Cortical activation changes induced by visual biofeedback ... - IOS Press

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NeuroRehabilitation 22 (2007) 77–84 IOS Press

Cortical activation changes induced by visual biofeedback tracking training in chronic stroke patients Sang-Hyun Cho a, Hwa-Kyung Shinb , Yong-Hyun Kwonc, Mi Young Leec, Young-Hee Lee d , Chu-Hee Leee , Dong Suk Yang f and Sung-Ho Jang f,∗ a

Department of Physical Therapy, Graduate School of Rehabilitation Therapy, Institute of Health Science, Yonsei University College of Health Science, Wonju, Republic of Korea b Department of Occupational Therapy, Kaya University College of Health Science, Goryeong, Republic of Korea c Department of Rehabilitation Science, Graduate School, Daegu University, Taegu, Republic of Korea d Department of Physical Medicine and Rehabilitation, Yonsei University of College of Medicine, Wonju, Republic of Korea e Department of Department of Biochemistry and Molecular Biology, Yeungnam University College of Medicine, Taegu, Republic of Korea f Department of Physical Medicine and Rehabilitation, Yeungnam University College of Medicine, Taegu, Republic of Korea

Abstract. Objectives: We tried to examine whether visual biofeedback tracking training (VBTT) can improve both the gait performance and cortical activation pattern in chronic stroke patients. Design: We enrolled 10 chronic hemiparetic patients with stroke(mean age 46.3 ± 5.19 years). The patients were randomly assigned to the training group (5 patients) or the control group (5 patients). VBTT was to follow the PC-generated sine waves with the knee joint electrogoniometer, and the two sine waves should appear as close to overlapping as possible on the PC monitor. The training was performed for 39 minutes/day, 5 days/week, for 4 weeks. Pre-training and post-training accuracy of tracking, functional status of gait, and functional MRI (fMRI) were measured. fMRI was performed at 1.5 T in parallel with timed knee flexion-extension movements at a fixed rate. Results: The accuracy of the tracking performance, walking speed, and motor scale for gait improved in the training group. Primary sensorimotor cortex (SM1) cortical activation shifted significantly from the unaffected to the affected hemisphere in the training group. Conclusions: We demonstrated that cortical activation changes occurred with gait function improvement in chronic stroke patients throughout the 4-week VBTT program. It seems that the cortical reorganization was induced by VBTT. Keywords: Functional MRI, gait, stroke, cortical reorganization, tracking training

1. Introduction

∗ Address for correspondence: Sung Ho Jang, MD, MS, Associate Professor, Department of Physical Medicine & Rehabilitation, School of Medicine, Yeungnam University, 317-1, Daemyungdong, Namku, Taegu 705-717, South Korea. Tel.: +83 53 620 3269; Fax: +83 53 620 3269; E-mail: [email protected].

The visual biofeedback tracking training (VBTT), mainly developed as a motor learning tool and/or motor control ability evaluation tool for healthy people, has evolved through various psychology- and neuroscience-related investigations [21,22,24]. This training method involves constant self-correction dur-

ISSN 1053-8135/07/$17.00  2007 – IOS Press and the authors. All rights reserved

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S.-H. Cho et al. / Cortical activation changes induced by visual biofeedback tracking training in chronic stroke patients

ing repeated series of a motor task pattern with visual biofeedback, during which the abilities of motor planning and motor control are continuously stimulated and beneficial neural plasticity may be induced [3,5,12]. Reports regarding the application of this principle to the paretic limbs of stroke patients have only emerged during the past decade. Above all, works by Carey et al. showed that either hand or ankle function improvement in parallel with cortical reorganization occurred in a group of stroke patients as a result of VBTT during functional MRI (fMRI) [3,5]. Several other previous studies have used the functional imaging method to demonstrate that physical intervention can induce cortical reorganization in stroke patients. These physical interventions include a home-based exercise program [15], task-oriented arm training [13], and a virtual reality exercise training program [14,25]. The purpose of the current study was to examine our hypothesis that a knee-joint VBTT program in chronic stroke patients would improve gait function and would be accompanied by cortical reorganization.

2. Subjects and methods 2.1. Subjects Ten stroke patients (7 men and 3 women) with hemiparetic stroke were recruited. Their mean age was 46.3 (SD 5.19) years, and the mean duration of illness was 15.3 (SD 2.83) months. Inclusion criteria were: (1) at least 1 year from the onset of stroke; (2) plateau for 2 months in the maximum motor recovery following a conventional neurorehabilitation; (3) without knee joint flexion contracture. Exclusion criteria were: (1) severe spasticity of the knee (modified Ashworth’s scale: > 2) [1] or tremor; (2) visual problem to see the sine waves are displayed on a PC monitor at 80 cm distance or severe cognitive impairments (scoring < 25 on the Mini-Mental State Examination). Informed consent was obtained from all subjects prior to the study, which was approved by a Human Subjects Committee. The patients were randomly assigned to either the control group or the VBTT group. The patients were alternatively assigned to either the control group or the VBTT group as they were enrolled into this study. 2.2. Motor function evaluation Gait function was determined using the Motoricity Index (MI, lower extremity only) and the modified mo-

tor assessment scale (MMAS, walking item only), a 10-meter walking test. MI is a measure of limb function with a maximum score of 100 for normal subjects. MMAS is a performance-based measure, which was purported to assess motor function. Each item is scored on a scale from 0 (unable to stand or walk) to 6 (able to walk up and down 4 steps). The 10-meter walking test is conducted on a 14-meter long walkway. Walking speed is calculated using a stopwatch to measure the time taken to cover the middle 10 meters of the walkway (the 2 meters at the start and finish are used for acceleration and deceleration). The reliability and validity of the MI, MMAS, and 10-meter walking test have been well established [8,10,11,17,20]. 2.3. Functional MRI Prior to the fMRI, the body parts of the patient, including the head, pelvis, and hip, were secured with straps and trunk immobilizer which is specially designed to effectively control any undesirable movement during fMRI. All patients practiced the prepared motor task in a supine position in the magnetic resonance (MR) scanner. The task involved sequential flexionextension of the knee at a predetermined angle of 0–60 ◦ and a metronome-controlled frequency of 0.5 Hz (cycle of 15 seconds of rest and 15 seconds of stimulus). A reference tape was placed on the scanner to indicate the corresponding angle position. The patient was then instructed to touch the target line with the apex of the patella, so as to control the amplitude of movement. To control the consistency of the rate, angle, and movement artifact, the two investigators carefully monitored the movement using a remote digital camera. The test was repeated if a there was a mismatch between the target and the actual performance or if any movement artifact was observed. Image signals were acquired using the Echo Planar Imaging (EPI) sequence in accordance with the blood oxygenation level-dependent (BOLD) technique. A 1.5-T MR scanner (Vision, Siemens, Erlangen, Germany) with a standard head coil was used. For the anatomic base images, 20 axial, 5-mm thick, T 1 weighted, conventional, spin echo images were obtained at a matrix size of 128 × 128 and a field of view (FOV) of 210 mm, parallel to the bicommissure line of the anterior commissure-posterior commissure (AC-PC). The EPI blood oxygen level-dependent, T 2 weighted fMRI images in the transverse plane were acquired over the same 20 axial sections for each epoch, producing 1200 images for the entire cerebrum


using the following parameters: TE (echo time) = 60 ms; TR (repetition time) = 3000 ms; FOV = 210 × 210 mm; matrix = 64 × 64; voxel dimensions 4 × 4 × 4;, and thickness = 5 mm. A mask was applied to the imaging data, such that any voxel variation in signal intensity greater than 5% during the control period was discarded to remove large vessel contributions. fMRI data were analyzed using SPM-99 software (Wellcome Department of Cognitive Neurology, London, UK) running under the MATLAB environment (the Mathworks, Inc., Natick, Ma, USA). Statistical parametric maps were obtained and voxels were considered significant at a threshold of p < 0.05, corrected. The functional images were realigned and then smoothed by an 8-mm Gaussian filter prior to statistical analysis. The realignment procedure will increase the sensitivity and reduce this noise that may be caused by movement that is unrelated to the task. Smoothing by Gausian filter enhances the potentially increased signal to noise ratio and validity of SPM software, and allows inter-subject averaging by blurring differences between subjects. Predetermined regions of interest (ROIs) were bilaterally drawn around the primary sensorimotor cortex (SM1), the premotor cortex (PMC), and the supplementary motor area (SMA), the posterior parietal cortex (PPC), cerebellar hemisphere (CBLL), and the vermis, because these areas have been reported to possess neuroplastic recovery potentials [5,7]. SM1 was defined as the combination of the postcentral gyrus and the posterior half of the precentral gyrus (including the anterior bank of the central sulcus) [9]. PMC included the anterior half of the precentral gyrus, as well as the anterior bank of the precentral sulcus. SMA was limited to the cortex on the medial wall of the hemisphere, extending from the top of the brain to the depth of the cingulate sulcus, including the dorsal bank of the cingulate sulcus; the posterior boundary was located halfway between the extension of the central and precentral sulci onto the medial surface, and the anterior boundary was defined by the vertical line drawn from the anterior commissure. PPC extended anteriorly to the postcentral sulcus, laterally to the lateral sulcus, posteriorly to the parieto-occipital sulcus, and medially to the parieto-occipital and cingulated sulci. Due to the large within-subject variability in the BOLD signal, a normalized index, the Laterality index (LI) was used to determine any shift in the symmetry of cortical activation between the two hemispheres for the ROIs as a function of intervention [5]. This index is expressed as (C−I)/(C + I), where C = the active voxel count for the ROIs in the hemisphere contralateral to the

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leg performing the movement and I = the active voxel count for the corresponding region in the hemisphere ipsilateral to the performing leg. The possible range is from −1.0 (all activity in the ipsilateral hemisphere) to +1.0 (all activity in the contralateral hemisphere) [5, 7]. 2.4. Visual biofeedback tracking training (VBTT) program 2.4.1. Imposing visual information Series of PC generated sine waves at 0.2 Hz were displayed on a PC monitor at 80 cm distance from the eyes of the subject. Two sets of sine wave amplitude ranges were employed: −20 ◦ ∼ +20◦ (40◦ tracking) or 0◦ ∼ +60◦ (60◦ tracking). 2.4.2. Recording the knee joint angle A double-axis electrogoniometer (Biometrics Ltd. Ladysmith, VA) was used to record the instant degrees of knee joint flexion-extension. Its basic composition was a flexible, double-layered metal beam housed in a flexible spring tube, with both of its ends fixed into box-shaped plastic arms. Its proximal stationary arm was secured on the imaginary line connecting the lateral femoral epicondyle and the greater trochanter, and its distal moving arm was secured on the line connecting the lateral malleolus and the head of the fibula. The instant degrees of knee joint flexion-extension electrogoniometer were then collected with a MP150 physiologic data acquisition system (Biopac Systems Inc., Goleta, CA) at a sampling rate of 100 Hz and went through a 1.5 Hz low-pass filter. Those two waves (the imposed sine wave and the electrogoniometer data) were adjusted to the same scale and displayed on the PC monitor as overlays (Fig. 1). 2.4.3. Scoring the knee joint tracking performance Comparison of the imposed sine wave and the measured joint angle wave was performed off-line. The Microsoft Excel program was used to calculate the AI (accuracy index; Eq. (1), which was introduced and has been verified by Carey et al. [2,4]. 100(P − E) (1) P According to their description, E is the root mean square (r.m.s.) error between the target line and the response line, and P is the r.m.s. value between the sine wave and the midline separating the upper and lower phases of the sine wave. The magnitude of P is AI =

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S.-H. Cho et al. / Cortical activation changes induced by visual biofeedback tracking training in chronic stroke patients Table 1 General Characteristics of the Subjects Training group

Control group

Subject # 1 2 3 4 5 mean (SD) 1 2 3 4 5 mean (SD)

Sex/Age M/42 M/41 M/45 F/59 F/44 46.2(7.3) F/43 M/54 M/45 M/45 M/57 48.8(6.3)

Lesion location Rt. CR infarct Rt. CR hemorrhage Lt. CR infarct Lt. CR infarct Rt. BG hemorrhage Lt. Rt. Lt. Lt. Rt.

BG hemorrhage BG hemorrhage BG hemorrhage CR infarct CR infarct

Months after attack 12 13 18 15 13 14.2(2.4) 15 18 17 12 20 16.4(3.1)

CR: corona radiata, BG: basal ganglia.

Fig. 1. Superimposing subject-generated wave on the PC-generated wave.

determined by the scale of the vertical axis, which is the range of knee motion of the subject. Therefore, the AI is normalized to the range of motion of each individual subject and takes into account any differences between subjects in the excursion of the tracking target. The maximum possible score is 100%. Negative scores occur when the response line is so distant from the target that it falls on the opposite side of the midline. 2.4.4. Process for the training and evaluation session The subjects were seated on the NK (NolandKuckhoff) table with both hands holding hand-grip bars at the ends of the armrests. When the affected knee

joint was flexed at 90 ◦ on the edge of the NK table, the electrogoniometer data at this position was calibrated as zero degrees, which was the starting position for the tracking task. When the knee joint was fully extended, the electrogoniometer data was set as +90 degrees. The training program was practiced only for the affected legs, and it consisted of 20 sessions; 5 days (Monday to Friday) per week for 4 weeks. Each session (39 minutes) was a collection of three 10-minute exercise sets and 3 minutes of rest period in between each exercise set. The 10-minute exercise set was to follow ten one-minute sine waves of either 40 ◦ or 60◦ amplitude ranges. The amplitude range for each of the


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Fig. 2. Accuracy Index Change in the Training Group. The median and distributions of the accuracy index (AI) in the training group. The box-and-whiskers graph shows changes in AI due to the training program. The boxes indicate the range between 25th and 75th percentile. Vertical capped bars show the 10th and 90th percentile, the horizontal bars the median. (Mean ± SD: Intact side, range 40◦ , before training: 47.21 ± 5.55; 40◦ after training: 43.61 ± 8.43; range 60◦ , before training: 55.91 ± 6.44; after training 56.49 ± 4.64; Affected side, range 40◦ , before training: 27.36 ± 11.80; after training 44.84 ± 4.34; range 60◦ , before training: 34.95 ± 11.49, after training 53.74 ± 5.43). * denotes one-tailed p < 0.05 in the Wilcoxon signed-rank test. † denotes the two-way ANOVA p-value to test the influence of two different motion ranges (40◦ vs. 60◦ ) on AI value changes

Fig. 3. Accuracy Index Change in the Control Group. The median and distributions of the accuracy index (AI) in the control group. The box-and-whiskers graph shows changes in AI from two separate measurement sessions. The boxes indicate the range between 25th and 75th percentile. Vertical capped bars show the 10th and 90th percentile, the horizontal bars the median. (Mean ± SD: Unaffected side, range 40◦ , 1st measurement: 47.08 ± 3.39; 40◦ 2nd measurement: 49.37 ± 7.52; range 60◦ , 1st measurement: 52.25 ± 7.10; 2nd measurement: 53.74 ± 6.51; Affected side, range 40◦ , 1st measurement: 28.60 ± 3.89; 2nd measurement 30.87 ± 2.52; range 60◦ , 1st measurement: 26.08 ± 10.80, 2nd measurement 27.68 ± 10.78). * denotes one-tailed p < 0.05 in the Wilcoxon signed-rank test. † denotes the two-way ANOVA p-value to test the influence of two different motion ranges (40◦ vs. 60◦ ) on AI value changes

one-minute sine waves was selected randomly by the main investigator throughout the exercise set. Also, both legs (affected and unaffected) of the training group underwent pre- and post-training evaluation sessions, and both legs (dominant and non-dominant) of the control group underwent two corresponding evaluations. For each evaluation session, subjects followed 3-minute sine waves of either 40 ◦ or 60◦ amplitude ranges in random sequences. Before each training or evaluation session, the subjects were encouraged to keep focused on following the PC-generated sine waves with their knee joint electrogoniometer, and to make the two sine waves appear as close to overlapping as possible on the PC monitor. A three-minute rehearsal and a oneminute rest period preceded the training and evaluation sessions.

amplitudes of the imposed sine wave. Its two-tailed statistical significance level was set at p < 0.05.

2.5. Statistical analysis

3.2. Accuracy Index (AI) changes

The limited number of subjects required us to use non-parametric statistical analysis to test any interval changes (Wilcoxon signed-rank test) or correlations (Spearman’s r) with the one-tailed statistical significance level set at p < 0.05. Two-way repeated ANOVA was additionally used to test the effect of the different

Figure 2 shows the median and distribution of the AI in the training group. The four-week training program did make significant improvements (one-tailed p < 0.05, Wilcoxon signed-rank test) in the affected legs, and tracking with a higher range of motion (60 ◦) produced a significantly greater (p < 0.05, two-way

3. Results 3.1. General characteristics of the subjects The training group included 4 men and 1 woman, with a mean age of 46.2 (SD 7.3) years and a mean duration of illness of 14.2 (SD 2.4) months (Table 1). The control group was composed of 3 men and 2 women, and their mean age was 48.8 (SD 6.3) years, with a mean duration of illness of 16.4 (SD 3.1) months. The Mann-Whitney test showed no significant difference in mean age or duration of illness.

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S.-H. Cho et al. / Cortical activation changes induced by visual biofeedback tracking training in chronic stroke patients Table 2 Changes in Clinical Scores and Laterality Index

Clinical Scores

MI MMAS Walk speed (m/sec.)

LI on fMRI

SM1 SMA PMC PPC CBLL Vermis

Before After Before After Before After Before After Before After Before After Before After Before After Before After

Training Group mean(SEM) p-value 57.40(1.40) 1.000 57.40(1.40) 3.6(0.24) 0.063 4.6(0.24) 0.31(0.03) 0.031 0.42(0.04) −0.06(0.25) 0.52(0.32) 0.20(0.21) 0.47(0.23) −0.04(0.04) 0.20(0.20) 0.24(0.20) 0.20(0.20) −0.07(0.32) 0.14(0.10) 0.20(0.20) 0.20(0.20)

0.031 0.125 0.250 0.438 0.375 0.500

Control Group mean(SEM) p-value 56.40(1.91) 0.500 56.40(1.91) 4.00(0.32) 0.500 4.00(0.32) 0.38(0.03) 0.500 0.37(0.01) 0.35(0.17) 0.22(0.83) 0.47(0.23) 0.14(0.39) 0.20(0.20) 0.04(0.04) 0.00(0.00) 0.00(0.00) 0.02(0.02) 0.20(0.20) 0.20(0.20) 0.20(0.20)

0.406 0.156 0.250 1.000 0.500 0.500

MI: motricity index/ MMAS: modified motor assessment scale. LI: Laterality index (for details, refer to the main text). SM1: primary sensory motor cortex/ SMA: supplementary motor area/ PMC: premotor cortex/ PPC: posterior parietal cortex/ CBLL: cerebellar hemisphere. p-value denotes the one-tailed significance of Wilcoxon’s signed rank test (non-parametric paired t-test).

ANOVA) AI value than seen with the lower range of motion (40 ◦ ). As seen in Fig. 3, significant changes (p < 0.05) occurred in the affected legs of the control group with the greater tracking motion range (60 ◦ ), but two-way ANOVA showed no significant difference due to the size of tracking motion range. 3.3. Changes in Clinical Scores, fMRI findings, and Accuracy Index (AI) Out of the three clinical scores and LIs from 6 ROIs, only two items of the training group showed significant interval changes (one-tailed p < 0.05 with Wilcoxon signed-rank test); walking speed increased from a mean 0.31 m/sec (SEM 0.03) to a mean 0.42 m/sec (SEM 0.04), and the LI at SM1 improved from a mean −0.06 (SEM 0.25) to a mean 0.52 (SEM 0.32)(Table 2). According to LI analysis, this finding indicated more normalized contralateral(ipsilesional) cortical reorganization while inhibiting the aberrant ipsilateral(contralesional) cortical activation during movement of the affected knee. In the aspect of individual analysis, as shown in Fig. 4, all patients showed ipsilateral activations at SM1 prior to VBTT. However, the ispilateral SM1 activity disappeared in two patients (patients

2 and 3) and decreased in three patients (patients 1, 4, and 5) after VBTT. Additionally, the p-value (0.063) for the MMAS interval change (3.6 ± 0.24 to 4.6 ± 0.24) was slightly outside of the significance level. No items of the control group showed any significant interval change.

4. Discussion This study examined whether visual biofeedback tracking training (VBTT) could improve both the gait performance and brain activation pattern of five stroke patients. Four weeks of VBTT for the affected knee caused significant improvements in AI scores, and it seems to be attributed to an effect of positive training. According to the related theories which are currently available, some possible mechanisms which could account for these improvements in performance are learning, reversal of learned nonuse, and skill training [16, 19,23]. The walking speed prior to the VBTT (mean 0.31 m/sec) belonged to the functional category between ‘most-limited community’ and ‘unlimited household’ [18]. After the VBTT course, the walking speed increased (mean 0.42 m/sec) to the ‘most-limited community’ category. Admitting the ethnic differences in physique between our subjects and those of Perry et al.,


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in association with functional recovery by physical intervention and with motor recovery over time [3,5,6, 14,15,25]. In terms of the proper length and quantity of VBTT, this study may appear to be insufficiently controlled. However, we were still able to make an indirect inference; size of tracking motion matters in the hemiparetic limb, as the greater tracking motion range (60 ◦) was found to be more effective. It is likely that the greater active motion provided more neural information for motor skill acquisition, but this assumption needs future verification. Like any other intervention used in the clinical field, the process of determining the dosing principle cannot be completed after only a few investigations. Certainly, we can think about the optimum type of visual biofeedback, such as the presentation of random sine waves to follow. We hope that the simple findings of this study will act as a stepping stone in this process. Additionally, in terms of the beneficial effect of knee-joint VBTT on gait function, our tools of evaluation may appear too crude to determine mechanism of the possible effect. Still, we can state that this training did improve the gait in the group of five chronic stroke patients. However, this study is limited by the small number of patients involved. Further complementary studies involving larger case numbers are warranted. Fig. 4. T2-weighted and functional brain MR images. The arrow indicates the lesion site. B. Before VBTT, all patients showed the ipsilateral activations (arrow) at primary sensori-motor cortex (SM1). C. After VBBT, the ispilateral SMC activity (arrow) disappeared (patient 2 and 3) or decreased (patients 1, 4 and 5) during affected knee movement.

those speed improvements could be interpreted as significant functional improvements. This conclusion has also been corroborated by the considerable improvement in MMAS (mean 3.6 to mean 4.6). Control group patients, in contrast, did not show such improvements in their gaits. It is expected that the manipulation of brain plasticity will become the main topic of the field of stroke rehabilitation in the near future. For this, the demonstration of the cortical effect of current or potential physical interventions on stroke patients is essential. Our VBTT group showed a significant SM1 cortical activation shift from the unaffected hemisphere to the affected hemisphere, and the change was accompanied by the recovery of gait function (walking speed and MMAS). Our findings corresponded with previous longitudinal fMRI studies which found that SM1 activation shifted from the unaffected hemisphere to the affected hemisphere

5. Conclusion In conclusion, we demonstrated that cortical activation changes occurred with gait function improvement in chronic stroke patients throughout the VBTT program. It seems that the cortical reorganization was induced by VBTT.

Acknowledgments This work was supported by the Korea Science and Engineering Foundation (KOSEF) grant funded by the Korea government (MOST) (No. M1064212000406N4212-00410).

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