Improved balance performance accompanied by structural plasticity in blind adults after training

Neuropsychologia 129 (2019) 318–330

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Neuropsychologia journal homepage: www.elsevier.com/locate/neuropsychologia

Improved balance performance accompanied by structural plasticity in blind adults after training

T

Ann-Kathrin Roggea,∗, Kirsten Höttinga, Volker Nagelb, Astrid Zechc, Cordula Höligc, Brigitte Rödera a

Universität Hamburg, Biological Psychology and Neuropsychology, Von-Melle-Park 11, 20146, Hamburg, Germany Universität Hamburg, Sports Medicine, Turmweg 2, 20146, Hamburg, Germany c Friedrich Schiller University, Human Movement Science, Seidelstraße 20, 07749, Jena, Germany b

ARTICLE INFO

ABSTRACT

Keywords: Balance training Blindness Vestibular system Structural plasticity Brain imaging

Postural control requires the sensory integration of visual, vestibular, and proprioceptive signals. In the absence of vision, either by blindfolding or in blind individuals, balance performance is typically poorer than with sight. Previous research has suggested that despite showing compensatory vestibular and proprioceptive processing during upright standing, balance performance in blind individuals is overall lower than in sighted controls with eyes open. The present study tested whether balance training, which places demands on vestibular and proprioceptive self-motion perception, improves balance performance in blind adults, and whether we find similar structural correlates in cortical and subcortical brain areas as have been reported in sighted individuals. Fourteen congenitally or late blind adults were randomly assigned to either a balance or a relaxation group and exercised twice a week for 12 weeks. Assessments prior to and after training included balance tests and the acquisition of T1-weighted MRI images. The blind balance group significantly improved in dynamic, static, and functional balance performance compared to the blind relaxation group. The balance performance improvement did not differ from that of age- and gender matched sighted adults after balance training. Cortical thickness increased in the left parahippocampus and decreased in the inferior insula bilaterally in the blind balance group compared to the blind relaxation group. Thickness decreases in the insula were related to improved static and functional balance. Gray matter volume was reduced in the left hippocampus proper and increased in the right subiculum in the blind balance group. The present data suggest that impaired balance performance in blind adults can be significantly improved by a training inducing plasticity in brain regions associated with vestibular and proprioceptive self-motion processing.

1. Introduction The detection of self-motion is fundamental to control upright standing and locomotion while we move through the world. To compute the optimal estimate of self-motion and orientation in space, the brain combines incoming sensory information from vestibular, visual, and proprioceptive signals (Cullen, 2012). For example, to maintain balance on unstable ground the vestibular system rapidly detects motion of the head in space, and these cues are integrated with optic flow, extra-retinal and proprioceptive signals to quickly stabilize gaze, trunk, and lower limbs (Cullen and Taube, 2017; Medendorp and Selen, 2017; Seemungal, 2015). Balance performance, ranging from static standing to dynamic balance on uneven ground (Sibley et al., 2015), is affected by the absence of one

sensory modality. For instance, vestibular patients experience imbalance, dizziness, and oscillopsia, and darkness or uneven ground further augment these balance deficits (Lucieer et al., 2018). In blind individuals, larger and stiffer postural sway patterns than in the sighted with eyes open have been reported, indicative of greater instability (Aydoğ et al., 2006; CampayoPiernas et al., 2017; Giagazoglou et al., 2009; Russo et al., 2017; Schmid et al., 2007; Schwesig et al., 2011; Sobry et al., 2014). Notably, postural sway and muscular co-activation of sighted adults in eyes closed conditions have been shown to increase to a similar level as observed in the blind (Campayo-Piernas et al., 2017; Duarte and Zatsiorsky, 2002; Giagazoglou et al., 2009; Schmid et al., 2007; Schwesig et al., 2011). Thus, vision seems to play a major role for postural control, irrespective of whether vision is temporarily or permanently absent.

Corresponding author. E-mail addresses: [email protected] (A.-K. Rogge), [email protected] (K. Hötting), [email protected] (V. Nagel), [email protected] (A. Zech), [email protected] (C. Hölig), [email protected] (B. Röder). ∗

https://doi.org/10.1016/j.neuropsychologia.2019.04.005 Received 23 November 2018; Received in revised form 18 March 2019; Accepted 13 April 2019 Available online 17 April 2019 0028-3932/ © 2019 Elsevier Ltd. All rights reserved.

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It has been suggested that blind individuals show behavioral compensation after extensive practice of certain non-visual skills (Kupers and Ptito, 2014; Singh et al., 2018). Evidence of superior behavioral performance, such as greater tactile sensitivity (Alary et al., 2008; Goldreich and Kanics, 2006; Wong et al., 2011), auditory localization (Röder et al., 1999), speech recognition (Röder et al., 2000), and verbal memory (Amedi et al., 2004; Röder et al., 2001) has been reported in the congenitally blind. Results for late blind individuals are typically more mixed, most likely due to their heterogeneity of blindness onset, duration, etiology, and rehabilitation efforts (Röder and Rösler, 2003). With regard to self-motion perception, blind individuals have been reported to display a faster reduction of postural sway when a light finger touch was allowed (Schieppati et al., 2014), and showed superior ankle proprioception and detection of roll tilts compared to blindfolded sighted adults (Moser et al., 2015; Ozdemir et al., 2013). During imagined upright stance and locomotion, congenitally blind individuals have been found to show higher functional activation of the insular cortex and superior temporal gyrus, and larger deactivation in the posterior parahippocampus than sighted participants (Deutschländer et al., 2009a, 2009b; Jahn et al., 2009). These results have been interpreted as enhanced vestibular and somatosensory perception during self-motion processing in the blind. In balance tasks, however, blind individuals did not perform better than blindfolded sighted controls or reach the performance level of sighted controls tested with eyes open (Campayo-Piernas et al., 2017; Nakata and Yabe, 2001; Ozdemir et al., 2013; Schmid et al., 2007). Since blind individuals have been reported to more often adapt a sedentary life-style (Augestad and Jiang, 2015; Houwen et al., 2009; Longmuir and Bar-Or, 2000), they may have lacked extensive experience to improve balance abilities (Schmid et al., 2007). In line with this notion, blind goalball athletes have been shown to outperform blind sedentary individuals in postural stability tasks, suggesting that regular physical activity can improve balance abilities in blind individuals (Aydoğ et al., 2006). Since cross-sectional studies cannot rule out that blind individuals having better balance skills are those who are more likely to participate in physical activities, randomized intervention studies are necessary to test whether training can improve balance performance in blind individuals. In sighted individuals, there is meta-analytic evidence that a few weeks of balance training enhance balance performance in athletes, untrained adults, and adolescents (Gebel et al., 2018; Kümmel et al., 2016; Lesinski et al., 2015). Furthermore, balance training in sighted individuals has been shown to elicit gray matter volume increases in parietal, frontal and premotor cortical areas as well as volume decreases in the putamen (Taubert et al., 2010). A recent study of our lab has found that 12 weeks of balance training significantly improved dynamic balance performance in sighted adults compared with relaxation training (Rogge et al., 2018). Furthermore, in this study we found that cortical thickness increased in visual association cortices, in superior temporal regions extending into the insula cortex, in the posterior cingulate, and in superior frontal regions. These areas have been related to visual and vestibular self-motion processing (Frank et al., 2016; Guterstam et al., 2015; Roberts et al., 2017; Strong et al., 2017). In a cross-sectional study, long-term balance expertise has been associated with smaller gray matter volume in the insular cortex, and larger volume in visual areas compared to individuals with no extensive balance experience (Hüfner et al., 2011). In the same study, balance experts showed larger posterior hippocampal and parahippocampal gray matter, but smaller anterior hippocampal volumes. The volume change was related to years of experience and weekly training hours. Hence, in sighted individuals, placing demands on self-motion perception by balance training seems to result in structural adaptations of underlying cortical networks associated with vestibular, proprioceptive, and visual motion processing. The aim of the present study was twofold. First, we tested whether balance performance in blind individuals can be improved by training

as it has been shown in sighted individuals. Second, we asked whether balance training induces structural plasticity in brain regions reported to be involved in vestibular and proprioceptive self-motion processing in blind and sighted individuals. To this end, a group of congenitally or late blind individuals was randomly assigned to either a balance or a relaxation group. All participants exercised twice a week for 12 weeks. Assessments prior to and after training included balance tests, a cardiorespiratory fitness test to control for changes in aerobic fitness, and T1-weighted MRI to assess structural brain changes. The balance training was designed to cover different components of postural control, such as dynamic, static, and functional balance. The relaxation training served as an active control training. In the blind balance group, we predicted improvements in balance performance and changes of gray matter in brain regions related to vestibular and proprioceptive self-motion processing, in particular in the insular cortex, the parahippocampus, and the hippocampus. 2. Methods 2.1. Participants Fourteen blind adults (mean age: 47, age range: 26–56 years, seven females, seven congenitally blind and seven late blind) participated in the study. Ten individuals reported to be right-handed, four participants were bi-manual. Educational achievements of the participants ranged from high school, grade 9 (n = 4), high school, grade 10 (n = 1), high school diploma (n = 4) to college degree (n = 5). All blind participants were legally blind: Ten of them were totally blind or had only rudimentary sensitivity for brightness differences, four (one congenitally blind, three late blind participants) had rudimentary contour vision. Blindness was due to retinitis pigmentosa (n = 4), retinopathy of prematurity (n = 3), glaucoma (n = 2), optic nerve atrophy (n = 1), Leber's congenital amaurosis (n = 1), retinal toxoplasmosis (n = 1), microphthalmia (n = 1), and idiopathic reasons (n = 1). Late blind participants reported their blindness onset after the age of five years (mean: 30.28, range: 6–50 years) with a minimum blindness duration of five years (mean: 20.14, range: 5–49 years). Characteristics of blindness were assessed via self-reports. The balance performance of the blind balance groups was compared to an age and gender matched sighted balance group (n = 7, mean age: 52, age range 29–64 years, four female), selected from a previous randomized balance training study with sighted participants (Rogge et al., 2017, 2018). For each blind participant, we selected a sighted individual of the same gender with the closest match in age. All sighted individuals had normal or corrected to normal vision, and all individuals were right-handed. Educational achievements ranged from high school, grade 10 (n = 2), high school diploma (n = 2) to college degree (n = 3). All participants were recruited from the local community of Hamburg (Germany), reported no history of untreated heart or respiratory diseases, musculoskeletal illnesses, neurological or psychiatric diseases, and had no extensive balance training experience. After a prescreening by phone, all individuals underwent a sport medical examination to assess their cardiorespiratory fitness level and to ensure that they were in the appropriate constitution to take part in the training. The study was approved by the ethical board of the German Psychological Society (DGPs) and was conducted in accordance with the ethical guidelines of the Declaration of Helsinki. All individuals gave written informed consent and received monetary compensation for the duration of the assessments before and after the intervention. 2.2. Experimental design All participants underwent either balance or relaxation training with two training sessions per week for 12 weeks. Before and after the 319

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2.2.2. Relaxation training The relaxation group practiced progressive muscle relaxation (Jacobson, 1987) and autogenic training (Stetter and Kupper, 2002) while laying or sitting on mats. During the first six weeks of training, the short form of progressive muscle relaxation following the manual of Bernstein et al. (1975) was instructed, whereby participants tensed single muscle groups for 5–7 s, followed by 45 s of relaxation. The training did not include muscle strengthening components. From week 7, autogenic training was practiced. Participants were instructed to imagine body parts as warm or cold and concentrate on breathing rhythm and heartbeat. During week 11 and 12, both relaxation methods were combined.

training period, balance performance, cardiorespiratory fitness, and structural MRI were assessed on separate days. Randomization to the balance or the relaxation training was achieved by grouping blind individuals into pairs matched for age, gender, and onset of blindness (congenital or late blind), and then randomly assigning the individuals of each pair either to the balance or to the relaxation group using a random number table. The training took place in separate groups. Each training session lasted 50 min. Sighted participants trained separately from the blind participants in groups of maximum 10–12 individuals (reported in Rogge et al., 2018). The two blind training groups and the sighted balance group were supervised by the same coaches, with the exception that additional coaches were present during the training of the blind participants to prevent injuries. Training procedure, training facilities and time of the day for the training were held constant across all groups. All participants were instructed to not change their level of habitual physical activity throughout the study period. Participants of the blind balance and the blind relaxation group did not differ with respect to age, gender, cardiorespiratory fitness, selfreported weekly physical activity (in MET, energy expenditure in metabolic rates, see Ainsworth et al., 2000; Ainsworth et al., 2011), and number of training sessions (Table 1). Similarly, participants of the blind and sighted balance groups did not differ in any of these variables with the exception that cardiorespiratory fitness was significantly lower in the blind balance than in the sighted balance group, see Table 1.

2.3. Balance assessment 2.3.1. Stability platform Dynamic balance was assessed with a stability platform (Stability Platform, Modell 16030 L, Lafayette Instrument, USA). Participants stood barefoot on an unstable platform with a maximum deviation of ± 15° to each side of its horizontal alignment. Participants were asked to place the hands on their hips, to direct their head straightahead and to keep the platform horizontally as long as possible within a trial. A handrail was available to prevent falls. After one practice trial, balance performance was assessed in two blocks, each consisting of three trials. Each trial lasted 30 s with an inter-trial rest of 30 s. The beginning and ending of the trials were signalized by two short tones. Between blocks, participants rested for 2 min to prevent fatigue. Sighted participants had their eyes open in one block and closed in the other block, the order was randomized across participants. Blind participants were asked to close the eyes in one block if they were able to control their eyes, which most of the late blind participants could do. Whenever a participant left the testing position (i.e. lifted the hands from the hips, grasped the handrail or, in case of the sighted participants opened the eyes in the eyes-closed condition), the trial was restarted. If three consecutive trials failed, the test block was marked as missing data. The time in which the platform was kept in the horizontal position ( ± 3° deviation tolerance) was used as dependent variable. Three blind participants (two of the relaxation group, one of the balance group) were not able to remain in the correct testing position for 30 s (neither at pre- nor at posttest) and were therefore excluded from the analysis of the stability platform task.

2.2.1. Balance training The balance training was composed of circuit training with eight exercises per session. At different stations, each lasting 5 min, participants trained on even and various uneven grounds such as wobble boards, cushions, foam and perturbation boards. The balance exercises were designed to induce reactive stabilization while challenging functional stability limits. The difficulty was varied by using bipedal vs. tandem vs. one-leg stance, static vs. dynamic stability, and eyes open vs. eyes closed conditions, the latter only in the sighted balance group, in line with the recommendations for balance training (Lesinski et al., 2015; Sibley et al., 2015). For example, participants were asked to stand on one leg while being pulled sideways by a strong elastic around the hips. To increase difficulty for keeping an upright posture, a soft underground such as a cushion or a trampoline was added. Other exercises required participants to stand on a shiftable wooden platform which was unexpectedly moved, thereby demanding a fast postural stabilization. No explicit strategies were taught. After six weeks, exercises were replaced with a new set in order to keep the training interesting and sufficiently challenging. Balance exercises, number of training sessions, and training duration were selected based on existing literature and meta-analytic recommendations (Gebel et al., 2018; Hrysomallis, 2011; Lesinski et al., 2015; Zech et al., 2010).

2.3.2. Force plate Postural stability was assessed with a force plate (Type 9260AA6, Kistler® Instrumente GmbH, Switzerland) with a sampling rate of 180 Hz using the software BioWare (Kistler Instruments AG, version 4.0.1.2). Center of pressure (CoP) data of the anterior-posterior and medial-lateral time series were collected during barefoot semi-tandem leg stances, were the big toe of the dominant leg was placed to the side

Table 1 Characteristics of the participants.

Age Gender (female/male) Training sessions VO2peak at pretest Self-reported weekly physical activity (MET)e at pretest

Blind balance group (n = 7)

Blind relaxation group (n = 7)

Pc

Sighted balance group (n = 7)

Pd

49.57 4/3 19.43 23.13 28.06

45.0 (9.95) 3/4 21.71 (2.81) 25.88 (3.67) 28.88 (12.19)

.431a .593b .271a .297 a .90 a

52.28 (12.34) 4/3 19.43 (2.07) 32.6 (3.75) 29.36 (15.03)

.67 a 1.0 b 1.0 a .002 a .86 a

(11.03) (2.67) (5.33) (11.53)

Note. a independent t-test. b Chi-square test. c only blind groups. d blind balance group vs. sighted balance group. VO2peak = maximal oxygen uptake in ml/min/kg. e Measured with the FFKA (Freiburger Fragebogen zur körperlichen Aktivität (Frey et al., 1999). MET = energy expenditure in metabolic rates.

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of and against the heel of the other foot. Six trials with a length of 30 s each were run. During testing, participants were asked to place their hands on their hips, with their head directed straight-ahead. Between trials, participants rested for 30 s. To calculate the CoP sway area (in cm2) per trial, prediction ellipse areas (PEA) with 95% probability were fitted to the time series data per trial (for details see Schubert and Kirchner, 2014, Duarte, 2015). Due to change of equipment, only data of the blind but not of sighted participants were available.

matter, and manually corrected in the event of tissue segmentation errors. Cortical thickness maps were smoothed with a 10 mm full-width half-maximum (FWHM) Gaussian kernel. 2.5.2. Subcortical gray matter volume The hippocampus was automatically segmented into subfields by FreeSurfer, using a statistical atlas built upon ultra-high resolution ex vivo MRI data (Iglesias et al., 2015) and a longitudinal subject-specific Bayesian atlas to increase power and robustness (Iglesias et al., 2016).

2.3.3. Single-leg stance To assess functional balance performance, single-leg stances (Springer et al., 2007) were performed on hard and soft (Airex© foam) ground. Participants were asked to place the hands on their hips, to lift their dominant foot, and to close their eyes if possible, with the head directed straight-ahead. Trial time ended when participants touched the floor with their raised foot, rotated or moved their foot of the standing leg to maintain balance, removed their hands from the hips, or when sighted individuals opened their eyes. Each trial had a maximum length of 20 s, and was followed by an inter-trial rest of 30 s. Two trials on each ground (soft/hard) were run. Trials were video-recorded and two independent observers measured the time (in sec) the participant remained in the correct position. Intra-class correlations ranged from r = 0.79 to r = 0.99 per condition (hard/soft).

2.6. Statistical analysis 2.6.1. Balance performance Balance performance at baseline and balance performance changes were fitted with linear mixed models (LME) in the statistical software R, version 3.5.0 (R Core Team, 2017) using the packages lme4 (Bates et al., 2015) and lmerTest (Kuznetsova et al., 2017). Equations to assess differences at baseline included Group (blind balance vs. blind relaxation), and Visual Status (blind participants vs. sighted participants). For the analysis of stability platform, data of all blind participants were compared to data of the sighted participants in the eyes closed condition (three trials) and in the eyes open condition (three trials). Equations on training changes included Time (pre- and posttest trials), Group (blind balance vs. blind relaxation and blind balance vs. sighted balance, respectively) and the interaction between Time and Group as fixed effects. Stability platform data of the blind balance group were compared to data of the sighted balance group in the eyes closed and in the eyes open test condition (three trials each). In all analyses, the intercept was included as random effect to fit individual biases (Bernal-Rusiel et al., 2013; Matuschek et al., 2017). Degrees of freedom, p-values, and Fvalues were estimated using Kenward-Roger's approximations for each fixed effect (Halekoh and Højsgaard, 2014). Significance level was set to p < .05, two-tailed. The test-retest correlation coefficients ranged from r = 0.57, p = .031 (force plate, blind participants), r = 0.70, p < .001 (single-leg stance) to r = 0.73, p < .001 (stability platform).

2.4. Cardiorespiratory fitness To control for aerobic fitness changes throughout the training period, cardiorespiratory fitness was assessed by a graded maximal ergospirometry. Participants started with an initial workload of 50 Watt on a cycle ergometer. Each minute, the resistance was increased by adding 50/3 Watt until subjectively perceived exhaustion (for more details see Rogge et al., 2017). Cardiorespiratory fitness was defined as maximum oxygen uptake at exhaustion, divided by body weight, hereinafter referred to as VO2peak (ml/min/kg). Technical problems during the assessment of blind participants led to missing data (n = 1 at pretest, n = 3 at posttest).

2.6.2. Brain imaging data 2.6.2.1. Cortical thickness ROI. We selected the insular cortex and the parahippocampus as regions of interest (ROIs), based on previous literature showing involvement of these regions in balance tasks (Goble et al., 2011; Hüfner et al., 2011; Rogge et al., 2018), in sensorimotor integration (Cauda et al., 2011), and upright standing in blind individuals (Deutschländer et al., 2009a, 2009b; Jahn et al., 2009). The ROIs were automatically labeled for each participant according to the Destrieux atlas (Destrieux et al., 2010) as implemented in Freesurfer, and included the following areas: the inferior circular sulcus of the insula, the long insular gyrus and central sulcus of the insula, the short insular gyrus, and the parahippocampal gyrus, bilaterally, see Fig. 3. Surface-based cortical thickness was analyzed in MATLAB (release 2017b, The MathWorks, Inc., USA) using LME for mass-univariate data with functions provided by FreeSurfer (Bernal-Rusiel et al., 2013). Equations included Time (pretest vs. posttest), Group, and the interaction between Time and Group as fixed effects, the intercept was included as random effect. Multiple comparison correction was performed based on a Monte-Carlo cluster-size simulation implemented in FreeSurfer within the mri_glmfit-sim tool, using white Gaussian noise smoothed on the cortical surface (Hagler et al., 2006). A normal distribution z-map was simulated with n = 10.000 iterations per hemisphere and spatial smoothing of 10 mm FWHM. The simulated null distribution of the maximum cluster size was tested against the obtained data. Statistical maps were thresholded at p < .01, and surviving clusters with a cluster-extent threshold of p < .05 were regarded significant. Significance maps for visualization were overlaid on the FreeSurfer standard brain. Coordinates are reported in MNI space. Whole-brain maps (thresholded at p < .01, uncorrected) for the

2.5. MRI acquisition and preprocessing Scanning was performed on a 3 T MR system (Magnetom Trio, Siemens, Germany) using a padded standard head coil. T1-weighted images were acquired using a MPRAGE sequence (TR = 2300 ms, TE = 2.98 ms, flip angle = 9°, FOV = 256 × 256, 240 coronal slices, voxel size = 1 mm3). Scanning time was 8 min. 2.5.1. Surface-based cortical thickness Processing of the images and surface-based morphometry were performed using the neuroimaging package FreeSurfer, version 6.0, http://surfer.nmr.mgh.harvard.edu/). The procedure of the automated image processing has been described elsewhere (Fischl and Dale, 2000). Briefly, the image reconstruction includes removal of non-brain tissue (Ségonne et al., 2004), intensity normalization, and tessellation of white and gray matter boundaries, topology correction (Fischl et al., 2001), Talairach transformation, automatic surface inflation, spherical atlas registration (Fischl et al., 1999a; Fischl et al., 1999b), and gyribased cortical parcellation (Desikan et al., 2006). In addition, volumetric segmentation of subcortical white and gray matter structures were performed (Fischl et al., 2002). To reduce within-subject noise, an unbiased, robust within-subject template (Reuter and Fischl, 2011) was created between the two time points of each participant, using the longitudinal stream of FreeSurfer (Reuter et al., 2012). The preprocessing steps including intensity normalization, Talairach transformation, subcortical segmentation, surface reconstruction, cortical atlas registration and parcellation were again performed based on the within-subject template information (Reuter et al., 2012). All images were visually inspected for accurate segmentation of white and gray 321

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contrast blind balance vs. blind relaxation group and for the contrast blind balance vs. sighted balance group are provided as supplementary material.

with eyes open (F (1, 63) = 1.03, β = 0.81, 95% CI = [−0.79, 2.41], p = .314), see Fig. 1 and Table 2. There was a significant main effect of Time indicating that both groups improved over time (F (1, 63) = 24.40, β = 1.57, 95% CI = [0.40, 2.75], p < .001) and a trend that sighted participants performed better than blind participants (F (1, 11) = 4.15, β = 2.16, 95% CI = [−0.69, 5.03], p = .066). Blind balance vs. Sighted balance, eyes closed. In contrast, when sighted participants were tested with eyes closed, the performance increase was larger in the blind group than in the sighted group (F (1, 63) = 12.73, β = 1.66, 95% CI = [0.73, 2.59], p = .001), see Fig. 1 and Table 2. There was a significant main effect of Time (F (1, 63) = 12.61, β = 1.65, 95% CI = [0.97, 2.33], p < .001), and a trend that blind participants performed better than sighted participants (F (1, 11) = 4.81, β = 0.62, 95% CI = [−0.88, 2.13], p = .051).

2.6.2.2. Subcortical gray matter volume ROI. To increase reliability, we created two ROIs for analyzing changes in the hippocampus by summarizing the volumes of the hippocampus proper subfields and the subiculum, respectively. The hippocampus proper ROI consisted of the CA fields (CA1-CA4) and the dentate gyrus, the subiculum ROI consisted of the subiculum, pre- and parasubiculum (Aggleton and Christiansen, 2015; Dalton et al., 2017; Flores et al., 2015). The volume data for each ROI were analyzed in MATLAB, separately per hemisphere, using univariate LME functions for longitudinal data provided by FreeSurfer (Bernal-Rusiel et al., 2013). The fixed effects in the models included Time, Group (blind balance vs. blind relaxation, and blind balance vs. sighted balance), and the interaction between Time and Group. Estimated total intracranial volume (centered to the mean, across groups) was submitted as a covariate of no interest to adjust for head size differences in gray matter volumetric analyses (Malone et al., 2015). The intercept was included as subject-specific random effect. The four p-values of the hippocampal volume analyses were corrected for multiple comparisons using Holm-correction (Holm, 1979). Uncorrected and corrected p-values are reported in the results section. The retest reliability coefficients of the hippocampus ROIs ranged from r = .97 to r = 0.99, p < .001.

3.1.2. Force plate 3.1.2.1. Performance at baseline. Static balance performance did neither differ between the blind balance and the blind relaxation group (F (1, 12) = 0.80, β = 2.65, 95% CI = [−9.12, 3.82], p = .389 nor between the congenitally and late blind individuals (F (1, 12) = 1.10, β = 3.07, 95% CI = [−3.53, 9.47], p = .316. 3.1.2.2. Training effects. Postural sway area decreased significantly more in the blind balance than the blind relaxation group (F (1, 138) = 5.79, β = −2.81, 95% CI = [−5.11, −0.50], p = .017), see Table 2. Postural sway area decreased in both groups over time (F (1, 138) = 17.42, β = −3.84, 95% CI = [−4.49, −2.18], p < .001). There was no main effect of Group (F (1, 12) = 0.02, ßβ = −2.57, 95% CI = [−8.01, 2.87], p = .643).

2.6.2.3. Relationship between changes in balance performance and brain structure. To assess the relationship between training-induced changes in brain structure and balance performance measures, we calculated the pre-to posttest difference in the three measures of balance performance, in individual mean cortical thickness values for each significant cluster and in hippocampal volumes. We then correlated brain changes with behavioral changes.

3.1.3. Single-leg stance 3.1.3.1. Performance at baseline. Blind participants. The functional balance performance assessed with the single-leg stance did not differ between the blind balance and the blind relaxation group (F (1, 12) = 0.002, β = −0.05, 95% CI = [−2.99, 2.89], p = .969. The blind participants performed significantly better on hard ground than on soft ground (F (1, 41) = 11.82, β = 3.02, 95% CI = [1.25, 4.80], p = .001, and there was no significant difference between congenitally and late blind individuals (F (1, 12) = 3.04, β = 2.10, 95% CI = [−0.52, 4.73], p = .107). Blind participants vs. Sighted participants. Functional balance did not differ between blind and sighted individuals (F (1, 61) = 0.45, β = 0.11, 95% CI = [−2.29, 2.08], p = .921, neither on hard ground nor on soft ground (all p > .969).

3. Results 3.1. Balance performance 3.1.1. Stability platform 3.1.1.1. Performance at baseline. Blind participants. Dynamic balance performance on the stability platform did neither differ between the blind balance and the blind relaxation group (F (1, 9) = 0.21, β = −0.35, 95% CI = [−2.06, 1.36], p = .655) nor between congenitally blind and late blind participants (F (1, 9) = 2.82, β = 1.12, 95% CI = [−0.39, 2.63], p = .127). Blind participants vs. Sighted participants. There was a significant interaction between Visual Status (blind vs. sighted) and Test Condition (eyes open vs. eyes closed in the sighted) (F (1, 88) = 31.30, β = 2.65, 95% CI = [1.71, 3.60], p < .001). Balance performance of sighted individuals with eyes open was significantly better than performance of blind participants (β = 2.26, p = .019, adjusted with Tukeys). In contrast, there were no differences in balance performance when sighted participants were tested with eyes closed (β = 0.39, p = .942, adjusted).

3.1.3.2. Training effects. Blind balance vs. Blind relaxation. Functional balance improvement was significantly larger in the blind balance than in the blind relaxation group on soft ground (F (1, 40) = 12.59, β = 2.05, 95% CI = [0.89, 3.21], p < .001), but not on hard ground (F (1, 40) = 2.14, β = 3.21, 95% CI = [−1.22, 7.65], p = .151), see Fig. 2 and Table 2. There was a significant main effect of Time for the soft ground condition (F (1, 40) = 5.46, β = 1.7, 95% CI = [0.88, 2.52], p = .024), but not for the hard ground condition (F (1, 40) = 1.75, β = 3.06, 95% CI = [−0.08, 6.19], p = .151). There was a trend that the blind balance group generally performed better than the blind relaxation group on soft ground (F (1, 12) = 3.58, β = 0.47, 95% CI = [−0.34, 1.30], p = .083), but not on hard ground (F (1, 12) = 3.58, β = 0.59, 95% CI = [−5.10, 6.27], p = .390). Blind balance vs. Sighted Balance. When comparing the blind balance with the sighted balance group, they did neither differ in their balance performance improvement on soft ground (F (1, 40) < 0.01, β = 0.02, 95% CI = [−1.33, 1.37], p = .974) nor on hard ground (F (1, 40) = 0.21, β = 0.96, 95% CI = [−3.29, 5.22], p = .649), see Fig. 2 and Table 2. Performance in both groups increased over time (soft ground: (F (1, 40) = 25.37, β = 1.7, 95% CI = [0.72, 2.64], p < .001; hard ground: (F (1, 40) = 5.98, β = 2.09, 95% CI = [−0.91, 5.10],

3.1.1.2. Training effects. Blind balance vs. Blind relaxation. The performance improvement on the stability platform was significantly larger in the blind balance group than in the blind relaxation group (F (1, 119) = 7.66, β = 1.09, 95% CI = [0.31, 1.88], p = .006), see Fig. 1 and Table 2. The main effect of Time was significant (F (1, 119) = 29.01, β = 1.61, 95% CI = [1.11, 2.14], p < .001), and there was no main effect of Group (F (1, 9) = 0.98, β = −0.35, 95% CI = [−2.42, 1.72], p = .349). Blind balance vs. Sighted balance, eyes open. When comparing the blind balance to the sighted balance group, both groups did not differ in their balance performance improvement when the sighted were tested 322

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Fig. 1. Dynamic balance performance as assessed with the stability platform for the blind balance (yellow), the blind relaxation (blue) and the sighted balance (purple) group, including individual data (depicted in gray, different shapes for congenitally blind (triangles), late blind (dots) and sighted participants (rectangles). Figure a) depicts the mean of six trials in the blind groups, collapsed across eyes open and eyes closed conditions. Figure b) and c) depict comparisons of the balance training groups separately for eyes open (EO) and eyes closed (EC) conditions in the sighted balance group (three trials each). Error bars depict standard errors of the mean. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

p = .019). There was no main effect of Group on either ground (p > .292).

p = .002). The main effect of Time was not significant (F (1, 11) = 0.01, β = 0.58, 95% CI = [−1.53, 2.70], p = .922, interaction: (F (1, 10) = 0.62, β = 1.73, 95% CI = [−3.92, 1.86], p = .449).

3.2. Cardiorespiratory fitness

3.3. Cortical thickness

Blind balance vs. Blind relaxation. Cardiorespiratory fitness did not differ between the blind balance and the blind relaxation group (F (1, 10) = 0.52, β = 2.76, 95% CI = [−3.29, 8.80], p = .486) and not between pre- and posttest (main effect of Time: (F (1, 9) = 0.03, β = 0.66, 95% CI = [−2.28, 3.61], p = .870; interaction: F (1, 9) = 0.73, β = −1.66, 95% CI = [−6.02, 2.71], p = .414). Blind balance vs. Sighted Balance. Cardiorespiratory fitness was generally higher for the sighted balance group than for the blind balance group (F (1, 10) = 14.69, β = 9.47, 95% CI = [4.27, 14.67],

3.3.1. Baseline measurements Blind participants. At baseline, cortical thickness of the insula and the parahippocampus did neither differ between the blind balance and the blind relaxation group, nor between congenitally blind and late blind participants (all p > .05, cluster-level corrected). Blind participants vs. Sighted participants. Cortical thickness did not differ between blind and sighted individuals in the ROIs (all p > .05, cluster-level corrected).

Table 2 Balance performance and cardiorespiratory fitness. Means (SD) at pre- and posttest for each group. Test

Time

Stability platform (sec)

pre post

2

Force plate (cm ) Single-leg stance (sec)

pre post pre post

Cardiorespiratory fitness (VO2peak)

pre post

EO EC EO EC soft hard soft hard

Blind balance

Blind relaxation

Sighted balance

3.75 (1.29) 3.89 (1.25) 5.32 (2.46) 5.55 (2.39) 12.94 (6.61) 9.18 (5.26) 1.36 (0.17) 4.92 (6.05) 3.06 (0.79) 7.98 (6.23) 23.13 (5.33) 24.75 (3.67)

3.55 (1.38) 3.40 (1.14) 3.94 (1.54) 4.04 (1.53) 10.25 (4.30) 9.43 (4.37) 1.84 (0.67) 4.33 (3.60) 1.49 (0.49) 4.18 (2.98) 25.88 (3.67) 25.00 (5.71)

5.91 3.28 8.30 3.27 NA

(2.78) (0.80) (3.09) (0.54)

1.90 (0.62) 4.06 (3.17) 3.63 (2.21) 6.16 (4.69) 32.6 (3.75) 32.15 (3.01)

Note. EO = eyes open, EC = eyes closed. NA = not available. Soft = tested on soft ground. Hard = tested on hard ground. VO2peak = maximum oxygen uptake (ml/ min/kg). 323

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Fig. 2. Balance performance as assessed with the single-leg stance for the blind balance (yellow), the blind relaxation (blue) and the sighted balance (purple) group on soft (left panel) and on hard (right panel) underground, including individual data in gray, different shapes for congenitally blind (triangles), late blind (dots) and sighted participants (rectangles). Error bars depict standard errors of the mean. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

3.3.2. Training effects Blind balance vs. Blind relaxation. Cortical thickness was significantly more decreased from pre-to post training in the blind balance group than in the blind relaxation group in two clusters in the left inferior insula and one cluster in the right short insular gyrus (peak coordinates x, y, z in mm: [−34 −9 −6; −45 −5 −18; 37 9 −5], p < . 05, cluster-level corrected, see Fig. 3, Table 3). Moreover, cortical thickness was more increased in the left parahippocampus in the blind balance than in the blind relaxation group [−14 −40 −6], see Fig. 3, Table 3). There were no significant main effects of Time and Group. Blind balance vs. Sighted Balance. In comparison with the sighted balance group, the blind balance group showed a significantly larger reduction in cortical thickness in the left inferior insula [−34 −8 −8], see Table 3), but not in the right insula. There were no significant effects in the parahippocampus and no main effects of Time and Group.

group than in the blind relaxation group (left: F (1, 12) = 9.28, β = 35.82, 95% CI = [10.20, 61.44], p = .010; right: F (1, 12) = 4.94, β = 20.13, 95% CI = [0.39, 39.87], p = .046, see Fig. 4). After correction for multiple comparisons, only the relatively larger decrease of the left hippocampal volume in the balance training group remained significant (left: p = .041, right: p = .093). There was a main effect of Time on the left side (F (1, 12) = 7.86, β = −34.39, 95% CI = [−52.50, −16.27], p = .016), but not on the right side (p > .657). The main effect of Group was not significant (all p > .097). In the right subiculum we observed a significantly larger increase in volume in the blind balance group than in the blind relaxation group (F (1, 12) = 8.60, β = −26.22, 95% CI = [−45.70, −6.74], p = .012 (corrected: p = .041), see Fig. 4), but not in the left subiculum (p > .816). There were no main effects of Time and Group (all p > .107). Blind balance vs. Sighted balance. There was no difference in the volume change in the bilateral hippocampus proper between the blind balance and the sighted balance group (all p > .128). The hippocampus proper volume decreased for both groups from pre-to posttest (left: F (1, 12) = 7.64, β = −34.39, 95% CI = [−63.00, −5.77], p = .017, right: F (1, 12) = 9.53, β = −12.12, 95% CI = [−37.18, 12.93], p = .009). The main effect of Group was not significant (all p > .124). The blind balance group showed a larger increase in the right subiculum than the sighted balance group (F (1, 12) = 11.32, β = −29.94, 95% CI = [−49.33, −10.55], p = .006 (corrected: p = .022)). Main effects of Time and Group were not significant (all p > .226).

3.4. Hippocampus 3.4.1. Baseline measurements Blind participants. At baseline, no significant differences were observed with respect to the hippocampus proper and the subiculum volume bilaterally, neither between congenitally and late blind participants nor between the blind balance and the blind relaxation group (all p > .170). Blind participants vs. Sighted participants. When comparing blind and sighted individuals at baseline, they did not differ in the volume of neither the hippocampus proper nor of the subiculum (all p > .182).

3.5. Correlation of balance performance and structural changes

3.4.2. Training effects Blind balance vs. Blind relaxation. In the bilateral hippocampus proper, we observed a significantly larger volume decrease in the blind balance

Cortical thickness changes in the inferior insula correlated negatively with the single-leg stance change on soft ground (left cluster 1: r Fig. 3. Cortical thickness significance maps of the Time × Group interaction, depicting larger cortical thickness decreases (in blue) and increases (in red) in the blind balance group than in the blind relaxation group in the ROIs. The maps are superimposed on the standard FreeSurfer brain and thresholded at p < .01, uncorrected. Color scale indicates -log(10) p-values. LH = left hemisphere, RH = right hemisphere. Top: lateral view, bottom: medial view. Yellow lines depict the outlines of the atlas-based ROIs. The three clusters in the insula (in blue, top row) and the cluster in the left parahippocampus (in red, bottom row) survived correction for multiple comparisons, see Table 3. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

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Table 3 Changes in cortical thickness (Time × Group interaction), ROI analysis and corrected at p < .05, cluster-level. Hem.

Region

Blind balance < Blind relaxation Left Insula (cluster 1) Left Insula (cluster 2) Right Insula Blind balance > Blind relaxation Left Parahippocampus Blind balance < Sighted balance Left Insula

X, Y, Z

mm2

no. of vertices

β

F

−34 −9 −6 −45 −5 −18 37 9 −5

50.83 37.48 29.12

108 108 60

−0.12 −0.11 −0.09

−12.35 −10.57 −14.11

−14 −40 −6

31.22

88

0.11

12.01

−34 −8 −8

3.35

7

−0.11

−9.63

Note. Peak coordinates are in MNI space.

Fig. 4. Volumes of the hippocampus proper and of the subiculum including pre- and parasubiculum (volume in mm3) in the blind balance (yellow), the blind relaxation (blue) and the sighted balance (purple) group, including individual data in gray, different shapes for congenitally blind (triangles), late blind (dots) and sighted participants (rectangles). Error bars depict standard errors of the mean. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Changes in balance performance in the blind participants did not correlate with changes in the parahippocampus and hippocampus, respectively (all r < 0.602, p > .152), and changes in balance performance in the sighted balance group did not correlate with changes in any ROI (all r < .596, all p > .158).

(df = 12) = −0.74, p = .002, left cluster 2; r = −0.55, p = .042, right cluster: r = −0.78, p = .001, see Fig. 5) across both blind training groups. Analyses run separately for the blind training groups, however, did not reach significance, neither in the blind balance group (left cluster 1: r (df = 5) = −0.66, p = .109, left cluster 2; r = 0.30, p = .518, right cluster: r = −0.59, p = .161) nor in the blind relaxation group (left cluster 1: r = 0.025, p = .912, left cluster 2; r = 0.66, p = .101, right cluster: r = −0.20, p = .663). Cortical thickness changes in the inferior insula correlated with the postural stability change assessed with the force plate at trend level (left cluster 1: r (df = 12) = 0.46, p = .101, right cluster: r = 0.52, p = .054). Analyses run separately for the blind training groups revealed significant correlations for postural stability in the blind balance group (left insular cluster 1: r (df = 5) = 0.91, p = .004, right cluster: r = 0.89, p = .006, see Fig. 6), indicating that larger balance improvements were associated with larger decreases in insular cortical thickness in this group. There were no significant correlations between changes in postural stability and insula thickness changes in the blind relaxation group (all r < 0.32, p > .489).

4. Discussion The aim of the present study was to investigate the influence of balance training on balance performance and underlying cortical and subcortical structural plasticity in blind individuals. To this end, blind adults were randomly assigned to either balance or relaxation training and exercised twice a week for 12 weeks. Dynamic, static, and functional balance performance improved in the blind balance group, but not in the blind relaxation group from pre- to posttest. The improvement in balance performance did not differ from training effects in ageand gender matched sighted adults. Furthermore, the blind balance group showed larger cortical thickness decreases in the inferior insula bilaterally and a larger cortical thickness increase in the left Fig. 5. Correlations between pre-post training changes of the left insular (left/ middle panel) and right insular cortical thickness (right panel) and pre-post training balance performance changes in the singleleg stance on soft ground in the blind balance (yellow) and the blind relaxation (blue) group. Square brackets contain peak coordinates in MNI space. Error bands depict 95% CI. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

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Fig. 6. Correlations between pre-post training changes of the left insular (left panel) and right insular cortical thickness (right panel) with pre-post training sway area changes (assessed with the force plate) within the blind balance (yellow) and the blind relaxation (blue) group. Square brackets contain peak coordinates in MNI space. Error bands depict 95% CI. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

parahippocampus than the blind relaxation group. Hippocampal gray matter volume decreases were observed in the left hippocampus proper whereas the right subiculum significantly increased in the blind balance compared to the blind relaxation group. Benefits in balance performance were associated with gray matter decreases in the inferior insula.

tested with eyes open. This pattern of results might suggest that participants relied on differently weighted sensory information during the training to improve balance performance: While the blind had to integrate vestibular, proprioceptive as well as motor-related information, the sighted additionally had access to optic flow signals to detect motion displacement and to stabilize the head in space, resulting in overall better dynamic balance performance. In fact, changes of cortical thickness in visual association areas of the sighted balance compared to the sighted relaxation group supports this argument (Rogge et al., 2018). In a whole brain analysis, we did not observe changes in visual association areas of the blind group after balance training, compared to the blind relaxation group and in contrast to the matched sighted balance group (see uncorrected whole brain significance maps in the supplementary material). On the one hand, this observation supports the notion that balance training-induced gray matter changes in the visual cortex of the sighted were related to visual processing during selfmotion (Rogge et al., 2018). On the other hand, this finding suggests that intramodal plasticity (within the vestibular-proprioceptive system) rather than crossmodal plasticity (in the visual cortex) accounts for training-related effects on balance performance of the blind participants.

4.1. Balance performance in blind individuals There is converging evidence that balance training improves balance performance in sighted individuals (Gebel et al., 2018; Lesinski et al., 2015), while the extent to which balance training would enhance balance performance in the blind remained to be determined. Here, we show that blind adults improved in dynamic, static, and functional balance after 12 weeks of balance training, but not after relaxation training. The results suggest that balance performance in blind individuals can be improved by specifically tailored physical exercise. Moreover, the blind balance group showed similar training gains in dynamic and functional balance performance compared to a genderand age-matched sighted balance group, indicating that visual input is not a prerequisite for balance performance improvements. It should be noted that both sighted and blind individuals had not reported experience in balance training before the study. Previous cross-sectional studies had reasoned that blind individuals were not able to compensate the absence of vision during postural control (Campayo-Piernas et al., 2017; Ozdemir et al., 2013; Schmid et al., 2007). In the present study, we show that pre-training dynamic balance performance was better in sighted individuals with eyes open than in blind individuals, while both groups did not differ when sighted individuals performed the balance assessments with eyes closed. This pattern of results suggests a lack of compensation in the blind group prior to training. At posttest, however, the blind balance group outperformed the sighted balance group tested with eyes closed, and reached a performance level similar to that of untrained sighted participants with visual input in the dynamic balance task, suggesting that explicit training of balance tasks might allow blind individuals to compensate the absence of vision. This finding is in accordance with and clarifies cross-sectional results in blind goalball athletes who had demonstrated better dynamic postural stability than sedentary blind individuals (Aydoğ et al., 2006). Blind participants of the present study reported to be similarly active in their leisure time as the sighted (as assessed with a questionnaire). However, the blind showed significantly lower cardiorespiratory fitness (as assessed with VO2peak), suggesting lower overall physical fitness. Thus, blind individuals might be less engaged in physically demanding exercise. Notably, the blind balance group improved their dynamic balance performance at posttest, whereas the performance of the sighted, who had primarily trained with visual input, improved only when they were

4.2. Cortical thickness Insula. The balance training induced larger cortical thickness decreases in the inferior insula bilaterally in the blind balance group than in the blind relaxation group. The finding resembles results from sighted balance experts (Hüfner et al., 2011). In this study, adults with several years of experience in ballet dancing and slacklining showed decreased gray matter volume in insular cortical regions in contrast to control participants without extensive balance experience. The insular cortex has been identified as part of a vestibular cortical network (Eulenburg et al., 2012; Fasold et al., 2002; Lopez et al., 2012). Specifically the inferior insula responded to vestibular otolith signals, coding linear acceleration (Oh et al., 2018). Caloric vestibular stimulation and visual gravitational stimuli functionally activated areas of the insula, which overlap with the cluster found in the present study (Indovina et al., 2005). Moreover, functional activation of the anterior insula during muscle spindle stimulation of the ankle has been associated with balance performance during static standing in sighted adults (Goble et al., 2011). In contrast, lesions of the inferior insular gyri have been reported to induce dizziness and tilted visual vertical perception (Baier et al., 2013). In the present study, insular gray matter changes were related to improvements in static balance performance in the blind balance group. Moreover, the left insular cortical thickness decrease was significantly larger in the blind balance group than in the blind relaxation and in the sighted balance group. Thus, training326

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induced structural changes of the inferior insula might be specifically related to vestibular and proprioceptive self-motion processing during upright balancing. Parahippocampus. Larger gray matter increases in the blind balance than in the blind relaxation group were observed in the left posterior parahippocampal gyrus. Similarly, posterior parahippocampus volumes have been reported to be larger in sighted balance experts compared with non-balance trained controls (Hüfner et al., 2011). Located between the hippocampus proper and visual association areas, the posterior parahippocampus has been associated with 3Dspace representation, navigation, visuospatial processing, and processing of vertical gravity information (Aminoff et al., 2013; Kim et al., 2017; Mullally and Maguire, 2011). Noteworthy, congenitally blind individuals have been shown to activate the posterior parahippocampus as well as visual areas and the insular cortex after being trained to use a sensory substitution device for navigational tasks (Kupers et al., 2010). The parahippocampus receives vestibular input (Hitier et al., 2014) and is strongly connected with the posterior cingulate gyrus and the retrosplenial cortex (Kravitz et al., 2011; Vann et al., 2009), a region we have recently reported to be increased after balance training in sighted adults (Rogge et al., 2018). Moreover, balance training has been shown to improve spatial cognitive functions in sighted adults (Dordevic et al., 2017; Rogge et al., 2017). In the present study, structural plasticity in the parahippocampus might therefore be related to a vestibular network involved in sensorimotor balance control and in higher vestibular spatial functions such as navigation and orientation (Seemungal, 2015).

life-time physical activity in congenitally blind participants has been suggested to mediate the link between vestibular perception and navigational abilities assessed with a path completion task (Seemungal et al., 2007). In the present study, cardiorespiratory fitness did not change neither after balance nor after relaxation training and neither in the blind nor in sighted individuals. We therefore speculate that the observed local gray matter changes in the hippocampus are related to physical exercise stimulating particularly the vestibular system. 4.4. Limitations Some limitations of the study need to be mentioned. The sample size of the present study was relatively small compared to similar studies in sighted individuals. The longitudinal study required regular participation in 24 onsite training sessions, and additional behavioral and brain imaging assessments. These time requirements were often in conflict with professional obligations of the blind volunteers who typically participate in our research, resulting in a small sample size. Nevertheless, our data revealed significant group differences between the blind balance and the blind relaxation group in the predicted direction in all three balance tests. This finding suggests a robust gain in balance performance from balance training. It seems, therefore, justified to recommend that rehabilitation efforts should promote a physically active lifestyle including physical exercise comprising balance tasks. Additionally, we included both congenitally and late blind participants, leading to a heterogeneous sample regarding the onset of blindness, although the proportion of late and congenitally blind participants was equal in both training groups. At baseline, balance performance did not differ between congenitally and late blind participants in neither of the three balance tasks. Similarly, no differences in cortical and subcortical gray matter were observed between congenital and late blind individuals. Looking at individual training data, we were not able to identify systematic differences neither between changes of balance performance nor between changes of gray matter between congenitally and late blind participants. Thus, differences observed at the behavioral and neural level between the blind balance and the blind relaxation group are likely benefits of balance training, shared by both congenitally and late blind individuals. In addition, the MRI scanning comprised T1-weighted scans with a resolution of 1 mm3. To reliably segment hippocampal subfields, complementing T2-weighted images and higher image resolution would allow a more precise subfield parcellation (Iglesias et al., 2015; Wisse et al., 2017) to study local hippocampal volume changes.

4.3. Hippocampal gray matter volume We observed local volume changes in the hippocampus with a larger increase of the right subiculum and a larger decrease of the left hippocampus proper in the blind balance than in the blind relaxation group. In rodents, enriched environments or rotarod training, placing substantial demands on balance and motor coordination abilities, have been reported to increase gray matter in the dorsal hippocampus and in the subiculum compared with rodents raised in standard cages (Scholz et al., 2015a; Scholz et al., 2015b). Moreover, electrical stimulation of the vestibular system of freely moving rodents has been shown to modulate the hippocampal theta-rhythm, associated with locomotion and spatial navigation (Aitken et al., 2018). In humans, smaller anterior but larger posterior gray matter volume of the hippocampus has been found in taxi drivers with years of navigational experience, compared with controls having less experience in navigation (Maguire et al., 2000). Moreover, balance expertise has been associated with smaller anterior hippocampal gray matter volume, compared with non-balance trained controls (Hüfner et al., 2011). Local structural plasticity in the hippocampus has also been observed in individuals with sensory loss: Blind individuals were reported to show larger anterior but smaller posterior hippocampal regions than sighted individuals (Chebat et al., 2007; Fortin et al., 2008; Leporé et al., 2009). Other studies, however, did not replicate these results (Bauer et al., 2017; Maller et al., 2016). Studies in patients with bilateral vestibular lesions and recovered unilateral neuritis found less gray matter volume in the posterior hippocampus of these patients compared with healthy controls (Eulenburg et al., 2010; Kremmyda et al., 2016), while incomplete vestibular failure did not change hippocampal gray matter (Göttlich et al., 2016). Together, these results converge to the conclusion that altered visual or vestibular input may be associated with a local change of hippocampal gray matter. Furthermore, neuroplasticity in the hippocampus has been directly linked with physical exercise and with cognitive functions such as memory and spatial functions, possibly mediated by vestibular self-motion perception (Smith, 2017). A high

5. Conclusion The findings of the present combined behavioral and structural brain imaging study suggest that systematic balance training is capable of improving balance performance in blind individuals. These changes might be related to training-induced structural plasticity in brain regions associated with vestibular and proprioceptive self-motion processing and postural control. We speculate that physical exercise improving balance skills might translate to higher vestibular cognitive functions such as spatial navigation. Data availability The datasets generated during the present study are available from the corresponding author on reasonable request. 327

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CRediT authorship contribution statement

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Ann-Kathrin Rogge: Conceptualization, Investigation, Formal analysis, Writing - original draft. Kirsten Hötting: Conceptualization, Writing - review & editing. Volker Nagel: Resources. Astrid Zech: Resources, Writing - review & editing. Cordula Hölig: Formal analysis, Writing - review & editing. Brigitte Röder: Conceptualization, Methodology, Funding acquisition, Writing - review & editing. Acknowledgements This research was supported by a grant from the European Commission [ABBI, 611452, FP7-ICT-2013-10] to Brigitte Röder, and a grant from the German Research Foundation [DFG Ro 2625/10-1] to Brigitte Röder. We thank Gudrun Nagel for carrying out the training programs, and Klaus-Michael Braumann and Karsten Hollander of the Institute for Sports Medicine at the University of Hamburg for conducting the medical examinations and cardiorespiratory fitness tests. We are sincerely grateful to all participants contributing to this study. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.neuropsychologia.2019.04.005. References Aggleton, J.P., Christiansen, K., 2015. The subiculum: the heart of the extended hippocampal system. Prog. Brain Res. 219, 65–82. https://doi.org/10.1016/bs.pbr.2015. 03.003. Ainsworth, B.E., Haskell, W.L., Whitt, M.C., Irwin, M.L., Swartz, A.M., Strath, S.J., ... Leon, A.S., 2000. Compendium of physical activities: an update of activity codes and MET intensities. Med. Sci. Sports Exerc. 32 (9 Suppl. l), S498–S504. Ainsworth, B.E., Haskell, W.L., Herrmann, S.D., Meckes, N., Bassett, D.R., Tudor-Locke, C., ... Leon, A.S., 2011. 2011 Compendium of Physical Activities: a second update of codes and MET values. Med. Sci. Sports Exerc. 43 (8), 1575–1581. https://doi.org/ 10.1249/MSS.0b013e31821ece12. Aitken, P., Zheng, Y., Smith, P.F., 2018. The modulation of hippocampal theta rhythm by the vestibular system. J. Neurophysiol. 119 (2), 548–562. https://doi.org/10.1152/ jn.00548.2017. Alary, F., Goldstein, R., Duquette, M., Chapman, C.E., Voss, P., Lepore, F., 2008. Tactile acuity in the blind: a psychophysical study using a two-dimensional angle discrimination task. Exp. Brain Res. 187 (4), 587–594. https://doi.org/10.1007/s00221008-1327-7. Amedi, A., Floel, A., Knecht, S., Zohary, E., Cohen, L.G., 2004. Transcranial magnetic stimulation of the occipital pole interferes with verbal processing in blind subjects. Nat. Neurosci. 7 (11), 1266–1270. https://doi.org/10.1038/nn1328. Aminoff, E.M., Kveraga, K., Bar, M., 2013. The role of the parahippocampal cortex in cognition. Trends Cognit. Sci. 17 (8), 379–390. https://doi.org/10.1016/j.tics.2013. 06.009. Augestad, L.B., Jiang, L., 2015. Physical activity, physical fitness, and body composition among children and young adults with visual impairments: a systematic review. Br. J. Vis. Impair. 33 (3), 167–182. https://doi.org/10.1177/0264619615599813. Aydoğ, E., Aydoğ, S., Çakci, A., Doral, M., 2006. Dynamic postural stability in blind athletes using the biodex stability system. Int. J. Sports Med. 27 (5), 415–418. https://doi.org/10.1055/s-2005-865777. Baier, B., Eulenburg, P., Zu Best, C., Geber, C., Müller-Forell, W., Birklein, F., Dieterich, M., 2013. Posterior insular cortex - a site of vestibular-somatosensory interaction? Brain Behav. 3 (5), 519–524. https://doi.org/10.1002/brb3.155. Bates, D., Mächler, M., Bolker, B., Walker, S., 2015. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67 (1). https://doi.org/10.18637/jss.v067.i01. Bauer, C.M., Hirsch, G.V., Zajac, L., Koo, B.-B., Collignon, O., Merabet, L.B., 2017. Multimodal MR-imaging reveals large-scale structural and functional connectivity changes in profound early blindness. PLoS One 12 (3), e0173064. https://doi.org/ 10.1371/journal.pone.0173064. Bernal-Rusiel, J.L., Greve, D.N., Reuter, M., Fischl, B., Sabuncu, M.R., 2013. Statistical analysis of longitudinal neuroimage data with Linear Mixed Effects models. Neuroimage 66, 249–260. https://doi.org/10.1016/j.neuroimage.2012.10.065. Bernstein, D.A., Borkovec, T.D., Ullmann, L.P., 1975. Progressive Relaxation Training: A Manual for the Helping Professions, 3rd pr. Research Press, Champaign. Campayo-Piernas, M., Caballero, C., Barbado, D., Reina, R., 2017. Role of vision in sighted and blind soccer players in adapting to an unstable balance task. Exp. Brain Res. 235 (4), 1269–1279. https://doi.org/10.1007/s00221-017-4885-8. Cauda, F., D'Agata, F., Sacco, K., Duca, S., Geminiani, G., Vercelli, A., 2011. Functional connectivity of the insula in the resting brain. Neuroimage 55 (1), 8–23. https://doi. org/10.1016/j.neuroimage.2010.11.049. Chebat, D.-R., Chen, J.-K., Schneider, F., Ptito, A., Kupers, R., Ptito, M., 2007. Alterations

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