Behavioural Brain Research 293 (2015) 89–95

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Behavioural Brain Research

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Research report

The impact of eye closure on somatosensory perception in the elderly

Stefan Brodoehl a,b,∗, Carsten Klingner a,b, Katharina Stieglitzb, Otto W. Witte a,b

a Hans Berger Department for Neurology, Friedrich Schiller University of Jena, Germanyb Brain Imaging Center, Friedrich Schiller University Jena, Germany

h i g h l i g h t s

• Eye closure improves somatosensory perception in healthy, young and old adults.• With aging the gain of increased perception diminishes.• Cortical activation due to eye closure differs in young and old adults.• Decreased ability for unisensory processing is a general phenomenon in aging.• Aging brain tends to shift toward multisensory integration.

a r t i c l e i n f o

Article history:

Received 4 June 2015

Received in revised form 1 July 2015

Accepted 3 July 2015

Available online 20 July 2015

Keywords:

Closed eyes

Darkness

Current perception threshold

Somatosensory

Visual

fMRI

Aging

a b s t r a c t

Visual dominance over other senses is a well-known phenomenon. Closing the eyes, even in complete

darkness, can improve somatosensory perception by switching off various aspects of visual dominance.

How and if this mechanism is affected by aging remains unknown. We performed detailed neurophys-

iological and functional MR-imaging on healthy young and elderly participants under the conditions of

opened and closed eyes. We found an improved perception threshold in both groups when the eyes

were closed, but the improvement was significantly less pronounced in the elderly. fMRI data revealed

increased resting activity in the somatosensory cortex with closed eyes, and the stimulus-induced activity

of the secondary somatosensory cortex decreased in the young but not in the elderly.

This study demonstrates that a switch towards unisensory processing via eye closure is preserved but

significantly reduced in the aging brain. We suggest that the decreased ability for unisensory processing

is a general phenomenon in the aging brain resulting in a shift toward multisensory integration.

© 2015 Elsevier B.V. All rights reserved.

1. Introduction

Closing the eyes is known to alter various aspects of brain phys-

iology. In 1929, Berger first described that the alpha-rhythm in EEG

is provoked by eye closure. Although studies relating to neuroimag-

ing and neurophysiology have analyzed the different brain states

that are affected by closed eyes compared to opened eyes, such

changes are often regarded as being due to the absence or presence

of visual information [1].

In a recent study [2], we demonstrated a substantial impact

of eye closure on somatosensory perception that was indepen-

dent of visual information. Our previous results from functional

brain imaging suggested that eye closure switches the brain from

thalamo-cortical networks that includes visual dominance to a

∗ Corresponding author. Fax: +49 3641-9323402.

E-mail address: stefan.brodoehl@med.uni-jena.de (S. Brodoehl).

non-visually dominated processing mode, resulting in superior per-

ception of somatosensory stimuli.

Although such a switch between different processing modes

may be highly beneficial for improving unisensory performance,

it may result in problems in the aging brain.

The aging brain is thought to progressively depend on multi-

sensory integration to compensate for the reduced sensitivity of

individual sensory systems and altered cerebral processing speed

and capacity [3]. However, the quality of multisensory integration is

determined by the overall function of the peripheral sensory organs

and cortical processing. In normal aging, there arises a weakening

of all senses, such as vision [4], audition [5] and somatosensory

perception [6] and a decline in motor and executive functions [7].

These declines are accompanied by changes in the peripheral [8,9]

and central nervous systems [10]. Regarding multisensory process-

ing, the parallel presentation of visual stimuli can suppress the

activity of other sensory modalities [11,12]. Whereas, the impact

of aging on cross-modal interactions between the visual and the

auditory system has been investigated [13], age dependent interac-

http://dx.doi.org/10.1016/j.bbr.2015.07.014

0166-4328/© 2015 Elsevier B.V. All rights reserved.

90 S. Brodoehl et al. / Behavioural Brain Research 293 (2015) 89–95

Table 1

Current perception threshold (CPT) of the young (Y01–Y18) and old (O01–O15) subjects under the conditions of opened and closed eyes. The mean and standard deviation

of the CPT for the closed and opened eye conditions (both measured in complete darkness) are shown. A one-way repeated-measurement analysis of variance (ANOVA)

revealed a significant impact of age and eye state on the CPT (P ≤ 0.05).

age (years) sex eyes closed (mA) eyes opened (mA) opened–closed (mA)

Y01 23 w 1.36 ± 0.03 1.39 ± 0.03 0.03

Y02 22 w 2.04 ± 0.06 2.12 ± 0.06 0.09

Y03 23 w 2.48 ± 0.04 2.47 ± 0.03 0.00

Y04 22 m 2.80 ± 0.15 2.79 ± 0.12 0.00

Y05 24 w 1.75 ± 0.04 1.91 ± 0.05 0.16

Y06 23 w 1.51 ± 0.05 1.52 ± 0.02 0.01

Y07 23 w 2.55 ± 0.09 2.61 ± 0.05 0.06

Y08 23 m 1.29 ± 0.04 1.35 ± 0.07 0.07

Y09 24 m 1.15 ± 0.02 1.21 ± 0.02 0.06

Y10 21 m 2.44 ± 0.18 2.49 ± 0.14 0.05

Y11 27 m 1.48 ± 0.02 1.52 ± 0.02 0.04

Y12 21 m 1.81 ± 0.07 1.80 ± 0.06 0.01

Y13 23 w 2.07 ± 0.22 2.10 ± 0.20 0.03

Y14 26 m 1.97 ± 0.16 2.18 ± 0.19 0.21

Y15 22 w 1.05 ± 0.03 1.12 ± 0.05 0.07

Y16 23 m 1.25 ± 0.12 1.34 ± 0.12 0.09

Y17 21 w 1.04 ± 0.06 1.11 ± 0.06 0.07

Y18 23 w 1.41 ± 0.18 1.43 ± 0.09 0.02

mean 23.0 ± 1.57 1.74 ± 0.09 1.80 ± 0.08 0.06 ± 0.054

O01 68 m 2.35 ± 0.19 2.40 ± 0.18 0.05

O02 69 m 2.60 ± 0.05 2.64 ± 0.07 0.04

O03 71 m 1.98 ± 0.07 1.96 ± 0.06 -0.02

O04 61 m 3.02 ± 0.06 3.02 ± 0.06 0.01

O05 67 m 2.07 ± 0.08 2.07 ± 0.04 0.00

O06 67 m 2.03 ± 0.02 2.07 ± 0.02 0.04

O07 69 m 1.26 ± 0.10 1.27 ± 0.08 0.01

O08 62 w 1.38 ± 0.16 1.40 ± 0.13 0.02

O09 65 w 2.92 ± 0.30 2.81 ± 0.24 -0.12

O10 68 w 1.66 ± 0.08 1.74 ± 0.09 0.08

O11 69 w 1.37 ± 0.20 1.37 ± 0.20 0.00

O12 69 w 2.08 ± 0.17 2.12 ± 0.10 0.04

O13 71 w 2.83 ± 0.18 2.90 ± 0.08 0.07

O14 62 w 3.03 ± 0.06 3.07 ± 0.06 0.04

O15 66 m 2.69 ± 0.07 2.72 ± 0.06 0.03

mean 66.9 ± 3.17 2.24 ± 0.10 2.24 ± 0.10 0.02 ± 0.045

tions between visual and somatosensory processing have not been

addressed until now.

Here, we aim to study whether the cross-modal modulation

towards unisensory processing induced by eye closure remains

present in healthy elderly. We compare a group of elderly subjects

with a group of young subjects based on behavior and informa-

tion transfer within the brain. The extent to which elderly are able

to modulate toward a unisensory processing mode may provide a

unique technique of solitary sensory stimulation for evading mul-

tisensory processing to provide new strategies of training therapy

in elderly.

2. Materials and methods

2.1. Subjects

We investigated 16 right-handed elderly (7 females; age range,

62–71 years; mean age, 66.9 ± 5.2 years (man ± standard devia-

tion [SD])) and 18 right-handed young subjects (10 females; age

range, 21–28 years; mean age, 23.0 ± 1.6), as detailed in Table 1. All

subjects had no history of neurological or psychiatric diseases. All

elderly subjects were examined by a neurologist, and conventional

electroneurography (nerve conduction velocity measurement of

the median nerve) was performed to exclude any peripheral nerve

lesion or polyneuropathy. Additional exclusion criteria included

diabetes mellitus, movement impairment, and a “Mini Mental State

Examination” [14] score of less than 29. Investigations were per-

formed according to the Declaration of Helsinki on Biomedical

Studies Involving Human Subjects. The study was approved by the

local ethics committee, and all subjects provided written informed

consent according to the declaration of Helsinki.

2.2. Psychophysical testing: current perception threshold (CPT)

We aimed to study the difference in the perception thresh-

old between the baseline conditions of eyes for both opened and

closed states in a completely darkened environment. Volunteers

wore completely darkened goggles and the room was darkened,

and each volunteer confirmed that no gleam of light was noticed

during the entire examination.

Starting in a relaxed sitting position with closed eyes (illu-

minated), we applied 40-Hz monophasic wave pulses starting at

0.5 mA to the right index finger using a clinical neurostimula-

tor (Digitimer Constant Current Stimulator model DS7A, Digitimer

Ltd., Welwyn Garden City, Hertfordshire, AL7 3BE, England). Cur-

rent intensity was slowly increased until each subject detected the

stimulus. The procedure was repeated up to 20 times until we

achieved a constant baseline current perception threshold (CPT).

After ten minutes of dark adaption and determining the baseline,

5 CPT blocks for eyes opened and eyes closed (5 min each) were

performed, and the CPT was determined every 30 s. Instructions

for opening and closing the eyes were given to the participants

verbally by the investigator. Results were considered significant at

P < 0.05.

S. Brodoehl et al. / Behavioural Brain Research 293 (2015) 89–95 91

2.3. MRI Recordings

All experiments were performed using a 3.0-T MR scanner (Trio,

Siemens, Erlangen, Germany) to obtain echo-planar T2*-weighted

image volumes (EPI) and transaxial T1-weighted structural images.

The high-resolution T1-weighted structural images had a voxel size

of 1 × 1 × 1 mm3 to allow for precise anatomical localization. fMRI

experiments were performed in complete darkness, and the volun-

teers wore completely darkened goggles. Instructions for opening

and closing the eyes were given to the participants via earphones.

We performed two different fMRI experiments. To exclude fatigue

and unpleasant sensations, these parameters were reported by all

subjects according to a standardized protocol after the experiment.

In the first fMRI experiment, we imposed a block-related

regime. Starting from the eyes closed condition, the subjects had

to alternately open and close their eyes every 27 s (20 blocks

each, total time less than 20 min). In total, 600 EPI images (voxel

size = 3 mm × 3 mm × 3 mm, repetition time = 2.52 s, TE = 35 ms; 40

transaxial slices including the whole cerebrum and cerebellum)

were acquired.

In the second experiment, we used a block design identical to

that of the first experiment, but within each block, a tactile stim-

ulation was applied to fingers 1–5 of the right hand. Stimulation

was delivered via balloon diaphragms driven by compressed air.

Each stimulus lasted for 100 ms (20 ms rise time, 30 ms plateau, and

50 ms return to baseline pressure) and was presented in an event-

related regime. To avoid systematic errors in the hemodynamic

response function estimation, the stimulus time was randomized

between 8.7 and 15.8 s after a block began. The timing of the stimu-

lus presentations was externally controlled using the MRI scanner

and was synchronized to the image acquisition.

2.4. Data analysis

Data analysis was performed on a PC using MATLAB (Math-

Works, Natick, MA) and SPM8 software (Wellcome Department

of Cognitive Neurology, London, UK, http://www.fil.ion.ucl.ac.uk/

spm). For each subject, all of the images were realigned to the first

volume using six-parameter rigid-body transformations to correct

for motion artifacts [15,16]. The images were co-registered with

the corresponding anatomical (T1-weighted) images of the sub-

ject, re-sliced to correct for acquisition delays (referenced to the

tenth slice only in the event-related design), normalized to the

Montreal Neurological Institute (MNI) standard brain [17] to report

MNI coordinates, and smoothed using a 6-mm full-width-at-half-

maximum Gaussian kernel.

2.5. fMRI analysis

Multiple regression analysis using a general linear model was

performed to obtain statistical parametric maps calculated for the

somatosensory stimulation. The fMRI signal time courses were

high-pass filtered (128 s) and modeled as an experimental-stimulus

onset function convolved using the canonical hemodynamic

response function (low-pass filter). Two contrasts of interest were

examined, resulting in two t-statistical (paired t-test) maps (eyes

closed > opened and closed < opened for the first fMRI experi-

ment, and stimulation while eyes closed > opened and stimulation

while closed < opened for the second fMRI experiment). Individual

results were projected onto their respective co-registered high-

resolution T1-weighted 3-D data set. The anatomical localization

of the activated areas was analyzed with reference to the standard

stereotaxic atlas and was mapped using the anatomical toolbox

of the SPM program [18,19] http://www.fz-juelich.de/ime/spm

anatomy toolbox). The resulting statistical maps were thresholded

according to the FDR (false discovery rate).

Fig. 1. Current perception threshold acquired due to electrical stimulation of the

right hand in young (N = 18) and old (N = 16) subjects during states of closed and

opened eyes. The error bars represent the standard error of the mean (SEM). The

open (black) and closed (red) bars represent to the absolute current perception

threshold (left y-axis); the difference between closed and opened eyes (gray bar)

are given on the right y-axis. (*) significant at P ≤ 0.05 (paired t-test CPT with closed

eyes compared to opened eyes (black star), two-sample t-test comparing the differ-

ence between closed and opened eyes in young and elderly subjects (gray star)). (For

interpretation of the references to color in this figure legend, the reader is referred

to the web version of this article)

To evaluate shape, timing (time to peak) and magnitude (height

and full-width at half-maximum) of the task/stimulus-evoked

hemodynamic response in the second fMRI experiment, we mod-

eled the hemodynamic response function (HRF) of extracted time

courses of the clusters of the highest t-values within the left

primary (−54 × −19 × 46 (BA1), −45 × −25 × 46 (BA2)) and sec-

ondary somatosensory cortex (−45 × −25 × 16), including the 26

surrounding voxels. We performed a least-squares fit of the exper-

imental signal time courses using an inverse logit function, as

previously described by Lindquist and Wagner [20]:

L =1

1 + e−x(1) inverse logit function

h(t) = ˛1 × L

(

t − T1

D1

)

+ ˛2 × L

(

t − T2

D2

)

+ ˛3 × L

(

t − T3

D3

)

(2) hemodynamic response function

˛3 = |˛2| − |˛1| × ˛2

= ˛1 ×

(

L(−T3)/D3 − L(−T1)/D1

L(−T3)/D3 + L(−T2)/D2

)

(3) constraints

The major advantage of this HR model compared to the double

gamma function implemented in SPM is the improved ability to

access the individual variance of the shape of the HRF that influence

the magnitude, delay, and duration of the HRF. The start parame-

ters (D1 = −1.834, D2 = −0.6314, D3 = −3.016, T1 = 4.358, T2 = 2.715,

T3 = 4.516, �1 = 5.143) were determined by fitting the model to the

SPM built-in hemodynamic response function. All of the individual

BOLD time courses were fit to the model. To assure the quality of the

curve fit, the R-square and root mean squared error (RMSE) of all

of the fits were below 0.9 (R-square) and 0.1 (RMSE), respectively.

The results are shown in Fig. 3.

3. Results

3.1. Psychophysical: Current perception threshold (CPT)

Eye closure led to a significantly decreased CPT in both

young (closed 1.74 ± 0.09 mA, opened 1.80 ± 0.08 mA, paired t-test

P < 0.001) and old (closed 2.22 ± 0.12 mA, opened 2.24 ± 0.10 mA,

paired t-test P = 0.049) subjects (Table 1, Fig. 1). A repeated mea-

sures analysis of variance (ANOVA) with age and eye state (opened

92 S. Brodoehl et al. / Behavioural Brain Research 293 (2015) 89–95

Fig. 2. Random effect group analysis of the BOLD responses for (A) eyes closed without tactile stimulation and (B) eyes opened (left) and closed (right) to a tactile stimulus of

digits 1–3 of the right hand comparing the young (n = 18) and elderly (n = 16) subjects (two-sample t-test). Bright colors indicate high levels of significance; numbers indicate

clusters of activation, as described in Table 2 (without stimulation) and 3 (with stimulation). Results for (A) are FDR corrected, (B) and (C) are uncorrected values.

or closed) as factors revealed a significant impact on the CPT.

Moreover, the CPT was significantly higher in the elderly subjects

(P = 0.03). Fig. 1 shows the change in the CPT for young and old

subjects. The increased perception threshold caused by eye clo-

sure is more pronounced in young (absolute perception change

of 0.06 ± 0.05 mA) compared to old (absolute perception change

0.02 ± 0.05 mA) subjects (unpaired t-test P = 0.003).

3.2. Functional MRI — without stimulation

Closing the eyes induced increased resting activity within the

primary and secondary somatosensory cortex in both groups. How-

ever, the increase in activity was less pronounced in the elderly

group. Fig. 2A and Table 2 show the increased brain activity induced

by eye closure in the young compared to old subjects.

Furthermore, there was no significant difference in the brain

activation patterns at rest between the young and elderly groups

with eyes opened (no figure).

3.3. Functional MRI — with stimulation

Tactile stimulation of the right hand evoked highly significant

activation in the random effect group analysis. In both groups, acti-

vation occurred within the left SI (BAs 3, 1, 2) and in the bilateral

secondary somatosensory cortex (SII) (BAs 13, 40, 41, 43).

Comparing the clusters of activation between both groups,

we found no significant difference between young and old sub-

jects while the eyes were closed within the somatosensory cortex

(Fig. 2B — left, Table 3). However, in young subjects the region of

activation was significantly increased within the secondary and pri-

mary (not related to the hand area) somatosensory cortices when

the eyes were opened (Fig. 2B — right, Table 3).

3.4. HRF analysis

To characterize the impact of age and eye closure on the indi-

vidual task/stimulus-evoked BOLD responses, 3 voxels from the left

Table 2

Cluster of SPM activations for young > old and closed > opened eyes without tactile stimulation (P ≤ 0.01 (FDR corrected)). Legend: BA – Brodmann area, hIP – intraparietal

sulcus, IPC – inferior parietal lobule, OP – parietal operculum, SPL – superior parietal lobule, r – right, l – left.

cluster vox (n) Area side peak at MNI (x, y, z) t-value

young > old and closed > opened

1 1097 BA1, BA2, BA3b, BA4, SPL, BA18 r + l 12 −82 43 6.14

2 153 BA6 l −15 8 64 5.66

3 116 BA1, BA2, BA3a, BA3b, BA4, hIP, SPL l −27 −40 55 5.08

4 45 BA1, BA2, BA3b, IPC, OP r + l 60 -19 31 4.81

5 33 BA3a, BA6, SPL r + l 15 −37 49 4.36

6 24 BA4, SPL l −6 −37 52 4.13

7 22 BA6 l -12 −7 73 4.78

8 22 IPC, OP l -60 −28 25 4.70

9 17 BA6 r 9 −13 40 4.59

10 16 BA6 l −24 −16 67 4.15

11 15 BA44 l −33 8 31 4.83

12 15 hIP, IPC r 39 −46 28 4.47

S. Brodoehl et al. / Behavioural Brain Research 293 (2015) 89–95 93

Fig. 3. Fitted time courses of the BOLD signal clusters with the highest t-values within the primary and secondary somatosensory cortices for the second fMRI experiment

(tactile stimulation was performed on the right hand for closed and open eyes). The BOLD time courses of all subjects in response to stimulation with closed and opened eyes

were extracted and fit to an inverse logit function. The fitted hemodynamic response function (hrf) displays a mean function of each group, and the results of the TTP (time

to peak) and AMP (amplitude) (including the standard deviation) correspond to the individual fits of each subject. (*) indicates a significant difference according to a paired

t-test at P ≤ 0.05.

primary (BA1 and BA2) and the secondary somatosensory cortex

(SII) with the highest t-values from the 3 clusters of the second-

level analysis were extracted and fit to a HRF-model (Fig. 3 and

Table 4).

Compared to eyes opened, eye closure tends to result in an accel-

eration of the time to peak and an increase in the amplitude of

the fitted hemodynamic response function in young and elderly

subjects (Fig. 3). A paired t-test showed significant differences at

P ≤ 0.05 for the time to peak (TTP) at BA1 in the elderly subjects

and at BA2 in the young subjects and for the amplitude at BA1 in

the young subjects. A repeated-measures ANOVA using age and eye

state (opened or closed) as factors did not reveal any significant

interactions at P ≤ 0.05 (Table 4).

4. Discussion

The current study compared the current perception thresh-

old of healthy young and elderly subjects under the conditions

of opened and closed eyes. We confirmed that eye closure leads

to improved somatosensory perception. This improvement exists

Table 3

Clusters of SPM activations for old > young with tactile stimulation (P ≤ 0.005 (uncorrected). Legend: BA – Brodmann area, hIP – inferior parietal lobule, IPC – rolandic

operculum, OP – parietal operculum, SPL – superior parietal lobule, r – right, l – left.

cluster vox (n) area side peak at MNI (x, y, z) t-value

opened > closed

1 115 IPC, hIP, SPL l −48 −55 55 4.29

2 78 hIP r 48 −55 55 4.95

3 16 superior frontal / medial gyrus r 15 29 46 4.29

4 16 SPL r 6 −64 43 3.36

5 15 SPL l −6 67 40 3.80

closed > opened

1 20 BA2, BA3b, BA4, IPC, OP l −57 −13 22 3.69

2 15 SPL l −12 −94 37 4.79

3 15 BA2, BA3b, IPC, OP r 54 −22 31 3.55

94 S. Brodoehl et al. / Behavioural Brain Research 293 (2015) 89–95

Table 4

Fitted time courses of the BOLD cluster signals with the highest t-values within the primary (SI) and secondary (SII) somatosensory cortices for the second fMRI experiment,

as shown in Fig. 3. TTP (time to peak) and AMP (amplitude), including the standard deviation, correspond to the individual fits of each subject. The results of a repeated

measurement ANOVA using age and eye state (opened or closed) as factors are listed. (*) indicates significance at P ≤ 0.05, BA – Brodmann area.

TTP (s) AMP (% change)

old young ANOVA old young ANOVA

left SI(BA1) all 5.0 ± 0.87 4.6 ± 0.70 age: P ≤ 0.061 1.1 ± 0.33 1.3 ± 0.42 age: P ≤ 0.024*

closed 4.8 ± 0.85 4.6 ± 0.69 eye: P ≤ 0.047* 1.0 ± 0.25 1.4 ± 0.46 eyes: P ≤ 0.869

opened 5.2 ± 0.86 4.7 ± 0.71 eye*age: P ≤ 0.132 1.1 ± 0.38 1.2 ± 0.34 eye*age: P ≤ 0.131

(BA2) all 4.5 ± 1.00 4.2 ± 0.94 age: P ≤ 0.517 0.9 ± 0.38 1.1 ± 0.42 age: P ≤ 0.065

closed 4.5 ± 0.99 4.1 ± 0.98 eyes: P ≤ 0.046* 1.0 ± 0.41 1.1 ± 0.42 eyes: P ≤ 0.548

opened 4.5 ± 1.01 4.2 ± 0.90 eye*age: P ≤ 0.148 0.9 ± 0.33 1.1 ± 0.42 eye*age: P ≤ 0.196

left SII all 4.4 ± 1.13 4.2 ± 0.59 age: P ≤ 0.122 1.1 ± 0.42 1.1 ± 0.45 age: P ≤ 0.404

closed 4.4 ± 1.02 4.2 ± 0.50 eyes: PP ≤ 0.583 1.1 ± 0.37 1.2 ± 0.51 eyes: P ≤ 0.757

opened 4.5 ± 1.23 4.3 ± 0.6 eye*age: P ≤ 0.983 1.1 ± 0.46 1.1 ± 0.36 eye*age: P ≤ 0.940

in both groups (young and elderly) but is less pronounced in the

elderly. This observation is accompanied by a minor increase in

the resting BOLD responses of the somatosensory cortex after

eye closure in the elderly (Fig. 2A). These results indicate that

the modulation of neuronal information processing, as caused

by eye closure, decreases during aging. This may resemble the

expression of compensatory mechanisms that suggest multisen-

sory integration during aging [21]. The cortical activation pattern

in elderly, for instance, is altered for a variety of sensory, motoric

and cognitive tasks involving associative and multisensory brain

areas [13,22,23]. The age-dependent increase in activity within

these association areas due to somatosensory stimulation with

opened eyes (Fig. 2b, left) supports the assumption of accentu-

ated multisensory information processing in the elderly. However,

the integration of multisensory information depends on the quality

of the information of each sensory source. It is known, that infor-

mation of both (visual and somatosensory) channels decreases in

quality with age and therefore is associated with increased vari-

ance of visual and somatosensory estimation. This is associated

with increased tactile perception thresholds [6,13] and slowed

responses in visual recognition in elderly [24]. According to stud-

ies of Ernst and Banks [25], it is assumed that a misbalance

between both sensory entities results in an augmentation of visual

dominance.

In the present study, the elderly exhibited increased bilateral

SII activation due to somatosensory stimulation with their eyes

closed (Fig. 2b, right). The SII is presumed to perform higher order

somatosensory processing, including the integration of informa-

tion from both hemispheres and context-dependent processing of

somatosensory information such as information from other sen-

sory modalities [26]. The fact that eye closure led to no altered

activity in the primary somatosensory cortex (SI) suggests that the

amount of somatosensory information input to the SI did not dif-

fer between the groups. However, the increased stimulus-induced

activity in the SII in the elderly demonstrates accentuated multi-

sensory information processing in the elderly that remains present

when the eyes are closed, indicating a reduced ability for unisensory

processing.

To further investigate the age-dependent impact of eye closure

on somatosensory processing, we measured the BOLD signal from

different clusters within the SI and SII (Fig. 3). The BOLD signal is

known to be tightly correlated with the underlying neuronal activ-

ity [27]. Similar to our previous work, eye closure tends to result

in increased amplitude and faster time to peak (TTP), although

the effect however was more pronounced in young subjects [6].

In view of the changes in the cerebral blood flow, as described

in the elderly [28–31], the results are potentially masked. How-

ever, our results demonstrate that eye closure triggers modulation

of neuronal processing in the aging brain. The resulting superior

somatosensory perception is of potential significance for everyday

life.

Given that our experiments were performed in complete dark-

ness, one may argue that visual deprivation affects the current

results and their interpretation. However, in our opinion, there

are several explanations why this result is not caused by effects

of visual deprivation. First, the effects of visual deprivation on the

somatosensory perception are ambivalent. Whereas previous stud-

ies demonstrated a favoring effect of visual deprivation on haptic

perception [32–34], more recent studies could not reproduce these

findings [35,36]. However, even for relevant visual deprivation, one

method to compensate for such an effect is to compare two condi-

tions during visual deprivation, which was performed in the current

study. Therefore, we suggest that the act of closing the eyes inde-

pendently of visual information induces improved somatosensory

processing.

Our results indicate that closing the eye leads to a switch

from multisensory to unisensory processing. A previous study has

shown that this is primarily achieved via decoupling the thala-

mus from the visual cortex and by increasing the information flow

between the thalamus and the somatosensory cortex [2]. In daily

life, we intuitively close our eyes when inspecting objects and sur-

faces by hand. In light of its potential evolutionary purpose, it is

conceivable that this is a predefined and reflex-like mechanism.

Given the preformed dominance of vision over other senses [37],

this may resemble a mechanism to shape and train senses in the

absence of visual information. However, as the aging brain tends to

rely increasingly on multisensory information and integration, the

impact of eye closure on sensory processing diminishes.

5. Conclusion

Here, we demonstrated that eye closure, independent of visual

information, results in an improved perception and processing of

somatosensory stimuli. This effect, although diminished, remains

present in the aging brain and does substantially affect somatosen-

sory perception. The relevance of the switch towards unisensory

processing induced by eye closure for the prevention and therapy of

age-dependent deficits and diseases (such as gait disorder, stroke,

neurodegenerative disorders) and the effects on more complex

somatosensory stimuli (such as grating orientation task) should be

further investigated.

Acknowledgements

The authors received support from: DFG FOR 1738 B2;

BMBF Bernstein Fokus (FKZ 01GQ0923); BMBF Gerontosys JenAge

(FKZ 031 5581B); EU BrainAge(FP 7/HEALTH.2011.2.22-2 GA

No.:2798219); BMBF Irestra (FKZ 16SV7209).

S. Brodoehl et al. / Behavioural Brain Research 293 (2015) 89–95 95

References

[1] G. Pfurtscheller, A. Stancak Jr., C. Neuper, Event-related synchronization (ERS)

in the alpha band—an electrophysiological correlate of cortical idling: a

review, Int. J. Psychophysiol. 24 (1996) 39–46.

[2] S. Brodoehl, C.M. Klingner, O.W. Witte, Eye closure enhances dark night

perceptions, Sci. Rep. 5 (2015) 10515.

[3] J. Freiherr, J.N. Lundstrom, U. Habel, K. Reetz, Multisensory integrationmechanisms during aging, Front. Human Neurosci. 7 (2013) 863.

[4] P.D. Spear, Neural bases of visual deficits during aging, Vision Res. 33 (1993)2589–2609.

[5] X.Z. Liu, D. Yan, Ageing and hearing loss, J. Pathol. 211 (2007) 188–197.[6] S. Brodoehl, C. Klingner, K. Stieglitz, O.W. Witte, Age-related changes in the

somatosensory processing of tactile stimulation—an fMRI study, Behav Brain

Res. 238 (2013) 259–264.[7] M. Falkenstein, J. Yordanova, V. Kolev, Effects of aging on slowing of

motor-response generation, Int. J. Psychophysiol. 59 (2006) 22–29.[8] J.C. McArthur, E.A. Stocks, P. Hauer, D.R. Cornblath, J.W. Griffin, Epidermal

nerve fiber density: normative reference range and diagnostic efficiency,

Arch. Neurol. 55 (1998) 1513–1520.

[9] A. Peters, The effects of normal aging on myelin and nerve fibers: a review, J.Neurocytol. 31 (2002) 581–593.

[10] A.M. Hedman, N.E. van Haren, H.G. Schnack, R.S. Kahn, H.E. Hulshoff Pol,

Human brain changes across the life span: a review of 56 longitudinal

magnetic resonance imaging studies, Hum. Brain Mapp. 33 (2012) 1987–2002.[11] E. Macaluso, J. Driver, Multisensory spatial interactions: a window onto

functional integration in the human brain, Trends Neurosci. 28 (2005)

264–271.[12] G.L. Shulman, M. Corbetta, R.L. Buckner, M.E. Raichle, J.A. Fiez, F.M. Miezin,

et al., Top-down modulation of early sensory cortex, Cereb. Cortex 7 (1997)

193–206.[13] A.M. Peiffer, C.E. Hugenschmidt, J.A. Maldjian, R. Casanova, R. Srikanth, S.

Hayasaka, et al., Aging and the interaction of sensory cortical function and

structure, Hum Brain Mapp. 30 (2009) 228–240.

[14] M.F. Folstein, S.E. Folstein, P.R. McHugh, Mini-mental state. A practical

method for grading the cognitive state of patients for the clinician, J.Psychiatr. Res. 1975 (12) (1975) 189–198.

[15] K.J. Friston, J. Ashburner, C.D. Frith, J.B. Poline, J.D. Heather, R.S.J. Frackowiak,

Spatial registration and normalization of images, Hum. Brain Mapp. 3 (1995)

165–189.

[16] S.J. Kiebel, J. Ashburner, J.B. Poline, K.J. Friston, MRI and PET coregistration–across validation of statistical parametric mapping and automated imageregistration, Neuroimage 5 (1997) 271–279.

[17] A.C. Evans, D.L. Collins, S.R. Mills, E.D. Brown, R.L. Kelly, T.M. Peters, Nuclearscience symposium and medical imaging conference, 1993, San Francisco, CA,USA 1993, in: 1993 IEEE Conference Record, 3, 1993,pp. 1813–1817.

[18] S.B. Eickhoff, S. Heim, K. Zilles, K. Amunts, Testing anatomically specifiedhypotheses in functional imaging using cytoarchitectonic maps, Neuroimage

32 (2006) 570–582.

[19] S.B. Eickhoff, K.E. Stephan, H. Mohlberg, C. Grefkes, G.R. Fink, K. Amunts, et al.,A new SPM toolbox for combining probabilistic cytoarchitectonic maps and

functional imaging data, Neuroimage 25 (2005) 1325–1335.[20] M.A. Lindquist, T.D. Wager, Validity and power in hemodynamic response

modeling: a comparison study and a new approach, Hum Brain Mapp. 28

(2007) 764–784.

[21] P.J. Laurienti, J.H. Burdette, J.A. Maldjian, M.T. Wallace, Enhanced multisensory

integration in older adults, Neurobiol Aging. 27 (2006) 1155–1163.[22] J. Langan, S.J. Peltier, J. Bo, B.W. Fling, R.C. Welsh, R.D. Seidler, Functional

implications of age differences in motor system connectivity, Front Syst.

Neurosci. 4 (2010) 17.

[23] V.S. Mattay, F. Fera, A. Tessitore, A.R. Hariri, S. Das, J.H. Callicott, et al.,

Neurophysiological correlates of age-related changes in human motor

function, Neurology (2002) 630–635.

[24] D.J. Madden, W.L. Whiting, J.M. Provenzale, S.A. Huettel, Age-related changesin neural activity during visual target detection measured by fMRI, CerebCortex. 14 (2004) 143–155.

[25] M.O. Ernst, M.S. Banks, Humans integrate visual and haptic information in a

statistically optimal fashion, Nature 415 (2002) 429–433.

[26] E. Disbrow, T. Roberts, D. Poeppel, L. Krubitzer, Evidence for interhemispheric

processing of inputs from the hands in human S2 and PV, J. Neurophysiol. 85

(2001) 2236–2244.

[27] N.K. Logothetis, J. Pauls, M. Augath, T. Trinath, A. Oeltermann,Neurophysiological investigation of the basis of the fMRI signal, Nature 412(2001) 150–157.

[28] M. D’Esposito, E. Zarahn, G.K. Aguirre, B. Rypma, The effect of normal aging onthe coupling of neural activity to the bold hemodynamic response,Neuroimage 10 (1999) 6–14.

[29] R.S. Frackowiak, G.L. Lenzi, T. Jones, J.D. Heather, Quantitative measurement

of regional cerebral blood flow and oxygen metabolism in man using 15O andpositron emission tomography: theory, procedure, and normal values, J.

Comput. Assist. Tomogr. 4 (1980) 727–736.

[30] K.L. Leenders, D. Perani, A.A. Lammertsma, J.D. Heather, P. Buckingham, M.J.

Healy, et al., Cerebral blood flow, blood volume and oxygen utilization.

Normal values and effect of age, Brain 113 (1990) 27–47 (Pt 1).

[31] G. Marchal, P. Rioux, M.C. Petit-Taboue, G. Sette, J.M. Travere, C. Le Poec, et al.,Regional cerebral oxygen consumption, blood flow, and blood volume in

healthy human aging, Arch. Neurol. 49 (1992) 1013–1020.

[32] S. Facchini, S.M. Aglioti, Short term light deprivation increases tactile spatialacuity in humans, Neurology 60 (2003) 1998–1999.

[33] H. Leiderman, J.H. Mendelson, D. Wexler, P. Solomon, Sensory deprivation;

clinical aspects, AMA Arch. Intern. Med. 101 (1958) 389–396.

[34] J.P. Zubek, Sensory Deprivation: Fifteen Years of Research, in: John P. Zubek

(Ed.), Appleton-Century-Crofts, New York, 1969.

[35] C.E. Crabtree, J.F. Norman, Short-term visual deprivation, tactile acuity, and

haptic solid shape discrimination, PLoS One 9 (2014) e112828.

[36] M. Wong, E. Hackeman, C. Hurd, D. Goldreich, Short-term visual deprivation

does not enhance passive tactile spatial acuity, PLoS One 6 (2011) e25277.

[37] F.B. Colavita, Human sensory dominance, Percept Psychophys. 16 (1974)409–412.