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. Author manuscript; available in PMC: 2018 Sep 1.
Published in final edited form as: Neuropsychology. 2017 Apr 17;31(6):613–623. doi: 10.1037/neu0000331

Dual Tasking in Parkinson’s Disease: Cognitive Consequences While Walking

Robert D Salazar 1, Xiaolin Ren 2, Terry D Ellis 3, Noor Toraif 4, Olivier J Barthelemy 5, Sandy Neargarder 6, Alice Cronin-Golomb 7
PMCID: PMC5578900  NIHMSID: NIHMS862221  PMID: 28414497

Abstract

Objective

Cognitive deficits are common in Parkinson’s disease (PD) and exacerbate the functional limitations imposed by PD’s hallmark motor symptoms, including impairments in walking. Though much research has addressed the effect of dual cognitive-locomotor tasks on walking, less is known about their effect on cognition. The purpose of this study was to investigate the relation between gait and executive function, with the hypothesis that dual tasking would exacerbate cognitive vulnerabilities in PD as well as being associated with gait disturbances.

Method

Nineteen individuals with mild-moderate PD without dementia and 13 age- and education-matched normal control adults (NC) participated. Executive function (set-shifting) and walking were assessed singly and during dual tasking.

Results

Dual tasking had a significant effect on cognition (reduced set-shifting) and on walking (speed, stride length) for both PD and NC, and also on stride frequency for PD only. The impact of dual tasking on walking speed and stride frequency was significantly greater for PD than NC. Though the group by condition interaction was not significant, PD had fewer set-shifts than NC on dual task. Further, relative to NC, PD showed significantly greater variability in cognitive performance under dual tasking, whereas variability in motor performance remained unaffected by dual tasking.

Conclusions

Dual tasking had a significantly greater effect in PD than in NC on cognition as well as on walking. The results suggest that assessment and treatment of PD should consider the cognitive as well as the gait components of PD-related deficits under dual-task conditions.

Keywords: Parkinson’s disease, dual tasking, executive function, gait dysfunction

Introduction

Parkinson’s disease (PD) is characterized by both motor and nonmotor symptoms that present challenges to activities of living and quality of life. A prominent example of the interaction of motor and nonmotor symptoms is in the domain of walking. Beginning with the motor symptoms, PD-related gait abnormalities include slow walking speed, short strides, propulsion, retropulsion, shuffling steps, reduced or absent arm swing, and rigidity in trunk movements (Rochester et al., 2004; Van Emmerik, Wagenaar, Winogrodzka, & Wolters, 1999; Winogrodzka, Wagenaar, Booij, & Wolters, 2005), with some individuals also experiencing freezing of gait (Davidsdottir, Cronin-Golomb, & Lee, 2005; Giladi et al., 2001). The severity of such impairments ranges from mild (i.e., “preclinical gait syndrome”; Panyakaew & Bhidayasiri, 2013) to debilitating (reviewed in Ebersbach, Moreau, Gandor, Defebvre, & Devos, 2013) and is associated with increased risk of physical harm from falls (Grimbergen, Munneke, & Bloem, 2004; Rochester et al., 2004; Wood, Bilclough, Bowron, & Walker, 2002; Woollacott & Shumway-Cook, 2002). Impairments of walking accordingly impose marked limitations to mobility and quality of life (Bloem, Hausdorff, Visser, & Giladi, 2004; Grimbergen et al., 2004; Martinez-Martin, 1998).

Among the nonmotor symptoms, cognitive impairments are common in PD and interact with walking and other motor symptoms. Even early in the disease course, disruptions to frontal-striatal circuitry result in attentional and executive dysfunction (Miller, Neargarder, Risi, & Cronin-Golomb, 2013). Executive function, including set-shifting, seems especially important to walking in PD. Set-shifting deficits occur in the early stages of PD (Cronin-Golomb, Corkin, & Growdon, 1994) and are related to disrupted frontal-striatal circuitry (Monchi et al., 2004). Such deficits limit the ability to manage complex task demands, and may affect locomotion by disrupting the ability to simultaneously execute cognitive and motor plans, and to flexibly respond to changes in the environment. For example, impaired set-shifting capacity has been found to be associated with reductions in gait speed and stride length (Plotnik, Dagan, Gurevich, Giladi, & Hausdorff, 2011). In PD with gait freezing, the extent of freezing correlated with set-shifting scores (Naismith, Shine, & Lewis, 2010) and with lower scores on a number of executive function measures (Amboni, Barone, & Hausdorff, 2013; Amboni, Cozzolino, Longo, Picillo, & Barone, 2008). Greater stride-time variability on dual tasking was associated with lower scores on a Stroop interference task (Yogev et al. 2005). Dual-tasking studies of PD have identified several deleterious changes in gait that are elicited by concurrent cognitive challenge (i.e., cognitive load), including slower walking speed (Yogev-Seligmann, Giladi, Gruendlinger, & Hausdorff, 2013), increased stride width (Panyakaew & Bhidayasiri, 2013), increased gait variability (Hausdorff, Balash, & Giladi, 2003; Yogev et al., 2005), shorter step length (Rochester et al., 2004), postural instability (Marchese, Bove, & Abbruzzese, 2003; Rochester, Galna, Lord, & Burn, 2014), more steps and increased cadence during turns (Spildooren et al., 2010), and poorer bilateral inter-limb coordination (Plotnik, Giladi, Dagan, & Hausdorff, 2011; Plotnik, Giladi, & Hausdorff, 2009).

As shown by the studies above, the overwhelming emphasis of dual-tasking (cognitive-motor) assessment in PD is on motor output (i.e., walking). That is, the dual-task cost is to motor function. Understanding of the effects of dual tasking in PD is incomplete, however, without also considering its cost to cognition. The use of dual-tasking experimental paradigms is based upon the premise that attentional resources are limited; simultaneous tasks compete for this finite store of attention. Commonly cited systems for executing multiple tasks include the supervisory attentional system, the executive control network, the central executive, and top-down attentional control; collectively these constructs can be subsumed under the category of executive control (Daffner & Willment, 2014), which is dependent upon cortical-subcortical circuitry that is disrupted in PD (Putcha, Ross, Cronin-Golomb, Janes, & Stern, 2015; Rowe et al., 2002; Shine, Halliday, Naismith, & Lewis, 2011; Shine et al., 2013; Tessitore et al., 2012).

Most clinical and research dual-tasking assessments emphasize the impact of cognitive load on motor function, presumably since deficient motor processes can most directly affect mobility, physical safety, and quality of life. By contrast, the “secondary” cognitive task is commonly unassessed: there is no measure of the impact of dual-tasking on baseline (single-task) cognitive capacity (e.g., accuracy on the cognitive task). Failing to assess cognition results in only a partial description of the effects of dual-tasking, masking the potential cognitive burden that it imposes. In light of the cognitive vulnerabilities associated with PD, it may be as likely that cognition will suffer from cognitive-motor dual-tasking as it is that motor function will suffer. The loss of motor automaticity in PD (Hausdorff, Cudkowicz, Firtion, Wei, & Goldberger, 1998; Obeso et al., 2000) requires recruitment of attentional and cognitive resources for managing basic motor function (motor single-task) (Morris, Iansek, Matyas, & Summers, 1996), thereby disadvantaging an already compromised cognitive system; accordingly, dual-task cost to at least some aspects of cognition is likely to be substantial.

There is limited, mixed evidence regarding the relation of cognitive performance in PD while walking. Rochester and colleagues (2014) found no effect of dual tasking on digit span performance (short-term memory). Spildooren and colleagues (2010) reported more errors in PD with freezing of gait than in PD without freezing or in control participants on an auditory association task while turning. Yogev and colleagues (2005) found more dual-tasking errors in PD than in a healthy control group on a Serial 7’s task (counting backward by 7; working memory). Executive function remains mainly unexamined although, as described above, it is often affected in PD including at the early disease stages. Deficits in set-shifting may be particularly vulnerable to the effects of locomotion, since locomotion independently requires coordination of multiple motor and cognitive functions.

The objective of the current study was to investigate the impact of walking on cognition, in particular on set-shifting. The hypothesis was that, relative to single-task cognitive performance, set-shifting under dual-task conditions would be disproportionately degraded in PD relative to what would be seen in healthy age- and education-matched normal control adults (NC). Effects of dual-tasking on cognition were first assessed by the interaction between group and task condition (single versus dual task) in regard to the mean output across three trials, with the expectation that dual tasking would result in a steeper cost to cognition for the PD group than the NC group. Next, variability across the three single-task and dual-task trials was assessed, as intra-individual variability provides an index of cognitive dysfunction (Kälin et al., 2014; MacDonald, Li, & Bäckman, 2009; Sliwinski & Buschke, 2004). We expected that compared to NC, PD would show a greater increase in cognitive variability on dual task, reflecting instability in cognitive output while dual tasking. Finally, direct comparisons between PD cognitive and motor function were conducted, with the expectation that dual tasking would lead to poorer cognitive output and greater cognitive variability compared to motor function.

Methods

Participants

Participants included 19 individuals with idiopathic PD (8 women, 11 men) and 13 NC (8 women, 5 men) (Table 1). All procedures were approved by the Institutional Review Board, and consent was obtained according to the Declaration of Helsinki.

Table 1.

Participant Characteristics

PD (n=19)
NC (n=13)
Significance
Age (years) 66.3 (5.6) 63.2 (4.5) NS
Education (years) 17.4 (1.8) 17.3 (2.4) NS
Women:Men 8:11 8:5 p=.28
Beck Anxiety Inventory 5.5 (5.0) 0.9 (1.6) p<.01
Beck Depression Inventory-II 5.1 (4.0) 2.6 (4.4) NS
Geriatric Depression Scale 3.4 (3.3) 2.3 (2.9) NS
Purdue Pegboard (left hand) 11.2 (2.4) 14.1 (1.9) p<.01
Purdue Pegboard (right hand) 11.9 (2.2) 14.6 (1.6) p<.01
UPDRS Total 34.8 (14.5) - -
UPDRS Motor Score 20.6 (10.1) - -
PD Duration (years) 4.9 (4.2) - -
H&Y (median, range) 2 (1–3) - -
LED (mg/day) 161.9 (141.1) - -
PDQ-39 Summary Index 18.2 (18.8) - -
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PD = Parkinson’s disease; NC = Normal control participants. UPDRS = Unified Parkinson’s Disease Rating Scale; H&Y = Hoehn & Yahr stage; LED = Levodopa equivalent dose; PDQ-39 = 39-item Parkinson’s Disease Questionnaire; NS = Not Significant; Values presented are means (standard deviations), unless otherwise indicated. The last six measures were specific to PD.

Participants with PD were recruited through the Parkinson’s Disease Clinic at Boston Medical Center and other community resources including Fox Trial Finder and PD support groups. NC participants were recruited from the general community. Exclusion criteria for both groups included reported coexisting serious chronic illness (including psychiatric or neurological); history of intracranial surgery, traumatic brain injury, alcoholism or other drug abuse; and visual acuity poorer than 20/40 binocular (Snellen eye chart; administered in the lab). Use of any psychoactive medication was an exclusion criterion for the NC group. The PD group was not taking psychoactive medications except for antidepressants and anxiolytics, which are commonly prescribed in this disorder. No participant had a clinical diagnosis of Mild Cognitive Impairment or dementia, and each obtained a score of 26 or better on the Mini-Mental State Examination (Stern, Sano, Paulson, & Mayeux, 1987), MMSE scoring.

Diagnosis of idiopathic PD was made by the participants’ neurologists, using UK Parkinson’s Disease Society Brain Bank clinical diagnostic criteria (Hughes, Daniel, Kilford, & Lees, 1992). They met clinical criteria for mild to moderate disease, with a modified Hoehn and Yahr stage range of 1–3 (Goetz et al., 2004). The PD sample included one in stage 1, two in stage 1.5, ten in stage 2, three in stage 2.5, and three in stage 3. Disease severity was assessed with the Unified Parkinson’s Disease Rating Scale (Fahn & Elton, 1987; Levy et al., 2005). The mean UPDRS total score was 34.8 (SD = 14.5), with a mean motor score of 20.6 (SD = 10.1). Average disease duration was 4.9 years (SD = 4.2). Levodopa equivalent dosages (LED), available for all participants with PD, were calculated according to Tomlinson and colleagues’ conversion formulae (Tomlinson et al., 2010). All were tested in the “on” medication state.

In both groups, psychomotor speed was assessed with the Purdue Pegboard (Tiffin, 1948), using the average number of pegs placed bilaterally. To assess mood, we used the Beck Anxiety Inventory (Beck & Steer, 1990), Beck Depression Inventory-II (Beck, Steer, & Brown, 1996), and the Geriatric Depression Scale (Yesavage et al., 1982). In the PD group only, subjective quality of life was measured with the 39-item Parkinson’s Disease Questionnaire (Peto, Jenkinson, Fitzpatrick, & Greenhall, 1995), and the PDQ-39 summary index was calculated (Peto, Jenkinson, & Fitzpatrick, 1998).

We compared PD and NC on characteristics that may have affected performance in this study. There were no significant differences for age, education, ratio of men to women, or depression. The PD group was slower than NC on the Purdue Pegboard Test, as expected. PD participants endorsed significantly more anxiety than NC, but BAI total score did not relate to the main cognitive and walking variables, and was not considered further in the analyses.

Procedures

Participants walked over ground at their preferred speed along a constructed hallway that was 3.7 m wide, 2.6 m high, and 10.4 m long. The walking surface was a dark carpet with white stripes (5cm x 250cm) that were spaced 45cm apart (in use for a parallel study). Black curtains were placed on each side along the length of the carpet, and the hallway was well lit. Multiple aspects of gait were evaluated using an OptoTrack/3020 System (Northern Digital Inc., Waterloo, ON, Canada), with a spatial resolution of 0.1 mm. An OptoTrak bank (i.e., position sensor) was placed on each side of the walkway and a third OptoTrak bank was located at the front end of the walkway in order to capture a full three-dimensional range of movement for at least eight strides. Infrared light-emitting diodes (IREDs) were fixed on the participants’ chin and bilaterally on the ankle (lateral malleolus), knee (patella), wrist (radiocarpal joint), shoulder (humeral head), cheek (2 cm below zygomatic arch), and hip (anterior superior iliac spine). Real time position of each IRED was sampled at a rate of 100 Hz and stored to disk for further analysis via MatLab (The MathWorks, Inc., Natick, MA). The position time-series were filtered using a zero-lag, fourth order, Butterworth, low-pass filter with a cut-off frequency of 5 Hz. To account for the increase and decrease in acceleration during the speed-up and slow-down phase of each trial, only the middle strides of each trial were included in the analysis. The number of consecutive strides used for analysis ranged from four to six.

After application of the IREDs, participants performed a set of practice trials to orient themselves to the walking environment. They were then instructed to walk at their preferred speed and to proceed down the middle of the carpeted 10 meter walkway three times (single task motor condition). Three baseline walking trials were conducted.

Dual tasking consisted of walking while performing the Oral Trail Making Test–Part B (TMT-B; Ricker, Axelrod, & Houtler, 1996). This task requires putting numbers and letters in alternating increasing sequence. Participants began the task by saying aloud “3-C” and continued verbal set-shifting aloud (4-D, 5-E, etc.), starting after the examiner said “Ready, Go” and ending once the participant reached the end of the walkway.

Participants were instructed to perform three trials of TMT-B while walking (dual-task condition). To limit practice effects, a distractor task (walking and Serial 7’s–counting backward from 100 by 7s) was performed between each dual task trial of walking and TMT-B. The single-task cognitive condition (TMT-B) was administered in a separate session that occurred an average of 16 days (range: 0–49 days) after the single-task walking, and dual-task assessment. The length between visits was dictated solely by participant availability and was considered acceptable for the NC group as well as for the PD group, which consisted of individuals with mild-moderate disease without dementia who had not reported significant changes between visits. For the PD group, 26% (n = 5) completed both study visits in 1 week, 47% (n = 9) within 2 weeks, 68% (n = 13) within 3 weeks, and 84% (n = 16) within 4 weeks. For the NC group, 23% (n = 3) completed both studies in 1 week, 39% (n = 5) within 2 weeks, 69% (n=9) within 3 weeks, and 85% (n = 11) within 4 weeks.

Because the length of time between tests did not differ between groups (t(30) = .68, p = .49) or correlate with cognitive performance (all r’s < .10, all p’s > .59), it was not considered further in the analysis. To prevent practice effects during dual tasking, single-task cognitive measurements were always collected after dual tasking.

Dependent variables of interest included those for cognition, gait (motor), and inter-trial variability (for both cognition and gait). The measure of cognition (executive function, TMT-B), was the ratio of total correct set-shifts (e.g., 3-C, 4-D) to time to complete the 10 meter walk (seconds). The measures of gait were for walking speed, stride length, and stride frequency. Walking speed (meters per second) for the middle strides was estimated by the displacement of the chin marker in the anteroposterior axis, divided by the total time to complete the middle strides. Stride length was calculated by dividing the total anteroposterior displacement of the respective ankle marker by the number of middle strides taken. To account for individual variability in leg length, stride length was normalized by dividing the stride length by the individual’s leg length (centimeters between the hip and ankle markers). Stride frequency (strides per second; Hz) was calculated by dividing the time it took to travel the middle stride distance by the number of strides taken.

In addition to considering the mean performance across trials, we also assessed inter-trial variability of cognition and gait. Variability was indexed by the standard deviation of performance on the three trials in each condition (single-task walking, dual-task walking, single-task cognition, dual-task cognition).

Data analysis

Analyses were performed with SPSS 18.0 (SPSS, Inc., Chicago, IL). Four mixed design analyses of variance (ANOVAs) were used to examine the main effect of group (PD, NC), condition (single, dual task), and the group by condition interaction for each dependent variable: TMT-B, walking speed, stride length, and stride frequency. These analyses were completed for mean performance and inter-trial variability. Significant interaction effects were followed by planned comparisons using independent and dependent samples t-tests. Because of the few number of comparisons made and the independence of the four dependent variables, we did not correct for multiple comparisons. An alpha level of .05 was chosen for all statistical analyses.

For direct comparison of cognition to motor function, z-scores were calculated with respect to the NC group and repeated measures ANOVAs were used to examine the main effect of task type (motor, cognition), condition (single, dual task), and the interaction between task type and condition. These ANOVAs were conducted for PD only. Significant interaction effects were followed by t-tests.

Results

We report the results of performance on the cognitive and walking measures (mean performance and inter-trial variability) under single-task and dual-task conditions.

For all dependent variables, the data were normally distributed (Shapiro-Wilk; all p’s > .11).

Mean performance

The ANOVA results for each task are displayed in Table 2 and Figure 1. A summary of the findings are highlighted below.

Table 2.

ANOVA Results for PD and NC under Single-Task and Dual-Task Conditions for Cognition (TMT-B) and Walking (Speed, Stride Length, Stride Frequency)

TMT-B Mean (SE) F-value (df) eta-squared p-value
Group PD .54 (.02) 3.91 (1, 30) .12 .06
NC .61 (.03)
Condition Single Task .63 (.02) 60.95 (1, 30) .67 < .001
Dual Task .51 (.02)
Group x Conditon PD Single Task .60 (.03) .75 (1, 30) .02 .39
PD Dual Task .47 (.03)
NC Single Task .67 (.03)
NC Dual Task .56 (.03)
Walking Speed Mean (SE) F-value (df) eta-squared p-value
Group PD 1.07 (.04) 5.90 (1, 30) .16 .02
NC 1.24 (.05)
Condition Single Task 1.24 (.03) 172.92 (1, 30) .85 < .001
Dual Task 1.07 (.04)
Group x Conditon PD Single Task 1.18 (.04) 5.84 (1, 30) .16 .02
PD Dual Task .97 (.05)
NC Single Task 1.31 (.05)
NC Dual Task 1.17 (.05)
Stride Length Mean (SE) F-value (df) eta-squared p-value
Group PD 1.50 (.05) 5.06 (1, 30) .14 .03
NC 1.68 (.06)
Condition Single Task 1.65 (.04) 80.86 (1, 30) .73 < .001
Dual Task 1.53 (.04)
Group x Conditon PD Single Task 1.56 (.05) 1.59 (1, 30) .05 .22
PD Dual Task 1.43 (.06)
NC Single Task 1.73 (.06)
NC Dual Task 1.63 (.07)
Stride Frequency Mean (SE) F-value (df) eta-squared p-value
Group PD .86 (.02) 2.64 (1, 30) .08 .12
NC .89 (.02)
Condition Single Task .91 (.01) 34.43 (1, 30) .53 < .001
Dual Task .85 (.02)
Group x Conditon PD Single Task .89 (.02) 6.79 (1, 30) .18 .01
PD Dual Task .82 (.02)
NC Single Task .91 (.02)
NC Dual Task .88 (.02)
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Figure 1.

Figure 1

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Comparisons of PD and NC performance on measures of cognition and walking under single- and dual-task conditions. There was a significant main effect of condition on cognition (Trail Making Test-B, TMT-B) and walking (speed, stride frequency, and stride length), with worse performance under the dual- than the single-task condition. There was a significant main effect of group for walking speed and stride length, and a trend for cognition. The interaction was significant for walking speed and stride frequency. Compared to NC, PD had slower walking speed, lower stride frequency, and fewer TMT-B set shifts on dual task, despite comparable performance on single task. Error bars represent standard error.

The main effect of group was significant for walking speed and stride length; PD walked with slower speed and shorter stride length. There was a trend for PD to make fewer shifts on TMT-B than NC. Comparing single task to dual task, there was a significant main effect of condition for TMT-B, walking speed, stride length, and stride frequency. For all variables, mean performance was poorer under the dual-task than the single-task condition. There was a significant group by condition interaction for walking speed and stride frequency; dual tasking affected walking speed and stride frequency in PD more than NC.

Independent samples t-tests showed comparable performance of PD and NC on single-task measurement of stride frequency (p = .49) and a trend for slower walking speed in PD [t(30) = 1.96, p = .06]. On dual task, PD had lower stride frequency [t(30) = 2.23, p = .03] and slower walking speed [t(17.47) = 2.54, p = .02] than NC. Paired samples t-tests comparing single to dual tasking showed a significant effect for PD and NC on walking speed [PD: t(18) = 10.50, p < .001; NC: t(12) = 10.13, p < .001]. A significant effect of dual tasking was found for stride frequency for PD [t(18) = 7.46, p < .001], with a trend for NC [t(12) = 1.85, p = .09].

The group by condition interaction was not significant for TMT-B, however, planned comparisons were still conducted between PD and NC on single and dual task TMT-B performance. PD had fewer TMT-B shifts on dual tasking [t(30) = 2.07, p = .047], but not on single tasking (p = .13). Paired samples t-tests showed an effect of dual tasking for both PD and NC [PD: t(18) = 5.64, p < .001; NC: t(12) = 8.03, p < .001].

Inter-trial Variability

For all variables, there was no main effect of group (all p’s >.12) or of condition (all p’s >.43). The interaction effect was not significant for walking speed, stride length, or stride frequency (all p’s > .85). There was a trend for a group by condition interaction for TMT-B shifts, [F(1, 30) = 4.11, p = .052]. PD showed no difference in inter-trial variability from single to dual task (p = .38), whereas NC showed a reduction in inter-trial variability on dual task [t(12) = 2.23, p = .045]. On dual task, inter-trial variability was greater for PD than NC [t(26.67) = 2.69, p = .01]; inter-trial variability on single task was comparable between PD and NC (p = .79).

Cognition-Motor Comparison

The following analyses used z-scores with respect to NC in order to allow for direct comparison of cognitive and motor function.

Mean Performance: PD task type by condition interaction

When considering PD function with respect to NC, there was a significant effect of condition for stride frequency [F(1,18) = 8.72, p = .009, η2 = .33], with a trend for walking speed [F(1,18) = 4.02, p = .06, η2 = .18]. This is consistent with the above results that indicated a greater impact of dual tasking on stride frequency and walking speed for PD than NC. The effect of condition was not significant for stride length (p = .18). When directly comparing task type (cognitive versus motor function), the main effect was not significant (all p’s > .34). The task type by condition interaction was not significant for any variable (all p’s > .18).

Inter-trial Variability: PD task type by condition interaction

There was a main effect of task type, with cognitive variability exceeding the variability of walking speed, stride length, and stride frequency. The main effect of condition was significant for all variables, with dual tasking resulting in greater variability compared to single tasking. There was a task type by condition interaction effect for stride length and stride frequency, and a trend for walking speed. Cognitive variability was greater under dual task than under single task conditions [t(18) = −3.19, p = .005], whereas motor variability remained constant across conditions (all p’s > .64). Though cognitive and motor variability were comparable for the single task condition (all p’s > .54), cognitive variability was greater than motor variability for the dual task condition -- walking speed [t(18) = 2.17, p = .04], stride length [t(18) = 3.33, p = .004], stride frequency [t(18) = 2.65, p = .02]. Results are displayed in Table 3 and Figure 2.

Table 3.

ANOVA Results for PD Inter-trial Variability. Z-scores for Cognition (TMT-B) and Walking (Speed, Stride Length, Stride Frequency) in PD

Walking Speed Mean (SE) F-value (df) eta-squared p-value
Task Type TMT-B .84 (.36) 3.28 (1, 18) .15 .09
Walking Speed .26 (.20)
Condition Single Task .15 (.18) 10.95 (1, 18) .38 .004
Dual Task .95 (.34)
Task x Condition TMT-B
Single Task		 .11 (.31) 4.03 (1, 18) .18 .06
TMT-B
Dual Task		 1.56 (.51)
Walking Speed
Single Task		 .18 (.12)
Walking Speed
Dual Task		 .34 (.35)
Stride Length Mean (SE) F-value (df) eta-squared p-value
Task Type TMT-B .84 (.36) 7.20 (1, 18) .29 .02
Stride Length -.09 (.12)
Condition Single Task .02 (.20) 7.22 (1, 18) .29 .02
Dual Task .74 (.28)
Task x Conditon TMT-B
Single Task		 .11 (.31) 10.20 (1, 18) .36 .005
TMT-B
Dual Task		 1.56 (.51)
Stride Length
Single Task		 -.08 (.17)
Stride Length
Dual Task		 -.09 (.14)
Stride Frequency Mean (SE) F-value (df) eta-squared p-value
Task Type TMT-B .84 (.36) 4.42 (1, 18) .20 .05
Stride Frequency .14 (.11)
Condition Single Task .11 (.20) 10.40 (1, 18) .37 .005
Dual Task .87 (.27)
Task x Conditon TMT-B
Single Task		 .11 (.31) 5.78 (1, 18) .24 .03
TMT-B
Dual Task		 1.56 (.51)
Stride Frequency
Single Task		 .10 (.20)
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Figure 2.

Figure 2

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Inter-trial variability for PD group on cognition and walking variables. Z-scores represent PD performance relative to NC. Effect of condition: For cognition (Trail-Making Test-B, TMT-B) but not for walking (speed, stride length, stride frequency), there was a significant difference in inter-trial variability between the single- and dual-task conditions (dual-task performance worse). Effect of task type: For the dual-task condition, inter-trial variability was significantly greater for cognition than for walking (speed, stride length, and stride frequency). For the single-task condition, there were no significant differences in inter-trial variability between cognition and any walking variable. Error bars represent standard error.

Discussion

This study assessed the impact of dual tasking on cognition in PD with the hypothesis that dual tasking would not only affect motor function, but would also affect cognition. This hypothesis arises from the characterization of PD as a disease marked by diminished motor automaticity, in which cognitive resources are required to facilitate the production of movements that are typically automatic and effortless. In a sense, PD locomotion is in itself a dual task in that it requires cognitive control while simultaneously engaging in the motor demands of locomotion. Consequently, the addition of attentional or cognitive demands should result in notable compromises in performance of a dual cognitive-motor task.

Cognition

We found that individuals with PD demonstrated an overall tendency to produce fewer set shifts than did NC. Dual tasking impacted the mean output of set shifts for both PD and NC similarly. Although the group by condition interaction was not significant, PD had fewer set-shifts than NC on dual task. Dual tasking had a greater impact on cognitive inter-trial variability for PD than NC, as reflected by the trend for a group by condition interaction. For PD, the impact of dual tasking on cognitive variability was significantly greater than the impact of dual tasking on motor variability.

These results support the long-documented evidence of reduced set-shifting capacity in PD (e.g., Cronin-Golomb et al., 1994), and demonstrate that cognition is impacted by dual tasking. Particularly, PD cognition was characterized by variability in cognitive output under dual tasking. Though overall cognitive output was not strikingly different than NC, the greater variability in PD may represent a marker of dysfunction in dual cognitive-motor processes. The NC group showed less variability in cognitive output on dual tasking than the PD group, suggesting that PD affects the ability to sustain cognitive output as task demands increase. Further, the pattern of PD cognitive dysfunction contrasted with the pattern of PD motor dysfunction. Although PD motor output showed an overall reduction on dual tasking relative to single tasking, variability in motor performance remained unaffected by dual tasking, whereas cognitive performance in PD was marked by significantly greater variability under dual tasking. Of note, these effects occurred for individuals with mild to moderate PD, and were observed while walking a very short distance, under highly controlled conditions. Even under these conditions that were not particularly challenging, the participants with PD showed cognitive vulnerabilities, suggesting that deleterious effects on cognition may be more prevalent in everyday environments that are less predictable and that feature greater environmental demands. The cognitive consequences of PD on dual cognitive-motor tasks has been observed on other motor tasks such as swallowing (Troche, Okun, Rosenbek, Altmann, & Sapienza, 2014), handwriting (Broeder et al., 2014) and copying figures (De Lucia, Grossi, Mauro, & Trojano, 2015), with implications for the role of neurorehabilitation in enhancing motor function by targeting PD cognitive vulnerabilities (Conradsson et al., 2015). Ultimately, cognition may prove to be a modifiable treatment target, with cognitive enhancement also resulting in improvement of traditional PD motor symptoms.

Gait

Individuals with PD walked with shorter strides and slower speed than NC. In both the PD and NC groups, dual tasking resulted in a decline in walking speed, stride length, and stride frequency, relative to the single-task walking condition. Compared to NC, dual tasking resulted in particular decrements in PD walking speed and stride frequency. The significant group by condition interaction indicates that dual tasking affected walking speed and stride frequency to a greater degree in PD than NC, underscoring the effect of cognitive load on gait in the PD group..

These findings highlight the impact of PD on aspects of walking, and point to practical implications. As we and others have found, walking dysfunction in PD consists of classic motor symptoms (e.g., reduced walking speed) that may be particularly exacerbated when combined with cognitive vulnerabilities (Yogev et al., 2008). In the present study, this was most clearly seen in the effect of dual tasking on stride frequency. Even though stride frequency problems are a common consequence of PD (Morris, Iansek, McGinley, Matyas, & Huxham, 2005; Young et al., 2010), in our study, PD stride frequency was comparable to that of NC under single-task conditions. Under the demands of dual tasking relative to single tasking, PD stride frequency significantly declined, and this decline was greater than that seen in NC. Until faced with combined cognitive and motor demands, PD function resembled that of NC, highlighting the PD disadvantage in locomotion under attentional demands. Since PD is associated with limited capacity to allocate cognitive resources (Bloem, Grimbergen, van Dijk, & Munneke, 2006; Dubois & Pillon, 1997), it is unsurprising that dual-tasking deficits were observed in PD.

The gait pattern of this PD sample under dual tasking suggested overall a cautious walking style marked by slower walking speed, shorter stride length, and shorter stride frequency, which contrasts with the typical PD gait as characterized by an increase in stride frequency (i.e., shuffling steps). The, baseline gait assessment showed comparable stride frequency for PD and NC, indicating that this relatively mild PD sample was not prone to shuffling gait. Instead, the observed reduction in stride frequency may reflect a more conscious, cautious gait pattern including slower walking speed and shorter stride length. Coupled with the greater cognitive variability demonstrated under dual tasking, this pattern may suggest that this PD sample prioritized walking safely over cognitive output. Cho et al. (2010) suggested that difficulty in matching walking speed and stride frequency is a primary problem in PD gait–individuals with the disorder walk with more frequent steps, but fail to generate a velocity appropriate to this frequency. Hence, a reduction in walking speed and stride frequency on dual tasking as seen in the present study may be a compensatory response to the cognitive loading. Additional studies have reported that stride frequency declines (Canning, 2005; O’Shea, Morris, & Iansek, 2002) or remain the same in PD (Bond & Morris, 2000; Rochester et al., 2004) under dual tasking, while walking speed and stride length decrease (Bond & Morris, 2000; Canning, 2005; O’Shea et al., 2002; Rochester et al., 2004), suggesting that in idiopathic, non-demented PD, this gait pattern may be a consequence of cognitive load.

Neural substrates of dual task effects

Considering the complex demands of navigating the environment, including planning, visual processing, goal-directed execution of behavior, and coordination of limbs, a better understanding of key neural structures and circuits responsible for these results may offer important insight into potential treatment targets. Most imaging research on gait dysfunction in PD has been limited to investigations of freezing of gait (Shine et al., 2013; Tessitore et al., 2012). In light of the cognitive and motor vulnerabilities described in the present study, specific consideration should be placed on the relation of walking dysfunction to reduced functional connectivity of core attentional-cognitive networks. Rowe and colleagues found an absence of effective connectivity between the prefrontal cortex (PFC) and the lateral premotor cortex and the supplementary motor area in PD (Rowe et al., 2002). More recent research has highlighted the role of disrupted connectivity between the default mode network (DMN) and networks important for attention and executive function (Shine et al., 2013). PD shows abnormal activation of the PFC and DMN, suggesting disruption of these frontal-basal ganglia circuits (Tinaz, Schendan, & Stern, 2008). Putcha and colleagues noted abnormal resting state connectivity between the DMN and the central executive network (CEN) in PD (Putcha et al., 2015). Whereas DMN and CEN interactions are typically anti-correlated in healthy individuals, those with PD showed greater DMN-CEN coupling at rest. Further, decreased connectivity in the DMN relates to severity of cognitive dysfunction in PD (Tessitore et al., 2012). Van Eimeren and colleagues reported the disturbance of the DMN during a card sorting task, speaking to the relation between DMN abnormalities in PD and executive function (van Eimeren, Monchi, Ballanger, & Strafella, 2009). Gait vulnerabilities may further be exacerbated by disrupted connections between the DMN and attentional networks that compromise the ability to accurately perceive aspects of the environment or to develop an appropriate response (Shine et al., 2011).

Taken together, these studies describe specific deficits to cognitive networks responsible for attention and executive function. As noted above, the investigation of neural networks related to gait has mainly been limited to freezing of gait. The results of the present study raise the expectation of a relation between disrupted functional connectivity of cognitive networks and the presence of both cognitive and motor deficits associated with dual tasking in PD, a prediction that will need to be assessed through future research.

Limitations

This study was subject to several limitations beyond the sample size. We examined only mild to moderate PD, and cannot generalize our results to individuals with more severe disease. Because those with more severe motor dysfunction are often also those with more advanced cognitive dysfunction, however, we would expect the interaction between motor and cognitive impairments to be even greater with increased disease severity. Another limitation was that this research was conducted in a research lab and the participants were confined to a walkway while wearing IREDs to collect kinematic data. Having now provided baseline information under controlled conditions, we suggest that future studies may enhance the ecological validity of these results, and presumably reveal even stronger PD effects, by use of a relatively unconfined space and simulation of more typical environmental demands (e.g., walking around moving and stationary obstacles, distraction by sounds, changing physical settings). A further potential limitation was that single- and dual-task cognitive data were collected on separate days (dual-task first) in order to minimize practice effects during dual tasking (which was the primary focus of the study) and to limit fatigue. The mean time between single-and dual-task cognitive assessment was the same for PD and NC, and did not relate to cognitive performance, suggesting that the gap between visits was inconsequential.

More important to note is that the study was designed to, if anything, underestimate the impact of dual-task demands on cognition, rather than overestimate it. For all participants, single-task walking and dual-task walking/cognition data were collected at the first study visit, whereas single-task cognition data were collected at the second visit. Had PD cognition declined between the first and second study visit, the difference in cognitive performance in the single-task vs dual-task conditions would have been reduced: In the dual-task condition, cognition would have been affected by dual tasking itself (our hypothesis), whereas in the single-task condition, it would have been affected by some potential effect of the gap between study visits (time-related decline). Hence, we would be unlikely to find an effect of dual-tasking on cognition unless it were quite a large effect (overriding any cognitive decline over the days between visits), or unless the dual-task effect were smaller (but still significant) but there really was no cognitive decline over that period. Taking together the shortness of the gap between visits, the mild-moderate severity of the disease and lack of dementia in the PD group, and the conservative study design, we are confident in our results of an effect of dual-tasking on cognition in this PD sample.

Conclusions

The combined effect of dual tasking on cognition and gait reflects limitations in the ability of individuals with PD to manage the complex cognitive and motor demands of locomotion. Targeting walking dysfunction in PD has been shown to improve gait speed (Uc et al., 2014), balance and self-reported activities of daily living (Tomlinson et al., 2012), reduce the risk of falls (Morris et al., 2015), and enhance health-related quality of life (Tickle-Degnen, Ellis, Saint-Hilaire, Thomas, & Wagenaar, 2010). Though physical interventions aimed at improving walking promote this goal, such treatments may be incomplete without considering simultaneous interventions to maximize cognition. A combination of cognitive interventions and physical rehabilitation may prove to be the most effective approach to optimize walking, while also promoting the individual’s ability to engage in cognition during locomotion, the need for which occurs commonly in everyday life. Future research may offer important contributions by determining the cognitive functions most compromised during dual tasking in PD and developing interventions that benefit both cognition and motor function.

Acknowledgments

This work was supported by National Institute of Neurological Disorders and Stroke grant R01 NS067128 to ACG, and the Dudley Allen Sargent Research Fund to XR. Our recruitment efforts were supported, with our gratitude, by Marie Saint-Hilaire, MD and Cathi Thomas, RN, MSN, of Boston Medical Center Neurology Associates, and by the Fox Foundation Trial Finder. We thank Laura Pistorino, who assisted with participant recruitment, and Tim Dorr and Norick Bowers for assistance with data collection. We are especially grateful to the participants in this study for their efforts.

Contributor Information

Robert D. Salazar, Boston University

Xiaolin Ren, Boston University.

Terry D. Ellis, Boston University

Noor Toraif, Boston University.

Olivier J. Barthelemy, Boston University

Sandy Neargarder, Boston University and Bridgewater State University.

Alice Cronin-Golomb, Boston University.

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