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Research Reports |
PS Pohl, PT, PhD, is Associate Professor, Department of Physical Therapy & Rehabilitation Sciences, University of Kansas Medical Center, Mail Stop 2002, 3901 Rainbow Blvd, Kansas City, KS 66160 (USA)
JM McDowd, PhD, is Professor, Department of Occupational Therapy Education, and Associate Director for Research, Landon Center on Aging, University of Kansas Medical Center
D Filion, PhD, is Associate Professor, Department of Psychology, University of Missouri, Kansas City, Mo
LG Richards, PhD, OTR, is Research Health Scientist, Research Service, North Florida/South Georgia Veterans Health System, Gainesville, Fla, and Associate Professor, Occupational Therapy Department, University of Florida, Gainesville, Fla
W Stiers, PhD, is Assistant Professor, Department of Physical Medicine and Rehabilitation, John Hopkins University, Baltimore, Md
P Kluding, PT, PhD, is Assistant Professor, Department of Physical Therapy & Rehabilitation Sciences, University of Kansas Medical Center
Address all correspondence to Dr Pohl at: ppohl{at}kumc.edu
Submitted March 23, 2006;
Accepted August 21, 2006
 | Abstract |
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Subjects: The participants in this study were 46 adults with stroke and 38 adults without stroke.
Methods: Subjects performed 2 computer-based switching tasks, an alternating task that relied on endogenous control and a cued task that relied on exogenous control. Testing was done in subjects’ homes at 1 and 3 months after stroke and at a 2-month interval for control subjects. Switch costs, or the difference between the no-switch condition and the switch condition, were calculated for accuracy and response time.
Results: Subjects in the stroke group had higher switch costs for accuracy than did subjects in the control group. The alternating task was more difficult than the cued task, with higher switch costs for accuracy and response time. The alternating task was particularly difficult for subjects in the stroke group, with high switch costs for accuracy. Both groups showed decreased response time switch costs at the second testing session.
Discussion and Conclusion: Task switching, particularly if under endogenous control, is impaired in adults in the subacute phase after stroke. Clinicians should be aware of performance deficits that may relate to task switching.
| Introduction |
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Task switching may be completely self-initiated, may occur at predictable time intervals, or may follow a pattern, such as alternating between 2 tasks. For example, walking with a one-handed walker requires a pattern of moving each leg and the walker in a prescribed sequence. In this case, switching relies primarily on internal cues and is considered to be under endogenous control.2 In contrast, the requirement to switch may be cued externally and may occur at unpredictable intervals, such as when a telephone rings while one is reading a book. The external cue provides imperative information about which task to perform. In this case, task switching is considered to be under exogenous control.2
The typical paradigm for measuring switching costs focuses on exogenous control. Subjects must respond to an unpredictable external cue to switch from one activity to another. Manipulations of interest include the time interval from the cue to the appearance of the stimulus and the time interval from a response to the appearance of the next cue (see Monsell2 for a review). Task switching under endogenous control is less well studied, but switching costs have been reported for a voluntary task switch, an activity in which subjects are given general guidelines about switching, but they decide when to switch.4 It has been suggested that alternating activity between 2 tasks, a form of endogenous control, may be particularly challenging because of the requirement to keep track of the sequence.2
A network of cortical and subcortical regions forms the neural substrate for successful task switching.5 Key structures that contribute to the cognitive flexibility to switch tasks include the parietal cortex6–8 and the frontal3,5,8–12 and prefrontal13,14 cortices. Given the vast connectivity of these cortical areas with other brain structures,15 it is not surprising that dysfunction in a wide range of brain regions can result in difficulties in task switching. There have been reports of higher switching costs in subjects with various diagnoses than in healthy control subjects; these diagnoses include cerebellar disease,16 Parkinson disease3,17 (see Gurd and Ward18 for an exception), Huntington disease,19 schizophrenia,20 and attentiondeficit/hyperactivity disorder.21
There is a paucity of literature on the ability of people who have survived a stroke to switch tasks. The adverse impact of focal lesions in the prefrontal cortex secondary to tumor resection or stroke on task-switching abilities has been reported.9 The most common stroke, however, is an ischemic event that follows the distribution of the middle cerebral artery.22 Given the extended branching of the arterial system, the resultant brain damage can affect numerous functional networks. With subject criteria expanded on the basis of the variable distribution and extent of lesions typical in stroke, we showed that people who are long-term survivors of stroke have deficits in task-switching abilities.23 Task switching can be part of many functional tasks and clinical activities that are incorporated into physical therapy interventions. Given that the majority of rehabilitation efforts occur in the first months after stroke onset, we sought to determine whether task-switching deficits are present in the subacute phase after stroke.
The overall objective of this study was to examine the effects of unilateral subacute stroke on task switching. Specifically, we had 4 purposes. First, we needed to verify that our experimental manipulation of a switch condition and a no-switch condition was effective. Second, we were interested in whether the task-switching deficits reported in people who are long-term survivors of stroke would be present at 1 and 3 months after stroke. We hypothesized that task-switching deficits would be evident in this subacute phase.
Our third purpose was to compare the switching ability for a task under endogenous control with that for a task under exogenous control, that is, an alternating switch task versus a cued switch task. Given the additional demands of a task under endogenous control, we hypothesized that the performance of adults who had had a stroke would be particularly impaired in the alternating switch task.
Our fourth purpose was to examine performance at 1 and 3 months after stroke. The typical rapid rate of recovery in the first few months after stroke onset led us to hypothesize that switch costs would decrease by 3 months after stroke but that group differences would persist. Finally, although the study was not designed to investigate the issue of laterality, we compared performance as a function of the hand used to complete the tasks and the side of brain damage.
| Method |
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TopAbstractIntroductionMethodResultsDiscussionConclusionReferences |
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Switch Tasks
Two tasks reported in our previous study were used to measure switching costs.23 For each trial, regardless of task, 1 of 4 differently shaped stimuli appeared on a computer screen (ie, circle, square, triangle, and cross). Between 1 and 4 of the same shapes appeared on the screen. Responses were made on a custom-designed device that interfaced with a laptop computer to record the accuracy of the response and the response time to the nearest millisecond. The device consisted of 4 microswitches that were assigned to the 4 shapes and numbers 1 to 4. In both switching tasks, the stimulus for each trial remained on the screen until a response was made. Completion of a response triggered the beginning of the next trial.
The alternating switch task was a measure of endogenous control. In the no-switch condition, participants had to respond to either the number of objects or the shape of the objects. Practice was organized into blocks that included a 12-stimulus sequence requiring responses to the number of objects and a 12-stimulus sequence requiring responses to the shape of the objects. In the alternating switch condition, participants had to respond to the shape of the objects and then to the number of objects on consecutive trials and so on in an alternating fashion. The task required that participants remember the just-executed response (to number or shape) so that they could respond to the other stimulus dimension (either number or shape) on the subsequent trial. A block included 24 trials. Participants performed a block of the no-switch condition and then a block of the alternating switch condition and so on until a total of 6 blocks were completed.
The cued switch task was a measure of exogenous control. Participants were cued by a written word (ie, number or shape) presented on the computer screen to indicate whether the subject should respond on the basis of the number of objects or the shape of the objects. The cue was presented simultaneously with the stimulus. After a variable number of trials (8–12), a participant would receive a cue to switch to the other response. Responses were made in the same manner as in the alternating switch task. Participants performed sufficient trials to respond to 30 cues to switch.
Procedure
All subjects provided oral and written consent. Screening tests were completed as described earlier. The 2 switch tasks were carried out as part of a larger study that included a battery of tests of attention and learning, some of which are reported elsewhere.31 The order of tests was randomized. To avoid performance deficits attributable to hemiplegia of the hand contralateral to the side of brain damage, subjects in the stroke group completed the responses with the hand on the same side as the side of brain damage. Twenty-two of the control subjects performed the tasks with their right (dominant) hand, and 16 of the control subjects performed the tasks with their left (nondominant) hand. To verify that the subjects understood the procedure, they performed 2 or 3 practice trials of each of the 2 tasks before data collection was begun. Subjects were instructed to be fast and accurate. Total testing time was approximately 2 hours, including intermittent rests to minimize any potential effects of fatigue. Subjects were tested in their homes in a quiet room without distractions.
Data Analysis
For the alternating switch task, accuracy was determined as the percentage of correct responses for the no-switch trials and the switch trials. Median response times were calculated for each subject from these 2 sets of trials. Switch costs for both accuracy and response times were determined by subtracting the values for the no-switch condition from the values for the alternating switch condition.
For the cued switch condition, the no-switch condition was defined by the 3 responses before the cue to switch. The switch condition was defined by the 3 responses just after the cue to switch. Examination of trials just before and after a switch for a task that does not follow an alternating or predictable pattern is compatible with the literature.4,23 Accuracy was again represented as the percentage of correct responses, and median response times were calculated. Switch costs were determined by subtracting the values for the no-switch condition from the values for the switch condition.
Individual subject data were used to calculate group means. We expected negative numbers for accuracy, indicating lower accuracy in the switch condition than in the no-switch condition. In contrast, we expected positive numbers for response times, indicating slower times for the switch condition than for the no-switch condition. Variance is presented as standard errors (SEs).
To verify that the manipulation of our no-switch and switch conditions was effective, we completed 2 multivariate analyses of variance (MANOVAs) with a main effect of condition (no switch, switch) for accuracy and response time—1 for the alternating switch task and 1 for the cued switch task. If a main effect of condition was found, then follow-up univariate analyses were planned to determine whether the condition effect was significant for both response time and accuracy.
We performed univariate analyses of variance with a between-subjects factor of group (stroke, control), a within-subject factor of task (alternating switch, cued switch), and a repeated-measures factor of time (time 1, time 2) for switch costs for accuracy and response time. To define the locus of interactions, post hoc tests with a Bonferroni correction were completed. Our hypothesis that subjects in the stroke group would have greater switching deficits compared with subjects in the control group would be supported by a main effect of group. If an endogenous switch task was more demanding than an exogenous switch task, then a main effect of task would reveal that the alternating switch task was more difficult than the cued switch task. The hypothesis that an endogenous task would be particularly difficult for subjects who had survived a stroke would be supported by an interaction of group and task. A significant interaction of group and time would support the hypothesis that subjects in the stroke group experienced some recovery in their task-switching ability and showed decreased switch costs from the 1-month test to the 3-month test.
Although not a purpose of this study, it would be informative to the understanding of the laterality of brain function as well as clinical practice to know whether the performance of subjects with right-side lesions was different from that of subjects with left-side lesions. Side was entered as a factor in a separate analysis to provide insight into this potential difference. A main effect of side would reveal differences in performance attributable to hand dominance. An interaction of side and group would reveal differences attributable to the side of the lesion.
All analyses were done with the personal computer version of SPSS,* version 13.0. The Greenhouse-Geisser test was used for the repeatedmeasures factor of time.
| Results |
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TopAbstractIntroductionMethodResultsDiscussionConclusionReferences |
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In the cued switch task, the manipulation was effective, but only for response time. In the reverse of our expectation, accuracy rates were better for the cued switch condition, at 93.1% (SE=1.1), than for the no-switch condition, at 90.9% (SE=1.2). Response times were shorter for the no-switch condition, with a mean of 1,190 (SE=34) milliseconds, than for the cued switch condition, with a mean of 1,591 (SE=56) milliseconds. The MANOVA revealed that the difference was significant (P<.001). The univariate analysis revealed that there were differences between conditions for accuracy (P<.001) and response time (P<.001).
In the following sections, we describe the main effects of group, task, and time and any interactions on switch costs.
Accuracy Switch Costs
Means and SEs by group, task, and time are shown in Figure 1. There was a main effect of group (P< .002). Subjects with stroke had higher switch costs than control subjects, with accuracy costs of –6.1% (SE= 0.9) for the stroke group and –1.4% (SE=1.0) for the control group. The main effect of task was significant (P<.001). Accuracy switch costs were higher for the alternating switch task, at –9.7% (SE=1.4), than for the cued switch task, at 2.3% (SE=0.5). There was also an interaction of group and task (P <.001). Post hoc tests revealed that the stroke group had higher accuracy switch costs than the control group in the alternating switch task (P<.001) but not in the cued switch task. Accuracy did not change over the 2 test times; the main effect of time was not significant, and there were no significant interactions with time.
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| Discussion |
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TopAbstractIntroductionMethodResultsDiscussionConclusionReferences |
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Difficulties in switching between tasks for subjects after stroke, a deficit similar to what is known as perseveration in the clinical literature,32 have been reported, but these paradigms have focused on the motor component of the tasks. Responses included changing hand postures in a predetermined pattern or in response to target lights.33,34 Difficulties in task switching in studies such as those have been described as motor control deficits. In the present study, switching deficits were apparent even when the necessary motor responses were minimal and equivalent across switch and no-switch conditions and when subjects with stroke used the hand that was not primarily affected by the stroke. Our results suggest that the control deficits in switching after stroke may be best described not as motor deficits but as deficits in executive function.
A higher switch cost for subjects with stroke than for control subjects was found only for accuracy. Switch costs for response time were similar between groups. The lack of a group difference in cost for response time despite the difference in cost for accuracy may be related to our calculation of the median response time; only correct response times were included in deriving the median. There was a tendency for subjects with stroke to have overall longer response times than control subjects. Slower movements, even with the hand ipsilateral to the side of brain damage, can be expected.35 The more salient issue for the present study is that switch costs were similar between groups for response time but were higher for subjects with stroke for accuracy. When faced with the dual goals of being accurate and fast, subjects may sacrifice one to accomplish the other.36
Our results suggest that subjects with stroke, faced with the demands inherent in the switch trials, were not able to maintain the same combination of speed and accuracy as control subjects. It is also possible that subjects with stroke did not slow their responses because they could not inhibit executing a response. The failure to automatically inhibit an incorrect response may be the primary dysfunction in task switching.37 Of note, impulsiveness is one of the clinical manifestations of stroke, particularly for those with right hemisphere lesions.38
As we hypothesized, the alternating task that relied on endogenous control was more difficult than the cued task that relied on exogenous control, as revealed by longer response times and lower accuracy. Alternating between 2 tasks provides a predictable pattern for switching, but the internal cuing necessary to alternate between 2 tasks is thought to place a greater load on working memory than an externally cued switch.2 The subject must remember the response just completed and remember the required pattern. In a cued switch task, a response is not dependent on the previous response. Each trial is independent of previous trials, and performers can rely on a cue (in this case, visual) to inform them of the appropriate response. Our results suggest that switching under endogenous control was more difficult than switching under exogenous control for both of our subject groups, particularly so for older adults with stroke.
It should be noted that the 2 switching tasks used in the present study cannot be unequivocally dichotomized as being under endogenous or exogenous control. A response made in the cued switch task must be self-initiated, even if the selection of the type of response is not necessary. Similarly, in the alternating switch task, there is some element of exogenous control, if only in the confines of the possible stimuli and responses. They are not selected from some unrestricted array of choices. It is possible that there is a continuum of control and switching abilities of older adults and that the abilities of adults with stroke vary along that continuum.
An unexpected finding was the higher accuracy rate for the switch condition than for the no-switch condition in the cued switch task. The mean percentages were high for both conditions, that is, over 90%, and differed by only 2%. It is possible that the cue to switch from number to shape or from shape to number alerted the participant to attend to the response and influenced accuracy. We have no data to support this conjecture, however, and the finding may be only spurious.
Our hypothesis that only subjects with stroke would be able to decrease switch costs over time was not supported. All subjects reduced switch costs for response time from time 1 to time 2 without a change in switch costs for accuracy. Over the 2-month period between testing times, subjects with stroke received no specific intervention targeted at the ability to switch tasks. The decrease in switch costs for response time for both groups suggests that control subjects and subjects with stroke benefited from the experience with the tasks during the first testing session.
Without brain images, we are unable to address questions regarding the relationship of lesion location or lesion extent to task-switching abilities. Switch costs were not related to the side of the lesion for our group of subjects, but further study is warranted. Higher switch costs for people with left-side brain damage have been reported.39 There also is evidence that switch costs are high regardless of lesion side but that the reasons for the difficulty in task switching are different for people with right-side lesions than for those with left-side lesions.9 We do not know whether our results can be generalized to other switching tasks, but it is interesting to note that tasks that require switches that are made at the discretion of the performer still reveal switch costs.4 Voluntary switching relies strongly on endogenous control and may closely mimic the manipulation of activities in daily life. The inability of subjects with stroke to switch between 2 or more tasks may have far-reaching effects contributing to disability.
Many motor activities that physical therapists include in their interventions with their clients after stroke require the executive function of task switching. Performance may rely on endogenous control. For example, sequencing a one-handed walker during gait follows a pattern of switching the movement of each lower extremity and the movement of the upper extremity with the walker; transferring from a wheelchair to a desk chair follows a sequence of switching from one task to another in preparing the wheelchair and executing the movement. In each case, the client must complete one task and initiate the next task while keeping track of the appropriate sequence. Performance of some activities in an intervention may depend on exogenous control. Verbal cues may guide a series of exercises. Saying "walker, right foot, left foot" during gait training provides external cues that incorporate aspects of exogenous control into an activity that would normally rely on endogenous control.
The results of the present study suggest that people with stroke may be particularly challenged by activities that involve switching, especially when the activities rely on the internal cues necessary for endogenous control. The clinician should consider that performance deficits may not be purely motor in nature; the deficits may have their foundation in cognitive impairment. Analyzing a client’s task-switching abilities across various tasks and under both endogenous and exogenous conditions may help the clinician understand the nature of the deficits and provide insight into potential interventions.
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TopAbstractIntroductionMethodResultsDiscussionConclusionReferences |
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| Footnotes |
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The study protocol was approved by the Institutional Review Board of the University of Kansas Medical Center.
This study was supported by National Institute on Aging grant P60 AG14635 (Kansas Claude D. Pepper Older Americans Independence Center; Stephanie Studenski, Principal Investigator). This material is the result of work supported with resources and the use of facilities at the Malcom Randall VA Medical Center, North Florida/South Georgia Veterans Health System, Gainesville, Fla.
* SPSS Inc, 233 S Wacker Dr, Chicago, IL 60606. 
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  P. Kluding and B. Gajewski Lower-Extremity Strength Differences Predict Activity Limitations in People With Chronic Stroke Physical Therapy, January 1, 2009; 89(1): 73 - 81. [Abstract] [Full Text] [PDF]
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