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Behavioral/Systems/Cognitive
Systems Neuroplasticity in the Aging Brain: Recruiting
Additional Neural Resources for Successful Motor
Performance in Elderly Persons
Sofie Heuninckx, Nicole Wenderoth, and Stephan P. Swinnen
Motor Control Laboratory, Group Biomedical Sciences, K.U. Leuven, B-3001 Heverlee, Belgium
Functional imaging studies have shown that seniors exhibit more elaborate brain activation than younger controls while performing
motor tasks. Here, we investigated whether this age-related overactivation reflects compensation or dedifferentiation mechanisms.
“Compensation” refers to additional activation that counteracts age-related decline of brain function and supports successful perfor-
mance, whereas “dedifferentiation” reflects age-related difficulties in recruiting specialized neural mechanisms and is not relevant to
task performance. To test these predictions, performance on a complex interlimb coordination task was correlated with brain activation.
Findings revealed that coordination resulted in activation of classical motor coordination regions, but also higher-level sensorimotor
regions, and frontal regions in the elderly. Interestingly, a positive correlation between activation level in these latter regions and motor
performance was observed in the elderly. This performance enhancing additional recruitment is consistent with the compensation
hypothesis and characterizes neuroplasticity at the systems level in the aging brain.
Key words: aging; fMRI; motor control; interlimb coordination; cognition; compensation; dedifferentiation; neuroplasticity
Introduction
One of the most prominent challenges of current society is to
develop a better understanding of the aging process. As a result of
the demographic evolution in which elderly people occupy a
gradually increasing cohort of the general population, it is of high
socioeconomic importance to promote functional independence
and comfort of living in this group. This requires a profound
knowledge of the processes of neural aging. Recently, imaging
studies have shown that seniors exhibit stronger brain activation
than younger controls during the execution of various motor
tasks. Old subjects activate the same regions as their younger
counterparts, but to a larger extent, and/or they activate addi-
tional regions that are not observed in the young subjects (Ca-
lautti et al., 2001; Mattay et al., 2002; Ward and Frackowiak, 2003;
Heuninckx et al., 2005). Although this “overactivation” in the
aging brain is well documented within the motor system, the
underlying neural mechanisms are still unclear. Based on previ-
ous results in cognitive aging studies, we put forward two major
hypotheses. On the one hand, the compensation hypothesis pre-
dicts that age-related increases in brain activation, as well as the
recruitment of additional areas, compensate for various neural/
behavioral deficits (e.g., neurodegeneration, attentional prob-
lems, reduction in sensory function, etc.) (Madden et al., 1999;
Reuter-Lorenz et al., 2000; Cabeza, 2002; Cabeza et al., 2002;
Grady, 2002; Reuter-Lorenz and Lustig, 2005). On the other
hand, the dedifferentiation hypothesis assumes that age-related
changes in functional activation reflect a generalized nonfunc-
tional spread of activity attributable to deficits in neurotransmis-
sion, which in turn causes a decrease in the signal-to-noise ratio
in neural firing and a loss of neural specialization (Li and Linden-
berger, 1999).
Here, we aimed to unravel whether the overactivation in the
motor networks of the elderly results from compensation or de-
differentiation on brain level. Functional magnetic imaging was
applied to 24 older adults and 11 young controls to register brain
activity during the performance of rhythmical hand–foot coor-
dination tasks, whereby both limbs moved either in the same
(isodirectional) or in the opposite (nonisodirectional) direction.
Previous behavioral work showed convincingly that the non-
isodirectional pattern is more difficult and is produced with
lower accuracy and stability than the isodirectional pattern
(Baldissera et al., 1982, 1991; Kelso and Jeka, 1992; Carson et al.,
1995; Swinnen et al., 1995; Serrien et al., 2000).
Subsequently, activation in dedicated brain regions was cor-
related with motor performance in the elderly. According to the
compensation hypothesis, the underlying rationale was that the
overactivation would be larger in good than in poor motor per-
formers, with the effect being more pronounced in more (non-
isodirectional) than less (isodirectional) demanding coordina-
tion tasks. Conversely, the dedifferentiation hypothesis assumed
overactivation to be larger in poor than in successful motor per-
formers because of nonfunctional neural irradiation. Thus, pos-
itive correlations between brain activation and motor perfor-
Received Feb. 15, 2007; revised Oct. 4, 2007; accepted Nov. 9, 2007.
This work was supported by a grant from the Research Council of K.U. Leuven, Belgium (Contract OT/07/73) and
the Research Program of the Research Foundation–Flanders (FWO) (G.0460.04 and G.0105.00). S.H. was supported
by a PhD fellowship from FWO.
Correspondence should be addressed to Dr. Stephan P. Swinnen, Laboratory of Motor Control, Division of Motor
Control and Neuroplasticity, Department of Biomedical Kinesiology, Group Biomedical Sciences, K.U. Leuven, Ter-
vuursevest 101, B-3001 Heverlee, Belgium. E-mail: Stephan.Swinnen@faber.kuleuven.be.
DOI:10.1523/JNEUROSCI.3300-07.2008
Copyright © 2008 Society for Neuroscience 0270-6474/08/280091-09$15.00/0
The Journal of Neuroscience, January 2, 2008 •28(1):91–99 • 91
mance were considered to reflect compensation, and negative
correlations were considered to reflect dedifferentiation.
Materials and Methods
Participants
Twelve young adults (mean age, 22.4 years; range, 20 –25 years; 6
women and 6 men) and 26 older adults (mean age, 65.7 years; range,
62–72 years; 12 women and 14 men) participated in the study. The
older subjects were all community-dwelling individuals. All partici-
pants were right-handed, as assessed by the Edinburgh Handedness
Inventory (Oldfield, 1971). None reported a history of neurological
disease or were taking psychoactive or vasoactive medication. General
cognitive functions were assessed using the Mini-Mental State Exam-
ination (Folstein et al., 1975). All participants scored within normal
limits (score ⱖ26). Participants were informed about the experimen-
tal procedures and provided written informed consent. The study was
approved by the local ethics Committee of Biomedical Research at
Katholieke Universiteit Leuven and was performed in accordance
with the ethical standards of the 1964 Declaration of Helsinki. Imag-
ing data of one young and two older subjects contained artifacts and
were excluded from all analyses.
Experimental design
Task
During scanning, the participants performed three different condi-
tions: two movement conditions requiring cyclical coordination of
the right hand and right foot according to either the isodirectional
(ISODIR) or the nonisodirectional (NONISODIR) mode, and one
rest (REST) condition in which no movements were performed. Dur-
ing ISODIR coordination, both limb segments were moved in the
same direction (i.e., hand flexion together with foot flexion) (Fig.
1A). During NONISODIR coordination, segments were moved in
opposite directions (i.e., hand flexion combined with foot extension)
(Fig. 1B). Additionally, the participants also performed cyclical
flexion-extension movements of the right wrist and right ankle sepa-
rately. However, the latter movement conditions will not be further
addressed here.
During scanning, participants lay supine in the scanner. The lower
legs were supported by a cushion to ensure free ankle rotation. The
right arm was extended along the trunk, and the distal part of the arm
was supported to enable free movements of the wrist. A bite-bar was
used to minimize head motion. In this position, subjects looked at a
display via a mirror (at a distance of 36 cm from their eyes) onto
which a visual template, displaying the task to be performed, was
provided by means of a Barco (Kortrijk, Belgium) 6400i liquid crystal
display projector (1024 ⫻768 pixels, 60 Hz). The wrist and foot were
positioned in a nonferromagnetic wrist– hand and ankle–foot ortho-
sis, respectively. Movements were restricted to the sagittal plane. The
frictionless axis of the orthosis was aligned with the anatomical axis of
the joint such that movements were not hindered. Angular displace-
ments of the joints were registered by means of high-precision shaft
encoders (4096 pulses per revolution; sampled at 100 Hz) fixed to the
movement axis of the orthosis. The nonferromagnetic kinematic reg-
istration device enabled us to register movements on-line during
brain scanning. Movements were limited to the wrist and ankle,
whereas the other segments were kept still. Subjects were trained to
look at a fixation cross, displayed in front of them at all times.
All conditions were paced by an electronic metronome (DTM-12;
KORG, Tokyo, Japan), whereby a full movement cycle was completed on
every beat (one beat for peak flexion and one for peak extension). The
older adults performed five scanning runs at a movement frequency of 1
Hz, whereas the younger adults performed 10 runs, five at a movement
frequency of 1 Hz and five at a movement frequency of 1.5 Hz. For
purposes of equating difficulty level, however, we compared the older
subjects’ performance at 1 Hz to that of the younger subjects’ perfor-
mance at 1.5 Hz. Indeed, previous work demonstrated that these cycling
frequencies represented a comparable ratio to the maximal frequency at
which these patterns could be performed successfully by both groups
(Heuninckx et al., 2004). Between the different scanning runs, rest peri-
ods of 3 min were provided.
Before scanning took place, a 45 min practice session was provided in
a dummy scanner to ensure correct performance. Subjects were trained
to avoid eye movements and to look at a fixation cross.
Scanning procedure
The magnetic resonance (MR) images were acquired in a 3 T Intera MR
scanner (Philips, Best, The Netherlands), using a six-element SENSE
head coil (MRI Devices, Waukesha, WI). Functional time series con-
sisted of 105 whole-brain gradient-echo echoplanar images (EPIs) [rep-
etition time (TR), 3000 ms; echo time (TE), 33 ms; field of view, 230 mm;
matrix, 112 ⫻112; slice thickness, 4.0 mm; interslice gap, 0.4 mm; 34
sagittal slices; SENSE factor, 2]. Each time series contained three blocks
of the five conditions. Each condition lasted 21 s (corresponding to seven
whole-brain images) and was triggered by a visual template displaying
the task to be performed. The different task conditions were randomized
across subjects and runs. Each scanning session ended with the acquisi-
tion of a three-dimensional SENSE high-resolution, T1-weighted image
(TR, 9.68 ms; TE, 4.6 ms; inversion time, 1100 ms; field of view, 250 mm;
matrix, 256 ⫻256; slice thickness, 1.2 mm; 182 slices; SENSE factor, 2)
for anatomical detail.
Figure 1. Cyclical ipsilateral coordination of the hand and foot according to the isodirectional mode (A; both limb segments are moved in the same direction) and the nonisodirectional mode (B;
both limb segments are moved in opposite directions).
92 •J. Neurosci., January 2, 2008 •28(1):91–99 Heuninckx et al. •Aging and Compensatory Recruitment
Data analyses
Kinematic analyses
The coordination between the limb segments was assessed by means of a
relative phase measure, that is the subtraction of the phase angles of each
limb according to the following formula: ⌽⫽
w
⫺
f
⫽tan
⫺1
[(dX
w
/
dt)/X
w
]⫺tan
⫺1
[(dX
f
/dt)/X
f
], where wand fare wrist and foot, respec-
tively;
w
is the phase of the wrist movement at each sample; X
w
is the
position of the wrist after rescaling to the interval [⫺1,1] for each cycle of
oscillation; and dX
w
/dt is the normalized instantaneous velocity. Abso-
lute deviations from the target relative phase (i.e., 0 and 180° for ISODIR
and NONISODIR coordination, respectively) were calculated to obtain a
measure of relative phase accuracy (AE⌽, phase error). The SD of relative
phase (SD⌽) was used as an estimate of movement pattern stability.
For the statistical analysis, the aforementioned parameters were deter-
mined for each condition and subsequently averaged across repetitions
and runs. The statistical analyses consisted of repeated-measures
ANOVA with the between-factor group (young, old) and the within-
factor mode (ISODIR, NONISODIR). The
␣
level of significance was set
to
␣
⫽0.05.
Imaging analysis
Imaging data were analyzed with Statistical Parametric Mapping 2
(SPM2) (Wellcome Department of Imaging Neuroscience, London, UK)
implemented in MatLab 6.5 (MathWorks, Natick, MA). For each subject,
all EPI volumes were realigned to the first volume of the first time series,
and a mean image of the realigned volumes was created. This mean image
was smoothed with a Gaussian kernel of 6 mm full-width at half-
maximum (FWHM) and coregistered to the anatomical T1-weighted
image. To normalize the anatomical image as well as the EPIs to a stan-
dard reference system (Talairach and Tournoux, 1988), the following
procedure was applied. First, the anatomical image as well as a represen-
tative template image [Montreal Neurological Institute (MNI)] was seg-
mented into gray matter, white matter, and CSFs. Then, the anatomical
gray matter image was smoothed (6 mm FWHM) and normalized to the
gray matter of the MNI brain. Subsequently, the derived normalization
parameters were applied to the EPIs, which were subsampled to a voxel
size of 2 ⫻2⫻2 mm and smoothed with a Gaussian kernel of 10 mm
FWHM.
All statistical analyses were performed in the context of the general
linear model (Friston et al., 1995a,b). Each condition was modeled using
a delayed boxcar function convolved with the SPM2 hemodynamic re-
sponse function. An appropriate high-pass filter was applied to remove
low-frequency drifts. Additionally, movement parameters derived from
realignment were added as covariates of no interest to correct for con-
founding effects induced by head movement. Contrasts of interest were
first estimated for each subject individually (averaging activation across
runs) and then subjected to a second-level random-effects analysis.
Between-group conjunction: regions similarly activated in the young and
the elderly. We investigated which regions were similarly activated in both
age groups during ISODIR and NONISODIR coordination, respectively.
First, within-group activations were calculated by contrasting each
movement condition with REST, and subsequently, the following
conjunctions were calculated: (ISODIR ⫺REST)
old
艚(ISODIR ⫺
REST)
young
and (NONISODIR ⫺REST)
old
艚(NONISODIR ⫺REST)
young
for ISODIR and NONISODIR coordination, respectively. Conjunctions
were determined in accordance with the method suggested by Nichols et al.
(2005). A positive conjunction test implies that a given region is significantly
activated by each age group. Additionally, our further analysis revealed that
none of these commonly activated areas differed significantly between
groups, indicating that the regions exhibited a
similar activation level in the young and in the
elderly. A false discovery rate (FDR) correction
was applied, ensuring an overall p⬍0.05 (i.e., t⬎
4.00). Only clusters with a size of ⱖ20 voxels will
be reported.
Between-group analysis: determining differen-
tially activated regions. To determine which re-
gions were differentially activated in old versus
young subjects for ISODIR and NONISODIR
coordination, between-group comparisons
were made by means of independent ttests. The following contrasts were
calculated: (ISODIR ⫺REST)
old
versus (ISODIR ⫺REST)
young
and
(NONISODIR ⫺REST)
old
versus (NONISODIR ⫺REST)
young
. FDR
correction was applied, ensuring an overall p⬍0.05 (i.e., t⬎4.00). Only
clusters with a size of ⱖ20 voxels will be reported.
Within-group analyses: correlation between motor performance and
brain activation with respect to similarly and differentially activated re-
gions. Within both age groups, multiple regression analyses were per-
formed to investigate which brain regions exhibited a significant corre-
lation with performance on the coordination task across subjects. For the
ISODIR ⫺REST contrast as well as for the NONISODIR ⫺REST con-
trast, separate second-level models were defined, containing the perfor-
mance level for each individual as well as age as a covariate of no interest.
Coordination performance was quantified by means of (1) the absolute
phase error (coordination accuracy) and (2) the SD of relative phase
(coordination stability). To simplify interpretation, the relationship be-
tween error scores and performance was inverted (1/AE and 1/SD, re-
spectively) such that high scores were indicative of good performance. In
a first step, we identified all regions exhibiting a significant positive or
negative correlation with performance ( p⬍0.001; t⬎2.52; uncorrected
for multiple comparisons). Within this performance-dependent net-
work, we applied small-volume corrections (FDR, p⬍0.05, t⬎2.86)
within the clusters that were either (1) similarly activated by the young
and elderly (i.e., clusters of the between-group conjunction reaching
significance on cluster level with p⬍0.05) or (2) differentially activated
in the young and elderly (i.e., clusters of the between-group analysis that
were more strongly activated in the elderly than in the young, and vice
versa, reaching significance on cluster level with p⬍0.05).
Results
Kinematic data
Separate group (young, elderly) ⫻coordination mode (ISODIR,
NONISODIR) ANOVAs with repeated measures on the last fac-
tor were conducted on relative phase error and SD of relative
phase, respectively. Both analyses revealed significant main ef-
fects of coordination mode (AE: F
(1,33)
⫽16.5, p⬍0.0005; SD:
F
(1,33)
⫽31.5, p⬍0.0001) and group (AE: F
(1,33)
⫽5.7, p⬍0.05;
SD: F
(1,33)
⫽26.4, p⬍0.0001). In accordance with the literature,
ISODIR coordination was performed with higher accuracy and
stability than NONISODIR coordination (Table 1). Although
different cycling frequencies were imposed to equate task diffi-
culty level across both groups, coordination performance of older
participants was slightly less accurate and stable than that of the
younger subjects (Table 1).
The range of AE and SD scores in the younger subjects was
fairly small with all subjects having comparable performance lev-
els (Table 1). In the elderly group, however, the range was much
larger, with some elderly performing poorly and others perform-
ing as well as the younger controls (Table 1).
fMRI data
Between-group conjunction: regions similarly activated in the
young and elderly
Brain regions that were activated by both age groups to a similar
extent were identified for the ISODIR and NONISODIR coordi-
Table 1. Kinematic results
Old Young
ISODIR NONISODIR ISODIR NONISODIR
AE mean 22.85° 26.18° 18.7° 22.9°
Range (14.94 –32.28°) (16.71– 46.40°) (15.88 –22.96°) (18.2–28.34°)
SD mean 18.5° 22.9° 14.5° 18.4°
Range (15.19 –29.83°) (16.09 – 42.14°) (13.21–15.58°) (15.76–21.47°)
Heuninckx et al. •Aging and Compensatory Recruitment J. Neurosci., January 2, 2008 •28(1):91–99 •93
nation modes, respectively. During the
ISODIR coordination mode, both groups
activated a typical coordination network,
including the contralateral precentral and
postcentral gyri and the paracentral lobule,
corresponding to the primary sensorimo-
tor cortex (SM1), the left and right supple-
mentary motor area (SMA), the left cingu-
late motor area (CMA), and the left and
right lateral sulcus/posterior insula, corre-
sponding to the secondary somatosensory
area (S2). Significant subcortical activation
was present in the contralateral thalamus,
putamen, and pallidum and in the ipsilat-
eral anterior cerebellum (for coordinates
and tvalues, see supplemental Table 1*,
available at www.jneurosci.org as supple-
mental material).
For the NONISODIR coordination pat-
tern, similar results were observed (i.e.,
brain regions similarly activated in both
age groups were the left SM1, CMA, and
SMA; the left and right S2; and subcorti-
cally, the left thalamus and pallidum and
the right anterior cerebellum) (Fig. 2; for
coordinates and tvalues, see supplemental
Table 1*, available at www.jneurosci.org as
supplemental material).
Within-group analyses: correlation between
motor performance and brain activation
with respect to the similarly activated
regions
In this section, areas are reported that ex-
hibit a significant correlation with perfor-
mance and are similarly activated in both
age groups. Motor performance was quan-
tified by means of the absolute phase error
(coordination accuracy) and the SD of relative phase (coordina-
tion stability), respectively. However, because relative phase error
and SD were highly correlated in the elderly (Pearson’s r⫽0.89
and r⫽0.86 for ISODIR and NONISODIR, respectively) and
appreciable in the younger adults (Pearson’s r⫽0.50 and r⫽
0.62 for ISODIR and NONISODIR, respectively), it is not sur-
prising that very similar results were obtained for both measures.
Therefore, we decided to only report the results using the phase
error scores as regressor.
In the elderly, a significant positive correlation between brain
activation and coordination performance on the relatively easy
ISODIR coordination task was observed in the left precentral and
postcentral gyri (SM1) ( p⬍0.05, cluster-wise FDR correction).
Additionally, there was a trend ( p⬍0.001, uncorrected) toward
a positive correlation in the right anterior cerebellar hemisphere
(Table 2). This suggests that the more the ISODIR coordination
task was performed successfully in elderly subjects, the higher the
levels of brain activation. In none of the similarly activated re-
gions was a negative relationship between brain activation and
ISODIR performance obtained.
In the young subjects, no significant relationship between
level of brain activation and performance on the ISODIR coordi-
nation task was observed.
In the elderly, a significant positive correlation between brain
activation and coordination performance on the more demand-
ing NONISODIR coordination task was observed in the left su-
perior postcentral gyrus/sulcus (Fig. 2 A) and inferior postcentral
gyrus (Fig. 2B). Additionally, positive correlations were also ob-
tained in the right SMA (Fig. 2C) and in the left CMA ( p⬍0.05,
cluster-wise FDR correction) (Fig. 2 D; see Table 2 for summary).
In Figure 2, these areas are indicated by an arrow. The graphics
display each subject’s blood oxygenation level-dependent
(BOLD) response for the within-cluster peak activation, as a
function of the inverse of phase error (1/AE), with the younger
subjects in blue and the older subjects in red. It can be inferred
that, on average, the elderly and young subjects exhibited similar
BOLD responses. However, the range of BOLD responses was
smaller in the young than elderly group. More specifically, the
well performing elderly showed equal or higher BOLD responses
than the young controls, whereas the poor performing elderly
exhibited lower BOLD responses than the young.
In the other brain regions, similarly activated in both groups
(i.e., the left central sulcus/precentral gyrus, paracentral lobule,
S2, thalamus, and pallidum and the right anterior cerebellum),
no significant relationships between level of brain activation and
performance on the NONISODIR coordination task were ob-
served in the elderly group ( p⬎0.001, uncorrected). In none of
the similarly activated regions were significant negative relation-
ships between brain activation and NONISODIR performance
obtained.
Figure 2. Statistical parametric maps representing brain regions that were similarly activated by both age groups, resulting
from the following conjunction analysis: (NONISODIR ⫺rest)
old
艚(NONISODIR ⫺rest)
young.
Significant voxels ( p⬍0.05;
corrected for multiple comparisons) are indicated in the red spectrum, and the height threshold is t⫽4.00. L, Left hemisphere;
R, right hemisphere. White arrows indicate brain regions that exhibit a significant correlation between brain activity level and
coordination performance, as identified by a whole-brain multiple regression analysis followed by a small-volume correction
with the similarly activated clusters as shown in the statistical parametric maps ( p⬍0.05, FDR corrected within the search
volume; for details, see Materials and Methods). The graphics display each subject’s BOLD response with respect to the within-
cluster peak activation as a function of the inverse of phase error (1/AE), with the younger subjects in blue and the older subjects
in red.
94 •J. Neurosci., January 2, 2008 •28(1):91–99 Heuninckx et al. •Aging and Compensatory Recruitment
In the young subjects, no significant relationship between
level of brain activation and performance on the NONISODIR
coordination task was observed.
Between-group analysis: determining differentially
activated regions
Between-group comparisons were made by means of indepen-
dent ttests for the ISODIR and NONISODIR coordination
mode, respectively. During the ISODIR coordination mode, the
elderly group exhibited significantly higher activation than the
young group in the left anterior insular cortex (for coordinates
and tvalues, see supplemental Table 2*, available at www.
jneurosci.org as supplemental material).
No region was significantly more activated in the younger
than older group.
During the NONISODIR coordination mode, the pattern of
activation in the old group was more widespread than in the
young group (Fig. 3; for coordinates and tvalues, see supplemen-
tal Table 2*, available at www.jneurosci.org as supplemental ma-
terial). The old group exhibited significantly higher activation in
the left anterior insular cortex, inferior frontal gyrus pars oper-
cularis (IFGPO), and inferior frontal gyrus pars triangularis
(IFGPT). In addition, larger activation for the old group was
observed in the left middle frontal gyrus, corresponding to the
dorsolateral prefrontal cortex (DLPFC), and in the left superior
frontal sulcus and gyrus, corresponding to the anterior dorsal
premotor area (pre-PMd). Larger activation for the old group
was also observed in the left superior temporal gyrus, angular
gyrus, superior parietal gyrus, fusiform gyrus, and inferior post-
central sulcus, corresponding to S2, and in the left and right
lingual gyrus. In the right hemisphere, the older group demon-
strated significantly larger activation in the paracentral lobule
and parahippocampal gyrus. Finally, the old group exhibited sig-
nificantly higher activation than the young group in the left and
right anterior cerebellum and in the right posterior cerebellum.
No region was significantly more activated in the younger
than in the older group.
For a detailed description of differences in brain activation
during ISODIR versus NONISODIR coordination, in young ver-
sus old subjects, see Heuninckx et al. (2005).
Within-group analyses: correlations between motor performance
and brain activation with respect to differentially activated regions
In this section, areas are reported that exhibit a significant corre-
lation with performance and are significantly overactivated in the
elderly.
For the ISODIR coordination mode, no significant relation-
ships between activation and coordination accuracy were identi-
fied. In contrast, for the more complex
NONISODIR coordination mode, signifi-
cant positive relationships were observed
in the left IFGPO and IFGPT (Fig. 3B),
anterior insular cortex (Fig. 3C), superior
parietal gyrus (Fig. 3F), pre-PMd (Fig.
3E), and DLPFC (Fig. 3A) and in the right
posterior (Fig. 3H) and left anterior (Fig.
3D) cerebellar hemisphere ( p⬍0.05,
cluster-wise FDR correction). Addition-
ally, there was a trend ( p⬍0.001, uncor-
rected) toward a positive correlation in the
left superior temporal gyrus (Fig. 3G; see
Table 3 for summary). In Figure 3, the
brain regions that were additionally acti-
vated by the elderly subjects while showing
a positive relationship between activation
and coordination performance are indicated by an arrow. The
individual BOLD responses with respect to the within-cluster
peak activation in the old (red) and young (blue) subjects are
displayed as a function of the inverse of phase error (1/AE). It can
be observed that the elderly performing poorly exhibited a similar
BOLD response as the young controls, whereas the more success-
ful elderly clearly exhibited higher levels of brain activation.
In the other differentially activated regions (i.e., the left S2,
fusiform gyrus, angular gyrus, lingual gyrus, posterior cerebel-
lum, right parahippocampal gyrus, and paracentral lobule), no
significant relationships were identified. In none of the differen-
tially activated regions were negative relationships observed.
The scatter plots in Figures 2 and 3 show one older adult
whose performance was much worse than the remaining ones
during the NONISODIR coordination task. Additional analyses
with exclusion of this subject revealed highly similar results, sug-
gesting that the present correlations are robust (see supplemental
Tables 3*, 4*, available at www.jneurosci.org as supplemental
material).
Discussion
The aim of the present study was to investigate whether age-
related overactivation during motor performance reflects com-
pensation or dedifferentiation mechanisms. According to the
compensation hypothesis, overactivation counteracts age-related
decline of brain function and supports performance (Madden et
al., 1999; Reuter-Lorenz et al., 2000; Cabeza, 2002; Cabeza et al.,
2002; Grady, 2002; Reuter-Lorenz and Lustig, 2005). According
to the dedifferentiation hypothesis, overactivation may be non-
functional, reflecting age-related difficulties in recruiting special-
ized neural mechanisms (Li and Lindenberger, 1999), and is
therefore either irrelevant for the task or associated with bad
performance. To contrast predictions from both hypotheses, per-
formance on coordination tasks with different levels of complex-
ity was correlated with brain activation in older subjects. This
approach was applied to brain regions that were (1) similarly
activated in both age groups or (2) more activated in the elderly
compared with the young group (e.g., compensatory
recruitment).
The kinematic data revealed that coordination accuracy var-
ied substantially in the elderly, with some performing poorly and
others performing as well as the younger controls.
Our main finding is that the elderly exhibited a significant corre-
lation between activation in dedicated brain regions and perfor-
mance, such that good performers exhibited higher brain activation
levels than poor performers. This effect was more prevalent during
Table 2. Brain regions that are similarly activated in both age groups and in which performance and brain
activation is positively correlated in the old group during ISODIR and NONISODIR coordination
Region activated Side xyztvalue
ISODIR coordination
Precentral gyrus (M1 hand area) L ⫺44 ⫺12 60 3.90
Postcentral gyrus (S1 hand area) L ⫺46 ⫺30 60 3.92
Cerebellar hemisphere (V) R 24 ⫺54 ⫺18 2.84
NONISODIR coordination
SMA M/R 8 ⫺16 58 3.79
Inferior postcentral gyrus L ⫺38 ⫺26 46 3.74
Cingulate cortex (CMA) Ml ⫺44 ⫺12 60 3.90
Postcentral gyrus/sulcus L ⫺46 ⫺30 60 3.92
The tvalues and localizations (MNI coordinates) of activation peaks showing a significant (p⬍0.05; cluster-wise FDR correction for multiple comparisons)
positive correlation between level of brain activity and coordination performance are shown. Regions reaching significance only at an uncorrected level (p⬍
0.001) are in italics. L, Left hemisphere; R, right hemisphere; M, medial; M1, primary motor cortex; S1, primary sensory cortex.
Heuninckx et al. •Aging and Compensatory Recruitment J. Neurosci., January 2, 2008 •28(1):91–99 •95
the more demanding nonisodirectional than
during the easier isodirectional coordination
task. Accordingly, our results provided
strong support for the compensation hy-
pothesis. Interestingly, this positive associa-
tion between performance and brain activity
was not evident across the entire brain but
rather in some specific, well defined regions
that were either recruited by both age groups
or additionally recruited by the elderly com-
pared with the young group.
Regions similarly activated by both age
groups and exhibiting a positive
association between brain activity level
and motor performance
In the elderly, significant positive correla-
tions were observed between motor perfor-
mance and activation in the contralateral
SM1 and ipsilateral anterior cerebellum
during the ISODIR coordination mode
and in the contralateral SM1, SMA, and
CMA during the more difficult NON-
ISODIR coordination mode. These regions
were activated by both age groups and rep-
resent typical motor regions that are usu-
ally activated by ipsilateral hand–foot
movements (Ehrsson et al., 2000; Debaere
et al., 2001; Heuninckx et al., 2005). In-
creased activations of SM1, SMA, CMA,
and cerebellum have repeatedly been ob-
served in multilimb coordination tasks
(Debaere et al., 2004; for review, see Wen-
deroth et al., 2004b). Especially SMA and
cerebellar activity are hypothesized to re-
flect increasing demands on motor timing
(Ivry, 1997; Macar et al., 1999; Mima et al.,
1999; Habas et al., 2004; Wenderoth et al.,
2004b) and/or sensory processing (Jueptner
et al., 1997; Bushara et al., 2001; Thickbroom
et al., 2003; Debaere et al., 2004). Therefore,
the observed positive correlations between
coordination performance and brain activity
in these motor regions may reflect a success-
ful compensatory response to increased
functional demands by the high-performing
elderly.
Overactivated regions in the elderly,
exhibiting a positive association between brain activity level
and motor performance
Interestingly, besides typical motor regions, more remote regions
were also additionally recruited in the elderly and correlated pos-
itively with performance on the coordination task.
First, positive correlations were observed in the contralateral
superior parietal cortex, contralateral posterior cerebellum, and
ipsilateral anterior cerebellum, which were previously shown to
be involved in higher-order sensorimotor coordination during
more demanding tasks (Debaere et al., 2004; Wenderoth et al.,
2004b). Whereas the cerebellum is a typical timing and coordi-
nation organ (see above), the superior parietal cortex is strongly
involved in sensorimotor integration and spatial aspects of move-
ment planning (Wenderoth et al., 2004a,b, 2005, 2006). Both
spatial and temporal integration are critical features of successful
interlimb coordination.
Second, we also identified several nonmotor regions that were
additionally recruited by the elderly as well as related to successful
motor performance. We identified relatively large clusters sur-
rounding the left frontal operculum, with peak activation in the
anterior insular cortex, IFGPO, IFGPT, and superior temporal
gyrus. The IFGPO, anterior insula and superior temporal gyrus
appear to be involved in higher-order auditory processing (Platel
et al., 1997; Bamiou et al., 2003; Thaut, 2003) and particularly in
motor synchronization to an auditory rhythm (Thaut, 2003;
Lewis et al., 2004). This suggests that older subjects made more
pervasive use of external information sources for controlling
their limb movements by means of the metronome-pacing signal,
Figure 3. Statistical parametric maps representing significantly larger activation in the old compared with the young group
during the NONISODIR coordination mode, resulting from the following contrast: (NONISODIR ⫺rest)
old
versus (NONISODIR ⫺
rest)
young
. Significant voxels ( p⬍0.05; corrected for multiple comparisons) are indicated in the red spectrum, and the height
threshold is t⫽4.00. L, Left hemisphere; R, right hemisphere. White arrows indicate brain regions that exhibit a significant
correlation between brain activity level and coordination performance, as identified by a whole-brain multiple regression anal-
ysis followed by a small-volume correction with the clusters, overactivated by the elderly as shown in the statistical parametric
maps ( p⬍0.05, FDR corrected within the search volume; for details, see Materials and Methods). The graphics display each
subject’s BOLD response with respect to the within-cluster peak activation as a function of the inverse of the phase error (1/AE),
with the younger subjects in blue and the older subjects in red.
96 •J. Neurosci., January 2, 2008 •28(1):91–99 Heuninckx et al. •Aging and Compensatory Recruitment
which resulted in more accurate coordination performance. Fur-
thermore, the IFGPO and IFGPT are involved in interfacing ex-
ternal information about biological motion with internal repre-
sentations of limb actions, as observed during movement
observation, imitation, or imagery (Grezes et al., 1998; Iacoboni
et al., 1999; Binkofski et al., 2000; Molnar-Szakacs et al., 2005).
The elevated activations in IFGPO and IFGPT therefore tenta-
tively suggest that the successful elderly used some form of visu-
alization strategy to control their movements. Together, the
higher activations of these regions appear to reflect higher-level
processing and integration of external and internal information
sources to successfully guide motor coordination.
Finally, positive correlations between level of coordination
performance and activation were observed in two regions in the
contralateral frontal lobe (i.e., the pre-PMd and DLPFC). There
is increasing agreement that the pre-PMd is more closely related
to cognitive than to motor processes. More specifically, the pre-
PMd is highly interconnected with the PFC (Lu et al., 1994; Geyer
et al., 2000) and becomes activated with increasing cognitive de-
mands of a motor task (for review, see Picard and Strick, 2001).
The DLPFC receives visual, somatosensory, and auditory infor-
mation from the occipital, temporal, and parietal cortices
(Goldman-Rakic and Schwartz, 1982; Barbas and Pandya, 1989;
Seltzer and Pandya, 1989; Pandya and Yeterian, 1990; Petrides
and Pandya, 1999) and has preferential connections with the mo-
tor system structures (Miller and Cohen, 2001). Accordingly, the
DLPFC is hypothesized to play a central role in the cognitive
control of motor behavior (Miller and Cohen, 2001). Overall, the
observed positive correlations between coordination accuracy
and activation in the pre-PMd and DLPFC suggest that the older
subjects relied on increased cognitive monitoring that had a ben-
eficial impact on complex coordination performance, suggesting
that the additional neural recruitment was compensatory.
The present findings are in partial agreement with several
“cognitive aging” studies in which activation levels in frontal re-
gions were shown to correlate positively with overall perfor-
mance in the elderly (Reuter-Lorenz et al., 2000; Grady et al.,
2003; Scarmeas et al., 2003; Madden et al., 2004; Rosano et al.,
2005). Similarly, when groups of good versus bad performing
elderly were compared, good performers exhibited more brain
activation than bad performers (Cabeza et al., 2002; Rosen et al.,
2002). In the present motor coordination study, the compensa-
tory recruitment extended far beyond the prefrontal regions and
involved a more extensive network, suggesting that such tasks are
very instrumental to studying age-related alterations in complex
brain function.
Summary and conclusions
Coordination in the elderly was associ-
ated with profound activations in (1)
classical motor control regions, (2)
higher-level sensorimotor regions re-
flecting increased reliance on sensory in-
formation processing, and (3) frontal re-
gions reflecting increased cognitive
control and performance monitoring.
Importantly, the majority of these re-
gions exhibited a positive correlation be-
tween brain activation level and perfor-
mance in the elderly, such that increased
recruitment in these regions was associ-
ated with higher motor coordination ac-
curacy. This enabled some elderly to
reach motor performance levels comparable to those obtained
in the younger controls, suggesting that the additional recruit-
ment is meaningful for preserving motor performance in the
elderly (i.e., it is primarily compensatory in nature). However,
compensatory recruitment might have a hidden cost. To the
extent that older brains engage more neural circuitry at the
same or lower levels of task demand than do younger adults,
seniors may rely more on “cognitive reserve” (Scarmeas et al.,
2003) and are thus more likely to reach a limit on the available
resources that can be brought to bear on task performance
(DiGirolamo et al., 2001; Reuter-Lorenz and Lustig, 2005;
Reuter-Lorenz and Mikels, 2006; P. A. Reuter-Lorenz and
K. A. Cappell, unpublished observation). This may perhaps
explain why poorly performing older adults showed BOLD
responses similar to those of the young participants, whereas
the successful elderly exhibited more elaborate activation than
young adults in some brain regions.
In contrast to recent cognitive aging studies in which com-
pensatory recruitment was established in the prefrontal re-
gions, the present study showed activation across a more elab-
orate network that was dedicated to increasing cognitive
control and enhanced processing of sensory information for
motor performance, indicative of systems-level neuroplastic-
ity at higher age. This penetration of cognition into motor
performance appears to be a marker of successful aging, and it
paves the way for rehabilitation interventions that promote
the exploitation of cognitive processing mechanisms for ac-
tion control.
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