R E S E A R C H A R T I C L E
Linking Vestibular Function and Subcortical Gray
Matter Volume Changes in a Longitudinal Study
ofAging Adults
Dominic Padova,
a,* J. Tilak Ratnanather,b Qian-Li Xue,c,d Susan M. Resnick,e and Yuri Agrawala
a Department of Otolaryngology – Head and Neck Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA
b Center for Imaging Science and Institute for Computational Medicine, Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
c Department of Medicine Division of Geriatric Medicine and Gerontology, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
d Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
e Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
ABSTRACT
Emerging evidence suggests a relationship between impairments of the vestibular (inner ear balance) system and alterations in the
function and the structure of the central nervous system (CNS) in older adults. However, it is unclear whether age-related vestibular
loss is associated with volume loss in brain regions known to receive vestibular input. To address this gap, we investigated the asso-
ciation between vestibular function and the volumes of four structures that process vestibular information (the hippocampus, ento-
rhinal cortex, thalamus, and basal ganglia) in a longitudinal study of 97 healthy, older participants from the Baltimore Longitudinal
Study of Aging. Vestibular testing included cervical vestibular-evoked myogenic potentials (cVEMP) to measure saccular function,
ocular VEMP (oVEMP) to measure utricular function, and video head impulse tests to measure the horizontal semicircular canal ves-
tibulo-ocular re ex (VOR). Participants in the sample had vestibular and brain MRI data for a total of one (18.6%), two (49.5%), and
three (32.0%) visits. Linear mixed-effects regression was used to model regional volume over time as a function of vestibular physi-
ological function, correcting for age, sex, intracranial volume, and intersubject random variation in the baseline levels and rates of
change of volume over time. We found that poorer saccular function, characterized by lower cVEMP amplitude, is associated with
reduced bilateral volumes of the basal ganglia and thalamus at each time point, demonstrated by a 0.0714 cm3 ± 0.0344 (unad-
justed p = 0.038; 95% CI: 0.00397–0.139) lower bilateral-mean volume of the basal ganglia and a 0.0440 cm3 ± 0.0221 (unadjusted
p = 0.046; 95% CI: 0.000727–0.0873) lower bilateral-mean volume of the thalamus for each 1-unit lower cVEMP amplitude. We also
found a relationship between a lower mean VOR gain and lower left hippocampal volume (β = 0.121, unadjusted p = 0.018, 95% CI:
0.0212–0.222). There were no signi cant associations between volume and oVEMP. These  ndings provide insight into the speci c
brain structures that undergo atrophy in the context of age-related loss of peripheral vestibular function.
Keywords: Vestibular, cVEMP, MRI, Volume, Sub-cortical, Longitudinal
Correspondence: Dominic Padova, Department of Otolaryngology – Head and Neck Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA,
Email: dpadova1@jhu.edu
Received: November 2, 2020
Accepted: August 24, 2021
DOI: 10.52294/6727e860-95c1-445c-a47a-177d9e699d46
Padova etal. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 IGO License, which permits the copy
and redistribution of the material in any medium or format provided the original work and author are properly credited. In any reproduction of this article there should not be any
suggestion that APERTURE NEURO or this article endorse any speci c organization or products. The use of the APERTURE NEURO logo is not permitted. This notice should be
preserved along with the article’s original URL. Open access logo and text by PLoS, under the Creative Commons Attribution-Share Alike 4.0 Unported license.
: 2021, Volume 1 - 1 - CC-BY: © Padova et al.
: 2021, Volume 1 - 1 -
INTRODUCTION
The vestibular (inner ear balance) system consists of semi-
circular canals, which detect rotational movements of the
head, and otolith organs, which detect linear head move-
ments and the orientation of the head with respect to
gravity [1]. The vestibular sensory system is known to play
a critical role in maintaining stable balance and gaze con-
trol. Additionally, a growing body of literature indicates a
preeminent contribution of the vestibular system to visuo-
spatial cognitive ability [2, 1–5]. Vestibular function declines
with normal aging [6–8], and vestibular dysfunction is as-
sociated with cognitive declines in older adults [2, 9, 10],
including declines in spatial cognitive function [11, 12].
Functional neuroimaging and vestibular stimulation
studies have demonstrated that vestibular information
is transmitted to multiple neural regions, including the
hippocampus, thalamus, basal ganglia, entorhinal cor-
tex, cerebellum, insula, parietal regions, and somatosen-
sory regions [13–25]. In fact, several clinical studies have
shown that lack of vestibular input leads to functional and
structural changes in the brain, either directly or indirectly.
: 2021, Volume 1 - 2 - CC-BY: © Padova et al.
R E S E A R C H A R T I C L E
: 2021, Volume 1 - 2 -
A pioneering study of subjects with bilateral vestibulop-
athy (BVP) by Brandt etal. [20] demonstrated that lack of
vestibular input leads to bilateral hippocampal atrophy
(16.91% reduction relative to controls) that correlated with
impaired spatial memory and navigation assessed by the
virtual Morris water navigation task (vMWT). Hufner etal.
[26] reported reductions in gray matter volume in the cer-
ebellum due to the schwannoma removal, supramarginal
gyrus on the same side as the lesion, postcentral and su-
perior temporal gyri, and motion-sensitive visual area MT/
V5 in pa tientswith complete unilateral vestibular deaffer-
entation (UVD) compared to healthy controls. Helmchen
etal. [27] demonstrated increases in gray matter volume
in the insula, retroinsular vestibular cortex, and superior
temporal gyrus correlated with improving clinical vestib-
ular assessments in patients recovering from vestibular
neuritis. zu Eulenburg et al. [28] showed that patients
with an acute unilateral vestibular de cit stemming from
vestibular neuritis recovery exhibited gray matter volume
reduction in the left posterior hippocampus, the right su-
perior temporal gyrus, and the right superior frontal gyrus
regardless of the side of vestibular impairment. Göttlich
etal. [29] used voxel-based morphometry (VBM) to  nd
reductions in gray matter volume in the CA3 region of
the hippocampus bilaterally with increasing vestibulop-
athy-related disability in patients with incomplete BVP
compared to healthy age- and gender-matched controls.
Kremmyda etal. [30] found that vestibular loss due to in-
complete BVP leads to gray matter volume reductions
bilaterally in the middle hippocampus and posterior par-
ahippocampus using VBM, to de cits in objective and
subjective evaluations of spatial memory and navigation
performance using the vMWT and questionnaires, and
to increased spatial anxiety. In a cross-sectional VBM
study of patients with persistent postural perceptual diz-
ziness, Wurthmann etal. [31] demonstrated reductions in
gray matter volumes in the left superior temporal gyrus,
left motion-sensitive visual area MT/V5 and bilateral
middle temporal gyrus, cerebellum (bilaterally), left-sided
posterior hippocampus, right precentral gyrus, left anterior
cingulate cortex, left side of left caudate nucleus, and left
dorsolateral prefrontal cortex.
However, little is known about which structures are affect-
ed by subclinical, age-related vestibular loss. Furthermore,
little is known about the speci c vestibular end organs (i.e.
semicircular canal and/or otolith organs) that contribute
to those changes. Bridging these knowledge gaps, novel
cross-sectional studies in healthy, older individuals found
signi cant associations between age-related vestibular
loss and gross gray matter loss of the hippocampus [38,
39] and the entorhinal cortex [39], as well as shape changes
in the hippocampus, amygdala, caudate nucleus, putamen,
thalamus, entorhinal cortex, and entorhinal-transentorhinal
cortical complex [39].
In this study, we examined the relationship between
age-related vestibular function and regional volume of
the hippocampus, entorhinal cortex, thalamus, and basal
ganglia, four structures known to process vestibular in-
formation. Linear mixed-effects regression was used to
evaluate the association between saccular, utricular, and
horizontal semicircular canal vestibulo-ocular re ex (VOR)
functions and MRI-based volumes of 97 healthy, older
participants aged 60 years and older from the Baltimore
Longitudinal Study of Aging (BLSA) over a 5-year fol-
low-up period. To our knowledge, this study is one of the
rst to investigate the associations over time between
age-related vestibular function and volumes of brain re-
gions that receive vestibular input.
MATERIALS AND METHODS
Data
Data on 97 older adult participants (aged ≥ 60 years)
who had at least one vestibular physiological test and
structural MRI scan on the same visit between 2013 and
2017 were selected from the BLSA [40–42]. All partici-
pants gave written informed consent, and none had any
history of psychiatric disorders or were diagnosed with
a vestibular, ophthalmological, or neurodegenerative
disease. Hearing loss was measured and was included
as a confounding variable in the supplemental analysis.
Vestibular physiologic testing
Vestibular function testing was based on the cervical
vestibular-evoked myogenic potential (cVEMP), ocular
VEMP (oVEMP), and video head impulse test (vHIT), which
measure saccular function, utricular function, and the
horizontal semicircular canal VOR, respectively. cVEMP
and oVEMP were recorded using a commercial electro-
myographic system (software version 14.1, Carefusion
Synergy, Dublin, OH) [32, 33]. Electromyograms (EMGs)
were recorded by disposable, pregelled Ag/AgCl elec-
trodes placed with 40-inch safety lead wires from GN
Otometrics (Schaumburg, IL). cVEMP and oVEMP signals
were ampli ed ×2500 and band-pass  ltered for the 20–
2000 Hz and 3–500 Hz frequency intervals, respectively.
Cervical vestibular-evoked myogenic potential
cVEMPs are short-latency EMGs of the relaxation re-
sponse of the sternocleidomastoid muscles induced by
sound stimuli in the ear or by head-tapping vibrations.
They measure saccular (and inferior vestibular nerve) func-
tion. The saccule is a vestibular end organ that transduces
linear acceleration, detects the orientation of the head
with respect to gravity, and plays a role in spatial cogni-
tion [32]. Testing followed an established protocol [33–35].
Participants sat on a chair inclined to 30° above the hor-
izontal plane, and quali ed examiners placed EMG elec-
trodes on the sternocleidomastoid and sternoclavicular
junction bilaterally and a ground electrode on the manu-
brium sterni. Sound stimuli of 500 Hz and 125 dB were
administered in bursts of 100 stimuli monoaurally through
: 2021, Volume 1 - 3 - CC-BY: © Padova et al.
R E S E A R C H A R T I C L E
: 2021, Volume 1 - 3 -
vestibular hypofunction [36, 44, 45]. The mean VOR gain
from the left and right sides was used in this study.
Structural MRI acquisition and processing
T1-weighted volumetric MRI scans were acquired in
the sagittal plane using a 3T Philips Achieva scanner at
the National Institute on Aging Clinical Research Unit.
Sequences included a T1 volumetric scan magnetization
prepared rapid acquisition with gradient echo (MPRAGE;
repetition time (TR) = 6.5 ms, echo time (TE) = 3.1 ms,  ip
angle = 8°, image matrix = 256 × 256, 170 slices, voxel size =
1.0 × 1.0 × 1.2 mm slice thickness, FOV = 256 × 240 mm,
sagittal acquisition). A semiautomated quality control pro-
tocol was employed to automatically identify and manu-
ally exclude scans that have segmentation errors de ned
as outliers of each region-speci c sample distribution.
Anatomical labels were obtained using Multi-atlas region
Segmentation using Ensembles of deformable registra-
tion algorithms and parameters [46]. Global and regional
brain volumes were calculated from the binary segmen-
tation output by MUSE by counting the total number of
voxels in the binary label image and multiplying that voxel
count by the spatial size of a voxel in cm3. We corrected
for intracranial volume (ICV) individually estimated at age
70 using the residual volume approach described by Jack
etal. [47]: for each region and each scan, residual volumes
were calculated as the difference, in cm3, of the measured
regional volume from the expected regional volume, given
the ICV for the individual. The basal ganglia volume was
de ned to be the sum of the volumes of the lenticular nu-
cleus, globus pallidus, and the caudate nucleus. Figure1
headphones. Recorded cVEMP amplitudes were correct-
ed for spontaneous background EMG activity collected
10 ms prior to the onset of the sound stimulus. An absent
response was de ned according to previously published
amplitude and latency thresholds [32, 33]. In case of an
absent recording, the response assessment was repeated
for con rmation. For present responses, the higher cVEMP
from the left and right sides was used in this analysis.
Ocular vestibular-evoked myogenic potential
oVEMPs are short-latency EMGs of the excitation re-
sponse of the inferior oblique muscles of the eye elicited
by vibration stimulation of the skull. They measure utric-
ular (and superior vestibular nerve) function [32]. The utri-
cle is the otolith organ that transduces linear acceleration
and detects the orientation of the head with respect to
gravity. Testing followed an established protocol [33–35].
Participants sat on a chair inclined to 30°, and quali ed
examiners placed a noninverting electrode ~3 mm below
the eye centered below the pupil, an inverting electrode
2 cm below the noninverting electrode, and a ground
electrode on the manubrium sterni. To ensure that the
signals recorded from both eyes are symmetric before
stimulation, participants were asked to perform multiple
20° vertical saccades. New electrodes were applied in
place of the old ones if the signal difference exhibited
>25% asymmetry. Participants were asked to maintain
an upgaze of 20° during oVEMP testing and recording.
Head taps were applied to the midline of the face at the
hairline and ~30% of the distance between the inion and
nasion using a re ex hammer (Aesculap model ACO12C,
Center Valley, PA). An absent response was de ned ac-
cording to previously published amplitude and latency
thresholds [32, 33]. In case of an absent recording, the
response assessment was repeated for con rmation. For
present responses, the higher oVEMP from the left and
right sides was used in this analysis.
Video head impulse test
The horizontal VOR was assessed using the vHIT [35–37].
To determine VOR gain, the vHIT was performed using
the EyeSeeCam system (Interacoustics, Eden Prarie, MN)
in the same plane as the right and left horizontal semi-
circular canals [37, 43]. The participant’s head was tilted
downward 30° below the horizontal plane to correctly
position the horizontal canals in the plane of stimulation.
Participants were asked to maintain their gaze on a wall
target ~1.5 m away. A quali ed examiner rotated the
participant’s head 5° –10° quickly (~150°–250° per sec-
ond) parallel to the ground toward the right and left at
least 10 times in both directions, chosen randomly for
unpredictability. The EyeSeeCam system quanti ed eye
and head velocity, and a corresponding VOR gain was
calculated as the unitless ratio of the eye velocity to the
head velocity. A normal eye and head velocity should be
equal, yielding a VOR gain equal to 1.0. A VOR gain <0.8
accompanied by re xation saccades suggests peripheral
Fig. 1. Simpli ed 3D illustration of three subcortical and one cortical regions of
the vestibular network in the left hemisphere of the JHU-MNI-SS brain [48]. The
medial view of the left side of the pial surface of the JHU-MNI-SS template [48]
generated by FreeSurfer and mapped to native space [49] is shown. The three
subcortical (thalamus, hippocampus, basal ganglia, comprised of the putamen,
caudate nucleus, and globus pallidus) and one cortical (entorhinal cortex) struc-
tures were obtained from the JHU-MNI-SS labels and triangulated. Vestibular
information from the semicircular canals (SCC), otoliths, and nuclei is relayed
through the thalamus to the hippocampus, entorhinal cortex, and basal ganglia.
The red arrow points toward the ventral lateral nucleus, a putative sub eld of the
thalamus that receives vestibular input [39]. CAWorks (www.cis.jhu.edu/software/
caworks) was used for visualization.
: 2021, Volume 1 - 4 - CC-BY: © Padova et al.
R E S E A R C H A R T I C L E
: 2021, Volume 1 - 4 -
where agei,j of subject i at visit j is centered at age 70,
sexi is a binary indicator variable for the sex of subject
i, and ICVi denotes baseline ICV, comprised of bilateral
cerebral volumes, cerebellum, brainstem, and cerebro-
spinal  uid, individually estimated at 70 years of age.
Age, sex, and ICV were treated as  xed effects. We
assumed linear dependence of regional volume with re-
spect to age. We assumed uai, u0i are zero-mean Gaussian
distributed with unknown variances and covariances and,
respectively, represent the intrasubject random effect,
which captures correlations between measurements
within subject i over time, and the between-subject het-
erogeneity in terms of individual deviation in regional
volume from its sample mean at age 70. The covariance
structure of random effects was taken to be unstructured.
We assumed measurement noise εi,j is independently
and identically distributed zero-mean Gaussian with un-
known common variance. The unknown  xed-effects
{βv, βo, βc, βa, βs, βi, μ} and random-effects covariance ma-
trix parameters were estimated via maximum likelihood.
All effects were considered signi cant at the p < 0.05 level.
A Benjamini-Hochberg procedure was used to control the
false discovery rate (FDR) of the comparisons made in this
study [50]. FDR q-values indicate the expected proportion
of rejected null hypotheses that are false. We considered
an FDR threshold of 0.05 and also 0.10, given that these
were initial analyses testing speci c hypotheses based
on prior work. These statistics were performed using the
xtmixed function in Stata 15 (College Station, TX).
RESULTS
Baseline and longitudinal characteristics
Table 1 shows the baseline characteristics for the study
sample from the BLSA. Eighteen participants had one
vestibular function on regional brain volume. The model
included a by-subject random intercept and a random
slope on age to account for intersubject heterogeneity
in the baseline level of and rate of change in regional
brain volume over time.
The null hypothesis in Eq. (1) predicts regional volume
voli,j, for participant i,i = 1,…,N for observation j,j = 1,…,ni.
The alternate hypotheses predict volume using mean
VOR gain termed VORi,j in Eq. (2), oVEMPi,j in Eq. (3), and
cVEMPi,j in Eq. (4) as continuous independent variables,
provides a visualization of the relative locations of the
thalamus, hippocampus, basal ganglia, and entorhinal
cortex in a three-dimensional hemibrain.
Mixed-effects modeling
Linear mixed-effects regression was used to model the
evolution of regional brain volume over time while al-
lowing a time-independent cross-sectional effect of
observation with both vestibular and MRI data available,
48 participants had two observations, and 31 participants
had three observations. In this sample, there was only a
single case of participant dropout, due to death, after two
visits. At baseline, this participant had low cVEMP, missing
oVEMP and VOR, and an average hippocampal volume.
Association between vestibular function
andregional brain volumes based
in mixed-effects models
Table 2 reports the association between vestibular func-
tion and regional brain volume. We found signi cant
relationships in which each 1-unit lower cVEMP ampli-
tude was associated with a 0.0714 cm3 ± 0.0344 (unad-
justed p = 0.038, 95% con dence interval (CI): 0.00397–
0.139) lower bilateral-mean volume of the basal ganglia
and a 0.0440 cm3 ± 0.0221 (unadjusted p= 0.046, 95%
CI: 0.000727–0.0873) lower bilateral-mean volume of
the thalamus. This means every 1-unit decrease in cVEMP
amplitude is associated with an average reduction of
~0.4% in the basal ganglia and ~0.31% in the thala-
mus. We examined the left and right hemispheres sep-
arately and found signi cant relationships for the left
thalamus (β = 0.0232, unadjusted p = 0.043, 95% CI:
0.000684–0.0457) and for both the left (β = 0.0376, un-
adjusted p = 0.048, 95% CI: 0.000385–0.0747) and right
(β =0.0359, unadjusted p = 0.045, 95% CI: 0.000727–
0.071) basal ganglia. The effect was borderline for the
right thalamus (β = 0.0231, unadjusted p = 0.065, 95%
CI: −0.00148 to 0.0477). We also found a signi cant rela-
tionship between a lower mean VOR gain and lower left
hippocampal volume (β = 0.121, unadjusted p = 0.018,
95% CI: 0.0212–0.222). In other words, every 1-unit de-
crease in mean VOR gain is associated with an average
H0vo:
i, j
l+
ai agu
)
i, j
eu
a0i
β
s
exs
ii
ICβ++V
i
=++ε
)
+
(
β
(
µi, j (1)
=β+β+β++
()
µεu+
1
Hv:ol ++β
()
uVORexsageICV
i, jv i, jaai i, jsiii0ii, j(2)
=β++
(
β+β++
()
µεu+
1
Hv:ol oVEMPexsuag
)
eICV
i, jaoi, jai i, jii 0ii i, j(3)
=β++
(
β+β:++
()
µεu+
1
Hvol cVEMPexsuag
)
eICV
i, jc ai, jai
+β
s
+β
si, jii 0ii i, j(4)
: 2021, Volume 1 - 5 - CC-BY: © Padova et al.
R E S E A R C H A R T I C L E
: 2021, Volume 1 - 5 -
with a 0.0778 cm3 ± 0.00834 (q << 0.0001 FDR correct-
ed, 95% CI: (−0.0941, −0.0614)), or −0.55% per year, re-
duction in bilateral-mean volume and a 0.0392 cm3 ±
0.0041 (q << 0.0001 FDR corrected, 95% CI: (−0.0472,
−0.0311)) reduction in left-side volume (−0.27%/year).
For the left hippocampus VOR model, every 1-year
increase in age was associated with a 0.0239 cm3 ±
0.00271 (q << 0.0001 FDR corrected, 95% CI: (−0.0292,
−0.0186)) reduction in volume (−0.33%/year). Sex pre-
dicted entorhinal cortex volume over time in each
model (q << 0.0001 FDR corrected) and right thalamus
volumes in the VOR model (β = 0.248, unadjusted p =
0.045, 95% CI: (0.00539, 0.49)). Despite failing to reject
the null hypothesis, sex showed strong trends for the
bilateral-mean (β= 0.485, unadjusted p = 0.052) and left
(β = 0.23, unadjusted p = 0.073) thalamus VOR models
and was not a predictor of volume trajectories for the
hippocampus, basal ganglia, or the thalamus cVEMP or
oVEMP models.
Because age is included as a covariate, the volume
growth trajectory related to vestibular function rep-
resents effects above and beyond those attributable to
normal age-related gray matter volume loss. This means,
in addition to the age-related volume reduction rate of
0.19% per year in the basal ganglia and 0.55% per year in
the thalamus, every 1-unit decrease in cVEMP amplitude
is associated with an average reduction of ~0.4% in the
basal ganglia and ~0.31% in the thalamus. In other words,
the cVEMP effects are 2.05 times larger in magnitude and
0.57 times smaller in magnitude than the age-related
volume reductions in the basal ganglia and thalamus, re-
spectively. The VOR effects are 5.08 times larger in mag-
nitude than the age-related volume reduction rate in the
left hippocampus.
DISCUSSION
These  ndings provide some of the  rst evidence for as-
sociations between lower cVEMP amplitude, indicative
of poorer saccular function, and signi cantly reduced
volumes of the thalamus and basal ganglia and lower
VOR gain (poorer canal function) and reduced left hip-
pocampal volumes over time in healthy, older adults
aged 60 years and older. These results are compatible
with clinical studies in patients with vestibular loss that
demonstrated that loss of peripheral vestibular inputs is
Table 1. Baseline characteristics of the study sample (n = 97). Regional volumes
are given in cm3. Observation count denotes the number of participants with at
least one visit where both vestibular and MRI data were available. SD, standard
deviation.
Characteristic Overall
N97
Age (years), mean (SD) 76 (8.39)
Sex (% female) 58.76
Region, mean (SD)
Intracranial volume 1391.39 (147.32)
Hippocampus 7.23 (0.81)
Thalamus 14.2 (1.41)
Basal ganglia 17.9 (1.99)
Entorhinal cortex 4.29 (0.605)
Observation count, n (%)
1 18 (18.6)
2 48 (49.5)
3 31 (32.0)
reduction of 0.121 cm3, or ~1.68%, in the left hippo-
campus. We found no signi cant relationships between
cVEMP and volume of the hippocampus or the ento-
rhinal cortex, no signi cant associations between VOR
and brain volume aside from the left hippocampus, and
no signi cant associations between oVEMP and region-
al volume. After controlling the FDR at the threshold
of 0.10, lower cVEMP amplitude was associated with
lower bilateral-mean volume of the thalamus (q = 0.092
FDR corrected) and with lower bilateral-mean volume
of the basal ganglia (q = 0.092 FDR corrected). In ad-
ditional analyses, we added hearing – represented by
the four-frequency pure tone average from the better
ear – to the regression models. The addition of hearing
to the models reduced the sample size from 97 to 84
participants and resulted in the signi cant associations
previously observed becoming marginally signi cant,
although with similar effect sizes (see Supplementary
Table S1).
The “aging” effect was signi cant for all models (q <<
0.0001 FDR corrected), except for the left (β = −0.0169,
unadjusted p = 0.104), right (β = −0.0167, unadjusted p=
0.064), and bilateral-mean (β = −0.0348, unadjusted p=
0.064) basal ganglia cVEMP models, which showed strong
trends of volume reductions. For the thalamus cVEMP
model, every 1-year increase in age was associated
Table 2. Vestibular predictors of regional volume (cm3) under the alternate hypothesis with mean ± standard error (unadjusted p-value). *p < 0.05.
Vestibular Variable Hippocampus Entorhinal Cortex Basal Ganglia Thalamus
Mean VOR gain 0.168 ± 0.0988
(p = 0.089)
0.0562 ± 0.169
(p = 0.740)
0.213 ± 0.183
(p = 0.244)
0.159 ± 0.129
(p = 0.217)
Best oVEMP amplitude (µV) −0.00161 ± 0.00228
(p = 0.479)
0.00116 ± 0.00337
(p = 0.730)
−0.00247 ± 0.00393
(p = 0.530)
−0.00223 ± 0.00286
(p = 0.436)
Best corrected cVEMP
amplitude
0.00119 ± 0.0174
(p = 0.945)
−0.0114 ± 0.0291
(p = 0.693)
0.0714 ± 0.0344
(p = 0.038*)
0.0440 ± 0.0221
(p = 0.046*)
: 2021, Volume 1 - 6 - CC-BY: © Padova et al.
R E S E A R C H A R T I C L E
: 2021, Volume 1 - 6 -
sample after two visits due to death. Additionally, there
was no difference in the proportion of participants with
normal versus low cVEMP amplitude (≤25th percentile)
at baseline who had intermittently missing follow-up
observations (and in all cases all available data were
used in analyses).
We note limitations of this study. The relationship
between vestibular function and brainstem and cere-
bellar structures were not studied, as these structures
have been more challenging to parcellate due to their
complex anatomy, and robust measures to analyze the
brainstem and cerebellum in all BLSA participants are
currently being developed. Additionally, we also did
not investigate the potential mediation or modi cation
of the effects of age-related vestibular loss by interven-
ing brain structures such as the cerebellum, brainstem,
or hypothalamus. Moreover, the generalizability of our
results is limited by the age range studied and the ten-
dency of the BLSA participants to have higher levels of
education and socioeconomic status than the broader
adult population. Whether these  ndings can also be
detected in younger adults with reduced vestibular func-
tion is unclear.
Future work will be needed to further clarify the rela-
tionships between vestibular function and the structure
of regions of the limbic system, temporoparietal junc-
tion, and frontal cortex – all of which receive vestibular
input – and their temporal sequence of effects relative
to each other. Additionally, subsequent studies will
need to investigate the direction of causal in uence
between vestibular loss and regional size and shape
changes, while correcting for potential confounding
factors such as hearing or vision loss. Structural equa-
tion modeling with longitudinal data in which vestib-
ular measurements precede structural measurements
can help tease out the direct or indirect relationships
between vestibular function and brain structures.
Cortical thickness of cortical structures, such as the
entorhinal cortex, insula, and prefrontal cortex, can
provide a sensitive measure of cortical integrity com-
plementary to shape changes. Changepoint analysis of
longitudinal data can identify nonlinearities in the tra-
jectories of structural change. By temporally ordering
the set of changepoints for each structure measure,
the sequence of changes in the vestibular network
can be revealed. Future studies will be needed to test
whether there are modulating effects on downstream
structures via intervening brain structures such as the
brainstem, hypothalamus, and cerebellum.
CONCLUSIONS
This study examined the association between reduced
vestibular function and regional brain volume over time
in aging adults. To our knowledge, this study is one of the
rst to demonstrate signi cant relationships between
associated with gray matter reductions in the hippocam-
pus [20, 28–31] and basal ganglia [31]. cVEMP measures
the physiological function of the saccule, the vestibular
end organ that detects linear acceleration and gravita-
tional cues, and preserves spatial orientation [1, 32]. VOR
gain measures the physiological function of the hori-
zontal semicircular canal, the vestibular end organ that
detects angular acceleration in the transverse plane [1].
Prior work has shown that abnormal VOR gain [11] and
lower cVEMP amplitude are signi cantly associated with
poorer spatial cognitive performance in healthy, older
adults [1, 11, 12]. Importantly, this work expands the un-
derstanding of the role of the peripheral vestibular sys-
tem in anatomical alterations.
We note that the effect sizes of the relationship be-
tween vestibular measures and changes in gray matter
volumes over time are small. These small, though signif-
icant, effect sizes may re ect the indirect links between
the peripheral vestibular system and the thalamus and
basal ganglia. Vestibular inputs are known to traverse
through brain structures such as the cerebellum, brain-
stem, and hypothalamus, where additional afferent in-
puts are integrated (e.g. visual, auditory, autonomic),
thereby modulating and attenuating the direct impact
of vestibular loss on central structural changes [51, 52].
Whether these changes in gray matter volumes repre-
sent loss of neurons remains unclear in the absence of
additional physiological or tissue studies. As such, the
extent to which these effect sizes re ect underlying neu-
ronal loss is unclear. Notably, the aging effects described
are consistent with the age-related cerebral volume re-
duction rates of ~0.5% per year found in previous longi-
tudinal studies in normal older controls [53, 54].
A previous cross-sectional study in healthy, older
adults demonstrated that saccular sensory loss, de ned
as lower cVEMP amplitude, was associated with signif-
icant gross volume loss of the hippocampus [38]. We
did not observe the same relationship between cVEMP
amplitude and hippocampal volume in this longitudi-
nal analysis. A possible explanation for this discrepancy
between the cross-sectional and longitudinal  ndings
is that the hippocampal volume reduction may have
largely occurred prior to the start of this longitudinal
period, such that the relationship was signi cant in the
baseline cross-sectional analysis but not in the longitu-
dinal analysis. In support of this explanation, one-way
analysis of covariance (ANCOVA) controlling for age,
sex, and ICV suggests the baseline bilateral-mean hip-
pocampal volume in participants with impaired cVEMP
at baseline is 0.34 cm3 smaller compared to those
withunimpaired cVEMP at baseline (p = 0.014, 95% CI:
(−0.608, −0.0717)). Another possible explanation for the
discrepancy between our cross-sectional and longitudi-
nal  ndings is a systematic difference between the two
cohorts, due to nonrandom, biased loss to longitudinal
follow-up. However, this is unlikely, given that there was
only a single participant who dropped out of this study
: 2021, Volume 1 - 7 - CC-BY: © Padova et al.
R E S E A R C H A R T I C L E
: 2021, Volume 1 - 7 -
16. Leong ATL, Gu Y, Chan YS, Zheng H, Dong CM, Chan RW, etal. Optogenetic
fMRI interrogation of brain-wide central vestibular pathways. Proceedings
of the National Academy of Sciences USA 2019;116(20):10122–29.
17. Stiles L, Smith PF. The vestibular–basal ganglia connection: balancing
motor control. Brain Research 2015;1597:180–88.
18. Fasold O, von Brevern M, Kuhberg M, Ploner CJ, Villringer A, Lempert T,
etal. Human vestibular cortex as identi ed with caloric stimulation in func-
tional magnetic resonance imaging. Neuroimage 2002;17(3):1384–93.
19. Dieterich M, Bense S, Lutz S, Drzezga A, Stephan T, Bartenstein P, et al.
Dominance for vestibular cortical function in the non-dominant hemisphere.
Cerebral Cortex 2003;13(9):994–1007.
20. Brandt T, Schautzer F, Hamilton DA, Brüning R, Markowitsch HJ, Kalla R,
et al. Vestibular loss causes hippocampal atrophy and impaired spatial
memory in humans. Brain: A Journal of Neurology 2005;128(11):2732–41.
21. Potegal M, Copack P, de Jong J, Krauthamer G, Gilman S. Vestibular input
to the caudate nucleus. Experimental Neurology 1971;32(3):448–65.
22. Suzuki M, Kitano H, Ito R, Kitanishi T, Yazawa Y, Ogawa T, etal. Cortical and
subcortical vestibular response to caloric stimulation detected by function-
al magnetic resonance imaging. Brain Research Cognitive Brain Research
2001;12(3):441–49.
23. Rancz EA, Moya J, Drawitsch F, Brichta AM, Canals S, Margrie TW. Widespread
vestibular activation of the rodent cortex. The Journal of Neuroscience
2015;35(15):5926–34.
24. Vitte E, Derosier C, Caritu Y, Berthoz A, Hasboun D, Soulié D. Activation of
the hippocampal formation by vestibular stimulation: a functional magnetic
resonance imaging study. Experimental Brain Research 1996;112(3):523–26.
25. Lopez C, Blanke O, Mast FW. The human vestibular cortex revealed by coor-
dinate-based activation likelihood estimation meta-analysis. Neuroscience
2012;212:159–79.
26. Hufner K, Stephan T, Hamilton D, Kalla R, Glasauer S, Strupp M, etal. Gray-
matter atrophy after chronic complete unilateral vestibular deafferentation.
Annals of the New York Academy of Sciences 2009;1164(1):383–85.
27. Helmchen C, Klinkenstein J, Machner B, Rambold H, Mohr C, Sander T.
Structural changes in the human brain following vestibular neuritis indicate
central vestibular compensation. Annals of the New York Academy of Sciences
2009;1164(1):104–15.
28. zu Eulenburg P, Stoeter P, Dieterich M. Voxel‐based morphometry de-
picts central compensation after vestibular neuritis. Annals of Neurology
2010;68(2):241–49.
29. Göttlich M, Jandl NM, Sprenger A, Wojak JF, Münte TF, Krämer UM, etal.
Hippocampal gray matter volume in bilateral vestibular failure. Human Brain
Mapping 2016;37(5):1998–2006.
30. Kremmyda O, Hüfner K, Flanagin VL, Hamilton DA, Linn J, Strupp M, etal.
Beyond dizziness: virtual navigation, spatial anxiety and hippocampal volume
in bilateral vestibulopathy. Frontiers in Human Neuroscience 2016;10:139.
31. Wurthmann S, Naegel S, Steinberg BS, Theysohn N, Diener HC,
Kleinschnitz C, etal. Cerebral gray matter changes in persistent postural
perceptual dizziness. Journal of Psychosomatic Research 2017;103:95–101.
32. Li C, Zuniga MG, Nguyen KD, Carey JP, Agrawal Y. How to interpret latencies
of cervical and ocular vestibular-evoked myogenic potentials: our experi-
ence in  fty-three participants. Clinical Otolaryngology 2014;39(5):297–301.
33. Nguyen KD, Welgampola MS, Carey JP, Nguyen KD, Welgampola MS,
Carey JP. Test-retest reliability and age-related characteristics of the oc-
ular and cervical vestibular evoked myogenic potential tests. Otology &
Neurotology 2010;31(5):793–802.
34. Li C, Layman AJ, Carey JP, Agrawal Y. Epidemiology of vestibular evoked
myogenic potentials: data from the Baltimore Longitudinal Study of Aging.
Clinical Neurophysiology 2015;126(11):2207–15.
35. Harun A, Oh ES, Bigelow RT, Studenski S, Agrawal Y. Vestibular impairment
in dementia. Otology & Neurotology 2016;37(8):1137–42.
36. Agrawal Y, Davalos-Bichara M, Zuniga MG, Carey JP. Head impulse test
abnormalities and in uence on gait speed and falls in older individuals.
Otology & Neurotology 2013;34(9):1729–35.
37. Agrawal Y, Schubert MC, Migliaccio AA, Zee DS, Schneider E, Lehnen N,
et al. Evaluation of quantitative head impulse testing using search coils
versus video-oculography in older individuals. Otology & Neurotology
2014;35(2):283–88.
38. Kamil RJ, Jacob A, Ratnanather JT, Resnick SM, Agrawal Y. Vestibular func-
tion and hippocampal volume in the baltimore longitudinal study of aging
(BLSA). Otology & Neurotology 2018;39(6):765–71.
39. Jacob A, Tward DJ, Resnick S, Smith PF, Lopez C, Rebello E, etal. Vestibular
function and cortical and sub-cortical alterations in an aging population.
Heliyon 2020;6(8):e04728.
40. Shock NW, Gerontology Research Center. Normal human aging: the
Baltimore longitudinal study of aging. Baltimore, MD: U.S. Dept. of Health
and Human Services, Public Health Service, National Institutes of Health,
vestibular loss – saccular and semicircular canal sensory
loss in particular – and gray matter volume loss of the
thalamus, basal ganglia, and left hippocampus, three
vestibular subcortical structures that receive peripher-
al vestibular input. Future work will need to determine
the timing and sequence of the relationships between
vestibular function and neuromorphological alterations.
ACKNOWLEDGMENTS
This work was supported in part by the National Institute
on Aging [grant number R01 AG057667], National
Institute on Deafness and Other Communication
Disorders [grant number R03 DC015583], and National
Institutes of Health [grant number P41 EB015909] and by
the Intramural Research Program, National Institute on
Aging, National Institutes of Health.
CONFLICTS OF INTEREST
The authors report no con icts of interest.
REFERENCES
1. Smith PF. The growing evidence for the importance of the otoliths in spatial
memory. Frontiers in Neural Circuits 2019;13:66.
2. Bigelow RT, Agrawal Y. Vestibular involvement in cognition: visuospatial
ability, attention, executive function, and memory. Journal of Vestibular
Research 2015;25(2):73–89.
3. Cullen KE. The neural encoding of self-generated and externally applied
movement: implications for the perception of self-motion and spatial
memory. Frontiers in Integrative Neuroscience 2014;7:108.
4. Smith PF, Zheng Y. From ear to uncertainty: vestibular contributions to cog-
nitive function. Frontiers in Integrative Neuroscience 2013;7:84.
5. Yoder RM, Taube JS. The vestibular contribution to the head direction sig-
nal and navigation. Frontiers in Integrative Neuroscience 2014;8:32.
6. Agrawal Y, Carey JP, Della Santina CC, Schubert MC, Minor LB. Disorders
of balance and vestibular function in US adults: data from the National
Health and Nutrition Examination Survey, 2001–2004. Archives of Internal
Medicine 2009;169(10):938–44.
7. Paige GD. Senescence of human visual-vestibular interactions. Journal of
Vestibular Research 1992;2(2):133–51.
8. Zalewski CK. Aging of the human vestibular system. Seminars in Hearing
2015;36(3):175–96.
9. Semenov YR, Bigelow RT, Xue Q, du Lac S, Agrawal Y. Association between
vestibular and cognitive function in U.S. adults: data from the National
Health and Nutrition Examination Survey. The Journals of Gerontology:
Series A: Biological Sciences and Medical Sciences 2016;71(2):243–50.
10. Bigelow RT, Semenov YR, Trevino C, Ferrucci L, Resnick SM, Simonsick EM,
etal. Association between visuospatial ability and vestibular function in the
Baltimore Longitudinal Study of Aging. Journal of the American Geriatrics
Society 2015;63(9):1837–44.
11. Xie Y, Bigelow RT, Frankenthaler SF, Studenski SA, Moffat SD, AgrawalY.
Vestibular loss in older adults is associated with impaired spatial navigation:
data from the triangle completion task. Frontiers in Neurology 2017;8:173.
12. Anson ER, Ehrenburg MR, Wei EX, Bakar D, Simonsick E, Agrawal Y.
Saccular function is associated with both angular and distance errors on the
triangle completion test. Clinical Neurophysiology 2019;130(11):2137–43.
13. Bilkey DK. Space and context in the temporal cortex. Hippocampus
2007;17(9):813–25.
14. Lopez C, Blanke O. The thalamocortical vestibular system in animals and
humans. Brain Research Reviews 2011;67(1–2):119–46.
15. Hitier M, Besnard S, Smith PF. Vestibular pathways involved in cognition.
Frontiers in Integrative Neuroscience 2014;8:59.