ArticlePDF Available

An Exploratory Investigation of Pupillometry As a Measure of Tinnitus Intrusiveness on a Test of Auditory Short-Term Memory

Authors:

Abstract

Objectives: The purpose of the current study was to investigate the potential of pupillometry to provide an objective measure of competition between tinnitus and external sounds during a test of auditory short-term memory. Design: Twelve participants with chronic tinnitus and twelve control participants without tinnitus took part in the study. Pretest sessions used an adaptive method to estimate listeners' frequency discrimination threshold on a test of delayed pitch discrimination for pure tones. Target and probe tones were presented at 72 dB SPL and centered on 750 Hz±2 semitones with an additional jitter of 5 to 20 Hz. Test sessions recorded baseline pupil diameter and task-related pupillary responses (TEPRs) during three blocks of delayed pitch discrimination trials. The difference between target and probe tones was set to the individual's frequency detection threshold for 80% response-accuracy. Listeners with tinnitus also completed the Tinnitus Handicap Inventory (THI). Linear mixed effects procedures were applied to examine changes in baseline pupil diameter and TEPRs associated with group (tinnitus versus control), block (1 to 3) and their interaction. The association between THI scores and maximum TEPRs was assessed using simple linear regression. Results: Patterns of baseline pupil dilation across trials diverged in listeners with tinnitus and controls. For controls, baseline pupil dilation remained constant across blocks. For listeners with tinnitus, baseline pupil dilation increased on blocks 2 and 3 compared with block 1. TEPR amplitudes were also larger in listeners with tinnitus than controls. Linear mixed effects models yielded a significant group by block interaction for baseline pupil diameter and a significant main effect of group on maximum TEPR amplitudes. Regression analyses yielded a significant association between THI scores and TEPR amplitude in listeners with tinnitus. Conclusions: Our data indicate measures of baseline pupil diameter, and TEPRs are sensitive to competition between tinnitus and external sounds during a test of auditory short-term memory. This result suggests pupillometry can provide an objective measure of intrusion in tinnitus. Future research will be required to establish whether our findings generalize to listeners across a full range of tinnitus severity.
1
An exploratory investigation of pupillometry as a measure of
tinnitus intrusiveness on a test of auditory short-term
memory
Doug J.K. Barrett1, David Souto1, Michael Pilling2 & David M. Baguley3,4,5
1Department of Neuroscience, Psychology and Behaviour, University of Leicester,
Leicester, UK.
2Department of Psychology, Oxford Brookes University, Oxford, UK.
3Hearing Sciences, Division of Clinical Neurosciences, School of Medicine,
University of Nottingham, Nottingham, UK.
4 Nottingham NIHR Biomedical Research Centre, University of Nottingham, UK.
5 Nottingham Audiology Services, Nottingham University Hospitals NHS Trust,
Nottingham, UK.
Financial disclosures/conflict of interest: This study was funded by the University of Leicester.
There are no conflicts of interest, financial, or otherwise.
The data that support the findings of this study will be openly available via the University of
Leicester Research Repository.
All correspondence should be addressed to:
Doug J.K. Barrett, Department of Neuroscience, Psychology and Behaviour, University of
Leicester, LE1 9HN, UK. E-mail: djkb1@le.ac.uk
Abstract
1
Objectives: The purpose of the current study was to investigate the potential of pupillometry to
2
provide an objective measure of competition between tinnitus and external sounds during a test
3
of auditory short-term memory.
4
5
Design: Twelve participants with chronic tinnitus and twelve control participants without tinnitus
6
took part in the study. Pre-test sessions used an adaptive method to estimate listeners’ frequency
7
discrimination threshold on a test of delayed pitch discrimination for pure tones. Target and
8
probe tones were presented at 72 dB SPL and centred on 750 Hz. ± 2 semitones with an additional
9
jitter of 5-20 Hz. Test sessions recorded baseline pupil diameter and task related pupillary
10
response (TEPRs) during three blocks of delayed pitch discrimination trials. The difference
11
between target and probe tones was set to the individual’s frequency detection threshold for
12
80% response-accuracy. Listeners with tinnitus also completed the Tinnitus Handicap Inventory
13
(THI). Linear mixed effects procedures were applied to examine changes in baseline pupil
14
diameter and TEPRs associated with group (Tinnitus vs. Control), block (1 to 3) and their
15
interaction. The association between THI scores and maximum TEPRs was assessed using simple
16
linear regression.
17
18
Results: Patterns of baseline pupil dilation across trials diverged in listeners with tinnitus and
19
controls. For controls, baseline pupil dilation remained constant across blocks. For listeners with
20
tinnitus, baseline pupil dilation increased on blocks 2 and 3 compared to block 1. TEPR amplitudes
21
were also larger in listeners with tinnitus than controls. Linear mixed effects models yielded a
22
significant group by block interaction for baseline pupil diameter and a significant main effect of
23
group on maximum TEPR amplitudes. Regression analyses yielded a significant association
24
between THI scores and TEPR amplitude in listeners with tinnitus.
25
26
Conclusions: Our data indicate measures of baseline pupil diameter and TEPRs are sensitive to
27
competition between tinnitus and external sounds during a test of auditory short-term memory.
28
This result suggests pupillometry can provide an objective measure of intrusion in tinnitus. Future
29
research will be required to establish whether our findings generalise to listeners across a full
30
range of tinnitus severity.
31
3
Introduction
32
Tinnitus is a prevalent condition (McCormack et al., 2016), often associated with
33
substantial burden and distress, which may include anxiety, depression, and insomnia (Watts et
34
al., 2018). This represents a very significant public health problem, and the societal costs of
35
tinnitus are substantial: a UK estimate of tinnitus healthcare costs is £750 (~ $1,059 or ~€873)
36
million per year (Stockdale et al., 2017). Whilst therapies to alleviate the impact of tinnitus are
37
widely available, a cure has proved elusive (McFerran et al., 2019). One reason for this, is that at
38
present there is no reliable biomarker or objective measure of tinnitus, so treatment studies rely
39
on self-report measures whose subjective nature may obscure possible benefits of interventions.
40
Therefore, the identification and verification of an objective measure of tinnitus is an urgent
41
priority.
42
In the absence of an objective measure, the severity of tinnitus and its impact on listeners
43
is assessed primarily using self-report questionnaires. These comprise subscales that evaluate
44
distinct aspects of tinnitus, such as perceptual difficulties, emotional and cognitive distress, and
45
intrusiveness (Kennedy et al., 2005). Intrusiveness is often defined in terms of competition
46
between external sounds and the tinnitus percept during the perception and evaluation of
47
auditory information (Andersson et al., 2006; Hallam et al., 1988). Hibbert and colleagues
48
(Hibbert et al., 2020) concluded intrusiveness is dependent on tinnitus awareness,
49
unpleasantness, and its impact on everyday activities. In the current manuscript, we use
50
intrusiveness to describe the impact of tinnitus on capacity-limited cognitive resources and
51
mental effort during listening, where capacity is defined as the amount of work a system can
52
perform in a given moment (Townsend & Ashby, 1978). This impact is likely to reflect both
53
perceptual qualities of the internal percept (i.e., loudness and pitch) and the extent to which it
54
captures attention (Kennedy et al., 2005).
55
The term selective attention describes neural mechanisms that operate to prioritise
56
relevant over irrelevant sensory input, increasing the acuity of attended information and gating
57
access to capacity-limited processes including short-term memory (Choi et al., 2014; Gazzaley,
58
2011; Hillyard et al., 1998; Myers et al., 2017). Behavioural data from dichotic listening tasks and
59
the Attentional Network Test suggests listeners with tinnitus exhibit an attentional bias towards
60
the tinnitus percept during the encoding and the retention of external sounds (Cuny et al., 2004;
61
Heeren et al., 2014; Roberts et al., 2013). This attentional bias may explain the absence of
62
4
habituation in problem tinnitus (Hallam et al., 1988; Walpurger et al., 2003), with attention
63
eliciting and reinforcing plastic changes in connectivity between auditory and frontal cortex,
64
hippocampal gyri (Vanneste & De Ridder, 2012) and the limbic system (Erlandsson et al., 1992;
65
Saunders, 2007; Ueyama et al., 2013). An attentional bias towards tinnitus is also likely to impact
66
negatively on hearing; reducing the resources available to encode, maintain and evaluate
67
external sounds in short-term memory. In listeners with normal hearing, the precision of auditory
68
recall is inversely related to perceptual set size (e.g., the number of sounds in a sequence).
69
Changes in the precision of recall for cued compared to uncued stimuli also demonstrate the role
70
of selective attention in gating access to relevant over irrelevant sounds to short-term memory
71
(Kumar et al., 2013). These findings have been interpreted in terms of a reciprocal relationship
72
between the number of attended sounds and the distribution of capacity-limited resources
73
during their encoding and maintenance (Joseph et al., 2015; Kumar et al., 2013).
74
The findings above demonstrate reliable associations between perceptual set size,
75
selective attention, and the precision of recall for auditory objects. In extending this evidence to
76
tinnitus, one can predict an association between the attentional weight assigned to tinnitus and
77
the extent to which it competes for short-term memory resources. Barrett and Pilling (2017)
78
tested this possibility by manipulating the locus of attention towards or away from simulated
79
tinnitus during a delayed pitch discrimination task. In their study, listeners with normal hearing
80
compared the pitch of two tones separated by a three second retention interval. The frequency-
81
difference between tones was varied using a method of constant stimuli (Harris, 1948) and the
82
slope of the resulting psychometric function was used to index the precision of recall. Tones were
83
presented in the absence or presence of simulated tinnitus, which was presented at constant or
84
modulated amplitude on a subset of trials. To avoid masking, the tones and simulated tinnitus
85
were separated by a large frequency difference and participants were required to ignore or
86
report the amplitude modulation of the tinnitus when present. The results revealed a decrease
87
in precision when tones were presented in the presence of simulated tinnitus compared to
88
silence. When participants were required to report the amplitude of simulated tinnitus, the
89
decrease in precision was significantly larger than in the silent baseline condition. When
90
participants were instructed to ignore simulated tinnitus, the reduction in precision was smaller,
91
and did not reach statistical significance.
92
Barrett and Pilling’s (2017) results suggest changes in the precision of auditory recall
93
reflect competition between simulated tinnitus and task-relevant sounds during tests of short-
94
5
term memory. For listeners with tinnitus, the internal percept represents an additional stimulus.
95
The extent to which this competes for resource with external sounds, depends on whether
96
attention is oriented towards or away from the tinnitus during listening. Competition between
97
tinnitus and external sounds is also likely to increase the mental effort required to encode and
98
maintain external sounds. In the psychological literature, task-evoked pupillary responses
99
(TEPRs) have been used to index changes in cognitive-load and mental effort during tests of
100
auditory and visual recall (Goldinger & Papesh, 2012; Pichora-Fuller et al., 2016). Early studies
101
revealed a positive association between pupil dilation and the number of tones or digits
102
participants had to retain during tests of auditory short-term memory (Beatty & Kahneman,
103
1966; Kahneman et al., 1967). Subsequent findings have revealed a close correspondence
104
between behavioural estimates of short-term memory capacity and asymptotic pupil dilation
105
during auditory recall (Granholm et al., 1996; Peavler, 1974) and visual change detection
106
(Kursawe & Zimmer, 2015). Distributing attention across two, compared to a single speaker, has
107
also been shown to elicit increases in pupil dilation over and above those associated with the
108
degradation of speech (Koelewijn et al., 2014). These findings indicate TEPRs are sensitive to the
109
number and the distribution of attention across sounds during encoding and maintenance in
110
short-term memory. If problem tinnitus reflects competition between tinnitus and external
111
sounds, differences in TEPRs may provide an objective measure of the increase in listening effort
112
required to encode and maintain sounds during tests of auditory short-term memory.
113
The current study is designed to evaluate pupillometry as an objective measure of
114
intrusiveness in tinnitus. To do this, we contrasted pupil size and TEPRs during a delayed pitch
115
discrimination task in listeners with and without tinnitus. TEPRs are defined as phasic changes in
116
pupil dilation relative to a baseline obtained in the absence of stimulation or task-demands
117
(Beatty & Lucero-Wagoner, 2000), which is time-locked to stimulus onsets (or offsets) and the
118
inferred mental operations they elicit, such as the encoding and maintenance of a sound on each
119
trial. In addition to TEPRs, we recorded changes in tonic pupil diameter prior to the onset of each
120
trial in the absence of auditory stimulation. Recent evidence has linked changes in tonic pupil
121
diameter to levels or arousal, shifts in selective attention, exploratory behaviour and increases in
122
processing-load (Bast et al., 2018; Pajkossy et al., 2017; Zénon, 2019). In tinnitus, competition
123
between the internal percept and external sounds is likely to increase demands associated with
124
the maintenance of task-relevant information in auditory short-term memory. Competition is
125
also likely to increase demands associated with the maintenance of an attentional set that
126
6
prioritises external sounds over blocks of trials (Maudoux et al., 2012). To control the impact of
127
potential of perceptual differences on these processes in listeners with and without tinnitus, we
128
measured delayed pitch discrimination accuracy for pure tones with frequencies below those
129
associated with i) age-related sensorineural and noise-induced hearing loss (Eggermont, 2019;
130
Jilek et al., 2014; Nicolas-Puel et al., 2002), and ii) psychoacoustic estimates of average tinnitus
131
frequency (Ibraheem & Hassaan, 2017; Schecklmann et al., 2012; Shekhawat et al., 2014). In
132
addition, we used an adaptive psychophysical procedure to estimate individual frequency
133
detection thresholds to ensure the accuracy of delayed pitch discrimination was equivalent for
134
listeners in each group. In this situation, differences in tonic pupil size and TEPRs can be
135
attributed to an increase in the mental effort required to obtain a fixed level of accuracy during
136
the encoding and maintenance of tone-frequency in auditory short-term memory.
137
138
Method
139
Participants
140
Fourteen participants with chronic tinnitus (TG) were recruited to the study from the local
141
community and Leicester branch of the British Tinnitus Association Support Group. All had
142
experienced tinnitus in one or both ears for at least six months. One participant withdrew from
143
the study during the session, and one was excluded because of astigmatism in their right eye.
144
Twelve participants with no history of tinnitus or neurological disorder were recruited as a
145
control group (CG) for the study. None of the participants wore hearing aids and differences in
146
the age of each group were not statistically significant (TG: M = 46.5, SD = 12.5. CG: M = 43.8, SD
147
= 16.4. t22 = 0.45, p = 0.66, Cohen’s d = 0.18). Approval for the study was obtained from the School
148
of Psychology Ethics Committee at the University of Leicester. Recruitment, consent, and
149
experimental procedures conformed to American Psychology Association ethics standards.
150
151
Apparatus
152
Experiments were run on an IBM PC with a 21-inch HP Trinition P1130 CRT monitor
153
(Walnut, CA, USA) at a frame-rate of 1000 Hz and resolution of 1,280 * 1,024 pixels. Sounds were
154
presented binaurally over headphones (HDA 200: Sennheiser Electronic Corporation, Wedemark,
155
Germany) and stimulus presentation and timing were controlled using custom-built software in
156
MATLAB (Mathworks, Natick, MA, USA) with Psychtoolbox (Brainard, 1997; Kleiner et al., 2007)
157
7
and Palamedes (Prins, 2014) toolbox extensions. Viewing distance was fixed at 60 cm using a
158
fixed chin rest and pupil dilation and fixation were measured using an EyeLink 1000 video-based
159
eye tracker (SR Research Ltd., Ottawa, ON, Canada) with spatial resolution of < 0.02 degrees at a
160
sample rate of 1000 Hz. The study was run in a dimly lit room at a constant light level for all
161
participants.
162
163
Stimuli
164
Stimuli for the delayed pitch discrimination (DPD) task were pure tones. Tones were 500
165
milliseconds (ms) long with 10 ms cosine onset and offset ramps presented at 72 dB SPL. Target
166
tones on each trial were centred at one of three frequencies; 750 Hz ± 2 semitones (668 & 842
167
Hz) with an additional jitter of ± 5 to 20 Hz to avoid consolidation in long-term memory. Probe
168
tones were higher or lower in frequency than target tones by a variable amount (see procedure
169
below). Trials also included white noise bursts of 500. Ms presented at 72 dB SPL. Participants
170
viewed a uniform mid-grey screen (52 cd/m2) with a centrally located Gabor patch subtending 1
171
x 1 visual degree on each trial. Gabor patches were generated by convolving a sine wave with a
172
Gaussian window to produce a discriminable grating with the same mean luminance as the
173
display.
174
175
Procedure
176
Participants completed the Tinnitus Handicap Inventory (THI: Newman, Jacobson &
177
Spitzer, 1996) and the DPD task. The THI consists of 25 questions that assesses the impact of
178
tinnitus on an individuals’ quality of life. Responses are scored on a 4-point scale to produce an
179
overall score between 0 and 100. Participants then undertook a calibration procedure requiring
180
them fixate a Gabor patch presented sequentially at the centre of the screen and then 5
181
equidistant points on the circumference of a virtual circle (eccentricity = 5°). Gabor patches were
182
presented at each location for 2 seconds and the calibration procedure was repeated using high
183
(72.5 cd/m2), mid (12.7 cd/m2) and low (3.8 cd/m2) luminance displays. The calibration was used
184
to ensure pupillary responses during experimental trials fell within listeners’ dynamic range.
185
Following calibration, participants were familiarised with the DPD task (see Figure 1).
186
Trials on the DPD task started with a Gabor at the centre of a mid-luminance display and
187
participants were instructed to maintain their gaze on the Gabor throughout the trial. One and a
188
half seconds after the onset of the fixation-point, a target and probe tone were presented. Tones
189
8
were separated by a silent retention interval of 2 seconds, and participants reported whether the
190
pitch of the probe was lower or higher than the target using the “up” and “down” arrows on a
191
standard keyboard. The number of low and high frequency probes was equal, and their order of
192
presentation was pseudorandomised across trials. Once a response was recorded, a 500 ms burst
193
of white noise was presented to signal the end of the trial and mask any perceptual priming
194
associated the target and probe tones. Trials were separated by silent interval and a uniform mid
195
luminance display for 500 ms.
196
During familiarisation, the difference between target and probe tones was set at 2
197
semitones. Participants were asked to verbalise their decisions to ensure they understood the
198
task and could make accurate lower-higher decisions. Trials were repeated until participants
199
made at least 10 correct responses. Following a short break, 3 blocks of the DPD task were used
200
to estimate listener’s frequency detection thresholds (FDTs). Individual estimates were obtained
201
using a weighted 1-up, 1-down staircase over 80 trials to calculate the frequency-difference
202
required to discriminate between low and high probe- relative to the target-tones with 80%
203
probability (Kaernbach, 1991). Individual FDTs were used to i) control for changes in sensory
204
acuity associated with hearing loss or tinnitus and ii) equate the difficulty of pitch discrimination
205
across TG and CG participants. Pupil size was not recorded during familiarisation or FDT
206
estimation.
207
Following FDT estimation, participants completed 3 test blocks of 50 trials on the DPD
208
task. The frequency-difference between target and probe tones was set at the participant’s mean
209
80% accuracy threshold (∆ Semitones). Pupil size and fixation location were recorded from the
210
right eye. Pupil size (area) was tracked using EyeLink’s proprietary centroid mode, which tracks
211
the centre of the pupil image using a centre-of-mass algorithm (Zhu et al., 1999). A square root
212
transformation of the pupil area results in a measure of linear angle in arbitrary units that scales
213
with pupil diameter and viewing distance (Hayes & Petrov, 2016). Each test block was preceded
214
by a 9-point calibration sequence to ensure gaze location could be tracked accurately and
215
participants could maintain their gaze on the central Gabor.
216
217
9
218
219
Figure 1. Illustration of the sequence of events on each trial. Changes in pupil dilation on each
220
trial were calculated using a baseline obtained during a silent period immediately preceding the
221
target-tone. Target-tones were 750 Hz, two semitones higher or lower, with the addition of a
222
random jitter (5-20 Hz). Probe-tones were adjusted with an adaptive procedure (weighted 1-up,
223
1-down) in semitone steps.
224
225
Participant’s accuracy on the test session was quantified as the proportion of correctly
226
categorized probe-tones. Pupillary responses were pre-processed off-line for correct responses
227
for each block of 50 trials. Errors were excluded from analyses as they could reflect poor attention
228
and add noise to the comparison between groups. Blinks and eye movements were excluded
229
from the data using the Eyelink 1000’s default detection algorithm. Trials with missing data on
230
30% or more samples were also excluded from further analyses. Pupil diameter recordings on
231
remaining trials (CG mean = 81.22%, SD = 10.81. TG mean = 71.83, SD = 18.04, t22 = 1.55, p > 0.05,
232
Cohen’s d = 0.63) were smoothed using Locally Weighted Scatterplot Smoothing (Lowess)
233
(Cleveland, 1981) with a 10% span (i.e., 350 ms). Baseline pupil dilation was measured at a single
234
sample before the onset of the target tone on each trial. Baseline correction is commonly
235
achieved by subtracting average pupil dilation over a period between 100 ms and 1 second before
236
the event of interest (Win et al., 2018). Averaging reduces the impact of blinks and outliers on
237
baseline measurements but can also be influenced by preparatory changes in arousal and
238
attention prior to stimulus onset (Akdoğan et al., 2016; Irons et al., 2017). To negate the potential
239
of individual and group differences in preparatory activity on the estimation of TEPR amplitude,
240
we used a single sample in the smoothed trace as an absolute baseline at the beginning of each
241
10
trial
1
. Baseline values were subtracted from the pupil diameter from the onset of the target tone
242
until 500 msec after the offset of the probe tone. Maximum TEPRs were calculated for the period
243
between the onsets of the target and probe tones. Maximum TEPR and baseline values ± 3
244
standard deviations from individual’s mean in each block were excluded as outliers.
245
246
Results
247
Self-Report and Behavioural Data
248
Mean THI scores in the tinnitus group ranged from 4 to 36 (Mean = 19.7, SD = 7.7, Median
249
= 22). This represents a relatively mild level of subjective tinnitus severity in our sample. Table 1
250
presents summary statistics for estimated FDTs and accuracy on the DPD task by group and block
251
during the test sessions. Differences between CG and TG listeners on FDTs were small (M = 0.016
252
semitones) and did not reach statistical significance (t22= 0.04, p > 0.95, Cohen’s d = 0.02). To
253
analyse potential differences in the accuracy of DPD across groups, the proportion of correct
254
responses for each participant were subject to a general linear mixed-effects analysis (GLME)
255
with a binomial link function. Group (CG vs. TG), Block (1, 2 & 3) and their interaction were
256
modelled as fixed-effects. Participant was modelled as a random-effect, to control for individual
257
differences in the intercept of the regression equation (Baayen et al., 2008). CG accuracy in block
258
1 was used as the reference and sliding contrasts were defined using the MASS package in R
259
(Venables, 2002). This yielded a non-significant difference between CG and TG listeners (ß = 0.11,
260
SE = 0.29, p > 0.05). The difference between blocks 1 and 3 (ß = 0.35, SE = 0.13, p < 0.05) was
261
statistically significant, but the difference between blocks 1 and 2 was not (ß = 0.23, SE = 0.0.12,
262
p > 0.05). Group by Block interactions for blocks 2 (ß = 0.04, SE = 0.23, p > 0.05) and 3 (ß = 0.21,
263
SE = 0.27, p > 0.05) did not reach statistical significance. The results indicate comparable
264
frequency detection thresholds and levels of accuracy on the DPD task for CG and TG listeners.
265
Table 1 presents descriptive statistics for FDTs and accuracy on the DPD. Table 5 presents GLME
266
statistics for accuracy by Group and Block.
267
268
269
270
1
Tonic and TEPR amplitude measured using a single sample and mean over 100ms as the baseline produced
equivalent results, suggesting both methods are similarly robust to pre-stimulus variability in pupil dilation.
11
Table1. Mean frequency detection threshold (FDT) and proportion of correct higher or lower
271
probe-tone responses for tinnitus and control participants by block
272
Proportion Correct
Group
FDT (semitones)
Block 1
Block 2
Block 3
Control Group
0.61 (0.45)
0.88 (0.33)
0.85 (0.34)
0.92 (0.28)
Tinnitus Group
0.62 (0.39)
0.86 (0.35)
0.83 (0.38)
0.88 (0.33)
273
Pupillometry
274
Pupil diameter during the calibration procedure was averaged across fixations for each
275
level of display luminance and subject to a linear mixed-effects (LME) analysis with group, display
276
luminance and their interaction modelled as fixed-factors. Participant was modelled as a random-
277
effect to control for individual differences in the intercept of the regression equation (Baayen et
278
al., 2008). Mid luminance displays were used as the reference and sliding contrasts were defined
279
using the MASS package in R. The MLE on pupil dilation yielded a significant increase in high (ß =
280
-3.94, SE = 1.06, t > 1.96) and decrease in low (ß = -6.70, SE = 1.06, t > 1.96) compared to mid
281
luminance displays. Differences between groups (ß = 3.56, SE = 3.45, t < 1.96) and Group by
282
Display Luminance interactions for high (ß = -0.91, SE = 1.50, t < 1.96) and low (ß = 0.13, SE = 1.50,
283
t < 1.96), compared to mid luminance displays were not significant. These results reveal similar
284
luminance driven changes in pupil diameter in CG and TG listeners. Pupil sizes for mid luminance
285
displays also fell within the dynamic range of listeners in both groups (see Table 2).
286
287
Table 2. Mean pupil diameter by Group and Display Luminance during initial calibration. Standard
288
deviation in parenthesis.
289
Mean Pupil Diameter
CG
TG
High Luminance Display
31.48 (3.49)
34.13 (7.45)
Mid Luminance Display
35.43 (4.56)
38.99 (9.18)
Low Luminance Display
42.09 (6.24)
45.78 (12.07)
290
291
12
Table 3. Statistical effects of Group, Display Luminance and Group * Display Luminance
292
interactions on pupil diameter during calibration.
293
Mean Pupil Diameter
ß
t-value
35.42
14.52
3.56
1.03
-3.94
*3.72
6.70
*6.28
-0.91
-0.61
-0.13
0.08
294
H = high, M = mid and L = low. Lum = display luminance. Random effect for participants’ variance
295
= 53.97, SD = 7.35. * Statistically significant effects on pupil diameter (|t| value > 1.96).
296
297
Due to technical issues, pupil dilation failed to record on one block of the DPD for two CG
298
and four TG participants. Data for 2 blocks for these participants and 3 blocks for the remainder
299
were subject to analyses. Figure 2 plots mean baseline-corrected TEPRs for blocks 1 to 3. To
300
contrast tonic pupil dilation and listening effort across groups, mean baseline pupil diameter and
301
maximum TEPR for each participant were subject to separate LME analyses. Group (CG vs. TG),
302
Block (1, 2 & 3) and their interaction were modelled as fixed-effects and participant as a random-
303
effect. Block 1 was used as the reference and sliding contrasts were defined using the MASS
304
package in R. Table 4 presents descriptive statistics and Table 5 the estimated coefficients for the
305
LME analyses of tonic pupil dilation and maximum TEPRs.
306
The LME on baseline pupil diameter yielded a non-significant difference between TG and
307
CG listeners (ß = 2.36, SE = 2.90, t < 1.96). Comparisons between blocks revealed a significant
308
increase on blocks 2 (ß = 0.92, SE = 0.16, t > 1.96) and 3 (ß = 0.84, SE = 0.16, t > 1.96) compared
309
to block 1. Estimated coefficients for Group by Block 2 (ß = 1.15, SE = 0.31, t > 1.96) and 3 (ß =
310
2.20, SE = 0.32, t > 1.96) interactions were also significant. Post hoc analyses revealed significant
311
increases in baseline pupil diameter in TG listeners on blocks 2 (ß = 1.50, t = 6.57, p < 0.001) and
312
3 (ß = 1.94, t = 8.26, p < 0.001) compared to block 1. Differences in CG listeners on blocks 2 (ß = -
313
0.35, t = 1.60, p > 0.05) and 3 (ß = 0.26, t = 1.20, p > 0.05) compared to 1 did not reach statistical
314
13
significance. These results indicate baseline pupil dilation across blocks was consistent in CG
315
listeners. Baseline pupil dilation among TG listeners in contrast, increased significantly on the last
316
two blocks of testing.
317
The MLE on TEPRs revealed a significantly higher maximum pupil dilation for TG compared
318
to CG listeners (ß = 0.84, SE = 0.32, t > 1.96). Estimated coefficients for the difference between
319
blocks 2 (ß = -0.03, SE = 0.9, t < 1.96) and 3 (ß = 0.05, SE = 0.09, t < 1.96) compared to 1 did not
320
reach statistical significance. Group by block 2 (ß = -0.07, SE = 0.17, t < 1.96) and 3 (ß = -0.24, SE
321
= 0.18, t < 1.96) interactions were also non-significant. These results indicate baseline corrected
322
TEPRs were significantly larger among TG than CG participants across all blocks of testing. The
323
lack of any significant group or by block interactions indicates differences between CG and TG
324
listeners in TEPR amplitude were relatively constant (see Table 4). To investigate the relationship
325
between TEPRs and subjective measures of tinnitus, we calculated a simple regression with THI
326
scores the predictor and the mean of participants’ maximum TEPR across blocks the outcome. A
327
significant regression equation was obtained (F1,10 = 16.15, p < 0.05) with an adjusted R2 of 0.58.
328
This indicates that for every unit increase in THI, maximum pupil dilation in TG listeners increased
329
by 0.8 arbitrary units compared to baseline.
330
331
Table 4. Mean baseline pupil diameter (PD) and maximum TEPRs in Blocks 1 to 3 for Control (CG)
332
and Tinnitus (TG) participants.
333
Mean Baseline PD (SD)
Max TEPR (SD)
CG
TG
CG
TG
Block 1
36.09
(7.01)
38.44
(8.81)
1.63
(1.59)
2.32
(2.27)
Block 2
36.29
(5.93)
39.94
(9.24)
1.62
(1.56)
2.31
(2.24)
Block 3
35.71
(5.38)
40.34
(8.55)
1.62
(1.82)
2.23
(2.10)
334
335
336
14
337
338
Figure 2 Mean baseline corrected pupil dilation for Control (CG) and Tinnitus (TG) groups by time
339
and block in arbitrary units. Vertical dotted lines denote the offset and onset of the probe and
340
target tones respectively. These data are baseline corrected grand average pupil diameter and
341
are distinct from the trial-by-trial baseline and maximum TEPRs subject to analyses and listed in
342
Table 5.
343
344
Table 5. Statistical effects of Group, Block and Group * Block interactions on accuracy, baseline
345
pupil diameter and maximum TEPR during test trials.
346
Accuracy (Proportion of correct higher or lower responses)
ß
z-value
1.98
*13.55
-0.11
0.38
-0.23
1.95
0.35
*2.67
-0.04
0.16
-0.21
0.80
Baseline Pupil Diameter
15
ß
t-value
37.17
*25.60
2.36
0.81
0.92
*5.88
0.84
*5.22
1.15
*3.68
2.20
*6.86
Mean Maximum TEPR
ß
t-value
2.24
*14.05
0.83
*2.63
-0.03
0.39
-0.04
0.52
-0.07
0.43
-0.24
1.34
347
Accuracy: Random effect for participant’s variance = 0.33, SD = 0.57. Baseline pupil diameter:
348
Random effect for participants’ variance = 50.32, SD = 7.09. Maximum TEPR: Random effect for
349
participant’s variance = 0.52, SD = 0.72. * Significant effects (|z| ! 1.96) and (|t| ! 1.96).
350
351
Discussion
352
The aim of the current study was to evaluate the use of pupillometry as an objective index
353
of intrusiveness in tinnitus. To do this, we compared baseline pupil diameter and TEPRs in
354
listeners with chronic tinnitus to age-matched controls without tinnitus during a delayed pitch
355
discrimination task. Frequency differences between target and probe tones were titrated using
356
an adaptive procedure to equate the perceptual difficulty of discrimination across listeners with
357
and without tinnitus. Our results reveal significantly larger TEPRs among listeners with tinnitus
358
compared to age-matched controls. TEPRs for TG and CG listeners diverged during the
359
presentation of the target tone, with the mean group differences peaking approximately 800 ms
360
after its presentation before returning to baseline levels before the onset of the probe tone.
361
Regressing the maximum amplitude of TEPRs with THI scores for listeners with tinnitus, also
362
16
revealed a significant positive association between subjective reports of tinnitus-disruption and
363
an objective measure of listening effort during a test of auditory short-term memory. In addition
364
to group differences in TEPRs, our data revealed divergent patterns of baseline pupil diameter
365
across blocks in listeners with and without tinnitus. For CG listeners, mean baseline or “tonic”
366
pupil diameter remained constant across blocks of trials. For TG listeners, tonic pupil diameter
367
was significantly larger on blocks two and three than the initial block of testing. These findings
368
demonstrate tinnitus-specific changes in i) phasic reactivity within trials and ii) tonic pupil size
369
across trials.
370
The results above suggest tinnitus contributes measurable effects on tonic pupil size and
371
reactivity. These effects were obtained for sounds that produced equivalent levels of behavioural
372
accuracy across participants, reducing the potential contribution of tinnitus-related changes in
373
perceptual acuity to differences in mental effort during the maintenance of pure tones. In
374
listeners without tinnitus, TEPR amplitude is positively associated with the number of sounds
375
(Kahneman et al., 1967) or sound sources (Koelewijn et al., 2014) during tests of perception and
376
short-term memory. Task-related increases in phasic pupil dilation have been attributed to an
377
increase in cognitive load, or the mental effort required to encode and maintain sounds over
378
short periods of time (Goldinger & Papesh, 2012; Pichora-Fuller et al., 2016). The increase in TEPR
379
amplitude among TG listeners in our study, is consistent with the prediction that competition
380
between tinnitus and external sounds increases listening effort during tests of auditory short-
381
term memory (Barrett & Pilling, 2017). The level of this competition is likely to reflect attentional
382
mechanisms, which determine the distribution of cognitive resources across internal and
383
external precepts during hearing (Cuny et al., 2004; Kumar et al., 2013; Maudoux et al., 2012;
384
Roberts et al., 2013). In addition to the phasic changes indexed by TEPRs, differences in the
385
magnitude of baseline pupil diameter in TG compared to CG listeners may also reflect attentional
386
processes that operate over blocks of trials. Task related changes in tonic pupil size have been
387
associated with demands on short-term memory (Peysakhovich et al., 2017), levels of uncertainty
388
(Zénon, 2019) and shifts between focussed and exploratory states of attention (Pajkossy et al.,
389
2017). A recent study by Unsworth and Robinson (2016), associated high baseline pupil size with
390
distractibility during a psychomotor vigilance task and elevated levels of intrinsic alertness and
391
sustained attention during a test of vigilance (Unsworth et al., 2020). In the presence of tinnitus,
392
maintaining accuracy on the DPD task in our study requires the maintenance of an attentional
393
set that prioritises external sounds over consecutive blocks of trials. The increase in baseline pupil
394
17
diameter observed in TG listeners on blocks 2 and 3, may reflect the temporal dynamics of this
395
process and provide an objective measure of tinnitus-related fluctuations in arousal, cognitive-
396
load and attentional set during tests of auditory short-term memory. Further research will be
397
required to establish the diagnostic sensitivity of changes in baseline pupil diameter to
398
competition between tinnitus and external sounds. Our results, however, suggest measures of
399
tonic pupil size and phasic reactivity have the potential to provide complementary information
400
about the impact of tinnitus on listening effort and attentional control during trials and across
401
blocks of testing.
402
Our results suggest pupillometry holds promise as an objective measure of tinnitus effects.
403
To date, we know of only one other study that has used pupillometry to investigate the impact
404
of tinnitus on listening effort. Juul Jensen and colleagues (Juul Jensen et al., 2018) used a speech-
405
in-noise task to contrast pupil dilation in a sample of hearing-impaired listeners with and without
406
tinnitus. The accuracy of participant’s responses was used to equate signal to noise ratios for all
407
listeners at two levels of speech intelligibility; 50% and 95%, and maximum TEPR amplitudes were
408
compared in the tinnitus and control groups at each level of intelligibility. In contrast to our own
409
findings, differences in TEPR amplitudes between the tinnitus and control groups did not reach
410
statistical significance. A further comparison using Growth Curve Analyses to estimate the best-
411
fitting cubic polynomial for TEPRs, revealed a significant decrease in pupil dilation among
412
listeners with tinnitus compared to controls. This direction of this effect is opposite to the
413
increase in TEPRs that we observed and is inconsistent with the hypothesis that competition
414
between tinnitus and external sounds elicits an increase in effort during tests of auditory
415
perception and short-term memory.
416
One explanation for the difference between Juul Jensen et al.'s (2018) result and our own,
417
is that pupillometric measures of listening effort are sensitive to task-demands. Speech
418
recognition is a cumulative process, which involves cognitive resources during the integration
419
and interpretation of sensory input. In addition to auditory short-term memory, report-accuracy
420
depends on linguistic factors, such as lexical similarity, word frequency, and the listener’s
421
vocabulary and experience (Kuchinsky et al., 2012). Phasic decreases in pupil size have been
422
observed during high presentation-rates in alternative forced choice tests (Poock, 1973), and
423
during digit span tasks when sequence length exceeds individual’s short-term memory (Johnson
424
et al., 2014). Juul Jensen and colleagues reported significantly higher levels of fatigue among
425
listeners with tinnitus compared to controls, suggesting task-difficulty and listener engagement
426
18
may have contributed to the reduction in phasic pupil diameter in their study. Our stimuli
427
comprised tones at a set level of discriminability that were presented in the absence of noise.
428
Comparing delayed pitch-discrimination accuracy provides a direct test of auditory short-term
429
memory that is independent of linguistic processes. Recording pupillary responses during
430
baseline and retention periods also provides an index of internal processes that operate in the
431
absence of external auditory stimulation. In this situation, group differences in pupillometry can
432
be attributed to the impact of tinnitus on post-perceptual processes, such as the retention and
433
evaluation of information in short-term memory. Differences in the stimuli and the cognitive
434
processes under test, therefore, caution against direct comparison between our own and Juul
435
Jensen et al.’s (2018) results, while providing insights into the task-attributes that are likely to
436
influence the magnitude and direction TEPRs to competition between tinnitus and external
437
sounds. These include selecting tasks designed to isolate specific cognitive functions (i.e., short-
438
term memory) and optimising task difficulty to maximise engagement and minimise fatigue
439
(Murphy et al., 2011; Zénon, 2019).
440
In addition to differences in the stimuli and task, other factors that may affect the
441
sensitivity of pupillometry to tinnitus include its severity and the incidence of comorbid hearing
442
loss. In our sample, tinnitus-severity was mild, and an important question for future studies is
443
whether group differences in pupillometry generalise to listeners who report higher levels of
444
tinnitus severity. Tinnitus is often preceded by hearing loss and the pitch of the internal percept
445
often correspond to frequency region with the greatest loss (Norena et al., 2002; Schecklmann
446
et al., 2012). To date, only a few studies have investigated the impact of hearing loss on pupil
447
reactivity, and these have produced mixed results (Zekveld et al., 2018). In the current study,
448
tones for the DPD task were selected to fall below frequencies commonly affected by
449
sensorineural hearing loss and tinnitus (Ibraheem & Hassaan, 2017; Nicolas-Puel et al., 2002;
450
Shekhawat et al., 2014). This was done to exclude the impact of perceptual masking of tones by
451
tinnitus on pupil responses or any reduction in tone discriminability associated with hearing
452
impairment. Measuring auditory thresholds and extending our method to include frequencies
453
that target individuals’ hearing loss and tinnitus frequency, is likely to provide valuable
454
information about the way sensory impairment and perceptual masking interact with cognitive
455
processes to influence pupil reactivity on tests of short-term memory. The current exploratory
456
results, however, provide preliminary evidence that changes in tonic and phasic pupil size can be
457
used to measure the impact of tinnitus on listening effort and sustained attention on a test of
458
19
auditory short-term memory. Building on this finding will require studies with larger samples that
459
are representative of the clinical population with a primary complaint of troublesome tinnitus.
460
This should include classifying tinnitus in terms of both aetiology and severity, as well as
461
information about treatments. Developing robust pupillometric measures, is also likely to require
462
a more nuanced understanding of the neural mechanisms that mediate task-related changes in
463
tonic and phasic pupil reactivity and their relationship to other factors that contribute to
464
individual’s cognitive and psychological responses to tinnitus. Integrating this understanding with
465
tests that target cognitive processes most susceptible to competition between tinnitus and
466
external sounds, has the potential to provide clinicians an objective measure of severity and
467
treatment efficacy in listeners with tinnitus.
468
469
Data Availability
470
471
Summary behavioural and pupillometry data are available at the University of Leicester’s
472
Research Repository.
473
474
Acknowledgments
475
476
All authors contributed equally to this work. D.B., M.P. and D.B. contributed to the design of the
477
study. D.B. developed the stimuli and ran the experimental sessions; D.S. contributed software
478
for recording pupil size and removing artefacts; D.B. authored the main paper. All authors
479
discussed the results and implications and commented on the manuscript at all stages. We would
480
like to thank participants from the Leicester branch of the British Tinnitus Association Support
481
Group and wider community. We also thank two anonymous reviewers for their helpful and
482
constructive comments.
483
484
References
485
Akdoğan, B., Balcı, F., & van Rijn, H. (2016). Temporal expectation indexed by pupillary response.
486
Timing & Time Perception, 4(4), 354-370.
487
Andersson, G., Jüris, L., Classon, E., Fredrikson, M., & Furmark, T. (2006). Consequences of
488
suppressing thoughts about tinnitus and the effects of cognitive distraction on brain
489
activity in tinnitus patients. Audiology and Neurotology, 11(5), 301-309.
490
20
Baayen, R. H., Davidson, D. J., & Bates, D. M. (2008). Mixed-effects modeling with crossed random
491
effects for subjects and items. Journal of memory and language, 59(4), 390-412.
492
Barrett, D. J., & Pilling, M. (2017). Evaluating the precision of auditory sensory memory as an
493
index of intrusion in tinnitus. Ear and hearing, 38(2), 262-265.
494
Bast, N., Poustka, L., & Freitag, C. M. (2018). The locus coeruleus–norepinephrine system as
495
pacemaker of attention–a developmental mechanism of derailed attentional function in
496
autism spectrum disorder. European Journal of Neuroscience, 47(2), 115-125.
497
Beatty, J., & Kahneman, D. (1966). Pupillary changes in two memory tasks. Psychonomic Science,
498
5(10), 371-372.
499
Beatty, J., & Lucero-Wagoner, B. (2000). The pupillary system. Handbook of psychophysiology,
500
2(142-162).
501
Brainard, D. H. (1997). The psychophysics toolbox. Spatial vision, 10(4), 433-436.
502
Choi, I., Wang, L., Bharadwaj, H., & Shinn-Cunningham, B. (2014). Individual differences in
503
attentional modulation of cortical responses correlate with selective attention
504
performance. Hearing research, 314, 10-19.
505
Cleveland, W. S. (1981). LOWESS: A program for smoothing scatterplots by robust locally
506
weighted regression. American Statistician, 35(1), 54.
507
Cuny, C., Norena, A., El Massioui, F., & Chéry-Croze, S. (2004). Reduced attention shift in response
508
to auditory changes in subjects with tinnitus. Audiology and Neurotology, 9(5), 294-302.
509
Eggermont, J. J. (2019). The auditory brain and age-related hearing impairment. Academic Press.
510
Erlandsson, S. I., Hallberg, L. R., & Axelsson, A. (1992). Psychological and audiological correlates
511
of perceived tinnitus severity. Audiology, 31(3), 168-179.
512
Gazzaley, A. (2011). Influence of early attentional modulation on working memory.
513
Neuropsychologia, 49(6), 1410-1424.
514
Goldinger, S. D., & Papesh, M. H. (2012). Pupil dilation reflects the creation and retrieval of
515
memories. Current directions in psychological science, 21(2), 90-95.
516
Granholm, E., Asarnow, R. F., Sarkin, A. J., & Dykes, K. L. (1996). Pupillary responses index
517
cognitive resource limitations. Psychophysiology, 33(4), 457-461.
518
Hallam, R., Jakes, S., & Hinchcliffe, R. (1988). Cognitive variables in tinnitus annoyance. British
519
Journal of Clinical Psychology, 27(3), 213-222.
520
Harris, J. D. (1948). Discrimination of pitch: suggestions toward method and procedure. The
521
American journal of psychology, 61(3), 309-322.
522
Hayes, T. R., & Petrov, A. A. (2016). Mapping and correcting the influence of gaze position on
523
pupil size measurements. Behavior Research Methods, 48(2), 510-527.
524
Heeren, A., Maurage, P., Perrot, H., De Volder, A., Renier, L., Araneda, R., Lacroix, E., Decat, M.,
525
Deggouj, N., & Philippot, P. (2014). Tinnitus specifically alters the top-down executive
526
control sub-component of attention: evidence from the attention network task.
527
Behavioural brain research, 269, 147-154.
528
Hibbert, A., Vesala, M., Kerr, M., Fackrell, K., Harrison, S., Smith, H., & Hall, D. A. (2020). Defining
529
Symptom Concepts in Chronic Subjective Tinnitus: Web-Based Discussion Forum Study.
530
Interactive journal of medical research, 9(1), e14446.
531
Hillyard, S. A., Vogel, E. K., & Luck, S. J. (1998). Sensory gain control (amplification) as a
532
mechanism of selective attention: electrophysiological and neuroimaging evidence.
533
Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences,
534
353(1373), 1257-1270.
535
21
Ibraheem, O. A., & Hassaan, M. R. (2017). Psychoacoustic characteristics of tinnitus versus
536
temporal resolution in subjects with normal hearing sensitivity. International archives of
537
otorhinolaryngology, 21(2), 144-150.
538
Irons, J. L., Jeon, M., & Leber, A. B. (2017). Pre-stimulus pupil dilation and the preparatory control
539
of attention. PLoS One, 12(12), e0188787.
540
Jilek, M., Šuta, D., & Syka, J. (2014). Reference hearing thresholds in an extended frequency range
541
as a function of age. The Journal of the Acoustical Society of America, 136(4), 1821-1830.
542
Johnson, E. L., Miller Singley, A. T., Peckham, A. D., Johnson, S. L., & Bunge, S. A. (2014). Task-
543
evoked pupillometry provides a window into the development of short-term memory
544
capacity. Frontiers in psychology, 5, 218.
545
Joseph, S., Kumar, S., Husain, M., & Griffiths, T. D. (2015). Auditory working memory for objects
546
vs. features. Frontiers in neuroscience, 9, 13.
547
Juul Jensen, J., Callaway, S. L., Lunner, T., & Wendt, D. (2018). Measuring the impact of tinnitus
548
on aided listening effort using pupillary response. Trends in hearing, 22,
549
2331216518795340.
550
Kaernbach, C. (1991). Simple adaptive testing with the weighted up-down method. Perception &
551
psychophysics, 49(3), 227-229.
552
Kahneman, D., Beatty, J., & Pollack, I. (1967). Perceptual deficit during a mental task. Science,
553
157(3785), 218-219.
554
Kennedy, V., Chéry-croze, S., Stephens, D., Kramer, S., Thai-van, H., & Collet, L. (2005).
555
Development of the International Tinnitus Inventory (ITI): a patient-directed problem
556
questionnaire. Audiological Medicine, 3(4), 228-237.
557
Kleiner, M., Brainard, D., & Pelli, D. (2007). What's new in Psychtoolbox-3?
558
Koelewijn, T., Shinn-Cunningham, B. G., Zekveld, A. A., & Kramer, S. E. (2014). The pupil response
559
is sensitive to divided attention during speech processing. Hearing research, 312, 114-
560
120.
561
Kuchinsky, S. E., Vaden Jr, K. I., Keren, N. I., Harris, K. C., Ahlstrom, J. B., Dubno, J. R., & Eckert, M.
562
A. (2012). Word intelligibility and age predict visual cortex activity during word listening.
563
Cerebral cortex, 22(6), 1360-1371.
564
Kumar, S., Joseph, S., Pearson, B., Teki, S., Fox, Z., Griffiths, T., & Husain, M. (2013). Resource
565
allocation and prioritization in auditory working memory. Cognitive neuroscience, 4(1),
566
12-20.
567
Kursawe, M. A., & Zimmer, H. D. (2015). Costs of storing colour and complex shape in visual
568
working memory: Insights from pupil size and slow waves. Acta Psychologica, 158, 67-77.
569
Maudoux, A., Lefebvre, P., Cabay, J.-E., Demertzi, A., Vanhaudenhuyse, A., Laureys, S., & Soddu,
570
A. (2012). Auditory resting-state network connectivity in tinnitus: a functional MRI study.
571
PLoS One, 7(5), e36222.
572
McCormack, A., Edmondson-Jones, M., Somerset, S., & Hall, D. (2016). A systematic review of the
573
reporting of tinnitus prevalence and severity. Hearing research, 337, 70-79.
574
McFerran, D. J., Stockdale, D., Holme, R., Large, C. H., & Baguley, D. M. (2019). Why is there no
575
cure for tinnitus? Frontiers in neuroscience, 13, 802.
576
Murphy, P. R., Robertson, I. H., Balsters, J. H., & O'connell, R. G. (2011). Pupillometry and P3 index
577
the locus coeruleus–noradrenergic arousal function in humans. Psychophysiology, 48(11),
578
1532-1543.
579
Myers, N. E., Stokes, M. G., & Nobre, A. C. (2017). Prioritizing information during working
580
memory: beyond sustained internal attention. Trends in cognitive sciences, 21(6), 449-
581
461.
582
22
Nicolas-Puel, C., Faulconbridge, R. L., Guitton, M., Puel, J.-L., Mondain, M., & Uziel, A. (2002).
583
Characteristics of tinnitus and etiology of associated hearing loss: a study of 123 patients.
584
The international tinnitus journal, 8(1), 37-44.
585
Norena, A., Micheyl, C., Chéry-Croze, S., & Collet, L. (2002). Psychoacoustic characterization of
586
the tinnitus spectrum: implications for the underlying mechanisms of tinnitus. Audiology
587
and Neurotology, 7(6), 358-369.
588
Pajkossy, P., Szőllősi, Á., Demeter, G., & Racsmány, M. (2017). Tonic noradrenergic activity
589
modulates explorative behavior and attentional set shifting: Evidence from pupillometry
590
and gaze pattern analysis. Psychophysiology, 54(12), 1839-1854.
591
Peavler, W. S. (1974). Individual differences in pupil size and performance. In Pupillary dynamics
592
and behavior (pp. 159-175). Springer.
593
Peysakhovich, V., Vachon, F., & Dehais, F. (2017). The impact of luminance on tonic and phasic
594
pupillary responses to sustained cognitive load. International Journal of
595
Psychophysiology, 112, 40-45.
596
Pichora-Fuller, M. K., Kramer, S. E., Eckert, M. A., Edwards, B., Hornsby, B. W., Humes, L. E.,
597
Lemke, U., Lunner, T., Matthen, M., & Mackersie, C. L. (2016). Hearing impairment and
598
cognitive energy: The framework for understanding effortful listening (FUEL). Ear and
599
hearing, 37, 5S-27S.
600
Poock, G. K. (1973). Information processing vs pupil diameter. Perceptual and Motor Skills, 37(3),
601
1000-1002.
602
Prins, N. (2014). Kingdom, FAA (2009). Palamedes: Matlab routines for analyzing psychophysical
603
data
604
Roberts, L. E., Husain, F. T., & Eggermont, J. J. (2013). Role of attention in the generation and
605
modulation of tinnitus. Neuroscience & Biobehavioral Reviews, 37(8), 1754-1773.
606
Saunders, J. C. (2007). The role of central nervous system plasticity in tinnitus. Journal of
607
communication disorders, 40(4), 313-334.
608
Schecklmann, M., Vielsmeier, V., Steffens, T., Landgrebe, M., Langguth, B., & Kleinjung, T. (2012).
609
Relationship between audiometric slope and tinnitus pitch in tinnitus patients: insights
610
into the mechanisms of tinnitus generation. PLoS One, 7(4), e34878.
611
Shekhawat, G. S., Searchfield, G. D., & Stinear, C. M. (2014). The relationship between tinnitus
612
pitch and hearing sensitivity. European Archives of Oto-Rhino-Laryngology, 271(1), 41-48.
613
Stockdale, D., McFerran, D., Brazier, P., Pritchard, C., Kay, T., Dowrick, C., & Hoare, D. J. (2017).
614
An economic evaluation of the healthcare cost of tinnitus management in the UK. BMC
615
health services research, 17(1), 1-9.
616
Townsend, J., & Ashby, F. (1978). Methods of modeling capacity in simple processing systems In
617
Castellan J & Restle F (Eds.), Cognitive theory (Vol. 3, pp. 200–239)
618
Ueyama, T., Donishi, T., Ukai, S., Ikeda, Y., Hotomi, M., Yamanaka, N., Shinosaki, K., Terada, M.,
619
& Kaneoke, Y. (2013). Brain regions responsible for tinnitus distress and loudness: a
620
resting-state FMRI study. PLoS One, 8(6), e67778.
621
Unsworth, N., Miller, A. L., & Robison, M. K. (2020). Individual differences in lapses of sustained
622
attention: Ocolumetric indicators of intrinsic alertness. Journal of Experimental
623
Psychology: Human Perception and Performance, 46(6), 569.
624
Vanneste, S., & De Ridder, D. (2012). The auditory and non-auditory brain areas involved in
625
tinnitus. An emergent property of multiple parallel overlapping subnetworks. Frontiers in
626
systems neuroscience, 6, 31.
627
Venables, W. R. (2002). BD (2002). Modern Applied Statistics with S. New York: Springer Science
628
& Business Media, 200, 183-206.
629
23
Walpurger, V., Hebing-Lennartz, G., Denecke, H., & Pietrowsky, R. (2003). Habituation deficit in
630
auditory event-related potentials in tinnitus complainers. Hearing research, 181(1-2), 57-
631
64.
632
Watts, E. J., Fackrell, K., Smith, S., Sheldrake, J., Haider, H., & Hoare, D. J. (2018). Why is tinnitus
633
a problem? A qualitative analysis of problems reported by tinnitus patients. Trends in
634
hearing, 22, 2331216518812250.
635
Zekveld, A. A., Koelewijn, T., & Kramer, S. E. (2018). The pupil dilation response to auditory
636
stimuli: current state of knowledge. Trends in hearing, 22, 2331216518777174.
637
Zénon, A. (2019). Eye pupil signals information gain. Proceedings of the Royal Society B,
638
286(1911), 20191593.
639
Zhu, D., Moore, S. T., & Raphan, T. (1999). Robust pupil center detection using a curvature
640
algorithm. Computer methods and programs in biomedicine, 59(3), 145-157.
641
642
ResearchGate has not been able to resolve any citations for this publication.
Article
Full-text available
In conditions of constant illumination, the eye pupil diameter indexes the modulation of arousal state and responds to a large breadth of cognitive processes, including mental effort, attention, surprise, decision processes, decision biases, value beliefs, uncertainty, volatility, exploitation/exploration trade-off, or learning rate. Here, I propose an information theoretic framework that has the potential to explain the ensemble of these findings as reflecting pupillary response to information processing. In short, updates of the brain's internal model, quantified formally as the Kullback-Leibler (KL) divergence between prior and posterior beliefs, would be the common denominator to all these instances of pupillary dilation to cognition. I show that stimulus presentation leads to pupillary response that is proportional to the amount of information the stimulus carries about itself and to the quantity of information it provides about other task variables. In the context of decision making, pupil dilation in relation to uncertainty is explained by the wandering of the evidence accumulation process, leading to large summed KL divergences. Finally, pupillary response to mental effort and variations in tonic pupil size are also formalized in terms of information theory. On the basis of this framework, I compare pupillary data from past studies to simple information-theoretic simulations of task designs and show good correspondance with data across studies. The present framework has the potential to unify the large set of results reported on pupillary dilation to cognition and to provide a theory to guide future research.
Article
Full-text available
Tinnitus is a prevalent complaint, and people with bothersome tinnitus can report any number of associated problems. Yet, to date, only a few studies, with different populations and relatively modest sample sizes, have qualitatively evaluated what those problems are. Our primary objective was to determine domains of tinnitus problem according to a large clinical data set. This was a retrospective analysis of anonymized clinical data from patients who attended a U.K. Tinnitus Treatment Center between 1989 and 2014. Content analysis was used to code and collate the responses of 678 patients to the clinical interview question "Why is tinnitus a problem?" into categories of problems (domains). We identified 18 distinct domains of tinnitus-associated problems. Reduced quality of life, tinnitus-related fear, and constant awareness were notably common problems. Clinicians need to be mindful of the numerous problem domains that might affect their tinnitus patients. Current questionnaires, as well as being measures of severity, are useful clinical tools for identifying problem domains that need further discussion and possibly measurement with additional questionnaires. The domains identified in this work should inform clinical assessment and the development of future clinical tinnitus questionnaire.
Article
Full-text available
The measurement of cognitive resource allocation during listening, or listening effort, provides valuable insight in the factors influencing auditory processing. In recent years, many studies inside and outside the field of hearing science have measured the pupil response evoked by auditory stimuli. The aim of the current review was to provide an exhaustive overview of these studies. The 146 studies included in this review originated from multiple domains, including hearing science and linguistics, but the review also covers research into motivation, memory, and emotion. The present review provides a unique overview of these studies and is organized according to the components of the Framework for Understanding Effortful Listening. A summary table presents the sample characteristics, an outline of the study design, stimuli, the pupil parameters analyzed, and the main findings of each study. The results indicate that the pupil response is sensitive to various task manipulations as well as interindividual differences. Many of the findings have been replicated. Frequent interactions between the independent factors affecting the pupil response have been reported, which indicates complex processes underlying cognitive resource allocation. This complexity should be taken into account in future studies that should focus more on interindividual differences, also including older participants. This review facilitates the careful design of new studies by indicating the factors that should be controlled for. In conclusion, measuring the pupil dilation response to auditory stimuli has been demonstrated to be sensitive method applicable to numerous research questions. The sensitivity of the measure calls for carefully designed stimuli.
Article
Full-text available
Tinnitus can have serious impact on a person’s life and is a common auditory symptom that is especially comorbid with hearing loss. This study investigated processing effort required for speech recognition in a group of hearing-impaired people with tinnitus and a control group (CG) of hearing-impaired people without tinnitus by means of pupillary response. Furthermore, the relationship between the pupillary response, self-rating measures of tinnitus severity, and fatigue was examined. Participants performed a speech-in-noise task with a competing four-talker babble at two speech intelligibility levels (50% and 95%) with either an active or inactive noise-reduction scheme while the pupillary response was recorded. Tinnitus participants showed significantly smaller time-dependent pupil dilations and significantly higher fatigue ratings. No correlation was found for the tinnitus severity and pupillary response, but a significant correlation was found between the tinnitus severity and fatigue. As participants with tinnitus generally reported higher fatigue and showed smaller task-evoked pupil dilations, it was speculated that this may suggest an increased activity of the parasympathetic nervous system, which governs the bodily response during rest. The finding that tinnitus participants showed higher fatigue has clinical implications, highlighting the importance of taking steps to decrease the risk of developing long-term fatigue. Finally, the tinnitus participants showed reduced pupillary responses when noise reduction was activated, suggesting a reduced effort from hearing aid signal processing.
Article
Full-text available
Children with autism spectrum disorder (ASD) exhibit diminished visual engagement to environmental stimuli. Aberrant attentional function provides an explanation by reduced phasic alerting and orienting to exogenous stimuli. We review aberrant attentional function (alerting, orienting, and attentional control) in children with ASD as studied by neurocognitive and neurophysiological tasks as well as magnetic resonance imaging studies. The locus coeruleus – norepinephrine (LC-NE) system is outlined as a pacemaker of attentional function. The LC-NE system regulates adaptive gain in synaptic signal transmission, which moderates phasic alerting (‘promoting’) and the activation of the ventral frontoparietal attention network within orienting (‘permitting’). In children with ASD, atypical LC-NE activity is proposed as underlying mechanism of aberrant attentional function. It may manifest as a) increased tonic activity with reduced phasic reactivity to exogenous stimuli, b) attenuated bottom-up signaling mitigating salience and predictive reward attribution during phasic alerting, and c) reduced activation of the ventral frontoparietal attention system attenuating orienting to exogenous stimuli. Increased tonic pupil dilation and aberrant pupil reactivity are discussed as indicators of atypical LC-NE activity. Pupillometry is outlined as feasible method to assess alerting, orienting, and attentional control that can be dissected from the pupil dilation time course. In children with ASD, aberrant attentional function through atypical LC-NE activity is proposed as developmental mechanism leading to reduced social attention as well as social interaction and communication impairments.
Article
Full-text available
Task preparation involves multiple component processes, including a general evaluative process that signals the need for adjustments in control, and the engagement of task-specific control settings. Here we examined the dynamics of these different mechanisms in preparing the attentional control system for visual search. We explored preparatory activity using pupil dilation, a well-established measure of task demands and effortful processing. In an initial exploratory experiment, participants were cued at the start of each trial to search for either a salient color singleton target (an easy search task) or a low-salience shape singleton target (a difficult search task). Pupil dilation was measured during the preparation period from cue onset to search display onset. Mean dilation was larger in preparation for the difficult shape target than the easy color target. In two additional experiments, we sought to vary effects of evaluative processing and task-specific preparation separately. Experiment 2 showed that when the color and shape search tasks were matched for difficulty, the shape target no longer evoked larger dilations, and the pattern of results was in fact reversed. In Experiment 3, we manipulated difficulty within a single feature dimension, and found that the difficult search task evoked larger dilations. These results suggest that pupil dilation reflects expectations of difficulty in preparation for a search task, consistent with the activity of an evaluative mechanism. We did not find consistent evidence for relationship between pupil dilation and search performance (accuracy and response timing), suggesting that pupil dilation during search preparation may not be strongly linked to ongoing task-specific preparation.
Article
Full-text available
A constant task for every living organism is to decide whether to exploit rewards associated with current behavior or to explore the environment for more rewarding options. Current empirical evidence indicates that exploitation is related to phasic whereas exploration is related to tonic firing mode of noradrenergic neurons in the locus coeruleus. In humans, this exploration-exploitation trade-off is subserved by the ability to flexibly switch attention between task-related and task-irrelevant information. Here, we investigated whether this function, called attentional set shifting, is related to exploration and tonic noradrenergic discharge. We measured pretrial baseline pupil dilation, proved to be strongly correlated with the activity of the locus coeruleus, while human participants took part in well-known tasks of attentional set shifting. Study 1 used the Wisconsin Card Sorting Task, whereas in Study 2, the Intra/Extradimensional Set Shifting Task was used. Both tasks require participants to choose between different compound stimuli based on feedback provided for their previous decisions. During the task, stimulus-reward contingencies change periodically, thus participants are repeatedly required to reassess which stimulus features are relevant (i.e., they shift their attentional set). Our results showed that baseline pupil diameter steadily decreased when the stimulus-reward contingencies were stable, whereas they suddenly increased when these contingencies changed. Analysis of looking patterns also confirmed the presence of exploratory behavior during attentional set shifting. Thus, our results suggest that tonic firing mode of noradrenergic neurons in the locus coeruleus is implicated in attentional set shifting, as it regulates the amount of exploration.
Article
Two experiments examined individual differences in lapses of sustained attention. Participants performed variants of the psychomotor vigilance task while pupillary responses and fixations were recorded. Examining pupillary responses during the interstimulus interval in both experiments suggested that individuals particularly susceptible to lapses of attention (indexed by the slowest response times) demonstrated a decreased pupillary response during the interstimulus interval, whereas individuals less susceptible to lapses of attention demonstrated an increased pupillary response during the interstimulus interval. These results suggest that variation in lapses of attention are partially attributable to individual differences in the ability to voluntarily control the intensity of attention (intrinsic alertness) and fully engage preparatory processes on a moment-by-moment basis. Furthermore, across both experiments additional individual differences factors covaried with lapses of attention, including attention control, working memory capacity, susceptibility to off-task thinking, task-specific motivation, and fixation stability. These results provide evidence for the notion that individual differences in lapses of attention are multifaceted and that variation in intrinsic alertness and other factors are important contributors to this variation. (PsycINFO Database Record (c) 2020 APA, all rights reserved).
Article
Working memory (WM) has limited capacity. This leaves attention with the important role of allowing into storage only the most relevant information. It is increasingly evident that attention is equally crucial for prioritizing representations within WM as the importance of individual items changes. Retrospective prioritization has been proposed to result from a focus of internal attention highlighting one of several representations. Here, we suggest an updated model, in which prioritization acts in multiple steps: first orienting towards and selecting a memory, and then reconfiguring its representational state in the service of upcoming task demands. Reconfiguration sets up an optimized perception-action mapping, obviating the need for sustained attention. This view is consistent with recent literature, makes testable predictions, and links WM with task switching and action preparation.
Article
Forming temporal expectations plays an instrumental role for the optimization of behavior and allocation of attentional resources. Although the effects of temporal expectations on visual attention are well-established, the question of whether temporal predictions modulate the behavioral outputs of the autonomic nervous system such as the pupillary response remains unanswered. Therefore, this study aimed to obtain an online measure of pupil size while human participants were asked to differentiate between visual targets presented after varying time intervals since trial onset. Specifically, we manipulated temporal predictability in the presentation of target stimuli consisting of letters which appeared after either a short or long delay duration (1.5 vs. 3 s) in the majority of trials (75%) within different test blocks. In the remaining trials (25%), no target stimulus was present to investigate the trajectory of preparatory pupillary response under a low level of temporal uncertainty. The results revealed that the rate of preparatory pupillary response was contingent upon the time of target appearance such that pupils dilated at a higher rate when the targets were expected to appear after a shorter as compared to a longer delay period irrespective of target presence. The finding that pupil size can track temporal regularities and exhibit differential preparatory response between different delay conditions points to the existence of a distributed neural network subserving temporal information processing which is crucial for cognitive functioning and goal-directed behavior.