230 and 530 ms after R-wave) were used [9,10,12,13],
in this study, we identified specific events during the respiratory
cycle. As it is very unlikely that events in both physiological signals
(e.g. peak inspiration and R-wave þ230 ms) occur exactly at the
same point in time, it is impossible to presentstartle stimulidepen-
dent on events in both physiological signals simultaneously. To
overcome this problem, we presented startle stimuli only depen-
dent on the respiratory cycle, but evaluated the latency to the
preceding R-wave offline to determine the cardiac cycle phase of
each startle stimulus. Based on the summary by Edwards et al.
[49] on the timing of arterial baroreceptor stimulation by the arter-
ial pulse wave, we considered the time period of 90–390 ms after
the R-wave the ‘early cardiac cycle phase’, while the remaining
interval was considered the ‘late cardiac cycle phase’. We evalu-
ated the number of startle stimuli appearing in the early and in
the late cardiac cycle phase and the average latency of startle
stimuli to the preceding R-wave for each of the respiratory cycle
phases. In agreement with this period as suggested by Edwards
et al. representing arterial baroreceptor stimulation, we previously
observed lower startle stimuli in a largely overlapping interval
(100– 400 ms after the R-wave) when compared with the late car-
diac cycle phase [9]. Furthermore, we introduced cardiac cycle
phase as additional factor in our analysis to investigate whether
it interferes with the respiratory cycle phase in its effect on startle.
(g) Statistical analysis
To evaluate the impact of the respiratory phases on startle, we
employed a repeated-measurements 4 2 ANOVA with the
T-scored startle response magnitude as a dependent variable.
The factors were ‘respiratory phase’ (peak expiration, midpoint
during on-going inspiration, peak inspiration, midpoint during
on-going expiration) and ‘breathing instruction’ (spontaneous
versus paced breathing). The same 4 2 ANOVA was calculated
to evaluate (i) the number of startle stimuli, which had occurred
by chance during the early and (ii) the late cardiac cycle phase,
and (iii) the average latency between startle stimulus and preced-
ing R-wave for each of the respiratory phases and breathing
conditions. A separate 4 22 repeated-measurements ANOVA
was employed with the additional within-subjects factor ‘cardiac
cycle phase’ and the T-scored startle responses as dependent vari-
able to determine if the cardiac cycle phases systematically
rstb.royalsocietypublishing.org Phil. Trans. R. Soc. B 371: 20160019
4
on October 10, 2016http://rstb.royalsocietypublishing.org/Downloaded from

affected startle responses across respiratory conditions. Respiratory
parameters (tidal volume, breathing frequency) across conditions
with different breathing instructions were compared using a one-
factorial two-levelled repeated-measurements ANOVA comprising
the factor ‘breathing instruction’. Critical alpha-level was set to
0.05 in all analyses. All p-values of within-subject factors with
more than two conditions are reported after Greenhouse–Geisser
correction. Post hoc analyses of simple main effects within the
ANOVA-models were performed with dependent t-tests.
(h) Analysis of pilot data
Beat-to-beat inter-beat interval (IBI), blood pressure (assessed
with a Finapres System, Ohmeda Corp., USA) and thoracic impe-
dance derived respiratory data reflecting lung volume changes of
10 healthy control subjects with a distribution of age and sex
comparable to those in the main study (4 m/6 f; mean age:
25.9 years) were taken from a previous study, in which paced res-
piration was performed at various frequencies, ranging between
0.15 and 0.4 Hz [50]. IBI, blood pressure and respiratory data
were resampled with 5 Hz and adjusted to individual averages.
Comparisons according to four time points of the respiratory
cycle (figure 3) were performed. At a paced breathing frequency
of 0.25 Hz, the difference between systolic blood pressure levels
at ‘on-going inspiration’ (breathing phase ‘II’; 0.27 [95% CI:
20.28 to 0.83] mmHg) and ‘on-going expiration’ (breathing
phase ‘IV’; 20.22 [95% CI: 20.79 to 0.35] mmHg) was minimal.
This finding is in line with Laude et al. [51] demonstrating a syn-
chronization of respiration and blood pressure in higher
breathing frequencies. We, therefore, used a paced breathing con-
dition of 0.25 Hz to minimize blood pressure differences between
on-going inspiration and expiration.
3. Results
(a) Startle eye blink responses
Startle response magnitudes did not differ between
spontaneous and paced breathing conditions (F
1,41
,1).
Nevertheless, we observed a significant main effect of ‘respi-
ratory phase’ on startle responses (F
3,123
¼6.17; p¼0.001;
h
2
¼0.13; figure 4). Post hoc analyses revealed that startle
response magnitudes were higher during on-going expiration
(M¼52.99 [s.e.m. ¼0.83]) compared with peak inspiration
(47.60 [0.77]), peak expiration (49.41 [0.72]) and on-going
inspiration (50.00 [0.80]; all ps,0.01). There was no interaction
effect of ‘respiratory phase’ and ‘breathing instruction’ on star-
tle responses (F
3,123
,1). In an exploratory analysis, we
additionally entered ‘sex’ as between-subjects factor into the
ANOVA model. While the main effect of ‘respiratory phase’
on startle responses remained (F
3,120
¼7.54; p,0.001;
h
2
¼
0.16), there was no significant interaction of the factor ‘sex’
with any other variable. The main effect also remained signifi-
cant when the ANOVA was re-calculated with raw startle eye
blink responses (F
3,123
¼4.03; p¼.01;
h
2
¼0.18; see electronic
supplementary material, S2).
(b) Control analyses of cardiac cycle phases
Across the four respiratory phases and both breathing con-
ditions, the number of startles presented in the early and in
the late cardiac cycle phase did not differ (main effects and
interaction effect: all ps.0.10; peak expiration: 3.6 early/
6.4 late [0.18]; on-going inspiration: 4.0/6.0 [0.20]; peak inspi-
ration: 4.1/5.8 [0.19] and on-going expiration: 3.9/6.1 [0.18]).
There was a main effect, however, of ‘respiratory phase’ on
the average latency to the preceding R-wave (F
3,123
¼5.71;
p¼0.002;
h
2
¼0.12). The post hoc analysis showed that this
effect was due to a significantly shorter latency at ‘peak inspi-
ration’ (374.0 [9.1] ms) compared with all other respiratory
phases (peak expiration: 418.7 [12.5]; on-going inspiration:
413.0 [14.6] and on-going expiration: 402.6 [12.1] ms; all
ps,0.05). When introducing ‘cardiac cycle’ (early/late) as
additional factor in the ANOVA to evaluate the impact on
startle responses, we again found the main effect of the ‘res-
piratory phase’ on startle (F
3,123
¼4.09; p¼0.01;
h
2
¼0.09).
Neither a main effect of the ‘cardiac cycle phase’ on startle
nor an interaction of the cardiac cycle phase with any other
factor was observed (all ps.0.05).
(c) Respiratory parameters
Adjusted tidal volume was higher in paced breathing (421.3
[29.9] ml) than during spontaneous breathing (326.9 [21.1] ml;
60
40
RSP (aU)-IBI (ms)-BP (mmHg ×10
–1
)
20
0
–20
–40
–60
0 1000
I II III IV
2000 3000
IBI
SBP
DBP
RSP
t (ms) in res
p
. c
y
cle
4000
Figure 3. Pilot data on the time course of inter-beat interval (IBI) length,
and systolic and diastolic blood pressure (SBP, DBP) across the respiratory
cycle at 0.25 Hz paced breathing (RSP, respiration). Note that at this breathing
frequency there were comparable systolic and diastolic blood pressures during
on-going inspiration (II) and on-going expiration (IV).
peak expiration
on-going inspiration
on-going expiration
peak inspiration
res
p
irator
y
p
hase
*
spontaneous breathing
startle response magnitude (T-scores)
56
54
52
50
48
46
paced breathing (0.25 Hz)
Figure 4. Startle response magnitudes (T-scored) for all four time points
within the respiratory cycle. Higher startle responses were found during
on-going expiration as compared to all other time points. Error bars represent
s.e.m.
rstb.royalsocietypublishing.org Phil. Trans. R. Soc. B 371: 20160019
5
on October 10, 2016http://rstb.royalsocietypublishing.org/Downloaded from

F
1,41
¼15.87; p,0.001;
h
2
¼0.28). Breathing frequency did not
differ between the two breathing conditions (spontaneous: 0.261
[0.003] Hz; paced: 0.259 [0.002] Hz; F
1,41
¼1.37; p¼0.25;
table 1). Additional analyses, using tidal volume as a covariate
in the statistical model on startle eye blink, are reported in
electronic supplementary material, S3.
4. Discussion
The aim of this study was to investigate whether respiration
affects human startle responsiveness. Indeed, higher startle
responses were observed during on-going expiration in com-
parison with all other time points investigated. This effect
was independent of spontaneous or paced breathing con-
ditions, although higher adjusted tidal volumes were found
during paced compared with spontaneous breathing.
These findings clearly demonstrate that respiration modu-
lates startle responses elicited by acoustic noise bursts. This
effect was independent of the breathing condition, e.g.
whether breathing instructions were applied, or not. During
spontaneous breathing, the generation of breathing rhythms
is mostly automatically operated by brainstem centres in
the pons, rostral and ventral medulla (e.g. pre-Bo
¨tzinger
and Bo
¨tzinger complex) [52,53], whereas in paced breathing,
higher cortical structures (e.g. supplementary motor area,
cortico-subcortical network) are taking control over these
brainstem centres [54,55]. The observed independence of
the respiratory startle modulation from breathing conditions
suggests, therefore, that neither automatic nor consciously
controlled efferent motor code generation are a prerequisite
of the observed effect. Two possible processes may contribute
to the effect of respiration on startle responsiveness: (i) affer-
ent neural input from slow adapting pulmonary stretch
receptors and (ii) an indirect effect of respiration on cardio-
vascular haemodynamics and respiratory sinus arrhythmia.
In analogy to the CMS (which is associated with afferent
input from arterial baroreceptors [9]), respiratory modulation
of startle may also be associated with afferent input from a
specific receptor type. One candidate is the slow adapting
pulmonary stretch receptor (SAR), which responds to transi-
ent changes in lung volume and to maintained inflation [56],
and is mainly located in the trachea and main stem bronchi
[57]. SARs may be further subdivided into low-threshold or
tonic SARs, which respond to the absolute lung volume
and are thus active at inspiration and expiration, and high-
threshold or phasic SARs, which are sensitive to changes
only during inspiration [56,58,59]. The stimulation of phasic
SARs starts with inspiration and is maintained until peak
inspiration is reached. The discharge of tonic SARs is linearly
related to the total lung volume, which implies comparable
stimulation during on-going inspiration and on-going expira-
tion, highest stimulation at peak inspiration and lowest
stimulation at peak expiration [58,59]. Because we observed
higher startle response magnitudes during on-going expir-
ation when compared with all other time points, the
explanation for this result may lie in a process that is specific
for the midpoint during expiration. On the one hand, it could
be argued that the relative unloading of phasic SARs, which
is uniquely observed during on-going expiration, is respon-
sible for the observed effects. On the other hand, the
interaction of tonic and phasic SARs may account for the res-
piratory modulation of startle. In particular, the stimulation
of tonic SARs may only enhance startle modulation if there
is no additional discharge of phasic SARs (i.e. on-going
expiration), in contrast to time points, during which a dis-
charge of phasic SARs can be observed (i.e. on-going
inspiration, peak inspiration).
Afferent neural traffic from SARs is transmitted over the
vagus nerve to the nucleus tractus solitarius (NTS) that con-
nects with the nucleus ambiguus and nucleus paraambiguus
to control motor output of respiratory muscles and airway
smooth muscles [58]. The NTS projects onto the parabrachial
nucleus and nucleus coeruleus, from where higher limbic
structures are reached [60]. At a cortical level, the sensory
cortex and the association cortex are involved in the processing
of afferent signals from the respiratory system [20,33]. The eye
blink startle response is a defence reflex that can be observed
when an organism is confronted with an intense stimulus
(e.g. loud noise) and whose amplitude is modulated by a
number of psychological (e.g. emotion [61], attention [62])
and physiological factors (e.g. neural [9] and endocrine signal
input [63]). These factors affect neural transmission of the pri-
mary acoustic startle circuit at the nucleus reticularis pontis
caudalis (NRPC) mediated over limbic and tegmental brain
structures [64]. In the earlier established CMS effect, we pro-
posed that visceral-afferent information from the NTS may be
transmitted to the NRPC [9]. Because afferent information
originating from the cardiovascular and respiratory system
share neural structures, it is plausible that this possible connec-
tion between the NTS and the NRPC may also be involved
in the respiratory modulation of startle. We conclude that star-
tle methodology is useful to examine afferent neural signal
transmission from the respiratory system.
Respiratory modulation of startle may also be explained by
respiratory effects on the cardiovascular system. During on-
going inspiration, the parasympathetic output via the vagal
nerve is reduced in order to increase pulmonary blood cir-
culation and gas exchange. Vice versa, vagal output during
expiration is increased. Because these oscillations in vagal
output induce an increase of heart rate during inspiration
and a decrease during expiration, this mechanism is called ‘res-
piratory sinus arrhythmia’ [65]. The increase of heart rate
during inspiration is then followed by an increase in systolic
and diastolic blood pressure [51,66,67]. As there is a time
delay of some seconds between the respective maxima in
heart rate and blood pressure, breathing frequency largely
determines the precise temporal location of the blood pres-
sure maximum within the respiratory cycle. Interestingly, as
Table 1. Mean tidal volume (based on standardization trials) and
breathing frequency during conditions of spontaneous and paced breathing.
spontaneous
breathing
paced
breathing
(0.25 Hz)
Ms.d. Ms.d.
measure unit
tidal volume
a
ml 326.9 136.6 421.3 194.0
breathing
frequency
Hz 0.261 0.018 0.259 0.014
a
Paced .spontaneous breathing (F
1,41
¼27.47; p,0.001;
h
2
¼0.40).
rstb.royalsocietypublishing.org Phil. Trans. R. Soc. B 371: 20160019
6
on October 10, 2016http://rstb.royalsocietypublishing.org/Downloaded from

indicated by the results of our pilot data, at 0.25 Hz breathing
there is no difference in blood pressure between on-going
inspiration and expiration. This finding suggests that differ-
ences in blood pressure and possibly arterial baroreceptor
stimulation do not play a role for the higher startle responses
during on-going expiration.
The question remains if startle stimuli were not distributed
equally across the cardiac cycles in the different respiratory
phases and breathing conditions. On the one hand, the results
show average latencies to preceding R-waves to be lower at
maximal inspiration when compared with all other conditions,
which may be explained with the observed higher heart rates
during inspiration. On the other hand, there was no difference
between the most relevant condition ‘on-going expiration’ and
the other conditions. Interestingly, and in contrast to the
shorter latency at peak inspiration, the frequency of startle pre-
sentations between the early and late cardiac cycle phase did
not differ between respiratory phases and breathing con-
ditions. As opposed to earlier observations [8–10,12,13], our
separate analysis on startle responses with ‘cardiac cycle
phase’ as an additional factor indicated no effect of the cardiac
cycle on startle responses, which may be due to the fact that the
number of valid startle responses in the early versus late car-
diac cycle varied between 1 : 9 and 9 : 1. Importantly, there
was no interaction of cardiac cycle phase with respiratory
phase or breathing condition. This suggests that different
ratios of duration between the early and late cardiac cycle
phases across the four respiratory cycles did not systematically
affect startle responses. CMS is, therefore, unlikely to have con-
tributed to the observed respiratory modulation of startle
effect, as there was a comparable number of startle stimuli in
the early versus late cardiac cycle phase and the observed
main effect in latencies to the preceding R-wave was only
owing to shorter latencies at ‘peak inspiration’, but not to
‘on-going expiration’.
The precision of detecting specific phases within the res-
piratory cycle may represent a crucial factor for the validity
of findings. Given the current lack of mathematic algorithms,
which sensitively and specifically detect respiratory phases,
the majority of previous studies has followed one of two
strategies: (i) the authors present stimuli without any contin-
gency to respiratory phases, assuming an equal distribution,
and assign trials later to respiratory phases in offline analyses
depending on predefined criteria [39,40] or (ii) an exper-
imenter continuously monitors respiratory activity and
manually elicits the presentation of stimuli depending on
current respiratory phase [36]. For future research, the pre-
sent algorithm may help to increase the precision in the
temporal location of stimulus presentation depending on
the respiratory cycle.
(a) Limitations
Owing to the non-invasive character of this study, we did not
experimentally manipulate SARs to determine if they play a
role in the observed effects. Further investigations of humans
with altered SAR function (e.g. in pulmonary disorders) or
their experimental manipulation in animals may be required
to reveal if they represent a critical factor for the respiratory
modulation of startle. The possible involvement of brain struc-
tures in the cardiac and respiratory modulation of startle is
based on theoretical considerations and may require the
additional support of systematic lesion studies in animals.
In the main study, we included only one paced breathing
frequency of 0.25 Hz, based on the findings of comparable
blood pressure during on-going inspiration and on-going
expiration. Moreover, the mean breathing frequency in the
spontaneous breathing condition did not significantly differ
from 0.25 Hz. These findings, therefore, may be limited to
this particular frequency. Future studies are suggested to
include multiple breathing frequencies. The concurrent moni-
toring of EMG, ECG and blood pressure in the main study
would have been desirable. We included blood pressure in
a pilot sample and decided against using beat-to-beat blood
pressure assessment in the main study as this technique
implies continuous somatosensory feedback, which may act
as pre-pulses for the subsequent processing of startle stimuli.
Although the demographics of the pilot sample were almost
identical to those in the main study, conclusions on blood
pressure responses in the main study remain speculative.
The reliability of the control analysis on cardiac and
respiratory modulation of startle may be limited owing to
the low number of valid startle responses in some cells.
Finally, the estimation of tidal volume was based on data
assessed using a respiratory belt and calibrated with standar-
dized air inhalation of 1, 2 and 3 l. Despite the fact that (i) this
procedure was repeatedly described as providing acceptable
results for volume estimation [68,69], and (ii) the data as
provided by the breathing belt show a strong positive corre-
lation with tidal volume, it needs to be acknowledged that
this technique may be less precise when compared with
spirometric measures.
5. Conclusion
The effect of respiratory modulation of startle suggests that
startle method is potentially useful for the investigation of
afferent neural signal transmission from the respiratory
system. The independence of the respiratory startle modu-
lation from the breathing conditions suggests that neither
automatic nor consciously controlled efferent motor code
generation are a prerequisite of the observed effect.
Ethics. Study procedures were approved by the local ethics committee
at the University of Trier.
Data accessibility. Data sheet including startle response magnitudes,
breathing frequency, adjusted tidal volume and all control analyses
depending on cardiac cycle phases is available as electronic
supplementary material, S1.
Authors’ contributions. A.S. and H.S. conceived the study idea and
designed the study. A.S. and T.M.S. performed data collection.
A.S., C.V., M.F.L. and H.S. analysed the data. A.S., T.M.S., C.V.,
M.F.L. and H.S. authored the manuscript.
Competing interests. The authors declare that they have no potential
conflict of interest.
Funding. This project was supported by the Research Funds of the
University of Trier (PI: Andre
´Schulz). The Research Office of the Uni-
versity of Trier had no further role in the study design, in the
collection, analysis and interpretation of data, in the writing of the
report, and in the decision to submit the paper for publication.
Acknowledgements. We thank Christoph Kinzig for the programming of
the DASYLab-based algorithm, Dr Immo Curio for employing the
algorithm in our laboratory devices, Alexandra H. Gra
¨bener and
Maria R. Barthmes for their help in data collection, Miriam-Linnea
Hale for her help in data analysis, as well as Dr Paul Davenport
for his literature suggestions.
rstb.royalsocietypublishing.org Phil. Trans. R. Soc. B 371: 20160019
7
on October 10, 2016http://rstb.royalsocietypublishing.org/Downloaded from

References
1. Barrett LF, Quigley KS, Bliss-Moreau E, Aronson KR.
2004 Interoceptive sensitivity and self-reports of
emotional experience. J. Pers. Soc. Psychol. 87,
684–697. (doi:10.1037/0022-3514.87.5.684)
2. Fustos J, Gramann K, Herbert BM, Pollatos O. 2013
On the embodiment of emotion regulation:
interoceptive awareness facilitates reappraisal. Soc.
Cogn. Affect. Neurosci. 8, 911– 917. (doi:10.1093/
scan/nss089)
3. Grynberg D, Pollatos O. 2015 Perceiving one’s body
shapes empathy. Physiol. Behav. 140, 54– 60.
(doi:10.1016/j.physbeh.2014.12.026)
4. Schandry R. 1981 Heart beat perception and
emotional experience. Psychophysiology 18,
483–488. (doi:10.1111/j.1469-8986.1981.tb02486.x)
5. Whitehead WE, Drescher VM, Heiman P, Blackwell
B. 1977 Relation of heart rate control to heartbeat
perception. Biofeedback Self-Regul. 2, 371– 392.
(doi:10.1007/BF00998623)
6. Schulz A, Lass-Hennemann J, Sutterlin S, Scha
¨chinger
H, Vo
¨gele C. 2013 Cold pressor stress induces opposite
effects on cardioceptive accuracy dependent on
assessment paradigm. Biol. Psychol. 93, 167– 174.
(doi:10.1016/j.biopsycho.2013.01.007)
7. Vaitl D. 1996 Interoception. Biol. Psychol. 42, 1– 27.
(doi:10.1016/0301-0511(95)05144-9)
8. Richter S, Schulz A, Port J, Blumenthal TD,
Schachinger H. 2009 Cardiopulmonary baroreceptors
affect reflexive startle eye blink. Physiol. Behav. 98,
587–593. (doi:10.1016/j.physbeh.2009.09.010)
9. Schulz A, Lass-Hennemann J, Nees F, Blumenthal
TD, Berger W, Scha
¨chinger H. 2009 Cardiac
modulation of startle eye blink. Psychophysiology
46, 234–240. (doi:10.1111/j.1469-8986.2008.
00768.x)
10. Schulz A, Lass-Hennemann J, Richter S, Romer S,
Blumenthal TD, Schachinger H. 2009 Lateralization
effects on the cardiac modulation of acoustic startle
eye blink. Biol. Psychol. 80, 287– 291. (doi:10.1016/
j.biopsycho.2008.10.006)
11. Schulz A, Matthey JH, Vo
¨gele C, Schaan V,
Scha
¨chinger H, Adler J, Beutel ME, Michal M. 2016
Cardiac modulation of startle is altered in
depersonalization-/derealization disorder: evidence
for impaired brainstem representation of baro-
afferent neural traffic. Psychiatry Res. 240, 4– 10.
(doi:10.1016/j.psychres.2016.03.051)
12. Schulz A, Plein DE, Richter S, Blumenthal TD,
Scha
¨chinger H. 2011 Cold pressor stress affects
cardiac attenuation of startle. Int. J. Psychophysiol.
79, 385–391. (doi:10.1016/j.ijpsycho.2010.12.008)
13. Schulz A, Reichert CF, Richter S, Lass-Hennemann J,
Blumenthal TD, Schachinger H. 2009 Cardiac
modulation of startle: effects on eye blink and
higher cognitive processing. Brain Cogn. 71,
265–271. (doi:10.1016/j.bandc.2009.08.002)
14. Dworkin BR. 2007 Interoception. In Handbook of
psychophysiology, 3rd edn (eds JT Cacioppo,
LG Tassinary, GG Berntson), pp. 482– 506.
Cambridge, UK: Cambridge University Press.
15. Bonnel AM, Mathiot MJ, Grimaud C. 1985
Inspiratory and expiratory resistive load detection in
normal and asthmatic subjects. A sensory decision
theory analysis. Respiration 48, 12– 23. (doi:10.
1159/000194793)
16. Dahme B, Richter R, Mass R. 1996 Interoception of
respiratory resistance in asthmatic patients. Biol.
Psychol. 42, 215– 229. (doi:10.1016/0301-0511
(95)05156-2)
17. Davenport KL, Huang CH, Davenport MP, Davenport
PW. 2012 Relationship between respiratory load
perception and perception of nonrespiratory sensory
modalities in subjects with life-threatening
asthma. Pulmon. Med. 2012, 310672. (doi:10.1155/
2012/310672)
18. Isenberg S, Lehrer P, Hochron S. 1997 Defensiveness
and perception of external inspiratory resistive loads
in asthma. J. Behav. Med. 20, 461– 472. (doi:10.
1023/A:1025551532756)
19. Gottfried SB, Redline S, Altose MD. 1985 Respiratory
sensation in chronic obstructive pulmonary disease.
Am. Rev. Respir. Dis. 132, 954–959. (doi:10.1164/
arrd.1985.132.5.954)
20. O’Donnell DE, Banzett RB, Carrieri-Kohlman V,
Casaburi R, Davenport PW, Gandevia SC, Gelb AF,
Mahler DA, Webb KA. 2007 Pathophysiology of
dyspnea in chronic obstructive pulmonary disease:
a roundtable. Proc. Am. Thorac. Soc. 4, 145– 168.
(doi:10.1513/pats.200611-159CC)
21. von Leupoldt A, Dahme B. 2007 Psychological
aspects in the perception of dyspnea in obstructive
pulmonary diseases. Respir. Med. 101, 411–422.
(doi:10.1016/j.rmed.2006.06.011)
22. Giardino ND, Curtis JL, Abelson JL, King AP, Pamp B,
Liberzon I, Martinez FJ. 2010 The impact of panic
disorder on interoception and dyspnea reports in
chronic obstructive pulmonary disease. Biol. Psychol.
84, 142– 146. (doi:10.1016/j.biopsycho.2010.02.007)
23. Livermore N, Butler JE, Sharpe L, McBain RA,
Gandevia SC, McKenzie DK. 2008 Panic attacks and
perception of inspiratory resistive loads in chronic
obstructive pulmonary disease. Am. J. Respir. Crit.
Care Med. 178, 7– 12. (doi:10.1164/rccm.200711-
1700OC)
24. Vogele C, von Leupoldt A. 2008 Mental disorders in
chronic obstructive pulmonary disease (COPD).
Respir. Med. 102, 764–773. (doi:10.1016/j.rmed.
2007.12.006)
25. Paulus MP. 2013 The breathing conundrum—
interoceptive sensitivity and anxiety. Depress.
Anxiety 30, 315–320. (doi:10.1002/da.22076)
26. Davenport PW, Friedman WA, Thompson FJ, Franzen
O. 1986 Respiratory-related cortical potentials
evoked by inspiratory occlusion in humans. J. Appl.
Physiol. (1985)60, 1843– 1848.
27. Pappens M, Van den Bergh O, Vansteenwegen D,
Ceunen E, De Peuter S, Van Diest I. 2013 Learning
to fear obstructed breathing: comparing
interoceptive and exteroceptive cues. Biol. Psychol.
92, 36– 42. (doi:10.1016/j.biopsycho.2011.05.004)
28. Acheson DT, Forsyth JP, Prenoveau JM, Bouton ME.
2007 Interoceptive fear conditioning as a learning
model of panic disorder: an experimental evaluation
using 20% CO
2
-enriched air in a non-clinical
sample. Behav. Res. Ther. 45, 2280– 2294. (doi:10.
1016/j.brat.2007.04.008)
29. Pappens M, De Peuter S, Vansteenwegen D, Van
den Bergh O, Van Diest I. 2012 Psychophysiological
responses to CO
2
inhalation. Int. J. Psychophysiol.
84, 45– 50. (doi:10.1016/j.ijpsycho.2012.01.008)
30. Holtz K, Pane-Farre CA, Wendt J, Lotze M, Hamm
AO. 2012 Brain activation during anticipation of
interoceptive threat. NeuroImage 61, 857–865.
(doi:10.1016/j.neuroimage.2012.03.019)
31. Melzig CA, Holtz K, Michalowski JM, Hamm AO.
2011 Interoceptive threat leads to defensive
mobilization in highly anxiety sensitive persons.
Psychophysiology 48, 745– 754. (doi:10.1111/j.
1469-8986.2010.01150.x)
32. Melzig CA, Michalowski JM, Holtz K, Hamm AO.
2008 Anticipation of interoceptive threat in highly
anxiety sensitive persons. Behav. Res. Ther. 46,
1126–1134. (doi:10.1016/j.brat.2008.07.002)
33. von Leupoldt A, Chan PY, Esser RW, Davenport PW.
2013 Emotions and neural processing of respiratory
sensations investigated with respiratory-related
evoked potentials. Psychosom. Med. 75, 244– 252.
(doi:10.1097/PSY.0b013e31828251cf)
34. von Leupoldt A, Keil A, Chan PY, Bradley MM, Lang
PJ, Davenport PW. 2010 Cortical sources of the
respiratory-related evoked potential. Respir. Physiol.
Neurobiol. 170, 198– 201. (doi:10.1016/j.resp.
2009.12.006)
35. Webster KE, Colrain IM. 2000 The relationship
between respiratory-related evoked potentials and
the perception of inspiratory resistive loads.
Psychophysiology 37, 831– 841. (doi:10.1111/1469-
8986.3760831)
36. Beh HC, Nix-James DR. 1974 The relationship
between respiration phase and reaction time.
Psychophysiology 11, 400– 401. (doi:10.1111/j.
1469-8986.1974.tb00563.x)
37. Engel BT, Thorne PR, Quilter RE. 1972 On the
relationships among sex, age, response mode,
cardiac cycle phase, breathing cycle phase, and
simple reaction time. J. Gerontol. 27, 456– 460.
(doi:10.1093/geronj/27.4.456)
38. Gallego J, Perruchet P, Camus JF. 1991 Assessing
attentional control of breathing by reaction time.
Psychophysiology 28, 217– 224. (doi:10.1111/j.
1469-8986.1991.tb00413.x)
39. Hildebrandt G, Engel P. 1963 Der Einfluß des
Atemrhythmus auf die Reaktionszeit. Pflu
¨gers
Archiv. 278, 113–129. (doi:10.1007/BF00362684)
40. Buchsbaum M, Callaway E. 1965 Influences of
respiratory cycle on simple reaction time. Percept. Motor
Skills 20, 961– 966. (doi:10.2466/pms.1965.20.3.961)
41. Gaskill HV. 1928 The relation of reaction time to
phase of breathing. J. Exp. Psychol. 11, 364– 369.
(doi:10.1037/h0073936)
rstb.royalsocietypublishing.org Phil. Trans. R. Soc. B 371: 20160019
8
on October 10, 2016http://rstb.royalsocietypublishing.org/Downloaded from

42. Flexman JE, Demaree RG, Simpson DD. 1974
Respiratory phase and visual signal detection.
Percept. Psychophys. 16, 337– 339. (doi:10.3758/
BF03203952)
43. Callaway 3rd E, Buchsbaum M. 1965 Effects of
cardiac and respiratory cycles on averaged visual
evoked responses. Electroencephalogr. Clin.
Neurophysiol. 19, 476– 480. (doi:10.1016/0013-
4694(65)90186-0)
44. Gokin AP, Karpukhina MV. 1986 Respiratory
modulation of startle reflexes in the cat.
Neurophysiology 18, 593– 603.
45. Blumenthal TD. 1999 Short lead interval
modification. In Startle modification. Implications for
neuroscience, cognitive science, and clinical science
(eds ME Dawson, AM Schell, AH Bo
¨hmelt), pp. 51–
71. Cambridge, UK: Cambridge University Press.
46. Blumenthal TD, Cuthbert BN, Filion DL, Hackley S,
Lipp OV, van Boxtel A. 2005 Committee report:
guidelines for human startle eyeblink
electromyographic studies. Psychophysiology 42,
1– 15. (doi:10.1111/j.1469-8986.2005.00271.x)
47. van Boxtel A, Boelhouwer AJ, Bos AR. 1998 Optimal
EMG signal bandwidth and interelectrode distance
for the recording of acoustic, electrocutaneous, and
photic blink reflexes. Psychophysiology 35,
690–697. (doi:10.1111/1469-8986.3560690)
48. Blumenthal TD. 1994 Signal attenuation as a
function of integrator time constant and signal
duration. Psychophysiology 31, 201– 203. (doi:10.
1111/j.1469-8986.1994.tb01041.x)
49. Edwards L, Ring C, McIntyre D, Winer JB, Martin U.
2009 Sensory detection thresholds are modulated
across the cardiac cycle: evidence that cutaneous
sensibility is greatest for systolic stimulation.
Psychophysiology 46, 252– 256. (doi:10.1111/j.
1469-8986.2008.00769.x)
50. Kuehl LK, Deuter CE, Richter S, Schulz A, Ruddel H,
Schachinger H. 2015 Two separable mechanisms are
responsible for mental stress effects on high
frequency heart rate variability: an intra-individual
approach in a healthy and a diabetic sample.
Int. J. Psychophysiol. 95, 299– 303. (doi:10.1016/j.
ijpsycho.2014.12.003)
51. Laude D, Goldman M, Escourrou P, Elghozi JL. 1993
Effect of breathing pattern on blood pressure and
heart rate oscillations in humans. Clin. Exp.
Pharmacol. Physiol. 20, 619– 626. (doi:10.1111/j.
1440-1681.1993.tb01643.x)
52. Lorig TS. 2007 Respiration. In Handbook of
psychophysiology, 3rd edn (eds JT Cacioppo, LG
Tassinary, GG Berntson), pp. 231– 244. Cambridge,
UK: Cambridge University Press.
53. Ramirez JM, Zuperku EJ, Alheid GF, Lieske SP, Ptak
K, McCrimmon DR. 2002 Respiratory rhythm
generation: converging concepts from in vitro
and in vivo approaches? Respir. Physiol.
Neurobiol. 131, 43– 56. (doi:10.1016/S1569-
9048(02)00036-8)
54. Cohen E, Murphy K, Adams L, Guz A, Benchetrit G.
1995 Is voluntary control of breathing impaired in
patients with chronic obstructive pulmonary
disease? Clin. Sci. (Lond.)88, 453– 461. (doi:10.
1042/cs0880453)
55. Haouzi P, Chenuel B, Barroche G. 2006 Interactions
between volitional and automatic breathing during
respiratory apraxia. Respir. Physiol. Neurobiol. 152,
169– 175. (doi:10.1016/j.resp.2005.08.004)
56. Sant’Ambrogio G. 1982 Information arising from the
tracheobronchial tree of mammals. Physiol. Rev. 62,
531– 569.
57. Widdicombe JG. 1954 Receptors in the trachea and
bronchi of the cat. J. Physiol. 123, 71– 104. (doi:10.
1113/jphysiol.1954.sp005034)
58. Schelegle ES. 2003 Functional morphology and
physiology of slowly adapting pulmonary stretch
receptors. Anatom. Rec. A 270, 11– 16. (doi:10.
1002/ar.a.10004)
59. Schelegle ES, Green JF. 2001 An overview of the
anatomy and physiology of slowly adapting
pulmonary stretch receptors. Respir. Physiol. 125,
17–31. (doi:10.1016/S0034-5687(00)00202-4)
60. Cameron OG. 2001 Interoception: the inside story—
a model for psychosomatic processes. Psychosom.
Med. 63, 697– 710. (doi:10.1097/00006842-
200109000-00001)
61. Davis M. 2006 Neural systems involved in fear and
anxiety measured with fear-potentiated startle. Am.
Psychol. 61, 741– 756. (doi:10.1037/0003-066X.61.
8.741)
62. Lang PJ, Bradley MM, Cuthbert BN. 1990 Emotion,
attention, and the startle reflex. Psychol. Rev. 97,
377–395. (doi:10.1037/0033-295X.97.3.377)
63. Roemer S, Nees F, Richter S, Blumenthal TD,
Schachinger H. 2009 Endogenous cortisol
suppression with metyrapone enhances acoustic
startle in healthy subjects. Horm. Behav. 55,
314–318. (doi:10.1016/j.yhbeh.2008.11.003)
64. Koch M. 1999 The neurobiology of startle. Prog.
Neurobiol. 59, 107– 128. (doi:10.1016/S0301-
0082(98)00098-7)
65. Grossman P, Taylor EW. 2007 Toward understanding
respiratory sinus arrhythmia: relations to cardiac
vagal tone, evolution and biobehavioral functions.
Biol. Psychol. 74, 263– 285. (doi:10.1016/j.
biopsycho.2005.11.014)
66. Kotani K, Takamasu K, Jimbo Y, Yamamoto Y. 2008
Postural-induced phase shift of respiratory sinus
arrhythmia and blood pressure variations: insight
from respiratory-phase domain analysis.
Am. J. Physiol. Heart Circ. Physiol. 294, H1481–
H1489. (doi:10.1152/ajpheart.00680.2007)
67. Sin PY, Galletly DC, Tzeng YC. 2010 Influence of
breathing frequency on the pattern of respiratory
sinus arrhythmia and blood pressure: old questions
revisited. Am. J. Physiol. Heart Circ. Physiol. 298,
H1588–H1599. (doi:10.1152/ajpheart.00036.2010)
68. Carry PY, Baconnier P, Eberhard A, Cotte P,
Benchetrit G. 1997 Evaluation of respiratory
inductive plethysmography: accuracy for analysis of
respiratory waveforms. Chest 111, 910– 915.
(doi:10.1378/chest.111.4.910)
69. Stromberg NO, Dahlback GO, Gustafsson PM. 1993
Evaluation of various models for respiratory
inductance plethysmography calibration. J. Appl.
Physiol. (1985)74, 1206– 1211.
rstb.royalsocietypublishing.org Phil. Trans. R. Soc. B 371: 20160019
9
on October 10, 2016http://rstb.royalsocietypublishing.org/Downloaded from