lesion location alters brain activation in chronically impaired stroke survivors

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NeuroImage 21 (2004) 924–935

Lesion location alters brain activation in chronically

impaired stroke survivors

Andreas R. Luft,a,b,* Sandy Waller,c Larry Forrester,c Gerald V. Smith,c Jill Whitall,c

Richard F. Macko,d,e Jorg B. Schulz,b and Daniel F. Hanleya

aDepartment of Neurology, Johns Hopkins University, Baltimore, MD 21287, USAbDepartment of Neurology, University of Tubingen, Tubingen 72076, GermanycDepartment of Physical Therapy, University of Maryland, Baltimore, MD 21201, USAdDepartment of Neurology, University of Maryland, Baltimore, MD, USAeDepartment of Veterans Affairs and the Baltimore VA Geriatric Research Education and Clinical Center (GRECC), USA

Received 25 June 2003; revised 2 October 2003; accepted 14 October 2003

Recovery of motor function after stroke is associated with reorganiza-

tion in central motor networks. Functional imaging has demonstrated

recovery-dependent alterations in brain activation patterns when

compared to healthy controls. These alterations are variable across

stroke subjects. Factors identified as contributing to this variability are

the degree of functional impairment, the time interval since stroke, and

rehabilitative therapies. Here, the hypothesis is tested that lesion

location influences the activation patterns. Using functional magnetic

resonance imaging, the objective was to characterize similarities or

differences in movement-related activation patterns in patients chroni-

cally disabled by cortical plus subcortical or subcortical lesions only.

Brain activation was mapped during paretic and non-paretic move-

ment in 11 patients with subcortical stroke, in nine patients with stroke

involving sensorimotor cortex, and in eight healthy volunteers. Patient

groups had similar average motor deficit as measured by a battery of

scores and strength measures. Substantial differences between patients

groups were found in activation patterns associated with paretic limb

movement: Whereas contralateral motor cortex, ipsilateral cerebellum

(relative to moving limb), bilateral mesial (cingulate, SMA), and

perisylvian regions were active in subcortical stroke, cortical patients

recruited only ipsilateral postcentral, mesial hemisphere regions, and

areas at the rim of the stroke cavity. For both groups, activation in

ipsilateral postcentral cortex correlated with motor function; in

subcortical stroke, the same was found for mesial and perisylvian

regions. Overall, brain activation in cortical stroke was less, while in

subcortical patients, more than in healthy controls. For non-paretic

movement, activation patterns were similar to control in cortical

patients. In subcortical patients, however, activation patterns differed:

the activation of non-paretic movement was similar to that of paretic

movement (corrected for side). The data demonstrate more differences

than similarities in the central control of paretic and non-paretic limb

movement in patients chronically disabled by subcortical versus

cortical stroke. Whereas standard motor circuitry is utilized in

subcortical stroke, alternative networks are recruited after cortical

stroke. This finding proposes lesion-specific mechanisms of reorgan-

1053-8119/$ - see front matter D 2004 Elsevier Inc. All rights reserved.

doi:10.1016/j.neuroimage.2003.10.026

* Corresponding author. Department of Neurology, Universitat Tubin-

gen, Hoppe-Seyler-Strasse 3, 72076 Tubingen, Germany. Fax: +49-7071-

967857.

E-mail address: [email protected] (A.R. Luft).

Available online on ScienceDirect (www.sciencedirect.com.)

ization. Optimal activation of these distinct networks may require

different rehabilitative strategies.

D 2004 Elsevier Inc. All rights reserved.

Keywords: Stroke; Hemiparesis; Sensorimotor cortex; Cerebellum; Func-

tional imaging; Chronic

Introduction

Recovery of motor function occurs in most patients after

hemiparetic stroke and is associated with reorganization of central

motor networks (Liepert et al., 2000; Nelles et al., 2001; Rijntjes

and Weiller, 2002). Activation patterns across these networks have

been characterized using functional MRI. Several studies described

the differences between brain activation patterns of patients and

healthy controls (Chollet et al., 1991; Cramer et al., 1997; Seitz et

al., 1998; Weiller et al., 1992, 1993). In recovered patients, three

patterns of activation have been identified likely representing

different mechanisms of reorganization: (1) enlarged activation in

primary motor cortex (M1) of the damaged hemisphere (contralat-

eral to movement). (2) Recruitment of secondary motor cortices

(SMA, premotor cortex, cingulate areas) or somatosensory cortex

in the lesioned hemisphere. (3) Recruitment of sensorimotor motor

cortex in the undamaged hemisphere ipsilateral to the moving limb

(Cao et al., 1998; Cramer et al., 1997; Rossini et al., 1998; Weiller

et al., 1993). During the phase of spontaneous recovery, lesioned

hemisphere (contralateral) motor cortex activation shrinks in a

subset of patients (Feydy et al., 2002) and may grow in others

(Cuadrado et al., 1999; Marshall et al., 2000).

Factors contributing to the variability of activation patterns

associated with hemiparetic movement in different subjects are

their individual degree of recovery (Ward et al., 2003) and the time

interval since stroke (Feydy et al., 2002). Some studies postulate or

indicate lesion location as another factor determining brain activa-

tion during paretic movement (Chen et al., 2000; Feydy et al.,

2002; Fries et al., 1993; Shelton and Reding, 2001). Several

A.R. Luft et al. / NeuroImage 21 (2004) 924–935 925

pathophysiological hypotheses have been proposed to explain this

influence: subcortical stroke may leave intracortical circuitry intact

thereby allowing for cortical reorganization to compensate func-

tional deficits (Byrnes et al., 2001). Cortical strokes may substan-

tially impair these mechanisms and require other brain areas to

mediate functional recovery. On the other hand, descending motor

pathways are more vulnerable at points of convergence in the

internal capsule and peduncles—regions injured in subcortical

stroke—as compared to corona radiata and motor cortex (Shelton

and Reding, 2001). In many studies mapping the motor system

during paretic movement, patients with various lesion distributions

and morphologies are being combined—in part due to the paucity

of eligible candidates for fMRI studies.

To gain a better understanding of the interrelation between

lesion location and the functioning of the lesioned central motor

system, subject samples corrected for other influencing factors—

time-since-stroke and degree of recovery—have to be studied.

Here, we investigate how lesion location (pure subcortical versus

cortical plus subcortical) affects the neural control of paretic limb

movement in patient groups with similar paresis and degree of

recovery at a time when all potential for spontaneous recovery has

been realized, hence, the patients are clinically stable.

Materials and methods

Subjects

Twenty patients (age: 62 F 9 years, mean F SD, 9 females, 11

males), who suffered a first-ever cortical or subcortical stroke 53.2F46.3 months (mean F SD) before inclusion, underwent fMRI of

bilateral elbow movement. All patients were hemiparetic with

residual movement from a single ischemic stroke, and were selected

based on the presence of residual hemiparesis, completion of all

conventional rehabilitation programs, and adequate language and

neurocognitive function to understand consenting and study-related

Fig. 1. For each patient group, the distribution of lesions is shown superimposed o

indicate in how many of 9 cortical stroke and 11 subcortical stroke patients, resp

instructions. Patients with more than one symptomatic stroke, other

neurological disease, chronic pain, emotional disorders, and/or

metal implants were excluded. All patients received comparable

conventional rehabilitation therapy during the initial 6 months after

their stroke. All subjects, recalling the time before their stroke, were

right-handed according to the Oldfield inventory.

Upper extremity motor function was assessed at the time of

study enrollment using a test battery including the upper-extremity

portion of the Fugl-Meyer Motor Performance assessment (scores

0–66, best) (Fugl-Meyer et al., 1975), the weight section of the

Wolf Motor Arm test (Wolf weight) (Wolf et al., 2001), the time to

complete the Wolf task battery (Wolf time), and strength of

shoulder and elbow extension measured as the peak force (in kg)

in three consecutive trials using a dynamometer. A combined

functional score consisting of the sum of the quotients individual

score/mean score per group was entered into a general linear

model (see below). Because medical records for patients with

distant strokes were not available, the degree of initial impairment

(acutely after stroke) was assessed by asking the patient to

subjectively categorize initial disabilities (‘‘no movement’’, ‘‘major

impairment/not able to lift arm’’, ‘‘minor impairment/able to lift

arm’’).

The patient sample was stratified according to whether the

lesion involved motor cortex F subcortical regions (further named

cortical group) or only subcortical regions (subcortical group,

subcortical regions were all areas medial to the insular cortex and

ventral to the corpus callosum, that is, basal ganglia and descend-

ing pathways). Fig. 1 shows the average stroke locations per group.

Table 1 summarizes the patient characteristics and details of lesion

location.

Patients were compared to a group of healthy volunteers (five

males, three females, age 55 F 8.5 years). Full written informed

consent was obtained from all subjects in accordance with the

Declaration of Helsinki. The study protocol and the consent forms

were approved by the participating institutions (Johns Hopkins

University and University of Maryland).

nto an averaged anatomical image derived from all patients. Shades of gray

ectively, a particular area was lesioned (brighter—injury more frequent).

Table 1

Patient characteristics

Case

number

Age Sex Side of

stroke

Months

since

stroke

Location of stroke Fugl-Meyer

score

Shoulder

strength

(kg)

Elbow

strength

(kg)

Wolf

weight

Wolf

time

(s)

Lesion

volume

(Al)

Subcortical

1 59 f R 50.9 posterior putamen, posterior limb of int. caps. 25 2.5 6.8 0.5 72.0 5135

2 68 f R 21.0 posterior putamen, posterior limb of int. caps. 42 6.4 6.1 0.0 29.5 2673

3 37 m L 9.2 pallidum, mid putamen, knee of int. caps. 31 10.2 22.3 0.9 53.1 3913

4 42 f R 60.1 putamen, int. caps. 49 6.1 8.2 2.7 11.8 9835

5 66 m L 9.6 putamen, ant limb of int. caps

(small extension into corona rad.)

56 15.4 13.6 4.1 18.7 6726

6 67 m R 33.2 ant. putamen, head of caudate, lateral thalamus 22 3.4 5.2 1.9 72.3 909

7 77 m R 91.2 upper pons (midline, extending to R more than to L) 54 14.5 20.4 4.1 3.7 981

8 64 f R 16.1 lower pons 25 5.4 5.0 0.0 70.7 776

9 75 m L 50.5 post limb of int. caps. 35 8.2 8.2 1.4 25.2 1664

10 74 m R 180.6 post limb of int. caps. (small extension into corona rad.) 26 3.4 6.6 0.0 33.7 162

11 71 f R 156.6 central corona radiata, upper pole of int. caps. 26 7.0 5.0 0.0 74.4 8018

Cortical

12 77 m L 38.2 parietal lobe, post. insula, int caps., putamen 36 6.1 8.0 0.0 66.2 248 556

13 61 f R 31.9 precentral, post. part of frontal lobe, insula,

putamen, int. caps.

21 13.0 0.0 1.6 105.0 104 988

14 61 m R 57.3 postcentral, corona rad., int. caps., putamen 28 10.7 13.2 0.5 21.0 48 880

15 76 m R 37.6 precentral, post. part of frontal lobe,

superior temp. gyrus,

corona rad., int. caps.

24 8.6 9.8 0.0 66.3 231 906

16 62 m R 79.2 pre-, postcentral, post. part of frontal lobe, int. caps.,

caudatum, putamen, (complete MCA territory)

27 5.0 0.0 0.0 55.9 238 308

17 54 m R 10.7 pre-, postcentral, caudatum 46 19.5 10.7 1.8 28.6 62 389

18 64 f L 71.5 premotor cortex, inf. frontal gyrus, ant. temporal lobe,

int. caps., caudatum, putamen

20 2.3 7.5 0.0 88.4 130 954

19 47 m R 9.8 pre-, postcentral, post. part of frontal lobe,

sup. temp. gyrus,

int. caps., caudatum, putamen (complete MCA territory)

23 3.2 6.6 0.0 89.2 245 709

20 75 m R 49.7 pre-, postcentral, premotor, insula, ant. putamen 43 6.6 7.3 1.8 19.5 63 128

A.R. Luft et al. / NeuroImage 21 (2004) 924–935926

fMRI technique and paradigms

fMRI technique and paradigms were described before (Luft et

al., 2002). In brief, a custom-made plexiglass scaffold was used

inside the scanner to ensure constant movement range and plane of

motion and to limit concomitant head motion by fixation of arm and

body. fMRI scanning was performed using a 1.5 Tesla scanner

(Gyroscan, Philips, Eindhoven, The Netherlands) at the F.M. Kirby

Center for Functional Brain Imaging, Kennedy Krieger Institute,

Baltimore. AT1-weighted 3D-MPRAGE sequence (TR 8.2 ms, TE

3.7 ms, flip angle 8j, NEX 1, matrix 256 � 256, voxel-resolution:

1 � 1 � 1 mm3) was obtained for anatomical mapping. BOLD-

weighted EPI sequences (TR 3 s, TE 40 ms, matrix: 64 � 64, slice

thickness 5 mm, pixel resolution 3.75 � 3.75, 30–36 slices to

obtain whole brain coverage, interleaved slice timing) were ac-

quired in axial orientation. For each movement paradigm, 60 scans

were acquired over a period of 3 min without interscan delay. One

measurement consisted of three cycles of rest and 10 elbow move-

ments beginning with rest. Elbow movements were acoustically

cued by computer-generated beeps (one every 3 s, beep duration 0.1

s). This low frequency of movement allowed all patients to perform

the movement without fatiguing, as tested before the scanning

procedure. Elbow flexion started at 45j and ended at 60j–75j and

was followed by return extension. The movement range was

adjusted according to the patient’s ability, again with the goal of

avoiding fatigue during the measurement. The plane of motion was

in parallel to the longitudinal axis of the supine body and angled

60j off the horizontal plane. Non-paretic and paretic limbs were

assessed separately. Likewise, control subjects moved their right

and left limbs separately. Performance was video-taped to monitor

for compliance. Subjects kept their eyes closed during scanning.

Before or after the fMRI session, biceps and deltoid EMG

activity were recorded bilaterally using surface electrodes while the

patient contracted the hemiparetic limb in a mock setup similar to

the fMRI setting. Neither was there evidence for cocontraction in

EMG tracings, nor did any patient show overt mirror movement

during the mock or the fMRI session (as monitored with contin-

uous video footage).

fMRI analysis

BrainVoyager (Brain Innovation B.V., Maastricht, The Nether-

lands) was used to analyze fMRI data according to standard

protocols.

Preprocessing

Functional images were corrected for motion and slice timing,

and temporally (high pass filter, linear trend removal) and spatially

(FWHM 4 mm) smoothed. Effectiveness of motion correction was

assessed by viewing post-correction movies of functional image

series. For none of the subjects did this procedure reveal any

visible head motion in the corrected data sets. Images were then


transformed to Talairach space, first, by applying rigid body

transformations (translation, rotation), followed by manual defini-

tion of Talairach landmarks, and third, by scaling of 12 landmark-

defined subvolumes into Talairach space.

Statistical analysis

Movement and rest periods were modeled by a boxcar function

with hemodynamic response modification (predictor movement).

Multistudy general linear models (GLM) were used to extract foci

of activation. Several GLMs were computed:

(1) a GLM including either paretic or non-paretic movement

paradigms of all patients per group (cortical, subcortical). Image

Fig. 2. Average activation maps per movement paradigm and group are shown [mu

two rows, data from subcortical (yellow) and cortical patients (red) are superimp

outlined on images in the top row (pink line). During paretic movement in cortica

(filled red arrow), in the intact ipsilateral hemisphere (open red arrow), and in regio

show more overall activation, especially in contralateral motor cortex (filled yellow

perisylvian areas. During non-paretic limb movement (middle row), both groups

activation. Subcortical stroke patients recruit additional mesial hemisphere and per

(data from right- and left sided movement combined; data from right elbow mov

SMA, and bilateral cerebellar activation.

data of patients with left hemisphere lesions were flipped about the

mid-sagittal line, such that all subjects were considered to have a

right-sided lesion. Independent variables were movement and a

constant term.

(2) A GLM combining two groups of subjects (cortical versus

subcortical patients or patients versus volunteers) for either para-

digm (paretic, non-paretic). For comparisons between patients and

volunteers, left- and right-sided movement trials were averaged in

voluenteers after flipping of the data about the mid-sagittal line

moving limb of the brain was always contralateral to the moving

limb. Independent variables of these GLMs were movement and

constant. Appropriate contrasts were formed to extract activation

ltisubject GLM, random effects, threshold P < 0.05 (corrected)]. In the upper

osed. The extent of the maximum lesion of patients with cortical stroke is

l stroke patients (top row), activation is found adjacent to the stroke cavity

ns on the medial surface of the hemispheres. Patients with subcortical stroke

arrow), ipsilateral cerebellum (open yellow arrow), mesial hemisphere, and

of patients demonstrate contralateral motor cortex and ipsilateral cerebellar

isylvian areas. Healthy controls show during elbow movement (bottom row)

ement were flipped about the mid-sagittal line), contralateral motor cortex,

Table 2

Average activation per group and task

Side Anatomical/functional Brodmann Talairach coordinate

region areax y z

Cortical patients-paretic

Contralateral cingulate gyrusa 31 17 �31 41

Contralateral fusiform gyrus 37 32 �47 �8

Ipsilateral S1 2 �37 �27 31

Ipsilateral paracentral lobule 5 �19 �43 50

Ipsilateral posterior cingulate 29 0 �38 18

Ipsilateral cingulate gyrus 24 �18 �16 38

Ipsilateral cingulate gyrus 31 �10 �10 43

Subcortical patients-paretic

Contralateral S1 3 47 �21 55

Contralateral M1 4 34 �21 56

Contralateral SMA 6 3 �21 55

Contralateral insula 13 36 �35 19

Contralateral cingulate gyrus 23 6 �23 31


Contralateral precentral gyrus 44 46 2 8

Bilateral paracentral lobule 31 F6 �23 45

Bilateral post. cingulate 29 F2 �39 19

Bilateral medial geniculate

body

thalamus F18 �23 �2

Ipsilateral precentral gyrus 6 �53 �3 8

Ipsilateral insula 13 �48 �34 19

Ipsilateral sup. temporal gyrus 22 48 �26 3

Bilateral quadrangular lobe cerebellum F10 �55 �7

Bilateral simple lobule cerebellum F18 �69 �17

culmen of vermis cerebellum 0 �56 �13

Cortical patients-nonparetic

Contralateral M1 4 �28 �24 51

Contralateral S1 2 �34 �33 40


Contralateral sup. temporal gyrus 42 �58 �24 17

Ipsilateral quadranguar lobe cerebellum 20 �47 �21

Ipsilateral culmen of vermis cerebellum 5 �53 �10

Subcortical patients-nonparetic

Contralateral M1 4 �46 �5 43



Contralateral SMA 6 �2 �19 50

Contralateral postcentral gyrus 5 �29 �42 63

Contralateral insula 13 �37 �23 15

Contralateral anterior cingulate 32 �2 25 �9

Contralateral fusiform gyrus 37 �31 �44 �13

Contralateral middle frontal gyrus 46 �40 33 12

Contralateral inferior frontal gyrus 47 �52 23 �1

Contralateral VL nucleus thalamus �19 �12 5

Ipsilateral M1 4 44 �14 45

Ipsilateral S1 2 38 �37 58

Ipsilateral premotor cortex 6a 41 3 38

Ipsilateral inferior frontal gyrus 9 52 5 30

Ipsilateral middle temporal

gyrus

19 45 �58 15

Ipsilateral inferior temporal

gyrus

20 46 �2 �32

Ipsilateral fusiform gyrus 37 44 �52 �20

Ipsilateral superior temporal

gyrus

39 45 �56 17

Ipsilateral inferior parietal

lobule

40 43 �41 40

Side Anatomical/functional Brodmann Talairach coordinate

region areax y z

Subcortical patients-nonparetic

Ipsilateral superior temporal

gyrus

41 47 �26 13

Ipsilateral inferior frontal

gyrus

46 39 34 14

Ipsilateral VL nucleus thalamus 11 �16 2

Ipsilateral culmen cerebellum 8 �53 �12

Ipsilateral quadrangular

lobule

cerebellum 24 �38 �27

Ipsilateral declive cerebellum 5 �76 �14

Ipsilateral pyramis cerebellum 5 �83 �24

Volunteers—left/right

Contralateral M1 4 29 �27 60


Contralateral SMA 6 2 �5 60

Contralateral insula 13 47 �23 24


Ipsilateral quadrangular

lobule

cerebellum �18 �46 �20

Contralateral quadrangular

lobule

cerebellum 33 �52 �24

a Activation focus adjacent to average stroke cavity.

Table 2 (continued)


present during both (conjunction map) or either one task (differ-

ence map: group A–group B, t value in map A greater than in map

B, yielding regions in which activation is more likely in group A).

Contrasts were balanced for different sample sizes.

(3) A GLM combining paretic and non-paretic or left- and

right-sided movement paradigms per group of patients (cortical,

subcortical) or volunteers, respectively. Image data of right-sided

movement paradigms were flipped about the mid-sagittal line (left

side of brain = contralateral to moving limb). The independent

variables of this model were movement and constant. Appropriate

contrasts were formed to extract activation present during both

(conjunction map) or either tasks (difference map).

(4) Similar to GLM 1. The contrast across the covariate

movement was then weighted according to the subject’s combined

functional score (see above), thereby extracting voxels with a

linear (direct or indirect) correlation between the functional score

and the parameter estimate for movement (Ward et al., 2003).

Random effects analysis with a uniform probability threshold

of 0.05 (corrected for multiple comparisons across the entire

brain) was applied. For visualization of functional data, T1-

weighted high-resolution image series were averaged per group.

The Talairach Daemon (Lancaster et al., 2000) with a query range

of 5 mm was used to identify cortical, subcortical, and cerebellar

regions.

Results

General variables characterizing subject groups

Subcortical and cortical stroke patients did not differ in age

(P = 0.93), time interval since stroke (P = 0.38), side of stroke

(subcortical: left/right 3/8, cortical: 2/7), deficit at the time of

stroke (P = 0.34), or motor function and strength scores at the

Fig. 3. Overall differences between activation patterns per paradigm and

group are demonstrated by plotting the number of significant voxels in

conjunction (black) and difference (gray) multisubject GLMs. The

conjunction GLM yields voxels, which are likely active in both groups/

paradigms. In the difference GLM, voxels more likely to be active in group

A than in group B (positive values) or vice versa (negative values) are

extracted.


time of study enrollment (FM: 35.5 F 12.6 vs. 29.8 F 9.6, P = 0.3;

Wolf weight: 1.4 F 1.6 vs. 0.6 F 0.8 P = 0.2; Wolf time: 42.3 F26.9 vs. 60.0 F 31.5, P = 0.2; shoulder strength: 7.5 F 4.3 vs.

Fig. 4. Multisubject conjunction GLM maps showing activation present in both,

paretic limb: (a) for cortical stroke patients only a small area in the contralater

postcentral gyri for patients with subcortical stroke.

8.3 F 5.4, P = 0.7; elbow strength: 9.8 F 6.2 vs. 7.9 F 3.8, P =

0.5). Stroke patient and volunteer groups did not differ in age or

gender distribution.

Activation maps in patients and volunteers (GLM 1)

Average activation maps for each group of patients and controls

are presented in Fig. 2. Activation foci and respective Talairach

coordinates are listed in Table 2.

Paretic limb

Activation of contralateral primary motor cortex (M1, BA 4),

primary somatosensory cortex (S1, BA 3, 1, 2) and supplementary

motor area (SMA) was consistently found in subcortical stroke

patients and controls (Fig. 2). In contrast, patients with cortical

stroke did show an activation focus in the contralateral hemisphere,

medial and ventral to the primary motor cortex (Fig. 2). This

activation mapped to the rim of the stroke cavity (outlined in Fig.

2). Other areas activated in cortical stroke were bilateral mesial

hemisphere regions (cingulate gyrus, paracentral lobule) and ipsi-

lateral S1 (BA 2) and premotor cortex (BA 6a). In subcortical

patients, besides activation in contralateral sensorimotor cortex,

activation was found in bilateral mesial hemispheres, bilateral

insulae, and ipsilateral premotor cortex (Table 2). Control subjects

showed additional activation of the contralateral insula and ipsi-

lateral S2.

The cerebellum was active in controls and subcortical stroke

with a strong ipsilateral dominance (Fig. 2). Foci mainly mapped to

quadrangular and simple lobules and the vermis. No cerebellar

activation was found in cortical stroke patients even after lowering

the probability threshold to 0.0001 (uncorrected).

Non-paretic limb

During non-paretic limb movement, both cortical and subcor-

tical patients showed contralateral M1 and S1 and ipsilateral

cerebellar (quadrangular lobe) activation (Fig. 2). In subcortical

patients, several additional regions were active (Table 2). Among

healthy controls (right and left averaged) and stroke patients moving their

al motor cortex is significant, (b) larger regions are extracted in pre- and

A.R. Luft et al. / NeuroImag930

those were ipsilateral sensorimotor areas, mesial hemisphere, and

regions in the temporal lobe.

Comparison: patients versus healthy volunteers (GLM 2)

Cortical stroke

During paretic limb movement, less voxels were activated in

cortical stroke patients than in controls (number of voxels in the

difference map cortical—control, Fig. 3). The difference GLM

showed that activation of contralateral M1, premotor cortex,

precuneus (BA 7), and bilateral cerebellum was more likely in

controls, whereas activation of the ipsilateral S1 (BA 2) was more

probable in cortical stroke patients than in controls. The conjunc-

tion GLM—areas active in both, volunteers and cortical patients—

extracted voxels in the contralateral S1 (BA 3, Fig. 4a).

Non-paretic movement produced similar activation maps be-

tween cortical stroke patients and controls. No activated voxels

were found in the difference GLM. The conjunction GLM

revealed activation of the ipsilateral cerebellum (quadrangular

lobule).

Fig. 5. Multisubject GLM maps (conjunction or difference as labeled) comparing

data is flipped about the mid-sagittal line). (a) In cortical stroke patients, a small are

map shows cerebellar activation to be more likely during non-paretic movemen

contralateral motor cortex, mesial areas, and cerebellum are found.

Subcortical stroke

Unlike cortical stroke patients, subcortical patients presented

more overall brain activation as compared to volunteers (Fig. 3).

Regions in which activation was more likely than in controls were

contralateral SMA, ipsilateral S1 (BA 3), ipsilateral insula (BA

13), bilateral mesial hemisphere areas (BA 7, 29), bilateral

superior temporal gyrus (BA 41), and bilateral cerebellum (simple

lobule). Conjunction analysis revealed congruent activation of

contralateral M1, S1, S2 (BA 40), SMA, bilateral insula (BA

13), and ipsilateral cerebellum in both subcortical stroke patients

and volunteers (Fig. 4b).

The comparison of non-paretic movement-related brain activa-

tion in subcortical patients and controls revealed differences and

similarities. The difference GLM extracted as many voxels as the

conjunction GLM (Fig. 3). Areas more likely to be active in

patients were all in the ipsilateral hemisphere including ipsilateral

M1, S1, BA 5, 9, 13, 21, 39, 41, and bilateral cerebellum

(quadrangular lobule). The conjunction map showed activation in

contralateral M1, S1, S2 (BA 40), SMA, bilateral insula (BA 13),

and ipsilateral cerebellum (quadrangular lobule).

e 21 (2004) 924–935

paretic and non-paretic movement per patient group (non-paretic movement

a of congruent activation is identified in the precentral gyrus. The difference

t. (b) In subcortical stroke patients, large areas of congruent activation in

Fig. 6. Multisubject GLM maps comparing paretic limb activation patterns in cortical and subcortical stroke patients are shown. Activation of contralateral

cortical stroke.


Comparison: paretic versus non-paretic movement (GLM 3)

Whereas subcortical stroke patients presented high congruence

between overall brain activation during paretic and non-paretic

movement, little congruence was found in cortical stroke patients

(Fig. 3). In cortical stroke, only the contralateral postcentral gyrus

(BA 2) was active in both paretic and non-paretic movement

(Fig. 5a, left). The difference GLM (non-paretic – paretic)

revealed activation in contralateral BA 9 and 37 and in bilateral

cerebellum (quadrangular and simple lobules, Fig. 5a, right). In

subcortical stroke patients, the conjunction GLM between paretic

and non-paretic movement paradigms showed congruent regions:

contralateral M1, S1, premotor cortex, bilateral S2 (BA 40),

bilateral SMA, bilateral insula (BA 13), ipsilateral cingulate

gyrus (BA 29 and 31), and bilateral cerebellum (simple lobule)

(Fig. 5b, left and right). The difference GLM (non-paretic–

paretic) revealed activation in contralateral SMA, ipsilateral

motor cortex and ipsilateral cerebellum is more likely in subcortical than in

Fig. 7. Multisubject GLMs with the combined functional score as covariate are sh

better motor function are indicated in red for cortical and yellow for subcortical

correlates with the functional score in cortical patients (filled red arrow). In patien

hemisphere regions (cingulum), and in ipsilateral postcentral gyrus (yellow arrow

premotor cortex (BA 6a), and bilateral superior frontal gyri

(BA 8, 10) (data not shown).

Comparison: cortical stroke versus subcortical stroke

(GLM 2)

Paretic arm

There was more overall brain activation in subcortical stroke

than in cortical stroke (Fig. 2). The number of voxels more likely

to be active in subcortical than in cortical stroke was higher than

the number of voxels in the conjunction GLM (Fig. 3). The

difference GLM (subcortical–cortical) extracted voxels in contra-

lateral M1, S1, insula (BA 13), ipsilateral superior temporal gyrus

(BA 22), and bilateral cerebellum (quadrangular and semilunar

lobules) (Fig. 6). The conjunction GLM showed activation in

contralateral S1 (BA 3), ipsilateral S2 (BA 40), and bilateral

cingulate gyri (BA 31) (data not shown).

own. Regions in which activation during paretic movement was related to

stroke patients. Activation in ipsilateral hemisphere S1 (BA 2, red arrow)

ts with subcortical stroke, the GLM extracted voxels in perisylvian, mesial

).

Table 3

Correlation of activation and combined functional score (GLM 4)

Side Anatomical/functional Brodmann Talairach

region areax y z

Cortical patients


Subcortical patients

Contralateral paracentral lobule 5 15 �35 49

Contralateral insula 13 44 8 7

Contralateral middle temporal gyrus 22 51 �30 6

Contralateral cingulate gyrus 23 5 �22 30

Contralateral precuneus 31 17 �40 30


Ipsilateral premotor cortex 6a �37 �5 42

Ipsilateral insula 13 �40 �6 18


Non-paretic arm

For non-paretic limb movement, activation patterns also dif-

fered between cortical and subcortical stroke patients (Fig. 2).

Regions more likely to be activated in subcortical stroke than in

cortical stroke (difference GLM) were contralateral M1, premotor

cortex (BA 6a), S1 (BA 3), and ipsilateral insula (BA 13). The

conjunction map revealed common activation of the ipsilateral

cerebellum (quadrangular lobule) (data not shown).

Correlation brain activation-functional score (GLM 4)

Regions in which activation correlated directly with the com-

bined functional score were identified for both cortical and

subcortical patients (Fig. 7). In cortical stroke patients, the ipsilat-

eral somatosensory cortex (S1, BA 2) was significant. In patients

with subcortical stroke, ipsilateral somatosensory (BA 2) and

premotor areas (BA 6) as well as mesial hemisphere and peri-

sylvian regions were more active in patients with better functional

score (Table 3).

Few regions were identified in which the parameter estimate

was inversely correlated with the combined functional score (more

activation, worse arm function). In cortical stroke patients, these

were ipsilateral precuneus (Talairach coordinates BA 31:�22/�77/

26, 19:�37/�74/36), in subcortical stroke patients, a small area in

the contralateral SMA (BA 6/8: 2/43/39).

Discussion

The main finding of this study is that activation patterns

associated with paretic limb movement differ in patients with

cortical (plus subcortical) versus subcortical lesions despite similar

chronic motor impairment. Secondly, activation patterns associated

with non-paretic limb movement differ from healthy control in

subcortical but not in cortical stroke patients. Subcortical stroke

patients demonstrate homology between activation patterns of

paretic and non-paretic movement.

Activation associated with paretic limb movement

In subcortical stroke, the activation pattern during paretic

movement was characterized by involvement of contralateral

motor cortex and ipsilateral cerebellum, representing standard, that

is, physiological motor circuitry, which was also found to be active

in controls. Additionally, activation was observed in ipsilateral pre-

and postcentral areas, bilateral perisylvian, and mesial regions.

Activation levels in the latter areas and in ipsilateral postcentral

gyrus were related to motor functional scores. Our data do not

confirm for chronic stroke patients, what has been reported in acute

stroke by Small et al. (2002), that is, that ipsilateral cerebellar

recruitment predicts good arm function (nine subcortical and five

cortical strokes). However, our analysis may be insensitive to

interrelation between activation and arm function because our

sample did not include subjects with complete motor recovery.

Therefore, the conclusion seems unjustified that contralateral

motor cortex and cerebellum are irrelevant to motor control of

paretic limb movement in subcortical stroke.

In a longitudinal study, Feydy et al. (2002) found widespread

activation in bilateral sensorimotor cortex (SMC), frontal and

mesial regions during the acute stage after stroke. With progressive

recovery, activation in ipsilateral, frontal, and mesial regions

disappeared while the contralateral SMC focus remained (progres-

sive focusing). In other subjects, widespread activation persisted.

Even, other subjects showed only contralateral SMC activation

already in the acute stage (initial focusing). There was no clear

association with the success of recovery. But, patients with M1

lesion were more likely to show persistence of widespread activa-

tion. Our data demonstrate a different pattern in stroke patients

with chronic impairment: widespread activation was a hallmark of

subcortical stroke whereas cortical stroke showed activation in few

areas, among those bilateral mesial regions and ipsilateral S1. This

discrepancy to the data of Feydy et al. suggests that activation

patterns may change between 6 months (last mapping in the study

by Feydy et al.) and 4.4 years (mean stroke-study interval in our

study). But, in view of limited sample sizes of both studies,

incomparabilities between the subject samples or fMRI paradigms

(hand or elbow or shoulder movements were used by Feydy et al.)

may simply account for divergent results.

Widespread activation in subcortical stroke, similar to our data,

was previously described in patients with striatocapsular infarction

and complete motor recovery (Weiller et al., 1992). In this study,

activation during finger-to-thumb opposition movement was found

in ipsilateral premotor, perisylvian (insula, BA 40) and mesial

regions (cingulate). Our data show similar activation patterns for

chronically impaired subjects performing elbow movement. Due to

these similarities between fully recovered and chronically impaired

subjects, one may be tempted to assume that brain activation is

unrelated to motor function. But this view may be too simplistic.

Other and in part unknown factors influence brain activation

during paretic movement as well as recovery itself. Our data

suggest that activation of regions, such as ipsilateral postcentral

gyrus, perisylvian, or mesial regions, is related to better motor

function; likely, more such areas exist (Small et al., 2002) and

might have been identified here if the sample included fully

recovered subjects.

Apart ipsilateral postcentral gyrus recruitment, cortical stroke

patients presented different patterns of activation than subcortical

stroke. No activation was found in standard corticocerebellar

circuits (contralateral SMC, ipsilateral cerebellum). It seems

expected that patients with motor cortex lesions cannot activate

the motor cortex secondary to critical tissue loss. However,

activation in cortex adjacent to the stroke cavity has been

reported (Cramer et al., 1997). Our data clearly support this

observation (Fig. 2). These adjacent regions represent cortical

areas which, in the intact brain, belong to premotor, frontal, or


postcentral (somatosensory) cortices. Which regions and to what

extent they are recruited in the individual patient, may depend on

lesion distribution. Movement-related activation of cortex adja-

cent to the stroke cavity may reflect the brain’s attempt to

compensate for lost cortical function. But, anatomically, these

areas have different projections as compared to M1, especially

regarding their corticocerebellar projection. Such projections may

or may not build (or become unmasked) during recovery. The

absence of cerebellar activation in our data suggests that these

projections are not established in chronically impaired cortical

stroke patients.

Despite inoperative physiological corticocerebellar circuits,

functional recovery occurred during the post-stroke period. Other

brain circuits than the standard, which is active in subcortical

stroke, may mediate motor function in cortical stroke patients.

Our candidate region is the ipsilateral postcentral gyrus. Interest-

ingly, cortical as well as (to a lesser degree, Fig. 2) subcortical

stroke patients showed activation in ipsilateral postcentral gyrus

which correlated with motor function. Several studies have

reported activation in the intact hemisphere ipsilateral to the

paretic limb (Cao et al., 1998; Chollet et al., 1991; Cramer et

al., 1997; Green et al., 1999; Honda et al., 1997; Marshall et al.,

2000; Nelles et al., 1999). Recruitment of ipsilateral hemisphere

regions may represent the brain’s attempt to compensate for lost

circuitry via transcallosal reorganization. However, the impor-

tance of ipsilateral recruitment during recovery from hemiparesis

is disputed (Herholz and Heiss, 2000). The presence of MEP

responses in the paretic limb upon stimulation of the intact

hemisphere correlated with poor motor function in several studies

(Hallett, 2001; Turton et al., 1996). Ipsilateral activation may be a

transient phenomenon being high early after stroke and then

decaying with progressive spontaneous recovery (Cuadrado et

al., 1999; Feydy et al., 2002; Marshall et al., 2000). Effective

rehabilitative therapy in chronically impaired stroke patients can

shift motor cortex activation from the ipsilateral to the contralat-

eral side (Carey et al., 2002). Our sample of chronically impaired

patients can be considered as poor recoverers. This group may

have ipsilateral recruitment because recovery remained incom-

plete. That ipsilateral activation is directly related to motor

function suggests that it is required to control the limb while it

is hemiparetic. In patients with full recovery, it may have

disappeared because contralateral areas have taken over. Our data

suggest that this phenomenon of reorganization may be a com-

mon feature of cortical and subcortical stroke.

Activation associated with non-paretic limb movement

Activation patterns associated with non-paretic limb movement

differed from healthy control only in subcortical stroke. In these

patients, activation of paretic and non-paretic movement was

similar, whereas in cortical stroke it is not (Fig. 2). Regions

differentially activated in subcortical non-paretic versus healthy

control movement were mainly in the ipsilateral hemisphere (S1,

M1, and perisylvian regions) and in bilateral cerebellum. Differ-

ences between activation patterns associated with paretic and

nonparetic movement have been described previously. Cramer et

al. (1997) observed decreased activation in sensorimotor cortex

during non-paretic hand movement. Changes in motor cortex

somatotopy that parallel spontaneous recovery have been identified

by transcranial magnetic stimulation of the intact hemisphere

(Traversa et al., 1997). Weiller et al. (1992) found increased

activation in the contralateral hemisphere (insula, prefrontal-BA

46, premotor cortices, BA 40, and anterior cingulate) in patients

with striatocapsular infarction moving their intact limb. Our data

identify the ipsilateral (lesioned) hemisphere as being distinctly

activated by non-paretic limb movement.

Several hypotheses are being proposed to explain alterations

in non-paretic activation patterns. Our data do not support the

notion that recruitment of intact hemisphere networks for paretic

limb movement affects non-paretic limb activation patterns:

cortical patients had stronger intact hemisphere recruitment dur-

ing paretic limb movement but no detectable difference to

controls when moving the non-paretic side. An alternative expla-

nation is that altered activation patterns reflect (minor) functional

impairments of the non-paretic limb (Colebatch and Gandevia,

1989; Jones et al., 1989). These impairments are thought to be

the consequence of transcallosal metabolic depression (Hoedt-

Rasmussen and Skinhoj, 1964). A third interpretation builds on

behavioral modifications adopted by disabled patients, for exam-

ple, the overuse of the intact limb. Accordingly, structural

plasticity can be observed in contralateral (intact) hemisphere of

rodents after unilateral cortical lesion (Jones and Schallert, 1994).

Why in subcortical stroke patients, mechanisms leading to reor-

ganization of the activation associated with non-paretic movement

are more prominant than in stroke patients, cannot be resolved

here. However, it should be mentioned in this context that Feydy

et al. (2002) did not find any differences in activation patterns of

non-paretic and healthy control movement.

Methodological issues and limitations

When comparing the present data to other studies, one has to

consider the movement paradigm implemented here. Most studies

investigate distal limb movements (Cramer et al., 1997; Feydy et

al., 2002; Small et al., 2002). Patients with chronic hemiparesis,

like those studied here, often have more difficulty with distal than

with proximal (elbow) movement. Elbow movement also allows

for a more precise definition of mechanical parameters of move-

ment such as plane, freedom, and angle of motion. Our proprietary

scaffold used inside the scanner was designed to keep these

parameters constant and comparable across subjects. Only the

movement range was slightly adjusted for some patients, who

could not move the elbow without shoulder/trunk coactivation.

Range was considered the parameter least likely to affect brain

activation as opposed to movement rate or complexity (Rao et al.,

1996; Schlaug et al., 1996; Wexler et al., 1997).

Comparing distal and proximal arm movement, fMRI studies in

healthy volunteers showed differential activation of primary motor

cortex (Lotze et al., 2000; Rao et al., 1995) and cerebellum (Grodd

et al., 2001). In a preliminary study, we compared the elbow

paradigm employed here to conventional finger tapping (Luft et

al., 2002). Elbow movement produced activation patterns across

motor regions, which were similar to those of finger movements.

Both movement types differed largely from knee movement.

Finger movement, however, showed a somewhat stronger activa-

tion of bilateral premotor cortex and contralateral M1, consistent

with the notion that distal movements underlie closer pyramidal

control. Differences related to motor cortex somatotopy were

confirmed.

Another limitation of the present study is that patient groups

included left and right hemispheric strokes. Sample sizes were not

sufficient to allow further stratification according to lesion side.


Therefore, potential differences between paretic or non-paretic

left- versus right-sided movement were not addressed in this

study.

Brain lesions were classified into only two categories. Most

likely, further differences can be identified with respect to the

spatial extent of the cortical (which functional regions are involved

in addition to sensorimotor cortex?) and subcortical lesion (which

nuclei or brainstem regions are involved?). Whether a stroke

involves only cortex or cortex plus subcortical areas is also likely

important. We computed a group GLM (fixed effects) including

patients with brainstem (n = 2) versus deep brain lesions (n = 9, see

Table 1). This GLM did not reveal any differences; therefore,

brainstem stroke was grouped together with deep brain lesions.

However, this analysis may be questioned due to the large

difference in sample size. More subjects are necessary to determine

the effects of lesion location on fMRI patterns associated with

paretic movement in more detail.

Conclusion

The present finding that paretic as well as non-paretic move-

ment-related brain activation differs between patients with cortical

and subcortical stroke, reflects the relationships between reorgani-

zation mechanisms and lesion location. Despite obvious differ-

ences, some phenomena occurring during reorganization

(ipsilateral postcentral recruitment) may coexist in cortical and

subcortical strokes. Nevertheless, stratification of patients accord-

ing to lesion location should be considered for studies investigating

recovery mechanisms. Specifically, selection and evaluation of

rehabilitative interventions may be best performed in location-

specific groups of stroke patients.

Acknowledgments

We thank Andrew Goldberg, Jim Boyd, Christina Stephenson

and Jill England for their support. Thanks also to Dr. John Sorkin

for his expert help with statistical analyses. We thank the F.M.

Kirby Center for Functional Brain Imaging, Kennedy Krieger

Institute (Baltimore, MD, USA), and its staff, especially Terry

Brawner, Dr. James Pekar, and Dr. Peter van Zijl. Dr. Luft is

supported by grants from Deutsche Forschungsgemeinschaft (Lu

748/2, 748/3). Funding for this study was obtained from the

National Institutes of Health (P60AG 12583 NIA University of

Maryland Claude D. Pepper Older Americans Independence

Center H133G010111) the Baltimore Department of Veterans

Affairs Geriatrics Research, Education and Clinical Center

(GRECC), Dr. Hanley is supported by 1RO1 NS 24282-08 and

the France-Merrick Foundation, the Johns Hopkins GCRC (grant

NCRR #MO1-00052), the National Center for Research Resour-

ces, MO1 RR-00052, and the Eleanor Naylor Dana Charitable

Trust.

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