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Prefrontal Cortical Activation With Open and Closed-Loop Tactile Cueing When Walking and Turning in Parkinson Disease: A Pilot Study

Stuart, Samuel PhD, MSc, BSc(Hons); Mancini, Martina PhD

Author Information
Journal of Neurologic Physical Therapy: April 2020 - Volume 44 - Issue 2 - p 121-131
doi: 10.1097/NPT.0000000000000286

Abstract

INTRODUCTION

Gait and turning impairments are common in people with Parkinson disease (PwPD),1,2 and are associated with reduced mobility, independence, quality of life, and increased fall risk. Gait impairments include reduced speed and shortened steps, and more complex phenomena such as freezing of gait (FOG).3 FOG develops in the majority of PwPD and involves transient periods of being unable to continue walking.4 Similarly, PwPD turn with reduced speed, increased duration, increased number of steps, narrower base of support, and tend to turn “en-bloc” with dysfunctional segmental coordination, which has been shown to reduce stability.5 Turning is also one of the most provocative tasks for FOG, which also leads to instability.6,7 To date, pharmacological treatment of mobility deficits has been unsatisfactory due to its refractory nature to dopaminergic treatments.8 Indeed, mobility remains deficient in PwPD compared with controls regardless of medication use; however, levodopa can improve pace-related gait measures, but other measures remain unresponsive.8 Therefore, nonpharmacological therapeutic interventions, such as cues,9–12 are used in clinical practice to alleviate deficits.

Auditory,13 visual,14 or tactile12 cueing modalities have been used to improve gait (ie, increased step length, speed, reduced variability, etc) and reduce FOG episodes in PwPD.15 Fewer studies have examined the influence of cues on turning in PwPD, but results have shown that turn speed increases,16 festination improves,17 and FOG is reduced with cues.18 Auditory and visual cues have received the most attention.19–21 However, tactile cueing may be particularly useful for those with FOG,22,23 as sensory integration and proprioceptive deficits accompany FOG.24,25 In addition, tactile cues may be more unobtrusive compared with other modalities. Cues are predominantly used in clinical practice in an open-loop (continuous rhythmic stimuli) rather than a closed-loop (intermittent stimuli based on individual movement) manner, likely due to limited availability (ie, the majority of closed-loop systems are not marketed yet) and ease of application. Only recently have devices been engineered to monitor gait and provide real-time biofeedback to improve performance.26,27 Indeed, our recent work has shown that closed-loop tactile cueing can reduce FOG episodes in PwPD,28 and improve turning performance to the same level as open-loop cueing.29 Despite similar behavioral results with open-loop and closed-loop cueing,29 the neural mechanisms involved may be very different and a greater understanding may help develop effective and individualized cue strategies.

Current open-loop cue response theories involve (1) attentional mechanisms that bypass defective basal ganglia (BG) circuitry9,30–33 or (2) replacement of rhythmic BG output via external stimuli.34–38 Similarly, closed-loop cues may replace defective internal and external feedback mechanisms by reinforcing or replacing weak or absent sensory signals required for adequate motor task performance.21,39 The integration of closed-loop cues may require attentional resources to process multiple sources of simultaneous information (ie, proprioception from feet but also simultaneously from cue).40 In general, gait leads to overactive conscious attentional activation in PwPD41 stemming from the prefrontal cortex (PFC)42 to compensate for BG impairment that affects movement automaticity. The first open-loop cue response theory suggests that further PFC activation during gait would be required to circumvent BG impairment. In line with this, tactile stimulus activates the PFC (frontostriatal and frontoparietal attentional pathways) in animal and human models,43,44 which may be impacted by performing a secondary task (dual-task).45 Alternatively, the second theory of open-loop cue response suggests that PFC activation for gait control in PwPD would reduce by replacing faulty inconsistent BG output with consistent external input. Indeed, rhythmic stimulation may facilitate BG and premotor cortex interactions,46,47 as well as cerebello-thalamo-cortical projections.48 Tactile cues may override the dominant visual proprioception49 that occurs in PwPD50 and allow faster subconscious sensory processing,51,52 which would reduce PFC burden. To date however, these theories remain relatively unexplored due being unable to image the brain while walking.

Technological progression has allowed monitoring of cortical activity during walking and turning in PwPD using functional near-infrared spectroscopy (fNIRS) or electroencephalogy (EEG).53 Changes in cortical activity with motor performance indicate that different mechanisms may underpin open- and closed-loop cueing. For instance, closed-loop biofeedback can alter attentional processing in healthy adults, specifically enhancing beta (16-22 Hz) and inhibiting high theta (4-8 Hz) frequencies in EEG recordings at CPz-PCz channels,54,55 which may support the attentional theory of cueing. However, imaging studies have demonstrated that open-loop rhythmic cueing relates to premotor cortex and supplementary motor area activation,46,47,56 which may support the BG output replacement theory of cueing. However, specific cortical contributions to open- and closed-loop cueing remain unknown and warrant further investigation to inform best practice to alleviate gait deficit in PwPD.

This pilot study investigated changes in PFC activity in response to open- (continuous metronome-like rhythmic stimuli) and closed-loop (intermittent stimuli based on individuals walking pattern) tactile cueing during walking and turning in PwPD. Our hypothesis was that cueing would alter PFC activation during walking and turning in PwPD, especially for those who report FOG. Specifically, we predicted that closed-loop cueing would increase PFC activity due to the attentional burden of integrating external sensory feedback into motor control. However, open-loop activity would reduce PFC activation due to replacing impaired BG output in PwPD.

METHODS

Participants

Inclusion criteria were aged 55 to 90 years, able to stand or walk for 2 minutes without assistance, diagnosis of Parkinson disease as defined by the UK Brain Bank criteria, Hoehn and Yahr scores II to IV57 (OFF medication), and taking anti-parkinsonian medication. Exclusion criteria were musculoskeletal, vestibular, visual, or other medical condition that affected gait or balance. Self-reported FOG was based on the new Freezing of Gait Questionnaire (nFOGQ).58 Participants were asked whether they have freezing defined as: “Freezing is the feeling that your feet are transiently glued to the floor while trying to initiate walking, making a turn, or when walking through narrow spaces, or in crowded places; sometimes it can be accompanied with trembling of the legs and small, shuffling steps.” Subjects were categorized as “freezers” (FOG+) if they have experienced such a feeling or episode over the past month58,59 or “nonfreezers” (FOG−) if they had not. This study was approved by the institutional ethics review board at Oregon Health and Science University (IRB00009903).

Experimental Design

Protocol and Tasks

Participants underwent demographic, clinical, cognitive assessments, and walking and turning tasks (OFF medication state; ∼12 hours withdrawal). Despite most cueing studies examining participants while ON medication, here, we assessed PwPD while OFF medication to see a larger magnitude of change with cueing, which may reduce when ON medication. In addition, testing while OFF medication may allow generalization of results to more advanced Parkinson disease. Future studies could examine cue response while ON levodopa medication as it may influence findings.

Participant age, sex, height, weight, education (years), and handedness were recorded. Standardized tests for depression (Geriatric Depression Scale),60 fatigue (Multidimensional Fatigue Inventory),61 and orthostatic hypotension (Orthostatic Hypotension Questionnaire)62 were collected, as these features are known to influence PFC activity. Global cognition was measured with the Montreal Cognitive Assessment.63 Executive function was examined using clock drawing (Royall's CLOX1).64 Attention was measured with the Trail Making Test (TMT; parts A and B). Visuospatial ability was measured with clock copying (Royall's CLOX2).64 Disease severity was measured using the Unified Parkinson's Disease Rating Scale (MDS-UPDRS III), freezing status was measured using the nFOGQ, and levodopa-equivalent daily dosage was calculated.

Gait, turning, and PFC activity were assessed during 4 walking tasks: (1) an unanticipated 180° turn while walking over 9 m, (2) an unanticipated 360° turn while walking over 9 m, (3) usual walking back and forth over 9 m for 2 minutes, and (4) walking back and forth over 9 m while performing a secondary cognitive task (dual-task) for 2 minutes. Participants performed randomized left and right 180° and 360° turns. Dual-tasking involved the Continuous Performance Task (AX-CPT); specifically, participants listened to random letters and had to press a button (held in their least Parkinson disease affected hand) every time the letter “I” followed an “A.” All tasks started and ended with 20 seconds of standing (not talking or moving) and researchers recorded observed FOG.

Equipment

A mobile fNIRS system (Octamon, 50 Hz, Artinis, the Netherlands) measured PFC activity (Figure 1). Transmitter-to-detector distance was 3.5 cm65 and data were collected (ie, standard 10-20 EEG position) and processed in line with previous studies.53,66 Two short-separation reference channels (1.5 cm; left and right PFC) removed peripheral interference (ie, blood flow in extracerebral layers). Eight inertial measurement units (IMUs; 128 Hz, Opals, APDM, Inc, Portland) were placed on the feet, shins, lumbar (L5), sternum, and wrists to measure gait and turning.67 The 2 systems were synchronized through a PortaSync (Artinis) device.

Figure 1.
Figure 1.:
Representative raw HbO2 data during the 2-minute walking task (gray dashed line is 0 point of HbO2 concentration). PD, Parkinson disease.

A tactile cueing device (VibroGait unit, Figure 2), described in detail elsewhere,28 was positioned on each foot sensor, with the vibrating tactor on each wrist. Briefly, the closed-loop setting consisted of a controller unit (Arduino microcontroller) that detected leg-stance phase and activated the vibration, and it then deactivated vibration in the swing phase. Alternatively, the open-loop setting provided a vibration every 750 ms for 250 ms. The tactors were C-2 tactors (Engineering Acustic, Inc) with a primary resonance of 200 to 300 Hz (vibration similar to a smartphone). The method of gait intervention of this device has been detailed elsewhere.28 Essentially the closed-loop device setting has the potential to detect online gait abnormalities and provide a tactile cue (Figure 2),28 whereas the open-loop setting provides rhythmic proprioceptive cues that have been shown to improve gait and step synchronization in PwPD.68,69

Figure 2.
Figure 2.:
(A) VibroGait cueing device and placement and (B) depiction of closed-loop cue method.

Data Analysis

A 3-dimensional digitizer (PATRIOT, Polhemus, Vermont) provided locations of PFC regions relative to fNIRS channel scalp position. Digitized data were entered into NIRS-statistical package metric mapping (NIRS-SPM, http://www.nitrc.org/projects/nirs_spm),70 which was implemented within MATLAB 2017a (Mathworks, Massachusetts). NIRS-SPM allowed registration of fNIRS channel data onto the Montreal Neurological Institute standard brain space,71 described in detail elsewhere.72 HbO2 changes were recorded bilaterally (left and right) within the PFC. Brodmann areas (BA) that corresponded to the PFC consisted of BA9 and BA10 for all participants. Raw fNIRS data (Figure 1) were median averaged53,73–75 and processed in stages within custom-made MATLAB algorithms (Figure 3).

Figure 3.
Figure 3.:
Data analysis flowchart. Stage 1: data filtering; stage 2: baseline correction; stage 3: reference channel correction; stage 4: visual signal inspection; stage 5: averaging across fNIRS channels; stage 6: derive outcomes.

The primary outcome measure was relative change in HbO2 concentration (a proxy for cortical activation). Relative changes from baseline standing in HbO2 concentrations were reported to account for individual physiological variations66; see below calculations. HbO2 rather than HHb was used due to its sensitivity to walking and cognitive tasks.76,77 IMU data-determined gait characteristics (speed, stride length, foot strike angle, and stride time variability) from foot sensors and turn characteristics (duration and peak velocity) with occurrence (onset and end of each turn) and timing periods (6 seconds prior to vs during turn) were calculated using angular velocity of the L5 sensor.67 Dual-task cost was calculated as 100 × (single-task − dual-task score)/single-task.

Statistical Analysis

Data were analyzed using SPSS (v22, IBM, Chicago, Illinois). Data normality was assessed using Kolmogorov-Smirnov tests with parametric or nonparametric analysis conducted where appropriate. Descriptive characteristics were assessed with independent t tests comparing groups (FOG+, FOG−), unless otherwise stated. PFC activity was not significantly different between left and right turns (eg, baseline during 180° turn P = 0.183 and during 360° turn P = 0.544); therefore, data were collapsed into single 180° and 360° turn outcomes. Separate linear-mixed effects models (LMEM) examined whether PFC activity changed during turning and walking with closed-loop or open-loop cueing. For turning, main effects of group (FOG+, FOG−), turn (180°, 360°), period (prior to, during), and condition (baseline, open-loop, closed-loop) were reported. For gait, main effects of group (FOG+, FOG−), task (single, dual), period (early, late), and condition (baseline, open-loop, closed-loop) were reported. Each LMEM included a random intercept for each subject to account for repeated measurements. Wilcoxon signed rank tests examined trends in PFC activation data. The same LMEMs examined change in gait and turning metrics with cueing. Spearman's rank correlations explored relationships between behavioral measures of gait and turning with PFC activity. As this was a pilot study, we did not correct for multiple comparisons and P < 0.05 was considered significant.

RESULTS

Participants

Twenty-eight PwPD completed testing for this study, but only 25 subjects (n = 13 FOG+ and n = 12 FOG−) were used within our data analysis. Three participants had poor fNIRS signal quality upon visual inspection (Figure 3, stage 4) and were removed before further analysis. Two participants were also unable to complete all of the testing conditions (baseline, open- or closed-loop), but their collected data were included for analysis. Table 1 displays the demographic, cognitive, sensory, and clinical data from the participants. FOG+ and FOG− participants were well matched for most characteristics, with the only significant difference seen in executive function (TMT B score) and as expected on nFOGQ that was used to classify the groups. The majority of participants were right handed and there was a relatively even split of participants who had symptoms onset on left or right side. Dual-task performance was also similar between the FOG groups across the cued conditions (Table 1).

Table 1 - Demographic, Cognitive, Sensory, and Clinical Outcomes
PwPD (n = 25) Mean (SD) FOG+ (n = 13) Mean (SD) FOG− (n = 12) Mean (SD) P
Demographic
Age 69.20 (3.99) 69.69 (4.21) 68.67 (3.85) 0.532
Gender, male/female 17/8 8/5 9/3 0.471
Height 1.62 (0.13) 1.61 (0.12) 1.63 (0.14) 0.210a
Weight 169.78 (31.84) 163.74 (23.23) 176.33 (39.15) 0.334
Education, y 17.88 (2.88) 18.39 (3.07) 17.33 (2.67) 0.373
MFI 51.16 (11.99) 53.77 (13.25) 48.33 (10.27) 0.266
OHQ 10.68 (13.18) 11.46 (14.16) 9.83 (12.59) 0.765
GDS 5.76 (3.78) 6.46 (3.99) 5.00 (3.54) 0.345
Handedness, left/right 2/23 1/12 1/11 0.953
Cognitive
MoCA 27.12 (3.83) 26.08 (3.62) 28.25 (3.62) 0.161
FAB 14.48 (3.04) 14.08 (3.23) 14.92 (2.91) 0.502
TMT A 51.48 (57.10) 65.25 (21.16) 36.56 (17.14) 0.056a
TMT B 98.35 (51.74) 123.55 (57.31) 71.04 (26.31) 0.008b
TMT B-A 46.87 (35.57) 58.30 (42.66) 34.48 (21.29) 0.095
CLOX1 11.76 (2.32) 12.08 (1.38) 11.42 (3.06) 0.488
CLOX2 13.44 (1.66) 12.92 (2.02) 14.00 (0.95) 0.106
Sensory (AASP)
Taste/smell 21.38 (3.56) 21.75 (2.80) 21.00 (4.29) 0.617
Movement processing 22.63 (3.92) 21.83 (4.71) 23.42 (2.94) 0.334
Visual processing 23.00 (4.60) 23.67 (6.23) 22.33 (2.10) 0.490
Touch processing 29.21 (5.12) 28.83 (6.48) 29.58 (3.55) 0.728
Activity level 27.00 (3.89) 27.33 (4.46) 26.67 (3.39) 0.684
Auditory processing 25.92 (5.99) 26.42 (6.22) 25.42 (5.98) 0.692
Clinical
Disease duration, y 10.00 (6.27) 12.08 (6.18) 7.75 (5.77) 0.084
UPDRS III 36.40 (11.67) 40.00 (14.01) 32.50 (7.15) 0.110
H&Y, I/II/III 0/22/3 0/10/3 0/12/0 0.076
LEDD 883.89 (501.40) 924.92 (609.37) 839.44 (373.20) 0.679
FOGQ 7.12 (8.51) 13.69 (6.89) 0.00 (0.00) <0.001b
Side initial symptoms, left/right/both 11/12/2 7/4/2 4/8/0 0.128
Dual-task Performance
Baseline
Accuracy, % 65 (37) 59 (41) 70 (35) 0.505
Reaction time, s 0.53 (0.32) 0.43 (0.14) 0.59 (0.40) 0.298
Closed-loop
Accuracy, % 70 (36) 69 (36) 71 (37) 0.876
Reaction time, s 0.41 (0.16) 0.47 (0.16) 0.36 (0.16) 0.127
Open-loop
Accuracy, % 74 (36) 69 (41) 78 (34) 0.543
Reaction time, s 0.36 (0.13) 0.32 (0.16) 0.38 (0.11) 0.443
A
bbreviations: AASP, The Adolescent and Adult Sensory Profile; FAB, Frontal Assessment Battery; FOG, freezing of gait; FOGQ, Freezing of Gait Questionnaire; GDS, Geriatric Depression Scale; H&Y, Hoehn and Yahr; LEDD, levodopa-equivalent daily dosage; MFI, modified fatigue inventory; MoCA, Montreal cognitive assessment; PwPD, people with Parkinson disease; OHQ, Orthostatic Hypotension Questionnaire; SD, standard deviation; TMT, Trail Making Test; UPDRS, Unified Parkinson's Disease Rating Scale.
a
Mann-Whitney U test.
b
Significance level P < 0.05.

PFC Activity Did Not Change With Open- or Closed-Loop Tactile Cues Compared With Baseline During Walking and Turning

After controlling for covariates (turn duration and gait speed), PFC activation was similar in FOG+ and FOG− participants during walking (P = 0.836) and turning (P = 0.652) (Table 2). Although Figure 4 shows that under dual-task walking conditions FOG+ had nonsignificantly higher PFC activation than FOG− during baseline (P = 0.443) and open-loop cueing (P = 0.928), there was a reduction in PFC activation with closed-loop cueing in FOG− (P = 0.037, Figure 4). The only significant differences in PFC activity were found between periods of a walk or turn (early walking vs late walking and before turn vs during turn), but not with different turns (180° vs 360°, P = 0.410) or task demands (single or dual, P = 0.975). Specifically, PFC activity was higher during turning compared with 6 seconds prior to turning in PwPD (P < 0.001). Similarly, PFC activity was higher within the first 40 seconds (early period) of walking and significantly reduced in the second 40 seconds (late period) of walking in PwPD (P < 0.001).

Table 2 - Fixed Effects of Relative Change in HbO2 During Turning While Walking and 2-Minute Walk Tasks
Estimate SE t df P
180° and 360° turns while walkinga
Group (FOG+ vs FOG−) −0.01 0.04 −0.21 277 0.836
Turn (180 vs 360) 0.02 0.03 0.83 277 0.410
Period (prior to vs during) 0.08 0.02 4.02 277 <0.001b
Closed-loop cue 0.02 0.03 0.86 277 0.392
Open-loop cue −0.00 0.03 −0.08 277 0.934
2-min walkingc
Group (FOG+ vs FOG−) −0.06 0.13 −0.45 273 0.652
Task (single vs dual) 0.00 0.05 0.03 273 0.975
Period (early vs late) −0.22 0.05 −4.70 273 <0.001b
Closed-loop cue −0.01 0.06 −0.25 273 0.805
Open-loop cue −0.07 0.06 −1.14 273 0.258
A
bbreviations: FOG, freezing of gait; SE, standard deviation.
a
Adjusted for turn duration.
b
Significance level P < 0.05.
c
Adjusted for gait speed.

Figure 4.
Figure 4.:
Changes in HbO2 concentration in people with Parkinson disease.

Following control for covariates, there were no differences in PFC activity from baseline with open- or closed-loop cueing (Table 2). Despite this, Figure 4 shows that there were nonsignificant trends in group differences in PFC activity. For example, FOG+ nonsignificantly reduced PFC activity from baseline during a 180° turn with closed-loop cueing (P = 0.450), whereas the opposite trend occurred for FOG− participants (P = 0.010). Similarly, there was a trend toward a reduction from baseline in PFC activity during the early phase of walking under dual-task with closed-loop cueing for FOG− (P = 0.084), whereas the opposite trend occurred for FOG+ (P = 0.110, Figure 4).

Behavioral Measures of Walking and Turning Improved With Cueing

Dual-task gait was significantly slower, with shorter strides and reduced foot strike angle compared with single-task gait (all P < 0.001, Table 3), regardless of cueing condition and freezing status. Similarly, 360° turns were significantly slower and longer than 180° turns in each condition (P < 0.001). There were significant improvements in dual-task cost of stride length and foot strike angle with both open- (P = 0.003 and P = 0.014, respectively) and closed-loop cueing (P < 0.001 and P = 0.031, respectively). There were also several trends for improvement with the cueing conditions in other gait characteristics (Table 3).

Table 3 - Gait Characteristic, Dual-Task Cost (%), and Turning Characteristic Change With Cueinga
Walking Baseline Closed-Loop Open-Loop Group P Task P Closed-Loop P Open-Loop P
Single Dual Single Dual Single Dual
FOG+ FOG− FOG+ FOG− FOG+ FOG− FOG+ FOG− FOG+ FOG− FOG+ FOG−
Gait speed, m/s 0.90 (0.20) 0.94 (0.15) 0.85 (0.22) 0.88 (0.15) 0.89 (0.21) 0.94 (0.16) 0.88 (0.23) 0.92 (0.17) 0.91 (0.20) 0.94 (0.17) 0.89 (0.23) 0.92 (0.19) 0.694 <0.001b 0.059 0.052
Stride length, m 0.95 (0.20) 1.03 (0.14) 0.89 (0.22) 0.98 (0.16) 0.95 (0.20) 1.03 (0.16) 0.92 (0.23) 1.00 (0.16) 0.95 (0.19) 1.03 (0.16) 0.91 (0.23) 1.01 (0.18) 0.267 <0.001b 0.170 0.219
Foot strike angle, ° 12.25 (5.68) 9.48 (0.57) 10.35 (6.00) 8.21 (6.22) 11.54 (5.23) 9.53 (5.05) 10.84 (5.08) 8.51 (5.16) 11.73 (4.85) 10.11 (4.58) 11.33 (5.17) 9.01 (4.55) 0.253 <0.001b 0.998 0.959
Stride time variability (CV) 3.76 (2.52) 2.70 (1.00) 3.46 (2.07) 2.96 (1.02) 3.31 (2.83) 3.03 (1.35) 4.14 (4.06) 2.67 (0.87) 3.64 (2.97) 2.87 (1.72) 3.42 (1.81) 2.93 (1.11) 0.370 0.825 0.864 0.934
Baseline Dual-Task Cost, % Closed-Loop Dual-Task Cost, % Open-Loop Dual-Task Cost, % Group P Task P Closed-Loop P Open-Loop P
FOG+ FOG− FOG+ FOG− FOG+ FOG−
Gait speed, m/s −7.43 (8.61) −5.83 (6.85) −3.80 (10.29) −2.38 (4.99) −4.40 (10.70) −2.25 (4.35) 0.716 ... 0.665 0.050b
Stride length, m −8.45 (8.63) −5.45 (5.21) −5.02 (10.32) −3.34 (3.25) −5.76 (10.49) −2.80 (3.95) 0.417 ... 0.003b <0.001b
Foot strike angle, ° −20.79 (−25.95 to −7.46) −17.85 (−21.64 to 1.18) −5.01 (−10.35 to −3.71) −7.90 (−16.74 to −2.03) −2.71 (−8.86 to 2.88) −11.00 (−27.61 to −2.79) 0.225 ... 0.014b 0.031b
Stride time variability (CV) −2.71 (24.76) 13.31 (27.84) 22.20 (30.92) −6.86 (24.54) 7.27 (58.61) 11.66 (32.50) 0.256 ... 0.784 0.069
Turning Baseline Closed-Loop Open-Loop Group P Turn P Closed-Loop P Open-Loop P
FOG+ FOG− FOG+ FOG− FOG+ FOG−
Duration, s 180° 2.37 (0.49) 2.38 (0.74) 2.39 (0.51) 2.33 (0.63) 2.45 (0.44) 2.25 (0.63) 0.449 <0.001b 0.402 0.019b
360° 4.38 (0.91) 4.34 (1.32) 4.92 (1.71) 4.78 (2.12) 6.93 (7.11) 4.71 (1.77)
Velocity, °/s 180° 115.58 (28.35) 115.62 (32.41) 123.56 (30.48) 115.24 (30.48) 117.39 (28.15) 109.26 (34.34) 0.970 <0.001b 0.653 0.059
360° 127.05 (31.66) 129.98 (36.94) 122.23 (31.63) 124.80 (33.63) 121.76 (29.56) 123.90 (35.80)
A
bbreviations: CV, coefficient of variation; FOG, freezing of gait; SD, standard deviation.
a
Mean (standard deviation) reported.
b
Significance level P < 0.05.

Turn duration was significantly longer with open-loop cueing in PwPD (P = 0.019). Participants tended to reduce velocity and increase durations of turns with both cueing conditions, but particularly with open-loop cueing (Table 3).

The number of FOG episodes with open- or closed-loop cueing was similar to baseline (Table 4). There were no consistent relationships between behavioral measures and PFC activation during any of the conditions (see Supplemental Digital Content 2, Supplementary Table 1, available at: http://links.lww.com/JNPT/A281). However, better executive function (CLOX1 and TMT A) and sensory function (touch processing) consistently related to greater PFC activation during baseline turning and walking (see Supplemental Digital Content 3, Supplementary Table 2, available at: http://links.lww.com/JNPT/A282).

Table 4 - Number of Freezing Episodes Observed During Turning and Walking
FOG Episodes, n Pa
Baseline
180° turn 1 ...
360° turn 6 ...
Single-task gait 3 ...
Dual-task gait 3 ...
Closed-loop
180° turn 1 1.000
360° turn 6 0.180
Single-task gait 1 0.157
Dual-task gait 3 1.000
Open-loop
180° turn 1 1.000
360° turn 5 0.083
Single-task gait 2 0.564
Dual-task gait 3 1.000
A
bbreviation; FOG, freezing of gait.
a
Wilcoxon signed rank test for difference between baseline and cued conditions.

DISCUSSION

This study investigated PFC activation response to open- and closed-loop tactile cueing during walking and turning in PwPD. In contrast to our hypothesis, PFC activity while walking or turning did not significantly change from baseline with open- or closed-loop tactile cueing. This was consistent across FOG+ and FOG− participants. However, there were significant improvements in gait with cueing, with reduction in dual-task cost. Turning characteristics also significantly changed with open-loop cueing, although participants tended to slow down during turning with both cue modalities. These novel preliminary findings suggest that tactile cueing can modify walking behavior in PwPD, which does not occur at the cost of overburdening PFC activity.

PFC Activation When Walking and Turning in People With Parkinson Disease

Without cueing, PFC activity was greater in the early period (first 40 seconds) than in the late period (last 40 seconds) of walking in PwPD, which is similar to previous older adult78 and PwPD studies.42 PFC activity also increased beyond usual walking during a turn in PwPD (irrespective of freezing status), which has only previously been reported in FOG+ subjects.42,65 Therefore, beginning to walk and throughout turning executive-attentional resources may be required to compensate for underlying motor deficits, with return to more automatic walking after the initial period or when task demands reduce. However, due to the robust methodology we employed and novelty of our cueing device, direct result comparisons to previous studies are limited. For example, unlike the current study, previous studies65 have only used subjective manual video observation rather than objective IMUs to determine turning periods. Similarly, other fNIRS studies42,65,76 have not used short-separation channels to remove peripheral noise, which may affect data quality.

PFC Activation During Walking and Turning Did Not Change With Tactile Cueing

Despite modifying behavioral outcomes, open- and closed-loop tactile cueing did not change PFC activation during walking or turning in PwPD, which was consistent regardless of FOG status or attentional demands (dual-task). Our findings reflect previous research in PwPD that has shown no significant differences in EEG-measured cortical activity with or without visual cues for motor (postural response) performance.79 However, results also contrast with previous auditory cueing studies during treadmill walking in healthy adults, which have shown increased PFC and motor-region activation with cues.76,80

Lack of PFC activity change with tactile cueing may relate to inflexibility or overburdening (ie, ceiling effect) of executive-attentional resources for gait or turning in PwPD, which may not allow further increased activity. For example, during gait the processing of environmentally salient stimuli rather than motor task performance may preoccupy executive-attentional resources in PwPD,81 whereas cueing may change resource allocation. Measuring only PFC activation provides limited understanding of specific resource application. Therefore, rather than increased use of PFC executive-attentional resources, tactile cues may prompt more appropriate focus of resources for application to particular task or movement elements (eg, selection, sequencing, timing, or amplitude of movements) that may involve PFC projections to alternative brain regions.

Different brain regions may play a larger role in tactile cue response than the PFC. Previous research suggests that with age and pathology additional cortical regions are recruited to manage the increased demands of a given task,82 such as walking. Similarly, selective activation of specific cortical regions (ie, PFC) is reduced with age82 and further with pathology.83 Consequently, our PwPD likely recruited diffuse brain regions, such as premotor, supplementary, motor or parietal regions, to compensate for additional demands of cueing. Another factor is that PFC activation represents conscious (voluntary, top-down) attention; however, improved motor performance in PwPD may relate to automatic (bottom-up) attentional integration of heightened sensory information that does not heavily involve the PFC.84

Clinical Implications

In line with previous research,85,86 both open- and closed-loop tactile cues can improve gait in PwPD, which occurs without further burdening executive-attentional resources beyond usual walking. Findings are limited to the immediate use of cueing, as future studies are needed to examine the effects of longer bouts of training with cues, and whether cue response differs overtime, or whether they lead to different learning strategies in PwPD.

Turning was slower particularly with open-loop cueing, while PFC activity was similar in all conditions. Turning performance in PwPD is generally impaired compared with controls (ie, more steps, slower, longer, etc). Previous open-loop auditory cue studies have reported reduced turn duration, increased turn velocity, and reduced FOG episodes in PwPD.85 However, other auditory cueing studies have shown increased number of steps required to turn and no change in FOG episodes.18 The tactile cues used in this study did not influence FOG episodes, and made turning longer and slower than without cues. However, we cannot be certain that the cues made turning “worse” per se, as fast turning in PwPD has been found to be less stable compared with slower turn.87 Therefore, slower turning possibly indicates a more conservative strategy with cueing compared with without. Further analysis on turning stability may explain whether slower turning with cueing is safer. It will also be important to assess whether cueing strategies are more valuable for reducing gait deficits compared with teaching the individuals to alter their movement strategy.88

Study Limitations

There were several limitations of this study. First, testing was only conducted OFF dopaminergic medication in a relatively small cohort. Post hoc power analysis demonstrated findings had sufficient power to detect PFC activation differences between conditions during walking (effect size f2 = 0.52, power [1 − β] = 0.92), but may have been slightly underpowered for turning (effect size f2 = 0.28, power [1− β] = 0.71); therefore, future studies in a larger cohort are required. Second, we were unable to adapt the open-loop cue to individual walking patterns (eg, 20% above usual cadence). Third, although our hypothesis focused on PFC activation with cueing, we may have found activation in other cortical regions with cueing by using a full-cap fNIRS system. Lastly, turns were repeated once, whereas continuous 360° turns may elicit more impairments in PwPD.

CONCLUSIONS

Preliminary observations suggest that providing open- or closed-loop tactile cueing may improve gait in PwPD, which does not burden PFC activity beyond usual walking. However, results on turning are less clear, as turning was longer with cueing compared with baseline. Future studies, with larger sample size, are required to assess contributions of various brain regions during open- and closed-loop cueing to provide a robust understanding of the underlying mechanisms involved.

ACKNOWLEDGMENTS

The authors would like to acknowledge the research participants for their involvement in this study, and Georgeann Booth for recruiting and scheduling participants.

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Keywords:

cueing; freezing; gait; Parkinson disease; rehabilitation; turning

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