Cortical control of unilateral simple movement in healthy aging

Neurobiology of Aging 32 (2011) 524–538

Cortical control of unilateral simple movement in healthy aging Alberto Inuggi, Ninfa Amato, Giuseppe Magnani, Javier J. González-Rosa, Raffaella Chieffo, Giancarlo Comi, Letizia Leocani ∗ Dept. of Clinical Neurophysiology, Neurology, Neurorehabilitation, Experimental Neurology Institute, IRCCS San Raffaele, Via Olgettina 60, 20132 Milan, Italy Received 30 August 2008; received in revised form 16 February 2009; accepted 19 February 2009 Available online 26 March 2009

Abstract Normal aging is associated with several modifications in the cerebral motor system that reflect into an increased and more bilateral activation in elderly subjects. Twelve young and nine elderly healthy right-handed subjects performed a self-initiated brisk right thumb extension while recorded with 32-channel EEG. The aging effect over cortical generators of bereithshaftspotential, reconstructed using cortical current density (CCD) method and a realistic volume conductor, was evaluated in five different periods and in both mesial and lateral motor-related areas. Over-activation occurred mainly at movement initiation in those areas related to simple movements (caudal mesial areas and both sensorimotor cortices) and in contralateral sensorimotor cortex during the post-movement phase. In those areas, the elderly group recruited a larger neuronal population than the young one in the presence of a significantly longer movement. This more likely suggests their reduced selectivity in activating the motor cortex than a compensatory mechanism to produce an optimum performance. Movement duration resulted negatively correlated with pre-SMA activity, suggesting its involvement in movement termination. © 2009 Elsevier Inc. All rights reserved. Keywords: Aging effect; Bereithshaftspotentials; Source reconstruction; EEG

1. Introduction Normal aging is associated with several modifications in the nervous motor system. They consist of morphological changes such as reduction in neuron size and spine density (Anderson and Rutledge, 1996; Masliah et al., 1993), progressive loss of corticospinal (Eisen et al., 1996) and spinal cord (Doherty et al., 1993) motor neurons, decreased efficacy of motor neuron recruitment (Erim et al., 1999), corticocortical and corticospinal connectivity changes due to the disruption of white matter integrity (Madden et al., 2004) and neuro-chemical modifications in primary motor cortex (MI) (Kaiser et al., 2005). The effect of such modifications has been widely investigated with fMRI and PET, analyzing either simple or more complex motor tasks. Age-related dif∗ Corresponding author at: Dept. of Clinical Neurophysiology, IRCCS San Raffaele, Via Olgettina 60, 20132 Milan, Italy. Tel.: +39 02 2643 2909; fax: +39 02 2643 3085. E-mail address: [email protected] (L. Leocani).

0197-4580/$ – see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.neurobiolaging.2009.02.020

ferences, detected particularly when similar performances are achieved (Cabeza et al., 2002) and when movement was more complex, consisted in an increased and more bilateral activation in elderly subjects (Ward, 2006). In simple movement, evidence is not fully converging for contralateral sensorimotor cortex (cSMC) activation in elderly subjects compared to the young ones, being unchanged (Calautti et al., 2001), over-activated (Mattay et al., 2002; Ward and Frackowiak, 2003; Naccarato et al., 2006) or lower-activated (Hutchinson et al., 2002). Conversely, ipsilateral SMC (iSMC) resulted more active with aging in several studies (Heuninckx et al., 2005; Hutchinson et al., 2002; Mattay et al., 2002; Ward and Frackowiak, 2003; Wu and Hallett, 2005, Naccarato et al., 2006). When simple movements at different increasing frequencies were performed, age-related over-activation (significantly in iSMC and ipsilateral dorso-lateral premotor cortex, iPMd) did not appear related to increasing functional demand (Riecker et al., 2006). Midline fronto central (MFC) areas, located in superior frontal gyrus and cingulate cortex, known to be activated especially in self-initiated

A. Inuggi et al. / Neurobiology of Aging 32 (2011) 524–538

movements (Picard and Strick, 1996; Cunnington et al., 1996; Wildgruber et al., 1997; Deiber et al., 1999), also showed an over-activation in elderly subjects (Mattay et al., 2002). Contrary to neuroimaging studies, whose significant differences are derived from an average of 2–3 s of cortical activity, EEG is expected to clarify where (although with a lower spatial accuracy compared with fMRI) and when, with respect to movement onset, the extensively reported over-activation occurs. The few EEG studies that analyzed age-related differences in movement-related cortical potentials (MRCP) reported a more bilateral pattern with aging with additional activation in iSMC (Sailer et al., 2000; Yordanova et al., 2004) and SMA (Sailer et al., 2000), but their source reconstruction approach could not investigate deep sources and separate the contribution of cingulate cortex from superior frontal gyrus supplementary motor areas. In the present study a distributed source method (cortical current density, CCD) was used to detect age-related differences in primary and secondary motor areas. This approach considers each superficial cortical patch in gray matter as a possible generator of the scalp recorded activity (Fuchs et al., 1999; Grav de Peralta Menendez and Gonzalez Andino, 1998) and their intensities are calculated for every EEG timepoint available. In each area and period, the origin of the over-activation mechanism will be investigated to understand whether it appears in all motorrelated areas or in those mainly involved in simple movements and whether it is produced by a recruitment of new cortical sub-regions or by an increased activity produced by the same neuronal population. In order to clarify if over-activation in elderly subjects is mainly due to a compensatory process or to a reduced selectivity of cortical activation, correlations between cortical activation and movement performance will be also investigated.

2. Methods 2.1. Subjects Twenty-one healthy volunteers, subdivided into two groups (12 ‘young’: 8 females; mean age 23.1 + 3.3 years, range 19–30; 9 ‘elderly’: 2 females, mean age 59.4 + 7.1 years, range 48–72). All subjects were free from medical, neurological or psychiatric diseases and were drug-free for at least 2 months before participating in the study; moreover, they were naïve to EEG recordings and were unfamiliar with the laboratory environment. They were right-handed according to a translated modified Edinburgh scale (Oldfield, 1971) and they all gave their written informed consent for participating in the study, which was approved by the local ethic committee. 2.2. EEG recordings Subjects were asked to perform self-initiated (every 5–7 s) brisk extension of right thumb with their eyes open. 29-

525

Fig. 1. Differences in movement performance. Group-averages of left (top) and right (bottom) EPB EMG activity of mirror-free epochs in elderly (solid line) and young (dotted line) subjects, with the same time and amplitude scale. Movement duration (EMGON–OFF ) is decomposed in movement initiation (EMGON–PEAK: time from EMG onset to peak) and termination (EMGPEAK–OFF : movement duration minus peak latency). Squared brackets with asterisks represent the approximate time delay of elderly compared to young subjects both in producing the EMG peak and the EMG offset, respectively, although the actual statistical analysis was performed over individual EMG traces.

channel EEG with binaural reference was recorded with scalp electrodes mounted on an elastic cap (Electro-cap International, Eaton, OH) according to the 10–20 international system of electrode placement, with additional electrodes along the longitudinal axis. Montage set-up procedure was accurately replied for every subject in order to minimize positioning differences. Nasion and inion were individuated over scalp surface and their respective distance was calculated on each subject, then the elastic cap was positioned placing FPz electrode at 10%, of that distance from nasion. The EEG signal was amplified (Synamps Amplifiers, Neuroscan Inc., Herndon, VA), filtered (DC to 50 Hz), and digitized (250 Hz sampling frequency). Bilateral bipolar EMG from the right and left extensor pollicis brevis (R-EPB, L-EPB) muscles was recorded. R-EPB to extract movement parameters and to monitor for contralateral complete relaxation, L-EPB to individuate homologous mirror movements. Bipolar electrooculogram was recorded to detect eye movements. For each movement, EMG onset and offset were manually marked by hand. For each subject, single epochs were rectified and averaged, then EMG peak was calculated. Movement duration (EMGON–OFF , the interval between EMG onset and EMG offset) was subdivided in EMG peak latency (EMGON–PEAK , the interval between EMG onset and EMG peak) and the difference between the two (EMGPEAK–OFF ) measuring the time to reach EMG silence after the peak, as shown in Fig. 1. Trials with artifacts, mirror movements and failure in EMG relaxation, outside the required movements,

526

A. Inuggi et al. / Neurobiology of Aging 32 (2011) 524–538

were excluded from the analysis. MRCPs were obtained by back-averaging EEG epochs −2.7 to +1.5 s from EMG onset, with the first 200 ms as baseline; MRCP sources in the interval from −2500 to 800 ms, with respect to EMG onset, were analyzed using CCD. 2.3. Sources reconstruction The conductor volume (a three-compartment boundary element model, 3420 nodes, skin–skull–liquor surfaces with conductivity values of 0.33–0.04–0.33 1/W m, respectively) was derived from a common anatomical MRI (voxel size: 2 mm × 2 mm × 2 mm), normalized in SPM-MNI space (Wellcome Department of Cognitive Neurology, London, UK). A common electrode montage was created, over the MRI derived skin surface, simulating the same procedure used in real electrodes positioning. FPz electrode was first created and the remaining positions were calculated according to real cap electrodes distances. Sources number (1347) and positions were obtained by sampling the cortex 10 mm wide, their orientations were fixed normally to the cortical surface they originated from and their intensity were calculated using a L2 norm algorithm. Leadfield matrix normalization was performed with an optimal (gain0.5 ) component-wise depth weighting method (Fuchs et al., 1999). Before source reconstruction MRCP were decomposed using an independent component analysis (ICA) algorithm in the interval −2500 to 800 ms respect to movement onset. The noise-normalized components, whose SNR was below 1 across all interval of interest, were excluded by reconstruction algorithm, CCD were performed in the same interval as ICA using Curry V4.6 software (Neuroscan, Inc., Herndon, VA).

2.4. Area segmentation Sources activity was evaluated in eight distinct areas: contra and ipsilateral sensory-motor cortex (cSMC and iSMC) and dorso-lateral premotor cortex (cPMd and iPMd) and the four mesial areas described by Picard and Strick (1996). SMC was composed by postcentral gyrus, both banks of central sulcus and precentral gyrus, where M1 activation related to hand movement is localized (Picard and Strick, 2001). PMd extended for 2 cm anterior to SMC. Ventral bounds of both SMC and PMd coincided to the beginning of white matter beneath their respective sulci. To segment mesial areas, Talairach anatomical landmarks (AC-PC line, VAC line, VPC line) were identified over the common normalized MRI; rostral from caudal part of both cortex (superior frontal gyrus and cingulate cortex) was individuated using the VAC line and four areas emerged: the rostral SMA (pre-SMA), the caudal SMA (proper SMA or SMA), the rostral cingulate cortex (CMAr) and the caudal cingulate cortex (CMAc). The anterior bounds of pre-SMA and CMAr were set rostral to VAC line in percentage of total anteroposterior brain dimension: pre-SMA at 17.1% and CMAr at 28.6% (Deiber et al., 1999). The posterior bounds of both caudal areas were determined by VPC line. Areas bounds are shown in Fig. 2. 2.5. Activation parameters According to the literature, the bereithshaftspotential can be analyzed in up to eight different periods, four preceding and four following the movement (Shibasaki and Hallett, 2006). In the present study five intervals were investigated: a baseline period (BL: from −2500 to −2000 ms), early (BP1: from −2000 to −1200 ms), intermediate (BP2: from −1200

Fig. 2. Areas bounds overlaid over a rendered cortex, here thinned 3 mm wide to better represent cortex shape, for (left) mesial areas segmentation. According to Picard and Strick (1996) functional subdivision of mesial premotor cortex. Anterior and posterior commissure (AC and PC) were marked over the common anatomical MRI, their position was imported in the brain model and VAC and VPC lines were calculated. VAC line divided superior frontal gyrus in a rostral pre-SMA and a caudal SMA and cingulate motor area in a rostral and caudal part, referred as CMAr and CMAc. Posterior bounds of caudal areas were at the intersection with VCP line, anterior bounds of rostral areas were selected according to Deiber et al. (1999) method: rostral to VAC line in percentage of total anteroposterior brain dimension: pre-SMA at 17.1% and CMAr at 28.6%. (Right) SMC was composed by postcentral gyrus, both banks of central sulcus and medial portion of precentral gyrus where M1 activation related to hand movement resides. PMd extended for 2 cm anterior to SMC. Ventral bounds of both SMC and PMd coincided to the beginning of white matter beneath their respective sulci. Over both images COGs during preparation for mesial areas and execution for lateral areas are shown with black and blue circles, representing elderly and young subjects, respectively.

A. Inuggi et al. / Neurobiology of Aging 32 (2011) 524–538

to −400 ms) and late (NS , from −400 to 0 ms) preparation periods and the movement-evoked potential one (MP1: from 60 to 160 ms). Considering that L2 algorithm produces a widespread activity, sources were thresholded according to the full width at half-maximum (FWHM) criterion: for each timepoint, only sources with intensity above the 50% of maximum were kept in consideration (Fuchs et al., 1999). For each subject-AREA-PERIOD, the following parameters were calculated: • Number of sources (NOS): for each timepoint, in a period of length nTp, sources fulfilling FWHM criteria were counted, their sum was then divided by nTp. • Total activation (TA): ij sij /nTp, where sij is the intensity of the ith FWHM source at timepoint j. • Mean activation (MA): TA/NOS, representing the mean contribute of each sources in a period. • Three coordinates of center-of-gravity position (COGx, COGy, COGz): representing medial-lateral, posterioranterior, dorso-ventral position of activation COG. NOS and TA values were divided by nTP to obtain measures comparable across periods of different length. These measures allowed to evaluate if TA (=MA*NOS) differences between groups and/or periods were due to an increased activity in the same area – MA increment – or a more widespread activity – NOS increment – in both space, involving more sources in the same area, or time, same sources active for more timepoints. To resolve this ambiguity, considering that a recruitment process of new sources is expected in elderly subjects, the mean NOS temporal evolution was calculated in all areas and periods in which a significant NOS difference was found. COG was the average of sources coordinates weighted by their intensity in the period, according to the following formula:    COG A = sij ∗ Aij / sij ij

ij

where sij is the intensity of the ith FWHM source at timepoint j and Aij is the x, y, z position of the ith source at timepoint j. The higher the COGy and COGz values, the more posterior and ventral are the positions. For mesial areas only, the closer to zero will be the COGx value, the more bilateral will result the activation. In addition, for each period a laterality index (LI) was calculated according to the following formula: LI = (TAcSMC − TAiSMC )/(TAiSMC − TAcSMC ) where cSMC and iSMC means contro and ipsilateral SMC, respectively. CCD sources time-series, written by Curry software into a text file, were extracted and analyzed using a custom-made software able to threshold sources according to FWHM criteria and their position, calculate the activation parameters and export them into a text file for statistical analysis.

527

2.6. Statistical analysis Data were analyzed with SPSS (Technologies, Inc., Chicago, IL, USA) using repeated-measures analysis of variance (ANOVA), with PERIOD (BL, BP1, BP2, NS , MP1) and AREA (iSMC, cSMC, iPMd, cPMd, pre-SMA, SMA, CMAr, CMAc) as within subject factors, and AGE (elderly, young) as the between subject factor. When the sphericity assumption, verified using the Mauchly’s criterion, was rejected, the Greenhouse–Geisser correction was performed. To analyze intra-period differences (IPD) in young and elderly subjects, one-way ANOVA over PERIOD was performed in every AREA and every group. To explain significant main effects or interactions with the independent variable AGE, contrast analysis in each area and period investigated were performed using independent samples ttest. Statistical significance was considered at p < 0.05. Data are presented as mean ± S.E. To assess that increased NOS values in a certain period were produced by an increased number of sources (and not by the same sources pool, active for more timepoints), independent samples t-test were performed over NOS temporal evolution for each timepoint. Two-tailed Pearson correlation analysis (p < 0.05) between age and LI were performed in each period. In NS and MP1, two-tailed Pearson and Pearson partial correlation analyses (p < 0.05) were performed to assess the reciprocal effect of age, cortical activity (TA, NOS, MA) and movement performance (EMGON–PEAK and EMGPEAK–OFF ). Initially, Pearson correlations were calculated between EMG parameters and age, and for each area, between cortical activity and both EMG parameters and age. Then, for all areas/periods with significant Pearson correlation between cortical activity and EMG parameters were found, separate Pearson partial correlation analyses were performed by removing the effects of cortical activity and of age, respectively. Finally, age and cortical activity were correlated while removing the effects of both EMG parameters. The existence of a linear relationship among all variables, mandatory for partial correlation analysis, was preliminarily tested.

3. Results 3.1. Movement performance A similar number of movements were performed in the two groups (elderly: 86 ± 24; young: 86 ± 25, p = 0.986). Among them, elderly subjects showed a significantly higher percentage of mirror movements compared to young ones (respectively 2.7 ± 1.1% and 0.11 ± 0.40%, p = 0.0001, independent samples t-test). Movement duration in elderly subjects resulted significantly higher than that of young ones (elderly: EMGON–OFF = 616 ± 122 ms; young: EMGON–OFF = 390 ± 103 ms, p = 0.0001). This was caused by a concomitant slowing both in producing the maximum EMG peak (elderly: EMGON–PEAK = 124 ± 19 ms, young:

528

A. Inuggi et al. / Neurobiology of Aging 32 (2011) 524–538

Fig. 3. Grand-average of movement-related cortical potentials. (Left) channels traces of elderly (black line) and young (red line) subjects. (Right) scalp potentials and CCD results in two representative latencies of late preparation (upper) and movement-evoked (lower) periods. CCD maps were clipped at 50% (FWHM). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of the article.)

EMGON–PEAK = 69 ± 16 ms, p = 0.0001) and in subsequent time to termination (elderly: EMGPEAK–OFF = 491 ± 122 ms, young: EMGPEAK–OFF = 321 ± 96 ms, p = 0.002) as shown in Fig. 1. No significant differences emerged in EMG peak amplitudes between the two groups. 3.2. Sources analysis To show the general quality of MRCP, group-averages of both young and elderly subjects were calculated and their EEG channel traces, scalp potentials and CCD, at two representative latencies, were shown in Fig. 3. Lateral and mesial areas mean activation parameters (TA, NOS, MA), calculated from each individual MRCP CCD, are shown in Fig. 4, activation COGs are represented in Fig. 2. Young and

elderly activation parameters temporal evolution during NS and MP1 are shown in Fig. 5. Activity differences across two periods are indicated with the following convention: period1 ≥ period2 (e.g. BP2 ≥ NS ). Repeated-measures analysis of variance (ANOVA), whom F- and p-values are summarized in Table 1, assessed a significant effect of both within subject (PERIOD, AREA) and between subject (AGE) factor and their interactions (PERIOD × AREA, AREA × AGE, PERIOD × AREA × AGE) over TA, MA and NOS and PERIOD × AGE over NOS. 3.2.1. Overall activation dynamics One-way ANOVA over PERIOD variable performed in each area of each group (8*2) showed a mean progressive increment of TA in all areas of both groups compared to

Table 1 Cortical activation: statistical analysis. Effect

PERIOD AREA PERIOD × AREA PERIOD × AGE AREA × AGE PERIOD × AREA × AGE

Parameter TA

NOS

MA

F = 35.438, p < 0.001 F = 41.968, p < 0.0001 F = 21.947, p < 0.001

F = 18.765, p < 0.001 F = 74.433, p < 0.001 F = 12.495, p < 0.001 F = 8.313, p < 0.001 F = 6.433, p < 0.001 F = 5.305, p < 0.001

F = 48.862, p < 0.001 F = 18.915, p < 0.001 F = 7.866, p < 0.001

F = 7.612, p < 0.0001 F = 5.449, p < 0.01

F = 9.305, p < 0.001 F = 7.660, p < 0.001

Repeated-measures analysis of variance (ANOVA), with PERIOD (BL, BP1, BP2, NS , MP1) and AREA (iSMC, cSMC, iPMd, cPMd, pre-SMA, SMA, CMAr, CMAc) as within subject factors, and AGE (elderly, young) as the between subject factor, p < 0.05.

A. Inuggi et al. / Neurobiology of Aging 32 (2011) 524–538

529

Fig. 4. Activation pattern in lateral and mesial areas. The eight columns represents investigated areas, the three rows the CCD activation parameters (TA, NOS and MA). Black and white bars represent respectively elderly and young subjects. On each graph, activation parameters (TA, NOS and MA) are calculated at abscissa’s periods values BL, BP1, BP2, NS and MP1. Significant differences between the two groups, to independent samples t-test (p < 0.05), were marked with the ‘*’.

baseline. In young subjects, a significant increment of MA in cSMC, CMAc, iSMC and iPMd and of TA in cSMC was seen in BP2 ≥ NS (Table 2). In elderly subjects, MA resulted significantly incremented in all areas while TA and NOS in caudal mesial areas (SMA and CMAc) and both SMC. In NS ≥ MP1, young subjects showed a significant MA increment in all areas but those (cSMC and CMAc) showing this increment in BP2 ≥ NS . iSMC and SMA also incremented both their TA and NOS, while CMAc and iPMd their NOS only. Elderly subjects did not show any further significant increment in NS ≥ MP1.

3.2.2. Topographical and dynamical activation pattern changes with age To investigate PERIOD × AREA × AGE significant effect (F(3.43, 65.2) = 5.449, p < 0.01), independent samples t-test analysis of age-related differences in each area and in each period was performed. No aging effects on TA, NOS and MA occurred during both BL and BP1 periods. During BP2, TA in SMA resulted significantly higher in elderly than in young subjects for a concurrent, but not significant, increase of NOS and MA. Almost all differences emerged during both NS and MP1 (Figs. 4 and 5).

Table 2 Areas recruitment between movement preparation and execution. BP2 ≥ NS

SMA CMAc pre-SMA CMAr cSMC iSMC cPMd iPMd

Elderly

Young

TA

NOS

MA

* *

* *

* *

* *

* * * * * * * *

TA

NOS

MA *

*

* * *

One-way ANOVA over period calculated in each area of both groups (p < 0.05). The asterisks represent activation parameters significant increments between movement intermediate and late preparations (BP2 ≥ NS ).

530

A. Inuggi et al. / Neurobiology of Aging 32 (2011) 524–538

Fig. 5. Cortical activity during movement late preparation, execution and termination. CCD evolution in elderly (solid line) and young (dotted line) subjects in mesial and lateral motor areas are shown with the corresponding rectified EMG activity. Significant differences are marked with the ‘*’.

A. Inuggi et al. / Neurobiology of Aging 32 (2011) 524–538

531

Table 3 Cortical topographical dynamics changes with age.

SMA

CMAc

BP2

NS

TA>

TA> NOS> TA> NOS> MA> IL COG

NS

MP1

cSMC

TA> NOS> MA>

TA> NOS>

iSMC

TA> NOS> MA>

MP1

BP2

pre-SMA

NOS< TA<

cPMd

CMAr

NOS< TA<

iPMd

Significant differences analyzed with independent samples t-test (two-tailed), p < 0.05. Symbol “>” indicates a higher value in elderly, “<” a lower value in elderly. IL COG means that COG was significantly ipsilateral in elderly and non-significantly bilateral in young. No differences emerged during baseline and early preparation (BL and BP1).

3.2.2.1. Lateral areas. During NS period, elderly subjects showed a bilateral significant TA increase (cSMC: +144%, p = 0.002, iSMC: +158%, p = 0.004) in SMCs that did not significantly reduce their laterality index (0.19 and 0.31 in elderly and young, respectively) and was due to an increased NOS occurring in both hemispheres (cSMC: +84%, p = 0.002, iSMC: +99%, p < 0.0001) and a significant increase of MA (cSMC: +60%, p = 0.046, iSMC: +46%, p = 0.044) (Fig. 4). During MP1, TA and NOS in cSMC resulted significantly incremented in elderly subjects compared to the young ones. PMd showed a lesser contribute in MRCP generation with respect to SMC and non-significant differences ever emerged. COG positions changes of each area, across the three periods, were in general not significant and in the order of few (1–3) millimeters. Significant changes are shown in Table 3. No significant correlation between LI and age was found at two-tailed Pearson correlation analysis. 3.2.2.2. Mesial areas. In mesial premotor cortex, caudal areas (SMA and CMAc) showed a different pattern than rostral (pre-SMA and CMAr) one. Caudal areas evolution resulted similar to cSMC with a significant TA increment (compared to BP2) during NS period (SMA: +150%, p = 0.008, CMAc: +140%, p = 0.014) mainly due to an increased NOS (SMA: +101%, p = 0.01, CMAc: +113%, p = 0.005) in elderly respect to young and a slighter and not significant increment of MA (SMA: +50%, p = 0.125, CMAc: +35%, p = 0.109), during MP1 both groups showed a similar activation in caudal areas. In rostral areas, TA did not differ between the two groups during NS and was considerably lower than that of caudal areas. Age-related differences emerged instead during MP1, elderly subjects showed a significantly reduced TA caused by a lower NOS (Fig. 4). In all periods of both groups, pre-SMA COGx was contralateral; SMA, CMAr and CMAc COGx were instead close to zero, suggesting a bilateral activation. The

latter area activity during NS was bilateral in young subjects and significantly shifted ipsilaterally in the elderly ones. 3.2.3. NOS temporal evolution analysis The t-test group comparison performed point-by-point over NOS values, in those periods where it resulted significantly increased in elderly group, showed that these were produced by a higher number of sources and not by a longer duration in activation of the same sources, as shown in Fig. 5. 3.3. Correlation between movement, cortical activation and age Rectified EMG activity, obtained from MRCP groupaverages, is shown in Fig. 5 along with CCD of all involved areas during movement execution and termination. Significant correlation (two-tailed Pearson, p < 0.05) was observed between age and EMG parameters (EMGON–PEAK : ρ = 0.777, p < 0.001; EMGPEAK–OFF : ρ = 0.561, p = 0.008) and between cortical activation and both age and EMG parameters (Table 4a and b). During NS (Table 4a), TA in SMA resulted positively correlated with EMGON–PEAK but not with EMGPEAK–OFF . Both SMC and CMAc TA were positively correlated with both measures. During MP1 (Table 4b), pre-SMA TA was negatively correlated with EMGPEAK–OFF and CMAr one with EMGON–PEAK , TA of cSMC and CMAc positively with EMGON–PEAK only. NOS parameter, along with the same correlations as TA, showed a further correlation in cSMC with EMGPEAK–OFF . Partial correlation analysis showed a general strong correlation of subject’s age with EMG parameters slowing in almost all areas when the effects of their cortical activity were controlled. Instead, after correcting for age, all partial correlation between EMG parameters and cortical activity disappeared except that of EMGON–PEAK with caudal mesial areas and

532

A. Inuggi et al. / Neurobiology of Aging 32 (2011) 524–538

Table 4 Correlation between movement parameters, cortical activation and subject age. CA–AGE

CA–EMG Init.

Term.

CA–EMG (AGE corrected)

EMG–AGE (CA corrected)

Init.

Init.

Term.

Term.

(NS )

(a) Late preparation cSMC TA 0.650** NOS 0.654** MA 0.441*

0.60** 0.44* 0.46*

0.50* 0.52*

CMAc TA NOS MA

0.483* 0.531* 0.430+

0.69** 0.72** 0.51*

0.47* 0.43*

iSMC TA NOS MA

0.542* 0.663** 0.428+

0.69** 0.72** 0.52*

0.56** 0.58**

SMA TA NOS MA

0.529* 0.609** 0.440*

0.67** 0.68** 0.51*

(b) Movement evoked (MP1) cSMC TA 0.595** NOS 0.685** MA

0.68** 0.62** 0.46*

CMAc TA NOS MA −0.463* −0.620**

CMAr TA NOS MA

−0.414+ −0.511*

−0.54*

–

0.70** 0.67** 0.71**

–

–

0.66** 0.57** 0.71**

–

0.51* 0.44*

– – –

0.67**

–

0.63** 0.61**

0.43*

0.71**

–

0.49* – −0.52* −0.55**

– –

−0.43* −0.51*

0.55* 0.46* –

0.58** 0.57**

0.48*

0.46* 0.51*

pre-SMA TA NOS MA

–

0.63** 0.69** 0.72**

– – – −0.43+ −0.42* – –

−0.43* –

–

– – –

– –

0.76** 0.77** –

– – –

– 0.67** –

–

0.72** 0.43* –

– 0.67** –

Age-related significant Pearson correlations of cortical activity (CA: TA, NOS and MA) and both age, ‘CA vs. AGE’, and movement initiation and termination, ‘CA vs. EMG’, calculated in mesial and lateral motor areas during late preparation (a) and movement-evoked phase (b). Correlation factor is represented with ρ. For completeness, nearly significant (p < 0.059) are represented with ‘+’. When a significant Pearson correlation (CA vs. EMG) was found, Pearson partial correlations were performed to verify if movement parameters correlated with cortical activity regardless of its age, ‘CA vs. EMG (age)’, and if movement parameters correlated with age regardless of cortical activity, ‘EMG vs. age (CA)’, otherwise the symbol ‘–’ was shown. * p < 0.05. ** p < 0.01.

iSMC (during NS ), and with CMAc (during MP1) and that of EMGPEAK–OFF with pre-SMA (during MP1) (Table 4 a and b). A partial correlation, controlling for both movement parameters, between age and NOS was found only in cSMC during NS (ρ = 0.589, p = 0.006).

4. Discussion In the present study, age-related differences in performing a simple right thumb extension were investigated by reconstructing the cortical generator of the MRCP. A finger

movement was selected for several reasons. BP generators and their temporal pattern are well known (Shibasaki and Hallett, 2006; Colebatch, 2007), since the first report of EEG activity preceding voluntary movement (Kornhuber and Deecke, 1964) it has been investigated with 64 channels, using fMRI-seeded dipoles (Toma et al., 2002), current source density (Cui et al., 1999) and cortical current density reconstruction, CCD, using a realistic volume conductor (Ball et al., 1999). Moreover, for its easiness and limited associated fatigue, such paradigm should minimize performance differences that may lead to age-related differences in brain activation (Cabeza et al., 2002).

A. Inuggi et al. / Neurobiology of Aging 32 (2011) 524–538

4.1. Methodological considerations Previous EEG studies investigating age-related differences in BP used a “classical” EEG approach that consisted in interpolating channels amplitude (Yordanova et al., 2004) or calculating CSD (Sailer et al., 2000) over the scalp surface. These methods can reveal several and interesting results, in particular when different paradigms are tested, but cannot clarify the contribution of deep sources to scalp potentials, although spatially enhanced. In a self-initiated movement, where mesial areas are highly activated, such methods cannot clarify the different contributes of cingulate cortex (caudal and/or rostral) and superior frontal gyrus (pre-SMA and proper SMA) to scalp potentials recorded over central-mesial regions corresponding to FCz and Cz electrodes. In the present study, a CCD method using a common realistic volume conductor was used to reconstruct cortical activity. The small number of EEG electrodes (29) and the lack of individual anatomical information limited the spatio-temporal accuracy of our study. When the effect of electrodes number over CCD reconstruction accuracy was tested, 29 channels montage showed a higher reconstruction error, compared with 61 and 128 channels, but was still able to locate SMC and SMA sources (Babiloni et al., 2003). According to these limitations, it would not have been possible to look for the generator of “Premotion Positivity” in intermediate SMA (Ball et al., 1999) nor to localize N-10 in M1 or N+50 in S1 (Shibasaki and Hallett, 2006). Therefore, S1 and M1 were then grouped in a same area (SMC) and intermediate SMA and CMA were not segmented separately (Ball et al., 1999). Posterior and anterior bounds of CMAc were delimited by VPC and VAC lines, respectively, differently from what defined by Deiber et al. (1999), to simplify the segmentation process performed by our custom software. The selected area bounds surely influenced our results, but less than one might expect. Considering for example SMC ventral bounds, if they were shifted ventrally enclosing a larger white matter region, the number of sources would have not changed as they were constrained to the gray matter. It cannot be excluded that our method for areas clustering might have introduced some error in the present results, but the consistency of our reconstructed generators with the literature, as will it be later discussed, suggests that this error should have been minor. According to activation parameter (TA, MA, NOS) definition, the NOS parameter is the average number of active 10-mm wide active patches – the cortex was divided into – during a certain period and it was stated that it could have been the product of either a higher number of active patches and/or a higher number of timepoints in which the same patches set was active. According to NOS temporal evolution analysis results, a higher NOS increment will be considered an activation extent increment due to a recruitment of new sub-regions inside the same area. Instead, the MA parameter, defined as a sort of activation density (TA/NOS), should be correlated with the number of active macro-columns inside each single patch. Sources, in

533

fact, were constrained to cortex surface and oriented normally to the cortical patch they originated from, hence simulating the activity of several pyramidal neurons located in the same macro-column, whose EEG is sensitive to. 4.2. Generators of MRCP According to previous literature, mesial areas are the main generators, in particularly in complex task, of early BP phase and implement the preparation of the movement. SMC activity, also present during early BP (Ikeda et al., 1996) first mainly contralateral and then ipsilateral to movement, become relevant during late preparation, when, through intense interactions with SMA aimed at selecting the appropriate muscles synergies (Wildgruber et al., 1997; Colebatch, 2007), the conscious will to move is transformed into the execution of a certain movement (Shibasaki and Hallett, 2006). Finally, SMC shows the contribution of both motor (Kristeva et al., 2006) and sensory regions during movement-evoked phase (MP1), representing the afferent feedback processing. In the present study, cSMC resulted the most intensely active region during the last two periods. iSMC activity, lower than cSMC and present since movement preparation, is consistent with previous EEG studies. Both SMC COGs resulted in the proximity of the precentral knob, known to be an affordable landmark of hand M1 position (Yousry et al., 1997). Lateral premotor cortex (PMd) contribute was of much lower intensity compared to SMC one, and should be related to the very simple task that did not need either any motor sequence programming or learning, known to positively correlate with PMd activity (Kawashima et al., 1998). Its mean distance from cSMC during execution was 8 mm, according to the results reviewed by Picard and Strick (2001). Mesial secondary motor areas are highly influenced by movement characteristics, rostral regions activity has been related to high-order motor functions needed in complex tasks (needing the selection of a motor response and the acquisition of conditional association) while caudal regions were more activated to simple movements or over-learned sequences (Friston et al., 1992; Jenkins et al., 1994; Picard and Strick, 1996). Our data, showing the most intense activity in caudal areas, is coherent with this subdivision as self-paced thumb extension is a simple movement. When eight different movements were tested (Deiber et al., 1999), CMAc was the only mesial area that was significantly contralateral and sensitive to every condition (compared with rest). Its considerable activation intensity in our data during late preparation is consistent with the definition of ‘secondary purely executive motor area’ (Deiber et al., 1999). Rostral areas (CMAr and pre-SMA) showed activation, although minor, during the whole preparation period, consistently with a previous EEG study (Ball et al., 1999). The activation peak observed in the latter study (investigating subjects aged 24–35 years) over the intermediate SMA (between SMA and pre-SMA) during movement-evoked phase, is also consistent with the intense activity of both SMA and pre-SMA of our young group in

534

A. Inuggi et al. / Neurobiology of Aging 32 (2011) 524–538

the same period. Rostral areas behaviour in elderly subjects during the last period will be later discussed. 4.3. Age-related differences Several authors addressed the issue of cortical motor over-activation with aging. Two main theories emerged: one suggests that the older brain shows a reduction of the strong functional brain lateralization (Cabeza et al., 2002; Cabeza, 2002) and recruits a wider cortical network in order to produce the same performance as their younger counterpart. The over-activation may represent a motor system countermeasure to compensate the reduction in neuron size and spine density (Anderson and Rutledge, 1996; Masliah et al., 1993), the progressive loss of corticospinal (Eisen et al., 1996) and spinal cord (Doherty et al., 1993) motor neurons and the decreased efficacy of motor neuron recruitment (Erim et al., 1999). Several studies support this scenario (see for review Ward, 2006): over-activation increases when movement is performed with the non-dominant hand (Hutchinson et al., 2002) or is more complex (Heuninckx et al., 2005) and shows a negative correlation with button press reaction times (Mattay et al., 2002) and a positive correlation with hand grip force increase (Ward and Frackowiak, 2003). Also EEG assessed an ipsilateral and mesial recruitment correlated with a better performance (Sailer et al., 2000). These evidences suggest that over-activation may emerge when it is useful to compensate for cortical motor system neuronal loss. Conversely, over-activation may also be due to a non-specific reduction in the selectivity of activation of a given cortical network as several findings suggest. Reduced center-surround inhibition with aging has been reported in the visual system (Betts et al., 2005). Moreover in animal studies, loss of inhibitory synapses occurring with age has been reported in the visual cortex (Leventhal et al., 2003), inferior colliculus (Caspary et al., 1999), hippocampus (Stanley and Shetty, 2004), and SM cortex (Poe et al., 2001) and in humans, intra-cortical inhibition, studied with transcranial magnetic stimulation, decreases with age (Peinemann et al., 2001). A recent fMRI study (Riecker et al., 2006) reported an uncoupling between elderly subjects over-activation and increased finger-tapping frequency, since functional demand did not significantly increase (with respect to that at 1 Hz) at 2–6 Hz. Therefore, the over-activation of medial frontal, parietal and ipsilateral SM regions in elderly compared to young subjects could be related to impaired inhibitory control on or within these structures, due to decreased corticocortical connectivity and neuronal loss. Our data showed that over-activation was specific, occurring only in some motor-related areas and only in certain periods. The areas (cSMC, iSMC, SMA, CMAc) were those related to the execution of a simple task (Picard and Strick, 1996) and the periods (NS and MP1) were those in which movement was performed and its afferent feedback was processed by SMC. The preparation period, not requiring the selection of a motor response and the acquisition of conditional associa-

tions, resulted similar between the two groups. Considering that subjects were asked to perform movements as brisk as possible, the over-activation in the elderly in the presence of a worse motor performance, such as a delayed EMG peak latency and a slower motor termination, is not consistent with the theory that associates over-activation with a preserved performance (or the execution of a complex task). Hints of a reduced selectivity of activation come from the analysis of the cortical pattern changes occurring during late preparation (compared to early and intermediate preparation) in the two groups. In young subjects, the activation increment over time occurred within almost the same cortical sub-regions (NOS unchanged) through the recruitment of a higher number of their macro-columns (increased MA) to perform the movement. Elderly subjects significantly incremented MA in all eight areas but also recruited new neighbour patches inside each of the four simple-movementrelated areas. If we consider the mosaic-like somatotopic organization of M1 (see for review Schieber, 2001), the most active and over-activated area in the present study, the neuronal population in these new recruited patches are too far (up to 3 cm) from each other to be considered those that induces EPB contraction and its antagonist relaxation. In primates in fact, the entire population of cortico-motor neurons cells innervating the motoneurons of an individual muscle resided in a region not larger than 11 mm × 5 mm (Rathelot and Strick, 2006). The macro-column recruitment inside the same 10 mm patch could hence be considered a physiological recruitment of cortico-motor neurons to perform the movement. The regional (within the same area) recruitment of new patches in elderly subjects instead could be more likely related to a reduced intra-cortical inhibitory activity within the motor system occurring with age (Peinemann et al., 2001). As only the EPB muscle had been monitored, it was not possible to verify whether the reduced selectivity in cortical activation observed in older subjects, as reflected in the increased NOS during late preparation, also corresponded to a more widespread activation at the muscle level. 4.4. Activation lateralization An issue our study could not confirm is the reduced hemispheric lateralization with aging. The significant increased activation of iSMC shown in the present study was demonstrated in several fMRI (Hutchinson et al., 2002; Mattay et al., 2002; Ward and Frackowiak, 2003; Wu and Hallett, 2005; Heuninckx et al., 2005; Naccarato et al., 2006) and EEG (Sailer et al., 2000; Yordanova et al., 2004) studies, while cSMC only in a subset of them (Mattay et al., 2002; Ward and Frackowiak, 2003; Yordanova et al., 2004; Naccarato et al., 2006). The study specifically investigating the laterality index changes with aging (Naccarato et al., 2006) reported a significant reduction of LI caused by the significant correlation between age and iM1 activity and the non-significant trend between the former and cM1. In the present study, activation

A. Inuggi et al. / Neurobiology of Aging 32 (2011) 524–538

in both SMC resulted positively correlated with age during execution, while LI did not. Two methodological differences between previous fMRI studies and the present one may explain this discrepancy. First, our LI was calculated after averaging M1 and S1 activities with the latter presumably less sensitive, than the former, to age-related motor differences before afferent feedback processing. Therefore, possible differences occurring only over M1 could have been averaged out in our data. Second, elderly subjects performing unilateral movements execute mirror movements more frequently than their younger counterpart also during simple tasks (Cincotta and Ziemann, 2008). By EMG monitoring of the homologous resting muscle, we confirmed this attitude but, meanwhile, we could also exclude them from the analysis. Conversely, the higher ipsilateral SMC cortex increase found in fMRI studies, that significantly reduced their LI, might have been partly the product of such underestimated left thumb movements. In our findings, the low increase of mirror occurrence in elderly (0.11% vs. 2.7% of young and elderly, respectively) may appear not sufficient to explain these differences. Nevertheless, we should consider that the real-time EMG monitoring allowed the experimenter to repeatedly invite the subject to concentrate and relax when a pre-movement EMG activity was observed or after a mirror movement was executed. Cognitive distraction and pre-existent muscle contraction demonstrated in fact a significant effect over mirror movement production (Baliz et al., 2005; Addamo et al., 2007; Ottaviani et al., 2008) that most fMRI experiments did not control for. The only significant age-related difference in lateralization (COGx) was found in CMAc during movement late preparation. In fact, while in young subjects it was almost bilateral, in elderly subjects it showed a slight but significant ipsilateral preponderance. The finding of a bilateral activation in young subjects during a simple motor task in our study is in apparent conflict with a previous fMRI study (Deiber et al., 1999) performed in a group with age comparable to our young group. In that study, activity in CMAc had a contralateral preponderance in all tasks. Nevertheless, fMRI is considered to be less sensitive to inhibitory than to excitatory activity (Waldvogel et al., 2000). Therefore, the ipsilateral CMAc CCD signal found in the present study could be the expression of inhibitory activity, to which EEG may be more sensitive compared with fMRI. Consistent with this interpretation is a previous finding on M1 activation to self-paced movement (Toma et al., 2002), which was more asymmetrical at fMRI as compared to EEG (around movement onset). Our result of a shift, in elderly subjects, of CMAc activity to the ipsilateral side is consistent with previous studies on M1 reporting that over-activation with aging in elderly was higher over iSMC than cSMC. These findings might result from altered transcallosal connections (Allison et al., 2000) or reduced intra-cortical (Peinemann et al., 2001) inhibitory activity occurring with aging. Since an intense inhibitory activity of CMAc has been never reported before, further studies are needed to verify such hypothesis.

535

4.5. Movement performance and cortical activity Our finding of increased movement duration in elderly subjects is consistent with previous findings reporting motor slowing with aging (Hsu et al., 1997; Krampe, 2002; Yordanova et al., 2004). The slowing occurred in both initiation (EMGON–PEAK ) and termination (EMGPEAK–OFF ) suggesting a reduced speed of both movement production and termination. Concerning the relationship between cortical activity and motor performance some considerations should be made. In our findings, most correlations between cortical activity and EMG parameters were lost after correction for age. Differently, partial correlation between age and motor slowing persisted even when removing the effect of cortical activity. The implications are twofold. First, a simple correlation between cortical activity and motor performance may be biased by a common age effect. Second, age is related to increased cortical activation which is not completely reflected in motor performance. In fact, we may consider that age affects the motor system at several central and peripheral levels (Ryall et al., 2008), while CCD may only reflect those occurring at the cortical level. We also have to consider that only the EMG of the primer mover muscle and its homologous have been measured, and not of antagonists or neighbouring muscles, which may have provided further indications on motor performance, particularly on its selectivity. The residual positive and negative partial correlations between cortical activity and motor slowing involved different cortical areas. The former were found in areas co-operating with cSMC in producing the unilateral simple movement (SMA, CMAc and iSMC), moreover with movement initiation only. In our findings, the loss of correlation between cSMC and motor performance, after removing the effect of age, is in apparent contrast with its pivotal role in motor execution. As previously mentioned, this finding may indicate that the cSMC over-activation found in older subjects reflects a loss of selectivity rather than a compensation to improve motor performance. Conversely, only in pre-SMA we found partial positive correlations between cortical activity and motor performance, which were limited to motor termination. This finding is consistent with the common inhibitory role of pre-SMA (Nachev et al., 2007), independent from sensory modalities (Nakata et al., 2008), and with its involvement in voluntary muscle relaxation, with a larger activation for the relaxation mode than for the contraction mode (Toma et al., 1999). The decreased pre-SMA activation found in the elderly group, together with poor task performance, may hence indicate involvement of that region itself or of its connections with SMC (Rizzolatti et al., 1996). A positive correlation between regional activation and performance has also been reported in previous studies investigating response inhibition (Jonides et al., 2000) and working memory (Reuter-Lorenz et al., 2000) in aging. On the contrary, another response inhibition study (Nielson et al., 2002) reported an increased regional activity in elderly poor performers compared to elderly good performers and

536

A. Inuggi et al. / Neurobiology of Aging 32 (2011) 524–538

young subjects. A close comparison between these and the present study is not possible due to differences in the task and in motor parameters used. Although it cannot exclude that the cortical over-activation observed in elderly subjects might represent a compensation to motor slowing, this possibility is less likely also considering that in our task no feedback on EMG was provided, thus reducing the need, in elderly subjects, of additional effort to improve performance.

5. Conclusions Using 29 channels and a common normalized MRI, cortical current density reconstruction could adequately describe the MRCP generators. A significant over-activation could be observed in elderly groups and our method allowed to identify two different activation patterns in young and elderly subjects. In the shift from preparation to execution, increased cortical activation resulted by enhancing signal intensity within the same regions. In addition, elderly subjects also recruited new sub-regions within the same areas, consistently with neuroimaging studies. In our findings, worsening motor performance with aging, at least at the simple task used, is related both to decreased activation on some areas (rostral mesial) and to increased activation in others (SMC and caudal mesial). This suggests that increased activation is not necessarily compensatory for improving performance but may also be detrimental or be an indicator of reduced cortical selectivity with aging. In addition, movement duration was negatively correlated with pre-SMA activity, consistently with its possible role in movement termination, as previously reported. Further studies using higher spatial resolution and also assessing the degree of muscle co-activation, in both contralateral adjacent and ipsilateral homologous muscles, are needed to investigate whether the reduction in selectivity of cortical activation corresponds to reduced selectivity in the efferent motor output. The importance of defining agerelated differences mainly stresses the need for age-matched control groups in studies of neurodegenerative or lesionderived pathological diseases that mainly occur in elderly patients.

Conflicts of interest In the present paper there are no actual or potential conflicts of interest.

Acknowledgements The authors would like to thank Andrea Nossa, TNFP, for EEG recordings, and Dr. Anna Cercignani for her help in the language editing of the manuscript.

References Addamo, P.K., Farrow, M., Hoy, K.E., Bradshaw, J.L., Georgiou-Karistianis, N., 2007. The effects of age and attention on motor overflow production—a review. Brain Res. Rev. 54, 189–204. Allison, J.D., Meador, K.J., Loring, D.W., Figueroa, R.E., Wright, J.C., 2000. Functional MRI cerebral activation and deactivation during finger movement. Neurology 54, 135–142. Anderson, B., Rutledge, V., 1996. Age and hemisphere effects on dendritic structure. Brain 0, 1983–1990. Babiloni, F., Babiloni, C., Carducci, F., Romani, G.L., Rossini, P.M., Angelone, L.M., Cincotti, F., 2003. Multimodal integration of highresolution EEG and functional magnetic resonance imaging data: a simulation study. Neuroimage 19, 1–15. Baliz, Y., Armatas, C., Farrow, M., Hoy, K.E., Fitzgerald, P.B., Bradshaw, J.L., Georgiou-Karistianis, N., 2005. The influence of attention and age on the occurrence of mirror movements. J. Int. Neuropsychol. Soc. 11, 855–862. Ball, T., Schreiber, A., Feige, B., Wagner, M., Lucking, C.H., Kristeva-Feige, R., 1999. The role of higher-order motor areas in voluntary movement as revealed by high-resolution EEG and fMRI. Neuroimage 10, 682–694. Betts, L.R., Taylor, C.P., Sekuler, A.B., Bennett, P.J., 2005. Aging reduces center-surround antagonism in visual motion processing. Neuron 45, 361–366. Cabeza, R., Anderson, N.D., Locantore, J.K., McIntosh, A.R., 2002. Aging gracefully: compensatory brain activity in high-performing older adults. Neuroimage 17, 1394–1402. Cabeza, R., 2002. Hemispheric asymmetry reduction in older adults: the HAROLD model. Psychol. Aging 17, 85–8100. Calautti, C., Serrati, C., Baron, J.C., 2001. Effects of age on brain activation during auditory-cued thumb-to-index opposition: a positron emission tomography study. Adv. Neurol. 32, 139–146. Caspary, D.M., Holder, T.M., Hughes, L.F., Milbrandt, J.C., McKernan, R.M., Naritoku, D.K., 1999. Age-related changes in GABA(A) receptor subunit composition and function in rat auditory system. Neuroscience 93, 307–312. Cincotta, M., Ziemann, U., 2008. Neurophysiology of unimanual motor control and mirror movements. Clin. Neurophysiol. 4, 744–762. Colebatch, J.G., 2007. Bereitschaftspotential and movement-related potentials: origin, significance, and application in disorders of human movement. Mov. Disord. 22, 601–610. Cui, R.Q., Huter, D., Lang, W., Deecke, L., 1999. Neuroimage of voluntary movement: topography of the Bereitschaftspotential, a 64-channel DC current source density study. Neuroimage 9, 124–134. Cunnington, R., Bradshaw, J.L., Iansek, R., 1996. The role of the supplementary motor area in the control of voluntary movement. Hum. Mov. Sci. 15, 627–647. Deiber, M.P., Honda, M., Ibanez, V., Sadato, N., Hallett, M., 1999. Mesial motor areas in self-initiated versus externally triggered movements examined with fMRI: effect of movement type and rate. Adv. Neurol. 81, 3065–3077. Doherty, T.J., Vandervoort, A.A., Taylor, A.W., Brown, W.F., 1993. Effects of motor unit losses on strength in older men and women. Adv. Neurol. 74, 868–874. Eisen, A., Entezari-Taher, M., Stewart, H., 1996. Cortical projections to spinal motoneurons: changes with aging and amyotrophic lateral sclerosis. Adv. Neurol. 46, 1396–1404. Erim, Z., Beg, M.F., Burke, D.T., de Luca, C.J., 1999. Effects of aging on motor-unit control properties. J. Neurophysiol. 82, 2081–2091. Friston, K.J., Frith, C.D., Passingham, R.E., Liddle, P.F., Frackowiak, R.S., 1992. Motor practice and neurophysiological adaptation in the cerebellum: a positron tomography study. Proc. Biol. Sci. 248, 223– 228. Fuchs, M., Wagner, M., Kohler, T., Wischmann, H.A., 1999. Linear and nonlinear current density reconstructions. Adv. Neurol. 16, 267–295.

A. Inuggi et al. / Neurobiology of Aging 32 (2011) 524–538 Grav de Peralta Menendez, R., Gonzalez Andino, S.L., 1998. Distributed source models: standard solutions and new developments. In: Uhl, C. (Ed.), Analysis of Neurophysiological Brain Functioning. Springer Verlag, New York, pp. 176–201. Heuninckx, S., Wenderoth, N., Debaere, F., Peeters, R., Swinnen, S.P., 2005. Neural basis of aging: the penetration of cognition into action control. J. Neurosci. 25, 6787–6796. Hsu, S.H., Huang, C.C., Tsuang, Y.H., Sun, J.S., 1997. Age differences in remote pointing performance. Percept. Mot. Skills 85, 515–527. Hutchinson, S., Kobayashi, M., Horkan, C.M., Pascual-Leone, A., Alexander, M.P., Schlaug, G., 2002. Age-related differences in movement representation. Arch. Neurol. 17, 1720–1728. Ikeda, A., Luders, H.O., Collura, T.F., Burgess, R.C., Morris, H.H., Hamano, T., Shibasaki, H., 1996. Subdural potentials at orbitofrontal and mesial prefrontal areas accompanying anticipation and decision making in humans: a comparison with Bereitschaftspotential. Adv. Neurol. 98, 206–212. Jenkins, I.H., Brooks, D.J., Nixon, P.D., Frackowiak, R.S., Passingham, R.E., 1994. Motor sequence learning: a study with positron emission tomography. Adv. Neurol. 14, 3775–3790. Jonides, J., Marshuetz, C., Smith, E.E., Reuter-Lorenz, P.A., Koeppe, R.A., Hartley, A., 2000. Age differences in behavior and PET activation reveal differences in interference resolution in verbal working memory. Adv. Neurol. 12, 188–196. Kaiser, L.G., Schuff, N., Cashdollar, N., Weiner, M.W., 2005. Agerelated glutamate and glutamine concentration changes in normal human brain: 1H MR spectroscopy study at 4 T. Adv. Neurol. 26, 665–672. Kawashima, R., Matsumura, M., Sadato, N., Naito, E., Waki, A., Nakamura, S., Matsunami, K., Fukuda, H., Yonekura, Y., 1998. Regional cerebral blood flow changes in human brain related to ipsilateral and contralateral complex hand movements—a PET study. Eur. J. Neurosci. 10, 2254–2260. Kornhuber, H.H., Deecke, L., 1964. Hirnpotentiala¨nderungen beim Menschen vor und nach Willkurbewegungen, dargestellt mit MagnetbandSpeicherung und Ruckwartsanalyse, in: Pflugers Arch, 281-52. Krampe, R.T., 2002. Aging, expertise and fine motor movement. Neurosci. Biobehav. Rev. 26, 769–776. Kristeva, R., Chakarov, V., Wagner, M., Schulte-Monting, J., HeppReymond, M.C., 2006. Is the movement-evoked potential mandatory for movement execution? A high-resolution EEG study in a deafferented patient. Arch. Neurol. 31, 677–685. Leventhal, A.G., Wang, Y., Pu, M., Zhou, Y., Ma, Y., 2003. GABA and its agonists improved visual cortical function in senescent monkeys. Science 300, 812–815. Madden, D.J., Whiting, W.L., Huettel, S.A., White, L.E., MacFall, J.R., Provenzale, J.M., 2004. Diffusion tensor imaging of adult age differences in cerebral white matter: relation to response time. Neuroimage 21, 1174–1181. Masliah, E., Mallory, M., Hansen, L., DeTeresa, R., Terry, R.D., 1993. Quantitative synaptic alterations in the human neocortex during normal aging. Neurology 43, 192–197. Mattay, V.S., Fera, F., Tessitore, A., Hariri, A.R., Das, S., Callicott, J.H., Weinberger, D.R., 2002. Neurophysiological correlates of age-related changes in human motor function. Adv. Neurol. 58, 630–635. Naccarato, M., Calautti, C., Jones, P.S., Day, D.J., Carpenter, T.A., Baron, J.C., 2006. Does healthy aging affect the hemispheric activation balance during paced index-to-thumb opposition task? An fMRI study. Adv. Neurol. 32, 1250–1256. Nachev, P., Wydell, H., O’neill, K., Husain, M., Kennard, C., 2007. The role of the pre-supplementary motor area in the control of action. Adv. Neurol. 1, T155–T163. Nielson, K.A., Langenecker, S.A., Garavan, H., 2002. Differences in the functional neuroanatomy of inhibitory control across the adult life span. Psychol. Aging 17, 56–71.

537

Nakata, H., Sakamoto, K., Ferretti, A., Gianni Perrucci, M., Del Gratta, C., Kakigi, R., Luca Romani, G., 2008. Somato-motor inhibitory processing in humans: an event-related functional MRI study. Neuroimage 39, 1858–1866. Oldfield, R.C., 1971. The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 9, 97–9113. Ottaviani, D., Tiple, D., Suppa, A., Colosimo, C., Fabbrini, G., Cincotta, M., Defazio, G., Berardelli, A., 2008. Mirror movements in patients with Parkinson’s disease. Mov. Disord. 23, 253–258. Peinemann, A., Lehner, C., Conrad, B., Siebner, H.R., 2001. Age-related decrease in paired-pulse intracortical inhibition in the human primary motor cortex. Neurosci. Lett. 255, 33–36. Picard, N., Strick, P.L., 1996. Motor areas of the medial wall: a review of their location and functional activation. Cereb. Cortex 6, 342–353. Picard, N., Strick, P.L., 2001. Imaging the premotor areas. Curr. Opin. Neurobiol. 11, 663–672. Poe, B.H., Linville, C., Brunso-Bechtold, J., 2001. Age-related decline of presumptive inhibitory synapses in the sensorimotor cortex as revealed by the physical dissector. Adv. Neurol. 255, 65–72. Rathelot, J.A., Strick, P.L., 2006. Muscle representation in the macaque motor cortex: an anatomical perspective. Proc. Natl. Acad. Sci. U.S.A. 103, 8257–8262. Reuter-Lorenz, P.A., Jonides, J., Smith, E.E., Hartley, A., Miller, A., Marshuetz, C., Koeppe, R.A., 2000. Age differences in the frontal lateralization of verbal and spatial working memory revealed by PET. J. Cogn. Neurosci. 12, 174–187. Riecker, A., Gröschel, K., Ackermann, H., Steinbrink, C., Witte, O., Kastrup, A., 2006. Functional significance of age-related differences in motor activation patterns. Neuroimage 32, 1345–1354. Rizzolatti, G., Luppino, G., Matelli, M., 1996. The classic supplementary motor area is formed by two independent areas. Adv. Neurol. 70, 45–56. Ryall, J.G., Schertzer, J.D., Lynch, G.S., 2008. Cellular and molecular mechanisms underlying age-related skeletal muscle wasting and weakness. Biogerontology 4, 213–228. Sailer, A., Dichgans, J., Gerloff, C., 2000. The influence of normal aging on the cortical processing of a simple motor task. Adv. Neurol. 55, 979–985. Schieber, M.H., 2001. Constraints on somatotopic organization in the primary motor cortex. J. Neurophysiol. 86, 2125–2143. Shibasaki, H., Hallett, M., 2006. What is the Bereitschaftspotential? Clin. Neurophysiol. 117, 2341–2356. Stanley, D.P., Shetty, A.K., 2004. Aging in the rat hippocampus is associated with widespread reductions in the number of glutamate decarboxylase67 positive interneurons but not interneuron degeneration. J. Neurochem. 89, 204–216. Toma, K., Matsuoka, T., Immisch, I., Mima, T., Waldvogel, D., Koshy, B., Hanakawa, T., Shill, H., Hallett, M., 2002. Generators of movementrelated cortical potentials: fMRI-constrained EEG dipole source analysis. Neuroimage 17, 161–173. Toma, K., Honda, M., Hanakawa, T., Okada, T., Fukuyama, H., Ikeda, A., Nishizawa, S., Konishi, J., Shibasaki, H., 1999. Activities of the primary and supplementary motor areas increase in preparation and execution of voluntary muscle relaxation: an event-related fMRI study. J. Neurosci. 19, 3527–3534. Waldvogel, D., van Gelderen, P., Muellbacher, W., Ziemann, U., Immisch, I., Hallett, M., 2000. The relative metabolic demand of inhibition and excitation. Adv. Neurol. 255, 995–998. Ward, N.S., Frackowiak, R.S., 2003. Age-related changes in the neural correlates of motor performance. Adv. Neurol. 126, 873–888. Ward, N.S., 2006. Compensatory mechanisms in the aging motor system. Ageing Res. Rev. 5, 239–254. Wildgruber, D., Erb, M., Klose, U., Grodd, W., 1997. Sequential activation of supplementary motor area and primary motor cortex during self-paced finger movement in human evaluated by functional MRI. Neurosci. Lett. 227, 161–164. Wu, T., Hallett, M., 2005. The influence of normal human ageing on automatic movements. J. Physiol. 255, 605–615.

538

A. Inuggi et al. / Neurobiology of Aging 32 (2011) 524–538

Yordanova, J., Kolev, V., Hohnsbein, J., Falkenstein, M., 2004. Sensorimotor slowing with ageing is mediated by a functional dysregulation of motor-generation processes: evidence from high-resolution event-related potentials. Adv. Neurol. 127, 351–362.

Yousry, T.A., Schmid, U.D., Alkadhi, H., Schmidt, D., Peraud, A., Buettner, A., Winkler, P., 1997. Localization of the motor hand area to a knob on the precentral gyrus. A new landmark. Brain 0, 141–157.