Dual tasking negatively impacts obstacle avoidance abilities in post-stroke individuals with visuospatial neglect: Task complexity matters!

Abstract

Background:

Persons with perceptual-attentional deficits due to visuospatial neglect (VSN) after a stroke are at a risk of collisions while walking in the presence of moving obstacles. The attentional burden of performing a dual-task may further compromise their obstacle avoidance performance, putting them at a greater risk of collisions.

Objective:

The objective of this study was to compare the ability of persons with (VSN+) and without VSN (VSN–) to dual task while negotiating moving obstacles.

Methods:

Twenty-six stroke survivors (13 VSN+, 13 VSN–) were assessed on their ability to (a) negotiate moving obstacles while walking (locomotor single task); (b) perform a pitch-discrimination task (cognitive single task) and (c) simultaneously perform the walking and cognitive tasks (dual task). We compared the groups on locomotor (collision rates, minimum distance from obstacle and onset of strategies) and cognitive (error rates) outcomes.

Results:

For both single and dual task walking, VSN+ individuals showed higher collision rates compared to VSN– individuals. Dual tasking caused deterioration of locomotor (more collisions, delayed onset and smaller minimum distances) and cognitive performances (higher error rate) in VSN+ individuals. Contrastingly, VSN– individuals maintained collision rates, increased minimum distance, but showed more cognitive errors, prioritizing their locomotor performance.

Conclusion:

Individuals with VSN demonstrate cognitive-locomotor interference under dual task conditions, which could severely compromise safety when ambulating in community environments and may explain the poor recovery of independent community ambulation in these individuals.

Keywords

Circumvention dual tasking hemineglect locomotion virtual reality

1 Introduction

Visuospatial neglect (VSN) is a common and disabling condition frequently observed in persons with stroke (Heilman, Valenstein, & Watson, 2000; Ringman, Saver, Woolson, Clarke, & Adams, 2004; Wertman, 2002). It is an attentional – perceptual disorder which impairs the ability to orient towards and/or respond to relevant stimuli on the side opposite to the brain lesion (i.e. contralesional side) (Heilman et al., 2000). During walking, such attentional-perceptual deficit could affect the ability to attend to visuospatial information such as the location of the intended goal or the presence of obstacles in the walking path, especially if these features are present in the contralesional side of space. Consequently, the planning and execution of adaptive strategies could be impaired leading to falls and collisions.

Successful community ambulation involves walking safely under different spatial and temporal constraints, in the presence of static and moving obstacles (Shumway-Cook et al., 2002). In our previous study, we demonstrated that post-stroke VSN+ individuals had difficulty negotiating moving obstacles while walking (Aravind & Lamontagne, 2014), which may hamper safety while walking in the community as moving obstacles are frequently encountered. Community ambulation also involves performing several tasks concurrently, such as walking while making a mental list or talking, which is commonly referred to as dual-task walking. If the total attentional demands of the tasks being performed simultaneously exceeds total processing capacity, it can result in the deterioration of the walking performance (locomotor cost), the cognitive performance (cognitive cost) or both (referred to as dual-task interference or, in this specific case, to cognitive-motor interference) (Rabuffetti et al., 2013).

Such interference is likely to be greater when the locomotor function is already compromised (e.g. after a stroke) or if attentional deficits (such as VSN) are present. Studies involving overground un-obstructed walking while performing a dual-task in post-stroke individuals have observed motor interference (reduction in walking speed, reduction in walking balance, increased risk of falls) or cognitive-motor interference (cognitive errors along with motor interference) during dual-task situations (Rabuffetti et al., 2013). However, dual-task walking during complex locomotor tasks such as obstacle avoidance has not been studied in persons with VSN.

Given that VSN+ individuals experience spatially lateralized (attentional bias, reduced contralesional exploration and increased response times) and non-spatially-lateralized (reduced attentional capacity and arousal) attention deficits (Husain & Rorden, 2003; Suchan, Rorden, & Karnath, 2012), along with post-stroke locomotor impairments, they may be more vulnerable to the effects of dual-tasking than VSN– individuals.

In order to understand the implications of dual-tasking on the safety of VSN+ and VSN– individuals while walking in complex environments, such as in the presence of moving obstacles, we assessed their abilities to negotiate moving obstacles while performing a cognitive task simultaneously, in a virtual reality set-up. The virtual environment (VE) offers a safe, controlled and realistic environment to assess walking while yielding behaviours similar to real-world behaviour (Gerin-Lajoie, Richards, Fung, & McFadyen, 2008.

We hypothesized that the concurrent performance of a locomotor and cognitive task would cause cognitive-motor interference both in VSN+ and VSN– individuals with stroke. The extent of interference, however, would be larger in VSN+ individuals than in VSN– individuals. Moreover, since VSN symptoms become more apparent with an increase in task complexity (Bonato, 2012), the interference would be greater for a more complex task. VSN+ individuals would further present with an asymmetry in the obstacle avoidance performance where performance on the locomotor and cognitive task are more compromised for obstacle approaching from the neglected (contralesional) as compared to the non-neglected (ipsilesional) side.

2 Methods

Twenty-six participants (Table 1) following a first-time right-sided supratentorial stroke (13 VSN+ and 13 VSN–) were recruited from 3 rehabilitation clinical sites of the Centre for Interdisciplinary Research in Rehabilitation of Greater Montreal (CRIR) based on the following inclusion criteria: a right-hemispheric stroke (CT scan/MRI); a clinical diagnosis of VSN (Motor Free Visual Perceptual Test, Letter Cancellation Test, or Bells Test); an ability to walk independently, (<1.2 m/s, with or without a walking-aid); and motor recovery scores of 3–6 out of 7 on the leg and foot components of the Chedoke McMaster Stroke Assessment (CMMSA). Individuals with visual field defects, hearing loss, cognitive deficits (<26 on the Mini-Mental State Examination) or other co-morbid conditions interfering with locomotion were excluded. To confirm the presence of VSN at the time of participation, participants were re-evaluated on clinical assessments of VSN, including the Bells test (Gauthier, Dehaut, & Joanette, 1989), Line Bisection test (Schenkenberg, Bradford, & Ajax, 1980), and the Apples test (Bickerton, Samson, Williamson, & Humphreys, 2011). Participants were included in the VSN+ group if they showed positive results (6 or more omissions on the Bells test (Gauthier et al., 1989), error 6 mm or greater on the Line Bisection test (Schenkenberg et al., 1980), and omission of 5 or more apples on the Apples test (Mancuso et al., 2015) on 2 out of the 3 tests. The study was approved by the Ethics Committee of CRIR and all participants gave their informed written consent.

Table 1
Participant characteristics: Abbreviations: VSN, Visuospatial neglect; MoCA, Montreal Cognitive Assessment; CMMSA, Chedoke-McMaster Stroke Assessment (CMMSA); TMT-B, Trail making test-B; SD, standard deviation

Subject ID Age (yrs) MoCA Chronicity (months) CMMSA TMT-B (seconds) Bells omission Line bisection Apples

VSN-1 72 28 13 6,6 101 5 28.5 0

VSN-2 60 28 18 5,5 40 2 60 5

VSN-3 53 25 6 6,5 104.3 4 43 0

VSN-4 64 29 18 6,5 100 2 75 4

VSN-5 68 26 20 6,6 88 4 64 5

VSN-6 65 27 8 6,6 76 0 68 2

VSN-7 58 28 7 5,4 92 0 62.5 0

VSN-8 53 27 5 6,5 48 1 86 1

VSN-9 64 26 7 6,6 109 1 26 1

VSN-10 51 28 10 6,6 92 0 109.5 0

VSN-11 57 26 11 6,6 60 4 46.5 0

VSN-12 69 30 12 5,5 79 1 40 1

VSN-13 56 24 19 6,5 60 1 40 1

Mean 60.8 27.1 11.8 – 80.7 1.9 57.6 1.5

SD 6.5 1.6 5.1 – 21.6 1.7 22.8 1.8

VSN+1 72 24 13 5,5 263 5 128.5 6

VSN+2 69 28 12 6,5 135 5 68 7

VSN+3 66 25 10 6,6 438 6 216 0

VSN+4 54 28 13 6,5 154 6 65 6

VSN+5 58 25 1 6,6 146 5 88 6

VSN+6 54 25 20 5,5 65 7 208 8

VSN+7 63 26 6 5,5 324 6 138 7

VSN+8 53 26 8 5,5 192 11 72.5 4

VSN+9 67 25 8 6,5 81 7 79 0

VSN+10 49 27 17 5,5 91 7 64.5 6

VSN+11 48 28 8 6,6 141 5 76.5 6

VSN+12 57 24 10 5,4 86 9 70.5 8

VSN+13 67 28 10 6,6 58 11 75 4

Mean 59.8 26.1 10.5 – 159.5 6.9 103.8 5.2

SD 7.7 1.5 4.6 – 113.3 2.1 51.2 2.5

Subject ID	Age (yrs)	MoCA	Chronicity (months)	CMMSA	TMT-B (seconds)	Bells omission	Line bisection	Apples
VSN-1	72	28	13	6,6	101	5	28.5	0
VSN-2	60	28	18	5,5	40	2	60	5
VSN-3	53	25	6	6,5	104.3	4	43	0
VSN-4	64	29	18	6,5	100	2	75	4
VSN-5	68	26	20	6,6	88	4	64	5
VSN-6	65	27	8	6,6	76	0	68	2
VSN-7	58	28	7	5,4	92	0	62.5	0
VSN-8	53	27	5	6,5	48	1	86	1
VSN-9	64	26	7	6,6	109	1	26	1
VSN-10	51	28	10	6,6	92	0	109.5	0
VSN-11	57	26	11	6,6	60	4	46.5	0
VSN-12	69	30	12	5,5	79	1	40	1
VSN-13	56	24	19	6,5	60	1	40	1
Mean	60.8	27.1	11.8	–	80.7	1.9	57.6	1.5
SD	6.5	1.6	5.1	–	21.6	1.7	22.8	1.8
VSN+1	72	24	13	5,5	263	5	128.5	6
VSN+2	69	28	12	6,5	135	5	68	7
VSN+3	66	25	10	6,6	438	6	216	0
VSN+4	54	28	13	6,5	154	6	65	6
VSN+5	58	25	1	6,6	146	5	88	6
VSN+6	54	25	20	5,5	65	7	208	8
VSN+7	63	26	6	5,5	324	6	138	7
VSN+8	53	26	8	5,5	192	11	72.5	4
VSN+9	67	25	8	6,5	81	7	79	0
VSN+10	49	27	17	5,5	91	7	64.5	6
VSN+11	48	28	8	6,6	141	5	76.5	6
VSN+12	57	24	10	5,4	86	9	70.5	8
VSN+13	67	28	10	6,6	58	11	75	4
Mean	59.8	26.1	10.5	–	159.5	6.9	103.8	5.2
SD	7.7	1.5	4.6	–	113.3	2.1	51.2	2.5

2.1 Clinical assessments

Executive cognitive function was assessed with the Montreal Cognitive Assessment (MoCA) (Nasreddine et al., 2005), Trail Making Test B (TMT-B) (Reitan & Wolfson, 1985) and Zoo Map test (Allain et al., 2005). Gait speed was assessed with the 10 m walk test. Recruited participants varied in their comfortable walking speed with values ranging from 0.45 m/s to 1.02 m/s (0.74±0.17 m/s, mean±1SD). All participants were identified as right-hand dominant on the Edinburg Handedness Inventory.

3 Experimental set-up and procedures

3.1 Locomotor Single Task (LocoST)

The locomotor task was conducted in a VE designed using the CAREN 3^TM software (Motek BV, Amsterdam), which the participants viewed through an nVisor SX60 HMD (NVIS, USA). A 12-camera Vicon-512^TM motion capture system tracked the position of three reflective-markers affixed to the HMD. This information, fed to CAREN 3^TM, provided real-time updates of the participants’ position in the VE. Markers were also placed on specific body landmarks as specified in the full-body maker set of the Plug-in-Gait model from Vicon^TM. Data were recorded at 300 Hz in CAREN 3^TM and at 120 Hz in Vicon^TM.

The VE (Fig. 1) presented a room (12 m×8 m) consisting of a blue target on the far-end wall (11 m) and three cylindrical obstacles positioned in front of a theoretical point-of-collision (TPC) in an arc at 0° (Head-on [HO]), 40° right (Ipsilesional side [IL] and 40° left (Contralesional side [CL]). The TPC is the point where the participant and the obstacle paths, if left unaltered, would meet and collide. Participants were instructed to walk towards the target while avoiding a collision with the approaching obstacle, if any. After advancing forward by 0.5 m, one of the 3 obstacles moved in the direction of the TPC and beyond, at a speed that matched the participants’ overground walking speed. Matched walking speeds ensured that a collision was imposed for every obstacle condition unless an avoidance strategy was executed. When a collision occurred, visual feedback was provided in the form of a flashing “Collision” sign. A control condition, with no obstacles in the walking path, was used to determine walking speed and walking trajectory in the absence of moving obstacles.

Fig.1

Schematic representation of the virtual scene. The figure shows an overhead view of the virtual scene with the three cylindrical obstacles and the target. The transparent cylinders represent the path taken by the ipsilesional (right) obstacle when approaching the participant. The avatar is for representational purposes only and is not viewed in the scene. The dotted trace is an example of a path taken to avoid the obstacle. Abbreviations: TPC, theoretical point of collision.

3.2 Cognitive Single Task (CogST)

The cognitive task was an auditory pitch-discrimination (Auditory Stroop) task. Participants were seated and passively observed the VE while responding to the Auditory Stroop stimuli. Two types of tasks were presented: (a) a simple task in which the word “Cat” was presented in a high or low pitch (CogST-CAT) and; (b) a more complex task in which the words “High” or “Low” were presented in a high or low pitch (CogST-HL). The HL task was considered more complex since greater attention and inhibition is required to correctly identify the pitch without being influenced by the sound of the word presented. Meanwhile, participants viewed a scene that simulated the locomotor task but were not required to respond. They were instructed to verbally report the pitch of the sound (High/low). Participants performed four blocks of five trials, resulting in 10 trials each for the CogST-CAT and CogST-HL tasks, with the task order balanced to minimize learning effects.

The auditory stimuli were presented to the participants via seven speakers placed around the room ensuring a uniform sound intensity throughout the walking space. The participants’ responses to the Stroop task were entered into the computer by the researcher and verified offline with an audio recording of the performance.

3.3 Locomotor Dual-task (LocoDT)

During the dual-task obstacle avoidance, participants were instructed to perform the obstacle avoidance and the cognitive tasks simultaneously. Two dual-task conditions were presented: LocoDT-CAT i.e. with “CAT” as the auditory stimulus and LocoDT-HL with “High” and “Low” as the auditory stimuli. The participants were instructed to perform both tasks as well as they could. The performances on the CAT and HL tasks during walking are referred to as CogDT-CAT and CogDT-HLrespectively.

For the locomotor tasks (LocoST, LocoDT-CAT and LocoDT-HL), participants were provided with at least 4 practice trials and 4 to 6 trials per condition were collected, depending on the participant’s endurance. The order of task and of direction of obstacle approach were not fixed, with balancing procedures employed to ensure almost similar number of trials for each task and direction of obstacle approach. Participants were given frequent rest pauses to avoid fatigue.

3.4 Data analysis

For the locomotor tasks, onset of an avoidance strategy was measured as the time at which a medio-lateral displacement (of the head markers) exceeded 0.25 m (half of average shoulder width) on either side. The minimum absolute distance was calculated as the minimum distance maintained between the participant and obstacle, before the obstacle passed beyond the participant. To identify a collision, a critical distance was set for each participant, calculated as the sum of the obstacle-radius and the distance between C7 and the lateral-most marker on the body or walking-aid. When the distance between the participants and the obstacle dropped below this critical distance, a collision event was detected. The number of trials in which collision were detected was divided by the total number of trials for each of the conditions to give the rate of collision. The average walking speeds were also recorded. Locomotor outcomes are suffixed by ST, CAT and HL depending on the task condition.

The extent of change caused by each type of dual-task (LocoDT-CAT or LocoDT-HL) relative to single task (LocoST), i.e. the Dual-task cost was calculated as follows: $Dual task Cost = \frac{LocoDT - LocoST}{LocoST} \times 100$ (1)

For the cognitive tasks, errors in pitch identification or failure to report the pitch were considered as cognitive errors. However, cognitive cost as a percent change from CogST could not be calculated since none of the participants made errors during the CogST-CAT or CogST-HL task. Therefore, actual cognitive error rates under dual-task conditions, as well as differences between CogDT-CAT and CogDT-HL are reported. The rate of cognitive errors was calculated as a proportion of cognitive errors to the total number of stimuli.

3.5 Statistical analysis

We conducted a linear mixed model analysis for repeated measures with unstructured covariance structure, with 1 between subject factor (group: VSN+, VSN–) and 2 within subject factor (task ST, DT-CAT and DT-HL; direction of obstacle approach: CL, HO and IL (exception: 4 levels including control condition (C) for the average walking speed outcome)) to assess the influence of VSN and of dual-tasking on locomotor and cognitive outcomes. Significant interaction terms were further elaborated using simple effects where a priori identified pairwise comparisons were carried out. For the cost outcomes, the analysis was conducted with 1 between subject factor (group: VSN+, VSN–) and 2 within subject factors (task: Dual-task Costs with CAT vs. with HL; direction of obstacle approach: 3 or 4 directions). Student t-tests were used to compare the two groups for age, stroke chronicity, MoCA scores, TMT scores. They were also used to compare the average cognitive errors rates during the first 50% of trials and the 2nd 50% of trials in both VSN+ and VSN– groups to confirm the absence of learning effects on the cognitive tasks.∥Pearson correlations were carried out between performances on the clinical measures (MoCA, TMT-B, Bells test, Line bisection test, Apples test) or other patient characteristics (age, time since stroke,) and dual-task walking costs. Correlations were carried out separately for each obstacle approach. All statistical analyses were performed in SAS v9.4. The level of significance was set to p < 0.05 and adjusted for the number of planned comparisons.

4 Results

Participant characteristics are presented in Table 1. Upon chart review, it was also found that two participants had shown signs of neglect during everyday behaviour and during rehabilitation sessions but did not have any tests performed to confirm the presence of VSN. As they scored positive on at least two of the three VSN clinical tests conducted during this study, they were included into the VSN+ group (participants VSN+10 and VSN+11).

All participants walked independently with two participants (VSN+5 and VSN– 7) using a cane. The VSN+ vs. VSN– groups did not differ in age or stroke chronicity, level of motor recovery (CMMSA), walking speed, cognitive status (MoCA, Zoo Map scores) and years of education (p > 0.05). The VSN+ group did, however, show significantly larger times on the TMT-B (p = 0.03) and, as expected, showed larger errors on the Bells test, Line Bisection test and the Apples test (p < 0.001).

Figure 2 shows examples of walking trajectories adopted by VSN+ and VSN– individuals for different tasks and obstacle conditions. As illustrated by these examples, VSN+ participants deviated to the ipsilesional side in most trials during single task walking (Walk ST), regardless of the obstacle condition (mean±1SD = 85.5±9.7% of trials); This preference became more pronounced for LocoDT-CAT (92.09±4.93% of trials) and even more so for LocoDT-HL (98.33±2.89% of trials). For all obstacle approaches and for all task complexities, VSN– participants did not show a preference to deviate to one side.

Fig.2

Representative diagram of walking strategies adopted by 2 participants. The top row shows the walking trajectories of a VSN– participant, while the bottom row shows the walking trajectories of a VSN+ participant during the LocoST, LocoDT-CAT and LocoDT-HL task. For the VSN+ participant, note the presence of collisions which are represented by red dots (collisions with head-on obstacles) and blue dots (collisions with contralesionally approaching obstacle).

4.1 Collision rates

Collision rates and number of colliders observed during the obstacle avoidance tasks are reported in Table 2. Overall, larger proportions of VSN+ individuals than VSN– individuals collided with obstacles, with higher collision rates under both single and dual-task conditions. Within the VSN+ group, a direction-specific gradient was observed during single task walking (LocoST) and to a greater extent during dual-task walking (LocoDT-CAT and LocoDT-HL), where the proportion of colliders and collision rates increased from the IL to the HO and CL obstacle approaches. Additionally, an effect of task complexity was observed in VSN+ individuals, as both the proportion of colliders and collision rates increased from LocoST to LocoDT-CAT and LocoDT-HL. In fact, 92% and 100% of VSN+ participants collided with HO and CL obstacles while performing the most complex locomotor task (LocoDT-HL), compared to 46% and 76% during single task walking. Within the VSN– group, collision rates did not show the presence of a direction-specific gradient and the number of colliders (range: 18–30%) and collision rates (range: 19–25%) did not drastically differ between the taskcomplexities.

Table 2
Number of colliders and collision rates: Number of colliders as a percentage of total participants are presented (n = 13 for each group). Mean collision rates (as a percentage of trials)±one standard deviation are presented. CL, HO and IL indicate the direction of obstacle approach, contralesional, head-on and ipsilesional, respectively

Group Task CL HO IL

Colliders Collision rate Colliders Collision rate Colliders Collision rate

VSN+ LocoST 76.9 34.4±8.1 46.2 24.7±6.5 0.0 NA

LocoDT-CAT 92.3 48.2±11.6 76.9 30.6±10.6 15.4 24.3±4.3

LocoDT-HL 100.0 61.3±14.4 92.3 39.6±11.9 38.5 30.6±9.1

VSN– LocoST 30.8 33.3±8.2 30.8 24.5±5.4 7.7 16.7

LocoDT-CAT 23.1 36.6±3.3 15.4 18.9±1.6 0.0 NA

LocoDT-HL 23.1 32±11.2 15.4 23.3±2.4 0.0 NA

Group	Task	CL		HO		IL
VSN+	LocoST	76.9	34.4±8.1	46.2	24.7±6.5	0.0	NA
	LocoDT-CAT	92.3	48.2±11.6	76.9	30.6±10.6	15.4	24.3±4.3
	LocoDT-HL	100.0	61.3±14.4	92.3	39.6±11.9	38.5	30.6±9.1
VSN–	LocoST	30.8	33.3±8.2	30.8	24.5±5.4	7.7	16.7
	LocoDT-CAT	23.1	36.6±3.3	15.4	18.9±1.6	0.0	NA
	LocoDT-HL	23.1	32±11.2	15.4	23.3±2.4	0.0	NA

4.2 Obstacle avoidance strategies

For the minimum distance maintained from the obstacle (Fig. 3), a significant interaction effect of Group×Task×Direction was observed (F(4,96) = 3.5, p < 0.05) where the VSN+ maintained significantly smaller minimum distances from the obstacle for the dual-task conditions (LocoDT-CAT and LocoDT-HL), regardless of the direction of obstacle approach, compared to VSN– group (p < 0.001). The VSN+ participants significantly reduced their minimum distances as task complexity increased (LocoST→ LocoDT-CAT→ LocoDT-HL), while the VSN– participants increased their minimum distances for all obstacle direction (p < 0.05). Regardless of task complexity, VSN+ participants also maintained significantly smaller minimum distances for CL and HO obstacles approaches compared to IL obstacles (p < 0.05). Such a direction-specific gradient of minimal distances was not observed for the VSN– group.

Fig.3

Obstacle avoidance outcomes. The figure shows mean (±1SD values) of time of onset of strategy (top row), minimum absolute distances maintained between the participants and the obstacles as well (middle row) and walking speed (bottom row) for the VSN– and VSN+ participants during single-task walking (ST) as well as walking while performing the CAT and the High-Low (HL) cognitive tasks. Statistically significant interaction terms are specified in the text inserts. *p < 0.05.

The onset of strategy showed significant two-way interactions of Group×Task (F (2,96) = 15.42, p < 0.001) and Group×Direction (F (2,96) = 52.49, p < 0.001). Post-hoc pairwise comparisons indicated that in VSN+ individuals, a greater task complexity led to significantly longer delays in onset of avoidance strategy (significant only for HL tasks), while the task complexity did not affect the onsets of VSN– individuals. Moreover, only the VSN+ group showed a significant effect of obstacle direction with longer onsets of avoidance strategy for CL and HO obstacles compared to IL obstacles (p < 0.05).

For walking speed, a Group×Task interaction (F(2,96) = 11.97, p < 0.05) and an effect of Direction ((F = 1,48) = 38.67, p < 0.001) emerged as significant. The difference between walking speeds for VSN+ and VSN– groups was evident only for the LocoDT-HL task (Fig. 3c). Furthermore, in the VSN+ group, the effect of task complexity translated to significantly slower walking speeds for the LocoDT-HL task compared to the LocoST task. Note that both groups walked significantly slower during trials with moving obstacles compared to control trials devoid of obstacles.

4.3 Dual-task costs

The cost outcomes compared changes observed during the simple dual-task (LocoDT-CAT) and the more complex dual-task waking condition (LocoDT-HL) relative to single task walking (LocoST). A significant Group×Task interaction was observed for all the locomotor cost outcomes, including: minimum distance cost (F(2,48) = 14.73, p < 0.05), onset of strategy cost (F(2,48) = 13.15, p < 0.05) and walking speed cost (F(2,48) = 9.61, p < 0.05) (Fig. 4). Overall, VSN+ participants demonstrated greater locomotor costs for both dual-task conditions (LocoDT-CAT and LocoDT-HL), compared to VSN– participants (p < 0.05).

Fig.4

Dual-task costs. The figure shows mean (±1SD values) for dual-task costs of time of onset of strategy (top row), minimum absolute distances maintained between the participants and the obstacles as well (middle row) and walking speed (bottom row) in the VSN+ and VSN– participants. Here CAT denotes the cost of performing LocoDT-CAT relative to LocoST task while HL denotes the cost of performing LocoDT-CAT relative to LocoST task. Statistically significant interaction terms are specified in the text inserts. *p < 0.05.

Within the VSN+ group, a significant effect of Task was observed, with individuals showing larger onset of strategy costs (increase in onsets), larger minimum distance costs (decrease in minimum distances), larger speed costs (reduction in walking speeds) in LocoDT-HL compared to LocoDT-CAT (p < 0.01). In addition, a significant Group×Direction interaction (F(2,48) = 3.14) was also observed for the onset of strategy cost outcome, as VSN+ individuals showed greater costs, i.e. greater delay in onset of strategy for CL and HO obstacles compared to IL obstacles. Among VSN– individuals, the minimum distance cost was greater for LocoDT-HL compared to LocoDT-CAT task (p < 0.05). There were no significant effects of the direction of obstacle approach on any of the locomotor cost outcomes for the VSN– group.

4.4 Cognitive outcomes

None of the participants made errors in pitch-recognition during the CogST-CAT and the CogST-HL tasks. Twelve out of the 13 VSN+ participants demonstrated errors in pitch recognition during for the CogDT-CAT (error rate = 16.01±8.93% of stimuli) and the CogDT-HL task (27.24±9.77% of stimuli). In the VSN– group, 9 and 10 out of the 13 participants made errors in the CogDT-CAT (7.96±4.87% of stimuli) task and CogDT-HL (in 16.9±17.43% of stimuli) task respectively.

A significant group×task interaction emerged for cognitive errors (F(2,48) = 8.41) with a more errors for the CogDT-HL task compared to CogDT-CAT and for the VSN+ group compared to the VSN- group (p < 0.05). There was no influence of direction of obstacle approach on cognitive errors and the extent of change caused by the complexity of the auditory task (CogDT-HL –CogDT-CAT) did not differ between the two groups (P > 0.05). Note that no learning effect in dual-task cognitive performance (e.g. CogDT-CAT and CogDT-HL) were observed in the VSN+ and VSN– groups who showed no difference in cognitive performance in the first and second 50% of trials (p > 0.05).

4.5 Relationship between locomotor and cognitive costs and clinical evaluations

The locomotor cost and cognitive cost outcomes did not show significant relationships with clinical measures of executive function (TMT-B test), overground walking speed, cognitive function (MoCA) or VSN assessments (e.g. Bells, Line bisection and Apples tests) (p > 0.05).

5 Discussion

The ability to cope with different traffic levels and with changing attentional demands are two essential requirements for community ambulation (Patla & Shumway-Cook, 1999). Poor dual-tasking and poor obstacle avoidance abilities are also associated with an increased risk of falls and accidents (Hegeman et al., 2012). Results of this study confirm the hypothesis that VSN+ individuals show a deterioration in both locomotor and cognitive performances while dual-tasking, and that such deterioration is larger compared to VSN– individuals. In the following sections, we discuss how the presence of post-stroke VSN alters obstacle avoidance abilities and how the simultaneous performance of a cognitive task further compromises these abilities in VSN+ individuals.

5.1 VSN alters the spatiotemporal relationships with the obstacle during the avoidance strategy and lead to increased collision rates

Obstacle avoidance is a complex task which requires processing of visuospatial information obtained from the environment and a planned and coordinated execution of locomotor adjustments that are in line with body capabilities (Iaria, Fox, Chen, Petrides, & Barton, 2008). Sensorimotor impairment resulting from a stroke could therefore compromise the ability to safely avoid obstacles leading to collisions (Darekar, Goussev, McFadyen, Lamontagne, & Fung, August 2013). In the present study, we showed that VSN+ and VSN– individuals who had similar level of motor recovery (CMMSA scores) differed in their ability to negotiate obstacles under single and dual-task conditions. Overall, a greater proportion of VSN+ individuals collided with obstacles, at higher collision rates, compared to VSN– individuals. Other studies too have documented the tendency of VSN+ to collide with static and moving objects while walking (Aravind & Lamontagne, 2014; Punt, Kitadono, Hulleman, Humphreys, & Riddoch, 2008; Robertson, Tegner, Goodrich, & Wilson, 1994; Tromp, Dinkla, & Mulder, 1995) and have mainly attributed this to the ipsilesional bias of attention and perception commonly observed in VSN (Kinsbourne, 1970a, 1987). This bias causes a spontaneous orientation of attention and gaze to ipsilesionally occurring events (Kinsbourne, 1970b, 1994). Therefore, contralesional stimuli are ignored or detected after a delay. For a moving object, this delay would bring the individual within close proximities of the obstacle, effectively reducing the time and distance available to plan and execute an avoidance strategy. In support of this idea, our team has previously shown that the perception of moving obstacles is indeed delayed in VSN+ individuals and is associated with obstacles being at closer distances at the onset of strategies, in a joystick-driven navigation task (Aravind, Darekar, Fung, & Lamontagne, 2015). This increases the risk of collision with the obstacle.

In the present study, the attentional-perceptual bias towards the ipsilesional side was evident in the delayed onsets of strategies, smaller minimum distances and higher collision rates observed for the CL and HO obstacle approaches compared to the IL approach. Moreover, a preference to deviate ipsilesionally, irrespective of the direction of obstacle approach, and in the absence of an obstacle, support the idea of such an ipsilesional bias. The VSN– group did not show direction-specific difference in their locomotor responses, deviating to both their ipsilesional and contralesional sides and did not show large deviations from the midline when no obstacles were present. Collectively, these observations support the idea that the attentional-perceptual deficits involved in VSN are the main factor explaining the altered obstacle avoidance strategies and increased risk of collisions.

5.2 VSN+ individuals experience greater cognitive-locomotor interference compared to vsn– individuals

It is widely accepted that the ability to dual-task while walking is impaired in post-stroke individuals, leading to deterioration of walking performance (Baetens et al., 2013; Bowen et al., 2001; Plummer-D’Amato et al., 2008; Yang, Wang, Chen, & Kao, 2007) or a deterioration of the competing cognitive/motor performance (Kizony, Levin, Hughey, Perez, & Fung, 2010; Plummer-D’Amato & Altmann, 2012; Smulders, van Swigchem, de Swart, Geurts, & Weerdesteyn, 2012). However, the impact of dual-tasking on the locomotor behaviour of VSN+ individuals had never been established. In this study, we demonstrated for the first time that dual-task walking dramatically compromises both locomotor and cognitive performances in individuals with VSN.

During dual-task walking, the VSN– participants adopted larger minimum distances from the obstacles compared to the single task condition but did not alter their onsets of strategy, walking speeds or collision rates. However, similar to VSN+ individuals, VSN– individuals did not successfully attend to the cognitive task, demonstrating high error rates for both the simple and complex cognitive task. Thus, VSN– individuals appear to adopt a safety-first strategy by prioritizing their attention to safely avoid obstacles at the expense of the cognitive performance, which can be referred to as a motor-related cognitive interference (Rabuffetti et al., 2013). This prioritization may have been influenced by the threat of an imminent collision and by the fact that the cognitive task itself does not inform the walking task (e.g. not providing information about turns, stops or goals).

In contrast, under dual-task conditions, VSN+ participants of this study experienced further delays in initiating an avoidance strategy, reduced minimum distances with respect to the obstacle and more frequent collisions. A reduction of walking speed was also observed for the LocoDT-HL task, which could interpreted as an attempt to increase stability (Dingwell & Marin, 2006) and divert attention towards the cognitive task. Nevertheless, the high rates of cognitive errors observed under dual-task conditions suggest that attentional resources were not prioritized towards one task over the other. Such “mutual interference” (Rabuffetti et al., 2013), that is a worsening of both the locomotor and cognitive performance in VSN+ individuals, might have resulted from the demands of the walking and cognitive task exceeding the already limited attentional resources associated with VSN.

Overall, cost (locomotor and cognitive) of dual-tasking was greater for VSN+ individuals compared to VSN– individuals. In addition to the attentional deficits in VSN, this could be attributed to the deficits in executive functioning. The TMT-B test is a good measure of working memory, attention switching and response inhibition, which are important components of dual-tasking (Coppin et al., 2006). The VSN+ participants in our study showed TMT-B completion times that were not only longer than normative values (age and years of education based) (Tombaugh, 2004), but were also significantly greater than those of the VSN– group, suggesting that their ability to flexibly allocate attention between tasks is impaired. In agreement with findings in our previous studies (Aravind et al., 2015; Aravind & Lamontagne, 2014) clinical evaluations of neglect, motor recovery and walking speed did not predict single task or dual-task performances in either group, emphasizing the need for task-specific assessments of obstacle avoidance abilities.

The complexity of the competing tasks is an important determinant of the extent of dual-task interference (Plummer-D’Amato et al., 2008). It can be inferred that the HL cognitive task used in this study imposed a greater attentional load than the CAT cognitive task due to the need to discern the pitch of the stimuli while ignoring the meaning of the announced word. For both groups, increased task complexity led to increased rates of cognitive errors under dual-task conditions. An effect of task complexity on walking performance, however, was observed only for the VSN+ group, with higher locomotor costs (e.g. smaller minimum distances and delayed onsets of strategies) and more numerous collisions being observed under the more complex (LocoDT-HL) vs. the simpler dual-task condition (LocoDT-CAT task). The latter observations indicate that task complexity matters for VSN+ individuals, with more complex tasks leading to greater cognitive locomotor interference.

In the context of community ambulation where obstacles and attentional distractors are frequently encountered, greater cognitive locomotor interference could lead to falls or accidents, reduce the ability to attend to extrinsic stimuli and limit participation to community walking. This highlights the need to train post-stroke individuals with VSN for dual task activities. In fact, dual task training in a virtual environment was shown to improve both single task and dual task performances in VSN+ individuals in the context of driving-simulation task (van Kessel, Geurts, Brouwer, & Fasotti, 2013). Future studies could thus focus on training dual task walking in post-stroke VSN while assessing the transferability of gains achieved in the virtual world to real world conditions.

6 Conclusion

This study presents a novel approach to understand limitations faced by post-stroke individuals with VSN while walking in the community. The results of the study are strongly suggestive of the dramatic deterioration demonstrated by individuals with post-stroke VSN in both their locomotor as well as cognitive performance during dual-task walking in comparison to individuals without VSN who prioritize their safety while walking. In addition, evidence that the dual-task paradigm revealed deficits in adapting to complex environmental demands which were not evident on clinical evaluations of neglect establishes its unique ability to revealing true functional status of stroke individuals. The virtual reality set-up described in this study can be effortlessly used as tool for evaluation as well as training of complex locomotor tasks in stroke survivors with and without perceptual-attentional deficits.

Conflict of interest

The authors declare that there is no conflict of interest.

Footnotes

Acknowledgments

This work was supported by the Canadian Institutes of Health Research (CIHR MOP- 77548). G.A. is the recipient of scholarships from the Richard and Edith Strauss foundation, McGill Faculty of Medicine, and Physiotherapy Foundation of Canada through the Heart and Stroke Foundation. A.L. holds a salary award from the Fonds de la recherche du Québec - Santé.

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Group	Task	CL		HO		IL
		Colliders	Collision rate	Colliders	Collision rate	Colliders	Collision rate
VSN+	LocoST	76.9	34.4±8.1	46.2	24.7±6.5	0.0	NA
	LocoDT-CAT	92.3	48.2±11.6	76.9	30.6±10.6	15.4	24.3±4.3
	LocoDT-HL	100.0	61.3±14.4	92.3	39.6±11.9	38.5	30.6±9.1
VSN–	LocoST	30.8	33.3±8.2	30.8	24.5±5.4	7.7	16.7
	LocoDT-CAT	23.1	36.6±3.3	15.4	18.9±1.6	0.0	NA
	LocoDT-HL	23.1	32±11.2	15.4	23.3±2.4	0.0	NA