Journal of Psychosomatic Research 77 (2014) 391–400

Contents lists available at ScienceDirect

Journal of Psychosomatic Research

Personality traits modulate subcortical and cortical vestibular and anxiety responses to sound-evoked otolithic receptor stimulation Iole Indovina a,b,⁎, Roberta Riccelli c, Jeffrey P. Staab d, Francesco Lacquaniti a,b,e, Luca Passamonti f a

Laboratory of Neuromotor Physiology, IRCCS Santa Lucia Foundation, 00179, Rome, Italy Centre of Space BioMedicine, University of Rome Tor Vergata, 00173, Rome, Italy Department of Medical and Surgical Sciences, University “Magna Graecia”, Catanzaro, Italy d Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA e Department of Systems Medicine, Neuroscience Section, University of Rome Tor Vergata, 00133 Rome, Italy f Institute of Bioimaging and Molecular Physiology, National Research Council 88100, Catanzaro, Italy b c

a r t i c l e

i n f o

Article history: Received 20 March 2014 Received in revised form 31 July 2014 Accepted 5 September 2014 Keywords: Anxiety Neuroticism Introversion Sound-evoked vestibular stimulation fMRI Chronic subjective dizziness

a b s t r a c t Objective: Strong links between anxiety, space-motion perception, and vestibular symptoms have been recognized for decades. These connections may extend to anxiety-related personality traits. Psychophysical studies showed that high trait anxiety affected postural control and visual scanning strategies under stress. Neuroticism and introversion were identified as risk factors for chronic subjective dizziness (CSD), a common psychosomatic syndrome. This study examined possible relationships between personality traits and activity in brain vestibular networks for the first time using functional magnetic resonance imaging (fMRI). Methods: Twenty-six right-handed healthy individuals underwent fMRI during sound-evoked vestibular stimulation. Regional brain activity and functional connectivity measures were correlated with personality traits of the Five Factor Model (neuroticism, extraversion-introversion, openness, agreeableness, consciousness). Results: Neuroticism correlated positively with activity in the pons, vestibulo-cerebellum, and para-striate cortex, and negatively with activity in the supra-marginal gyrus. Neuroticism also correlated positively with connectivity between pons and amygdala, vestibulo-cerebellum and amygdala, inferior frontal gyrus and supra-marginal gyrus, and inferior frontal gyrus and para-striate cortex. Introversion correlated positively with amygdala activity and negatively with connectivity between amygdala and inferior frontal gyrus. Conclusions: Neuroticism and introversion correlated with activity and connectivity in cortical and subcortical vestibular, visual, and anxiety systems during vestibular stimulation. These personality-related changes in brain activity may represent neural correlates of threat sensitivity in posture and gaze control mechanisms in normal individuals. They also may reflect risk factors for anxiety-related morbidity in patients with vestibular disorders, including previously observed associations of neuroticism and introversion with CSD. © 2014 Elsevier Inc. All rights reserved.

Introduction Anxiety influences postural control and locomotion in health and disease, though neural mechanisms responsible for these effects are incompletely understood. In the 1870s, publication of the original definition of agoraphobia (i.e., spatial disorientation and fear in busy town squares) sparked debates about interactions among anxiety, spatial orientation, and gait [1]. A century later, these interactions were investigated in clinical and laboratory studies [1,2]. Healthy people, when positioned at height, were found to have a stiffer stance and experience greater state anxiety, lower balance confidence, and higher autonomic arousal [3–9]. Individuals with high trait anxiety stiffened their stance under modest stress that did not alter postural control of those with ⁎ Corresponding author at: Santa Lucia Foundation, Via Ardeatina 306, 00179 Rome Italy. E-mail address: [email protected] (I. Indovina).

http://dx.doi.org/10.1016/j.jpsychores.2014.09.005 0022-3999/© 2014 Elsevier Inc. All rights reserved.

low trait anxiety [10]. Conversely, vestibular disorders were identified as potent triggers of secondary anxiety disorders [11–18] and elevated state anxiety was associated with lower functional status [19] and poorer treatment outcomes [19,20]. Animal studies provided evidence about important neural connections between subcortical anxiety and vestibular systems [21–26]. Information about head motion is conveyed from vestibular labyrinths to vestibular nuclei, and then to pathways that control oculomotor and spinal reflexes, modulated by loops through the cerebellum. This information reaches systems that mediate affective responses via pathways from vestibular nuclei through the pontine nuclei to the amygdala [2,21–23]. In the cortex, vestibular, visual, proprioceptive, and somatosensory information about space and motion reach associative regions via the thalamus. In monkeys, the core vestibular cortex is called the parieto-insular vestibular cortex. The human homologue of this region includes sylvian and peri-sylvian areas at the interface between the posterior- and retro-insula, posterior superior temporal gyrus (STg)

392

I. Indovina et al. / Journal of Psychosomatic Research 77 (2014) 391–400

and parietal operculum. Neuroimaging studies showed that human vestibular cortical network includes the inferior parietal lobule [supramarginal gyrus (SMg), temporo-parietal junction and ventral intraparietal area], parts of the prefrontal cortex [e.g., the inferior frontal gyrus (IFg)], and the anterior cingulate cortex and hippocampus [27–33]. Vestibular and visual cortices interact in a reciprocally inhibitory manner. Vestibular stimuli activate vestibular cortex and suppress visual cortical function, whereas visual motion stimuli do the opposite [34,35]. Thus, the human vestibular cortex is a multimodal processor that integrates vestibular, visual, proprioceptive, somatosensory, and motor information [36–38]. It also overlaps regions that process anxiety and affective responses, particularly in the posterior parietal, insular, hippocampal and prefrontal areas [25,39–41]. This may provide the cortical substrate for anxiety to influence vestibular information processing and for vestibular data to affect emotional states. Researchers have developed increasingly sophisticated models of vestibular–anxiety interactions at subcortical and cortical levels to explain vestibular symptoms in patients with primary anxiety disorders, and secondary anxiety disorders in patients with vestibular illnesses [2,21,23]. These models may extend to other conditions with vestibularanxiety interactions, such as height phobia and phobic postural vertigo [42,43] or chronic subjective dizziness (CSD) [2,44,45]. The latter two are similar conditions that manifest with chronic non-vertiginous dizziness or unsteadiness exacerbated by upright posture, head motion, and exposure to complex or moving visual stimuli, usually triggered by acute vestibular or balance disorders. They occupy a place in clinical neurotology akin to irritable bowel syndrome in gastroenterology (i.e., independent psychosomatic conditions that occur with or without medical or psychiatric comorbidity). A pre-existing anxiety diathesis may increase the risk of developing CSD [18,46], add chronic psychiatric comorbidity [18,46], and reduce treatment response [47]. Personality traits of neuroticism and introversion were more closely associated with CSD than with comorbid neurotologic disorders producing similar levels of vestibular and psychological symptoms [48]. In contrast, resilience, life satisfaction, and strong sense of coherence predicted lower rates of persistent dizziness after acute vestibular illnesses [49]. Thus, personality traits associated with anxiety, specifically neuroticism and introversion may be important factors for anxiety-mediated vestibular conditions. This untested hypothesis rests on the supposition that neurotic, introverted people compared to non-neurotic, extraverted individuals have: (1) central vestibular systems that are more reactive to vestibular stimuli, (2) anxiety systems that are more reactive to vestibular stimuli, or (3) central vestibular systems that react more strongly to inputs from anxiety systems during vestibular stimulation. To investigate these possible mechanisms, we examined correlations between personality traits of the Five Factor Model (neuroticism, extraversion–introversion, agreeableness, openness, and conscientiousness) measured by the Revised NEO Personality Inventory (NEO-PI-R) [50] and brain activity and connectivity within vestibular and anxiety networks using functional magnetic resonance imaging (fMRI) in healthy volunteers stimulated with short tone bursts (STB) at 100 dB SPL. The STB procedure is known to activate primary afferents in sacculi of the labyrinths and evoke robust responses in vestibular cortical areas [51–53]. By using healthy and drug-free volunteers imaged while in a comfortably relaxed state, we focused on inherent relationships among personality traits and brain activity during vestibular stimulation in subjects who were free of potential confounds of high state anxiety, vestibular or anxiety disorders, and medications. We predicted that higher neuroticism and lower extraversion scores (i.e., introversion) would correlate with increased reactivity to STB stimuli in subcortical and cortical vestibular and anxiety regions and greater vestibular–anxiety system connectivity, thereby identifying potential neural substrates for clinical vestibular conditions ranging from comorbid anxiety in vestibular illnesses to CSD and phobias of heights [2].

Participants and methods Participants Twenty-six healthy volunteers (14 females, mean age = 32.4 ± 7.3 years) gave written informed consent to participate in this study, which was approved by the local Research Ethics Committee according to the Helsinki declaration (http://www.wma.net/en/30publications/ 10policies/b3/). Participants were systematically screened to exclude migraine, chronic medical illnesses, pregnancy, medication use, smoking, or history of head injury. The MINI International Neuropsychiatric Inventory was used to exclude those with past or present psychiatric disorders [54]. All participants were right-handed, as assessed via the Edinburgh Handedness Inventory [55]. To measure personality traits of the Five Factor model, all participants completed a computerized version of the Italian translation of the NEO-PI-R questionnaire [50]. Standardized T-scores for each personality factor were calculated via a script written in SPSS (Statistical Package for Social Sciences, http://www.spss.it/) using combined sex-norms reported in the NEO-PI-R manual. fMRI task Experimental stimuli were administered via piezo-electric MRI compatible headphones (NordicNeuroLab,http://www.nordicneurolab. com/Products_and_Solutions/fMRI_Hardware/AudioSystem.aspx). Previous studies demonstrated that unilateral STB stimuli at 100 dB sound pressure level (SPL) generate vestibular evoked motor potentials (VEMPs) in sternocleidomastoid muscles ipsi- and contralateral to the stimulated ear, a response used in clinical practice to assess saccular function [51,53,56–58]. STB 100 dB SPL also evoke robust responses in vestibular cortical regions [51,53] (see also Supplementary Materials). In contrast, the same STB stimuli delivered at 65 dB SPL do not evoke VEMPs or activate the cortex [51,53]. Caloric and galvanic vestibular stimuli have been used in other fMRI studies of vestibular brain activity [31], although their thermal and electrical sensations create undesirable effects that are more difficult to control than non-vestibular responses to STBs. For example, caloric and galvanic stimuli are more likely to elicit head movements that degrade fMRI data. Hence, to investigate how personality traits influenced reactivity of the vestibular and anxiety systems, we compared responses to identical STBs at 100 dB and 65 dB SPL. To control for non-specific reactions to sound, we also obtained brain responses to white-noise stimuli at 100 dB SPL. STBs had a frequency of 500 Hz, rise and fall times of 1 ms, plateau times of 8 ms, and were presented at repetition rates of 3 Hz, as recommended in a number of previous studies [59–61]. Whitenoise stimuli were sinusoidally modulated signals that reproduced the time variability of STBs. In particular, white-noise had a loudness that varied at a frequency of 3 Hz. This prevented habituation to white-noise stimuli while obtaining data to control for startle and other non-specific responses. The experimental task included four stimuli: (1) STB100dB SPL; (2) STB65dB SPL; (3) white noise 100dB SPL; and (4) rest periods with no stimulus presentation. Forty-five stimuli per type were grouped in blocks lasting 15 sec each (rest blocks also lasted 15 sec). Four sessions (2 for the left and 2 for the right ear) including 4 blocks per type of stimuli were presented in about 16 minutes. The order of sessions and side of first stimulated ear were counterbalanced across all participants. To attenuate interferences from MRI scanner noise, we isolated the headphones with soundproof foam cushions and used foam plugs in the non-stimulated ear. Participants were asked to fixate a central point, attend to auditory stimuli, and report how many types of stimuli they heard. Following data acquisition, participants were asked to report the unpleasantness of each type of stimulus on an annoyance scale from 1 to 10 and any sensations of illusory body motion. All

I. Indovina et al. / Journal of Psychosomatic Research 77 (2014) 391–400

393

Table 1 Correlation between sound-evoked brain vestibular responses and personality traits Positive

Negative P

Z

x

y

0.045

3.60

−56

−58

42

B. Extraversion Amygdala R (ReS)

0.008

3.38

24

0

−24

C. Openness IFg (Triang) L (ReS)

0.014

3.97

−52

34

12

A. Neuroticism Cerebellar nuclei L (ReS) Cerebellar nuclei R (ReS) Pontine nuclei L (ReS) Pontine nuclei R (ReS) Visual cortex L (V2) (LeS) SMg L (PFm) (LeS)

P

Z

x

y

z

0.002 0.005 0.009 0.030 0.009

3.85 3.53 3.81 3.38 4.17

−8 2 −2 2 −18

−52 −54 −22 −24 −102

−24 −24 −26 −24 −4

z

Correlation between sound-evoked brain vestibular responses (STB100dB vs. STB 65 dB excluding white noise vs. rest related activity) and personality traits at P b 0.05, small volume correction. Activations in the visual area (V2) and SMg refer to the Left ear Stimulation (LeS) while activations in the cerebellum, amygdala and IFg (Triang) refer to the Right ear Stimulation (ReS). Z = Z-score, L = left hemisphere, R = right hemisphere. x,y,z = MNI coordinates in millimeters. SMg = supra marginal gyrus, IFg (triang) = inferior frontal gyrus pars triangularis.

volunteers confirmed that all stimuli were clearly distinguishable. They reported that STB and white-noise stimuli at 100 dB were equally annoying (mean ± std = 4.7 ± 2.7 and 5.2 ± 2.9, respectively; paired t-test p = 0.3), whereas STB stimuli at 65 dB were less bothersome

(mean ± std = 2.3 ± 2.2; p b 0.001 paired t-test versus STB100dB and white noise). Levels of annoyance did not correlate with NEOPI-R scores (p N 0.2). Participants did not report any illusory body motion.

Fig. 1. Main effects of vestibular and acoustic stimulation. Statistical parametric maps (shown at P b 0.001 uncorrected for visualization purposes) for the STB100dB N rest comparison (A), STB65dB N rest (B), modulated white noise 100 dB N rest (C), and STB100dB N STB65dB exclusively masked for white noise (D). Maps are separately reported for right and left ear stimulation in normalized sterotactic space, overlaid on a high-resolution anatomical MR image (CH2, Montreal Neurological Institute), with the right side shown on the right. Sagittal, coronal and axial slices are centered on the first peak relative to each contrast reported on Supplementary Table S1.

394

I. Indovina et al. / Journal of Psychosomatic Research 77 (2014) 391–400

Image acquisition

Image pre-processing

fMRI was performed on a 3-T unit with an eight-channel head coil. Head movements were minimized using foam pads around participants' head. No participant had head movements N2 mm. Whole-brain fMRI data were acquired with echo planar images sensitive to blood oxygenation level-dependent (BOLD) contrast (39 axial slices, 3-mm thickness each; repetition time = 2000 ms; echo time = 30 ms; voxel size: 3× 3 × 3 mm).

Data were pre-processed using SPM8 (http://www.fil.ion.ucl.ac.uk/spm/). Images were realigned to the first scan by rigid body transformations to correct for head movements. Realigned scans were normalized to the standard template in the Montreal Neurological Institute space using linear and nonlinear transformations, and finally images were smoothed with a Gaussian kernel of full width at half maximum of 8 mm.

Fig. 2. Effect of individual differences in neuroticism on brain activations during unilateral sound-evoked vestibular stimulation. Neuroticism scores were positively associated with the activity in the cerebellar fastigial nuclei (A), and superior pons (B) during right saccular stimulation, and with parastriate visual cortex (V2) response during left saccular stimulation (C). In contrast, neuroticism levels were negatively linked with the response in the supra-marginal gyrus (SMg) during left ear stimulation (D). The plots of the data are from the local maxima in each region. The coordinates (X,Y,Z) are in the Montreal Neurological Institute space. Color bars represent T-statistics. Black lines represent the regression lines. Red lines are the 95% confidence interval. BOLD, blood oxygenation level dependent.

I. Indovina et al. / Journal of Psychosomatic Research 77 (2014) 391–400

fMRI analysis of regional responses For each participant, general linear models (GLMs) assessed regionally specific effects of task parameters on BOLD activations. First-level GLMs included 4 experimental conditions (STB100dB, STB65dB, whitenoise 100dB, and rest) modeled as epochs of fixed duration and convolved with the hemodynamic response function, and 6 realignment parameters as effects of no interest to remove residual motion-related variance. Low-frequency signal drift was eliminated using a high-pass filter (cut-off, 128 sec). Autoregressive AR(1) models corrected for voxels' autocorrelations. Subjects' specific contrast images (i.e., STB100dB N rest, STB65dB N rest, white-noise 100dB N rest, STB100dB N STB65dB) were generated separately for right and left ears, averaging the two sessions of each side, and entered into second-level GLMs investigating the main effect of the task per each contrast (one sample t-tests). Because whitenoise stimuli were qualitatively different from STBs, they were not included in the comparison assessing brain activations associated with vestibular stimulation (i.e., the STB100dB N STB65dB contrast). Instead, white noise 100dB N rest contrast was used to exclusively mask the STB100dB N STB65dB comparison. This way, we eliminated residual auditory activity that may have been present in the STB100dB N STB65dB contrast as a result of differences in stimulus loudness. To create the exclusive mask from the white noise 100dB N rest contrast, we used a lenient threshold of P ≤ 0.05, uncorrected. This threshold was chosen

395

to exclude non-specific auditory voxels from the main STB100dB N STB65dB comparison in a conservative way. The effects of Five Factor personality traits on brain vestibular responses were evaluated via multiple regression GLMs assessing correlations between subject-specific BOLD activity for the contrast STB100dB N STB65dB (exclusively masked for the white-noise 100dB N rest comparison) with individual scores of NEO-PI-R personality factors. Second level maps were thresholded using two methods. First, we reported regions that met a threshold of P≤0.05, Family Wise Error (FWE), whole-brain correction for multiple comparisons. Second, we employed a region of interest (ROI) approach using a threshold of P ≤ 0.05, FWE, small volume correction (svc). This standard, commonly employed procedure not only ensured robust protection against type I errors but also prevented false negative results, particularly in ROIs for which we had strong a priori hypotheses [62,63]. The vestibular nuclei, cerebellar fastigial nuclei and parieto-insular vestibular cortex homologue were defined as ROIs given their key roles in processing vestibular stimuli [27–32]. Primary and secondary visual areas (i.e., V1 and V2) were included as a ROI to test for the presence of reciprocal inhibitory effects between visual and vestibular cortices found in previous studies [34,35,64]. The amygdala was considered a ROI given its role in emotional behaviors in healthy people [40]. Finally SMg, IFg, anterior cingulum, and hippocampus were considered for their roles in both anxiety and vestibular mechanisms [29–31,33, 39–41]. Each ROI was defined according to anatomical regions described in the SPM Anatomy toolbox and automated anatomical labeling (aal) atlas [65–68]. The visual cortex ROI included primary and secondary visual cortices (V1 plus V2), whereas the peri-sylvian ROI was constituted by the whole insula (as obtained from aal), parietal operculum, and STg. This ROI also included retro-insula that was not incorporated into the whole insula anatomical ROI. The SMg ROI included five regions defined by von Economo's nomenclature [69]. The IFg comprised pars opercularis, triangularis, and orbitalis. The amygdala, anterior cingulum and hippocampal ROIs were taken from aal. As specific anatomical ROIs for cerebellar fastigial nuclei were not available, we used a 8-mm radius sphere ROI centered on coordinates reported in Dimitrova et al. 2002 (i.e., X ± 4, Y − 50, Z − 28) [70]. Similarly, reliable coordinates for brainstem vestibular nuclei were not available, so we defined a 15-mm radius ROI centered on the coordinates in the brainstem obtained from a previous fMRI study using vestibular stimulation [71]. Next, to localize more precisely pontine activations that were found in correlation analyses, we employed the Duvernoy’s atlas [72]. Task-dependent functional connectivity analyses

Fig. 3. Effect of individual differences in introversion on brain activations during right ear vestibular stimulation. Introversion scores were positively associated with the activity in the right amygdala during right saccular stimulation. The plot of the data is from the local maxima in the amygdala. The coordinates (X,Y,Z) are in the Montreal Neurological Institute space. The color bars represents T-statistics. Black line represents the regression line. Red lines are the 95% confidence interval. BOLD, blood oxygenation level dependent.

Psycho-physiological interaction (PPI) in GLMs To investigate how personality traits modulated functional connectivity within the vestibular and anxiety systems, we performed psychophysiological interaction (PPI) analyses. A PPI represents the change in connectivity (i.e., correlation) between couples of regions (i.e., the ‘seed’ and the rest of the brain) that is induced by a specific task (here, vestibular N non-vestibular stimulation) [73]. We sought to identify brain target areas that had differential connectivity with a series of seed regions (i.e., V1–V2, SMg, cerebellum (fastigium), pons, amygdala and IFg, Table 1) as functions of processing vestibular Nnon-vestibular stimuli and personality factors (i.e., higher-order PPIs) [74–76]. Seed regions were those that showed significant effects of personality traits on regional brain responses (Table 1). Time-series for participants' seeds were computed using first eigenvariates from all voxels' time series within a 8-mm sphere and then deconvolved to estimate neuronal time series [77]. Separate PPIs were carried out for the contrast STB100dB N STB65dB (exclusively masked for the white-noise 100dB N rest comparison), using right or left ear stimulation data and each previously described seed. PPI

396

I. Indovina et al. / Journal of Psychosomatic Research 77 (2014) 391–400

Fig. 4. Effect of individual differences in neuroticism on brain functional connectivity during sound-evoked vestibular stimulation. During right saccular stimulation, neuroticism scores were positively associated with the functional connectivity between the left cerebellar fastigial nucleus “seed” region and the right amygdala (A), and with the functional connectivity between the superior pons “seed” and the right amygdala (B). During left saccular stimulation, neuroticism levels were positively linked with the functional connectivity between the left para-striate visual cortex (V2) “seed” and the left inferior frontal gyrus (IFg) pars triangularis (C) and with the connectivity between the left supra-marginal gyrus (SMg) “seed” and the left IFg pars triangularis (D). The plots of the data are from the local maxima in each region. The coordinates (X,Y,Z) are in the Montreal Neurological Institute space. Color bars represent T-statistics. Black lines represent the regression lines. Red lines are the 95% confidence interval. BOLD, blood oxygenation level dependent.

regressors were calculated as element-by-element products of the seed region neuronal time series and a vector coding main effect of task (i.e., 1 for STB100dB, − 1 for STB65dB). PPI regressors were entered in first-level GLMs including the main effect of task and 6 movement parameters as effects of no interest. Subject-specific PPI contrast images were entered into second-level GLMs that identified brain areas for which changes in connectivity to seeds (for the contrast STB100dB NSTB65dB, exclusively masked by the white-noise

100dB N rest) were modulated by individual differences in personality scores. Results Personality traits Means and ranges of NEO-PI-R T-scores were: Neuroticism (50.1, 31.5–71.6), Extraversion (53.7, 35.6–73.1), Openness (55.8, 34.0–71.6), Agreeableness (46.3, 28.9–59.3),

I. Indovina et al. / Journal of Psychosomatic Research 77 (2014) 391–400

397

Table 2 Regional coupling during sound-evoked response as a function of personality A. Coupling correlates with neuroticism. Target: Seed:

IFg (Triang) L P

Z

x

y

Cerebellar nuclei L (ReS) Pontine nuclei L (ReS) Visual cortex L 0.002 4.61 −52 18 (V2) (LeS) SMg L (LeS) 0.034 3.84 −34 32

Amygdala R z

P

Z

x

y

z

0.006 3.54

18 −2 −16

0.044 2.83

18 −2 −16

22 18

B. Coupling correlates with extraversion. Target: Seed: Amygdala R (ReS)

IFg (Orb) R P

Z

0.003 4.51

x

IFg (Orb) L y

z

P

Z

x

36 24 −22 0.034 3.86 −20

y

z

14 −20

Correlation of coupling (between SEED and target areas) and personality traits at P ≤ 0.05, small volume correction. SEED areas are from Table 1, TARGET areas are those areas that showed a significant dependence of coupling on personality traits in the PPI analysis. Z = Z-score, L = left hemisphere, R = right hemisphere. x,y,z = MNI coordinates in millimeters. SMg = supra marginal gyrus, IFg (Orb) = inferior frontal gyrus pars orbitalis.

and Conscientiousness (52.0, 33.5–68.1). Mean T-scores were within general population norms (45–55), except for minimally elevated openness. Individual T-scores covered the full range from low (b45) to high (N55) for all five traits.

Main effect of STB stimulation on regional brain activity Main effects of experimental stimuli on regional brain activation patterns were examined and compared to published data. Regional effects for the contrasts STB100dB N rest, STB65dB N rest, and white noise 100dB N rest are reported in Supplementary Table 1 and Fig. 1 (A,B,C, respectively). The contrast STB100dB N STB65dB (exclusively masked by the white noise 100dB N rest comparison, separately for right and left ear) showed significant activations in posterior insula, retro-insula and parietal operculum (one sample ttest, P b 0.05 FWE, whole-brain correction) (Supplementary Table 1D, and Fig. 1D). Activations of these cortical regions in the human homologue of the parieto-insular vestibular cortex were fully consistent with previous results [28–32]. In addition, activation of bilateral cerebellar nuclei including fastigial nuclei was observed at a small volume correction level (Supplementary Table 1D).

Fig. 5. Effect of individual differences in introversion on brain functional connectivity. Introversion scores were negatively associated with the functional connectivity between the right amygdala “seed” and the bilateral inferior frontal gyrus (IFg) pars orbitalis during right saccular stimulation. The plot of the data is from the local maxima in the right IFg. The coordinates (X,Y,Z) are in the Montreal Neurological Institute space. The color bar represents T-statistics. Black line represents the regression line. Red lines are the 95% confidence interval. BOLD, blood oxygenation level dependent.

Discussion Effect of personality traits on vestibular and anxiety system activation Neuroticism scores correlated (Table 1A): 1) positively with bilateral cerebellar fastigial nuclei and pontine activity during right ear stimulation (Fig. 2A, B); 2) positively with left V2 cortical activity during left ear stimulation (Fig. 2C); and 3) negatively with the left SMg activity during left ear stimulation (Fig. 2D). Extraversion-introversion scores did not correlate with stimulated activity in predominately vestibular regions. Openness scores correlated negatively with left IFg activity during right ear stimulation (Table 1C). Agreeableness and consciousness scores did not significantly modulate activity in any ROI during right or left vestibular stimulation (all analyses refer to STB100dB N STB65dB contrast, exclusively masked for the white-noise 100dB N rest contrast) (P b 0.05, FWE, svc). Extraversion scores correlated negatively (i.e., introversion correlated positively) with right amygdala activation during right ear stimulation (Fig. 3 and Table 1B). Other traits did not correlate with stimulated activity in predominately anxiety regions.

Effect of personality traits on functional connectivity Brain regions showing correlations with neuroticism, extraversion and openness (Table 1A,B,C) were used as seeds for connectivity analyses exploring influences of personality traits on coupling between areas. Neuroticism was associated positively with connectivity between: 1) left cerebellar/pontine nuclei and right amygdala, 2) left V2 and left IFg, and 3) left SMg and left IFg (Fig. 4A–D, Table 2A). Extraversion was positively associated (i.e., introversion correlated negatively) with connectivity between right amygdala and IFg (Fig. 5, Table 2B). No significant effects were found for the remaining seed regions.

The results, summarized in Fig. 6, support the latest models integrating vestibular and anxiety function in health and disease [2], and are consistent with findings regarding neuroticism and introversion as risk factors for CSD [48]. They offer the first evidence of possible neural mechanisms linking personality traits to functional alterations in central vestibular pathways and support the suppositions that: (1) central vestibular systems may be more reactive to vestibular stimuli than normal (in neurotic individuals), (2) anxiety systems may be more reactive to vestibular stimuli than normal (in introverted individuals), and (3) increased connectivity between subcortical vestibular and anxiety systems may facilitate amplified vestibular–anxiety reactions to vestibular stimuli (in neurotic individuals). Consistently with past studies [31], the posterior insula showed robust activation to vestibular stimuli across all participants, but surprisingly, its response did not correlate with any personality trait. This null result is in contrast to previous findings showing that the insula response during cognitive and emotional tasks may be modulated by individual differences in anxiety-related traits [25,78,79]. It may be that the sound-evoked vestibular stimulation was insufficient per se to trigger altered insula responses in healthy individuals with variable levels of neuroticism, while these effects may become evident in clinical populations (e.g., CSD patients). Further studies are warranted to explore these issues.

398

I. Indovina et al. / Journal of Psychosomatic Research 77 (2014) 391–400

Fig. 6. Summary of regional effects and functional connectivity results. Neuroticism was positively correlated with activity in cerebellar fastigial and superior pontine nuclei and with functional connectivity between these nuclei and the right amygdala during vestibular stimulation. These findings reflect potentiated processing of vestibular inputs in neurotic people that may predispose them to enhanced viscero-motor and emotional responses to space-motion stimuli. Introversion was linked with increased amygdala response to vestibular stimuli and reduced functional connectivity between the right amygdala and IFg pars orbitalis bilaterally. These results may be neural correlates of enhanced acquisition or decreased extinction of fear conditioned responses to vestibular stimuli that are thought to play a role in development of specific phobias of falling and chronic subjective dizziness. Neuroticism levels were positively associated with increased activity in the parastriate visual cortex (V2) and reduced response in the supra-marginal gyrus (SMg) during vestibular stimulation. Neuroticism also modulated the connectivity between the IFg pars triangularis and both the V2 and SMg. The combination of SMg hypoactivity and V2 hyperactivity may reflect a visual bias in the reciprocally inhibitory connectivity of vestibular and visual cortices modulated by the IFg pars triangularis, a key region in attentional modulation. The lines connecting different brain areas represent the positive (continuous lines) or negative (dotted lines) correlation of the inter-regional connectivity with the personality factor indicated within the black arrow.

Neuroticism and reactivity of vestibular systems to vestibular stimulation Neuroticism scores were positively associated with activity in the superior pons and cerebellar fastigial nuclei bilaterally. Feedback loops through these regions modulate vestibulo-ocular and postural reflexes. In the cortex, neuroticism was positively linked with V2 response and negatively with SMg activity. Although not tested explicitly in this experiment as visual stimuli were not used, this result may reflect visual bias in the reciprocally inhibitory interactions of visual and vestibular cortices thought to stabilize optic flow during self-motion [34,35,64], a possible neural correlate of visual motion hypersensitivity in neurotic individuals [80] and persistent visually induced dizziness, a core symptom of CSD [45].

Introversion, openness and reactivity of anxiety systems to vestibular stimulation Introversion (low-extraversion) was associated with increased amygdala activity during vestibular stimulation. In previous imaging studies using resting-state measures in healthy volunteers, introversion was not associated with amygdala activity [78]. However, during emotional learning tasks, increased amygdala activity and high introversion were associated with enhanced fear conditioning and reward learning [81]. The increased amygdala response to vestibular stimuli in introverted subjects may thus support the hypothesis that conditioned hypersensitivity to vestibular stimuli plays a role in developing CSD [2]. Openness was also negatively associated with activation in the IFg. Openness was previously linked to increased prefrontal cortical greymatter volume and activity during working-memory tasks and at rest [82–85]. For unknown reasons, this result was opposite the expected direction. However, the finding of just one significant correlation

between openness and brain activity and none with connectivity suggests that openness may influence vestibular–anxiety interactions less than neuroticism or introversion. This mirrors the personality trait study of CSD, in which only one facet of openness differed between CSD and comparison groups versus multiple facets of neuroticism and extraversion [48]. Additional research is necessary to investigate the role that openness may play in mediating anxiety responses in vestibular disturbances and vice versa. Neuroticism, introversion and anxiety–vestibular system connectivity High neuroticism correlated with vestibulo-cerebellum (i.e., fastigial nuclei)-amygdala connectivity as well as with the pons-amygdala connectivity. The superior part of the pons contains nuclei involved in vestibular functions, although spatial resolution of fMRI cannot distinguish amongst these structures. These nuclei integrate vestibular inputs with other interoceptive stimuli and send this information to the amygdala. The cross-talk with the amygdala is thought to orchestrate the viscero-motor responses to emotional stimuli and postural perturbations [21,22,86,87]. Hence, enhanced pons-amygdala connectivity could mediate amplified reflexive responses of neurotic individuals to vestibular stimuli, including exaggerated emotional reactivity. Less is known about the cerebellar fastigial nuclei-amygdala link, but it may be responsible for small gain increases in canal-ocular and otolith– ocular reflexes observed in patients with panic disorder and agoraphobia [80]. Furthermore, neuroticism correlated with connectivity between IFg and both visual cortex and SMg. The IFg has been implicated in redirecting attention towards relevant stimuli [88–90], including voluntary shifts of attention during visual search [91]. Hyper-vigilance to potentially threatening visual stimuli was observed in highly neurotic individuals with no vestibular symptoms [92]; hence, the finding of

I. Indovina et al. / Journal of Psychosomatic Research 77 (2014) 391–400

reduced SMg activity and increased V2 response to STB100dB stimuli raises the possibility of visual bias in multi-sensory integration of space-motion stimuli in neurotic people. Introversion was negatively associated (extraversion positively correlated) with amgydala-IFg (the orbitalis part) connectivity. Extensive connections between amygdala and IFg are important for extinguishing fear responses to conditioned stimuli [41,93–96]. Imaging studies found reduced connectivity between amygdala and frontal cortical areas in social and generalized anxiety disorders [78,81], suggesting that reduced amygdala-prefrontal cortical connectivity may reflect a general proneness to anxiety-related disorders in introverts. Although CSD was previously independently linked to neuroticism and introversion, the two traits together separated CSD most strongly from other neurotologic/anxiety disorders [48]. Therefore, the risk of CSD may be conveyed by vestibular and anxiety systems that simultaneously express heightened reactivity to vestibular stimulation, mediated by neuroticism and introversion, respectively. Personality traits have not been studied as explicitly in other anxiety-related vestibular disorders, though the converse of neuroticism and introversion (i.e., resilience and sense of coherence) predicted fewer psychosomatic sequelae of acute vestibular syndromes [49]. This study provides the first evidence that individual differences in neuroticism, introversion, and possibly openness influence activity and functional connectivity within central vestibular and anxiety systems in a pattern consistent with published models of vestibularanxiety interactions from brainstem to cortex [21,22,48]. Strengths of this investigation included use of a previously well-developed experimental paradigm to evoke vestibular responses, and a study sample with a full spectrum of personality traits compatible with population norms, which provided valid data to test the personality modulation hypotheses. The main limitation is that any correlates between brain activation patterns and clinical phenotypes must be interpreted conservatively until they can be replicated and extended. For personality trait modulation of vestibular responses that will require testing of additional visual and vestibular stimuli in larger cohorts of normal individuals and patients with anxiety-related vestibular disorders (e.g., CSD). Nevertheless, the concordance of these results with existing human and animal data and recent neuroanatomical models is promising. Financial support Italian Ministry of University and Research (PRIN grant), National Research Council. Financial disclosures None of the authors have conflicts of interests. Acknowledgments We thank our volunteers for kindly participating in this study and Dr. Martin Vestergaard for helping with auditory stimuli production. Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.jpsychores.2014.09.005. References [1] Balaban CD, Jacob RG. Background and history of the interface between anxiety and vertigo. J Anxiety Disord 2001;15:27–51. [2] Staab JP, Balaban CD, Furman JM. Threat assessment and locomotion: clinical applications of an integrated model of anxiety and postural control. Semin Neurol 2013; 33:297–306. [3] Carpenter MG, Frank JS, Silcher CP. Surface height effects on postural control: a hypothesis for a stiffness strategy for stance. J Vestib Res 1999;9:277–86.

399

[4] Adkin AL, Frank JS, Carpenter MG, Peysar GW. Postural control is scaled to level of postural threat. Gait Posture 2000;12:87–93. [5] Brown LA, Frank JS. Postural compensations to the potential consequences of instability: kinematics. Gait Posture 1997;6:89–97. [6] Davis JR, Campbell AD, Adkin AL, Carpenter MG. The relationship between fear of falling and human postural control. Gait Posture 2009;29:275–9. [7] Davis JR, Horslen BC, Nishikawa K, Fukushima K, Chua R, Inglis JT, et al. Human proprioceptive adaptations during states of height-induced fear and anxiety. J Neurophysiol 2011;106:3082–90. [8] Cleworth TW, Horslen BC, Carpenter MG. Influence of real and virtual heights on standing balance. Gait Posture 2012;36:172–6. [9] Adkin AL, Frank JS, Carpenter MG, Peysar GW. Fear of falling modifies anticipatory postural control. Exp Brain Res 2002;143:160–70. [10] Hainaut J-P, Caillet G, Lestienne FG, Bolmont B. The role of trait anxiety on static balance performance in control and anxiogenic situations. Gait Posture 2011; 33:604–8. [11] Eckhardt A, Tettenborn B, Krauthauser H, Thomalske C, Hartmann O, Hoffmann SO, et al. Vertigo and anxiety disorders – results of interdisciplinary evaluation. Laryngorhinootologie 1996;75:517–22. [12] Eckhardt-Henn A, Breuer P, Thomalske C, Hoffmann SO, Hopf HC. Anxiety disorders and other psychiatric subgroups in patients complaining of dizziness. J Anxiety Disord 2003;17:369–88. [13] Clark DB, Hirsch BE, Smith MG, Furman JM, Jacob RG. Panic in otolaryngology patients presenting with dizziness or hearing loss. Am J Psychiatry 1994;151:1223–5. [14] Persoons P, Luyckx K, Desloovere C, Vandenberghe J, Fischler B. Anxiety and mood disorders in otorhinolaryngology outpatients presenting with dizziness: validation of the self-administered PRIME-MD Patient Health Questionnaire and epidemiology. Gen Hosp Psychiatry 2003;25:316–23. [15] Eagger S, Luxon LM, Davies RA, Coelho A, Ron MA. Psychiatric morbidity in patients with peripheral vestibular disorder: a clinical and neuro-otological study. J Neurol Neurosurg Psychiatry 1992;55:383–7. [16] Kammerlind A-SC, Ledin TEA, Skargren EIB, Odkvist LM. Long-term follow-up after acute unilateral vestibular loss and comparison between subjects with and without remaining symptoms. Acta Otolaryngol (Stockh) 2005;125:946–53. [17] Celestino D, Rosini E, Carucci ML, Marconi PL, Vercillo E. Ménière's disease and anxiety disorders. Acta Otorhinolaryngol Ital 2003;23:421–7. [18] Best C, Eckhardt-Henn A, Tschan R, Dieterich M. Psychiatric morbidity and comorbidity in different vestibular vertigo syndromes. Results of a prospective longitudinal study over one year. J Neurol 2009;256:58–65. [19] Boleas-Aguirre MS, Sánchez-Ferrandiz N, Guillén-Grima F, Perez N. Long-term disability of class A patients with Ménière's disease after treatment with intratympanic gentamicin. Laryngoscope 2007;117:1474–81. [20] Staab JP. Chronic dizziness: the interface between psychiatry and neuro-otology. Curr Opin Neurol 2006;19:41–8. [21] Balaban CD. Neural substrates linking balance control and anxiety. Physiol Behav 2002;77:469–75. [22] Balaban CD. Projections from the parabrachial nucleus to the vestibular nuclei: potential substrates for autonomic and limbic influences on vestibular responses. Brain Res 2004;996:126–37. [23] Balaban CD, Thayer JF. Neurological bases for balance-anxiety links. J Anxiety Disord 2001;15:53–79. [24] Gurvich C, Maller JJ, Lithgow B, Haghgooie S, Kulkarni J. Vestibular insights into cognition and psychiatry. Brain Res 2013;1537:244–59. [25] Paulus MP, Stein MB. An insular view of anxiety. Biol Psychiatry 2006;60:383–7. [26] Viaud-Delmon I, Venault P, Chapouthier G. Behavioral models for anxiety and multisensory integration in animals and humans. Prog Neuropsychopharmacol Biol Psychiatry 2011;35:1391–9. [27] Angelaki DE, Cullen KE. Vestibular system: the many facets of a multimodal sense. Annu Rev Neurosci 2008;31:125–50. [28] Brandt T, Dieterich M. The vestibular cortex. Its locations, functions, and disorders. Ann N Y Acad Sci 1999;871:293–312. [29] Zu Eulenburg P, Caspers S, Roski C, Eickhoff SB. Meta-analytical definition and functional connectivity of the human vestibular cortex. Neuroimage 2012;60:162–9. [30] Indovina I, Maffei V, Bosco G, Zago M, Macaluso E, Lacquaniti F. Representation of visual gravitational motion in the human vestibular cortex. Science 2005;308: 416–9. [31] Lopez C, Blanke O, Mast FW. The human vestibular cortex revealed by coordinatebased activation likelihood estimation meta-analysis. Neuroscience 2012;212:159–79. [32] Lopez C, Blanke O. The thalamocortical vestibular system in animals and humans. Brain Res Rev 2011;67:119–46. [33] Hüfner K, Strupp M, Smith P, Brandt T, Jahn K. Spatial separation of visual and vestibular processing in the human hippocampal formation. Ann N Y Acad Sci 2011;1233:177–86. [34] Brandt T. Cortical visual–vestibular interaction for spatial orientation and selfmotion perception. Curr Opin Neurol 1999;12:1–4. [35] Brandt T, Bartenstein P, Janek A, Dieterich M. Reciprocal inhibitory visual–vestibular interaction. Visual motion stimulation deactivates the parieto-insular vestibular cortex. Brain 1998;121:1749–58. [36] Bremmer F, Schlack A, Shah NJ, Zafiris O, Kubischik M, Hoffmann K, et al. Polymodal motion processing in posterior parietal and premotor cortex: a human fMRI study strongly implies equivalencies between humans and monkeys. Neuron 2001;29: 287–96. [37] Britten KH. Mechanisms of self-motion perception. Annu Rev Neurosci 2008;31: 389–410. [38] De Waele C, Baudonnière PM, Lepecq JC, Tran Ba Huy P, Vidal PP. Vestibular projections in the human cortex. Exp Brain Res 2001;141:541–51.

400

I. Indovina et al. / Journal of Psychosomatic Research 77 (2014) 391–400

[39] Sylvester CM, Corbetta M, Raichle ME, Rodebaugh TL, Schlaggar BL, Sheline YI, et al. Functional network dysfunction in anxiety and anxiety disorders. Trends Neurosci 2012;35:527–35. [40] Bishop SJ. Neurocognitive mechanisms of anxiety: an integrative account. Trends Cogn Sci 2007;11:307–16. [41] Indovina I, Robbins TW, Núñez-Elizalde AO, Dunn BD, Bishop SJ. Fear-conditioning mechanisms associated with trait vulnerability to anxiety in humans. Neuron 2011;69:563–71. [42] Brandt T. Phobic postural vertigo. Neurology 1996;46:1515–9. [43] Brandt T, Dieterich M. Phobischer Attacken-Schwank-schwindel, ein neues Syndrom? Munch Med Wochenschr 1986;28:247–50. [44] Staab JP, Ruckenstein MJ. Expanding the differential diagnosis of chronic dizziness. Arch Otolaryngol Head Neck Surg 2007;133:170–6. [45] Staab JP. Chronic subjective dizziness. Continuum (Minneap Minn) 2012;18:1118–41. [46] Staab JP, Ruckenstein MJ. Which comes first? Psychogenic dizziness versus otogenic anxiety. Laryngoscope 2003;113:1714–8. [47] Staab JP, Ruckenstein MJ. Chronic dizziness and anxiety: effect of course of illness on treatment outcome. Arch Otolaryngol Head Neck Surg 2005;131:675–9. [48] Staab JP, Rohe DE, Eggers SDZ, Shepard NT. Anxious, introverted personality traits in patients with chronic subjective dizziness. J Psychosom Res 2014;76:80–3. [49] Tschan R, Best C, Beutel ME, Knebel A, Wiltink J, Dieterich M, et al. Patients' psychological well-being and resilient coping protect from secondary somatoform vertigo and dizziness (SVD) 1 year after vestibular disease. J Neurol 2011;258:104–12. [50] Costa Jr PT, McCrae RR. Stability and change in personality assessment: the revised NEO Personality Inventory in the year 2000. J Pers Assess 1997;68:86–94. [51] Janzen J, Schlindwein P, Bense S, Bauermann T, Vucurevic G, Stoeter P, et al. Neural correlates of hemispheric dominance and ipsilaterality within the vestibular system. Neuroimage 2008;42:1508–18. [52] Miyamoto T, Fukushima K, Takada T, de Waele C, Vidal P-P. Saccular stimulation of the human cortex: a functional magnetic resonance imaging study. Neurosci Lett 2007;423:68–72. [53] Schlindwein P, Mueller M, Bauermann T, Brandt T, Stoeter P, Dieterich M. Cortical representation of saccular vestibular stimulation: VEMPs in fMRI. Neuroimage 2008;39:19–31. [54] Sheehan DV, Lecrubier Y, Sheehan KH, Amorim P, Janavs J, Weiller E, et al. The MiniInternational Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry 1998;59:22–33 [quiz 34–57]. [55] Oldfield RC. The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 1971;9:97–113. [56] Brantberg K. Vestibular evoked myogenic potentials (VEMPs): usefulness in clinical neurotology. Semin Neurol 2009;29:541–7. [57] Colebatch JG, Halmagyi GM, Skuse NF. Myogenic potentials generated by a clickevoked vestibulocollic reflex. J Neurol Neurosurg Psychiatry 1994;57:190–7. [58] Isaradisaikul S, Navacharoen N, Hanprasertpong C, Kangsanarak J. Cervical vestibular-evoked myogenic potentials: norms and protocols. Int J Otolaryngol 2012;2012:913515. [59] Akin FW, Murnane OD, Proffitt TM. The effects of click and tone-burst stimulus parameters on the vestibular evoked myogenic potential (VEMP). J Am Acad Audiol 2003;14:500–9 [quiz 534–535]. [60] Cheng PW, Murofushi T. The effect of rise/fall time on vestibular-evoked myogenic potential triggered by short tone bursts. Acta Otolaryngol (Stockh) 2001;121:696–9. [61] Cheng PW, Murofushi T. The effects of plateau time on vestibular-evoked myogenic potentials triggered by tone bursts. Acta Otolaryngol (Stockh) 2001;121:935–8. [62] Friston KJ. Testing for anatomically specified regional effects. Hum Brain Mapp 1997; 5:133–6. [63] Worsley KJ, Marrett S, Neelin P, Vandal AC, Friston KJ, Evans AC. A unified statistical approach for determining significant signals in images of cerebral activation. Hum Brain Mapp 1996;4:58–73. [64] Bense S, Stephan T, Yousry TA, Brandt T, Dieterich M. Multisensory cortical signal increases and decreases during vestibular galvanic stimulation (fMRI). J Neurophysiol 2001;85:886–99. [65] Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O, Delcroix N, et al. Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage 2002;15: 273–89. [66] Eickhoff SB, Stephan KE, Mohlberg H, Grefkes C, Fink GR, Amunts K, et al. A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data. Neuroimage 2005;25:1325–35. [67] Eickhoff SB, Heim S, Zilles K, Amunts K. Testing anatomically specified hypotheses in functional imaging using cytoarchitectonic maps. Neuroimage 2006;32:570–82. [68] Eickhoff SB, Paus T, Caspers S, Grosbras M-H, Evans AC, Zilles K, et al. Assignment of functional activations to probabilistic cytoarchitectonic areas revisited. Neuroimage 2007;36:511–21.

[69] von Economo C, Koskinas GN. Atlas of cytoarchitectonics of the adult human cerebral cortex. In: Triarhou LC, editor. Basel: Karger; 2008 [trans, rev]. [70] Dimitrova A, Weber J, Redies C, Kindsvater K, Maschke M, Kolb FP, et al. MRI atlas of the human cerebellar nuclei. Neuroimage 2002;17:240–55. [71] Stephan T, Deutschländer A, Nolte A, Schneider E, Wiesmann M, Brandt T, et al. Functional MRI of galvanic vestibular stimulation with alternating currents at different frequencies. Neuroimage 2005;26:721–32. [72] Naidich TP, Duvernoy HM, Delman BN, Sorensen AG, Kollias SS, Haacke EM. Duvernoy's Atlas of the Human Brain Stem and Cerebellum. Springer; 2009. [73] Friston KJ, Buechel C, Fink GR, Morris J, Rolls E, Dolan RJ. Psychophysiological and modulatory interactions in neuroimaging. Neuroimage 1997;6:218–29. [74] Passamonti L, Rowe JB, Ewbank M, Hampshire A, Keane J, Calder AJ. Connectivity from the ventral anterior cingulate to the amygdala is modulated by appetitive motivation in response to facial signals of aggression. Neuroimage 2008;43:562–70. [75] Passamonti L, Rowe JB, Schwarzbauer C, Ewbank MP, von dem Hagen E, Calder AJ. Personality predicts the brain's response to viewing appetizing foods: the neural basis of a risk factor for overeating. J Neurosci 2009;29:43–51. [76] Passamonti L, Crockett MJ, Apergis-Schoute AM, Clark L, Rowe JB, Calder AJ, et al. Effects of Acute Tryptophan Depletion on Prefrontal-Amygdala Connectivity While Viewing Facial Signals of Aggression. Biol Psychiatry 2012;71:36–43. [77] Gitelman DR, Penny WD, Ashburner J, Friston KJ. Modeling regional and psychophysiologic interactions in fMRI: the importance of hemodynamic deconvolution. Neuroimage 2003;19:200–7. [78] Deckersbach T, Miller KK, Klibanski A, Fischman A, Dougherty DD, Blais MA, et al. Regional cerebral brain metabolism correlates of neuroticism and extraversion. Depress Anxiety 2006;23:133–8. [79] Paulus MP, Rogalsky C, Simmons A, Feinstein JS, Stein MB. Increased activation in the right insula during risk-taking decision making is related to harm avoidance and neuroticism. Neuroimage 2003;19:1439–48. [80] Jacob RG, Redfern MS, Furman JM. Space and motion discomfort and abnormal balance control in patients with anxiety disorders. J Neurol Neurosurg Psychiatry 2009;80:74–8. [81] Hooker CI, Verosky SC, Miyakawa A, Knight RT, D'Esposito M. The influence of personality on neural mechanisms of observational fear and reward learning. Neuropsychologia 2008;46:2709–24. [82] Sutin AR, Beason-Held LL, Resnick SM, Costa PT. Sex differences in resting-state neural correlates of openness to experience among older adults. Cereb Cortex 2009;19:2797–802. [83] DeYoung CG, Shamosh NA, Green AE, Braver TS, Gray JR. Intellect as distinct from Openness: differences revealed by fMRI of working memory. J Pers Soc Psychol 2009;97:883–92. [84] Kapogiannis D, Sutin A, Davatzikos C, Costa Jr P, Resnick S. The five factors of personality and regional cortical variability in the Baltimore longitudinal study of aging. Hum Brain Mapp 2013;34:2829–40. [85] Hu X, Erb M, Ackermann H, Martin JA, Grodd W, Reiterer SM. Voxel-based morphometry studies of personality: issue of statistical model specification–effect of nuisance covariates. Neuroimage 2011;54:1994–2005. [86] Halberstadt AL, Balaban CD. Anterograde tracing of projections from the dorsal raphe nucleus to the vestibular nuclei. Neuroscience 2006;143:641–54. [87] Halberstadt AL, Balaban CD. Selective anterograde tracing of the individual serotonergic and nonserotonergic components of the dorsal raphe nucleus projection to the vestibular nuclei. Neuroscience 2007;147:207–23. [88] Corbetta M, Patel G, Shulman GL. The reorienting system of the human brain: from environment to theory of mind. Neuron 2008;58:306–24. [89] Indovina I, Macaluso E. Occipital-parietal interactions during shifts of exogenous visuospatial attention: trial-dependent changes of effective connectivity. Magn Reson Imaging 2004;22:1477–86. [90] Indovina I, Macaluso E. Dissociation of stimulus relevance and saliency factors during shifts of visuospatial attention. Cereb Cortex 2007;17:1701–11. [91] Fairhall SL, Indovina I, Driver J, Macaluso E. The brain network underlying serial visual search: comparing overt and covert spatial orienting, for activations and for effective connectivity. Cereb Cortex 2009;19:2946–58. [92] Staab JP. The influence of anxiety on ocular motor control and gaze. Curr Opin Neurol 2014;27:118–24. [93] Delgado MR, Nearing KI, Ledoux JE, Phelps EA. Neural circuitry underlying the regulation of conditioned fear and its relation to extinction. Neuron 2008;59:829–38. [94] Hartley CA, Phelps EA. Changing fear: the neurocircuitry of emotion regulation. Neuropsychopharmacology 2010;35:136–46. [95] Milad MR, Wright CI, Orr SP, Pitman RK, Quirk GJ, Rauch SL. Recall of fear extinction in humans activates the ventromedial prefrontal cortex and hippocampus in concert. Biol Psychiatry 2007;62:446–54. [96] Ochsner KN, Gross JJ. The cognitive control of emotion. Trends Cogn Sci 2005;9: 242–9.