EXAMINING A VISUOSPATIAL/VISUOMOTOR TRAINING PROGRAM AS AN
INTERVENTION TO INDUCE COGNITIVE IMPROVEMENT DURING ACUTE
POST-STROKE RECOVERY

by

Mireille Rizkalla
BSc., University of Toronto, 2008

THESIS SUBMITTED IN PARTIAL FULFILLMENT OF
THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE
IN
PSYCHOLOGY

UNIVERSITY OF NORTHERN BRITISH COLUMBIA
May 2011

© Mireille Rizkalla, 2011

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Abstract
Purpose: A novel visuospatial (VS) /visuomotor (VM) cognitive training program
was examined as an intervention tool to improve acute post-stroke recovery.
Method: A randomized controlled trial was conducted with 9 experimental
participants (age 65 ± 9.31) and 9 controls (age 67 ± 7.81). Intervention training included 1
hour/ 5-days a week for 4 weeks. Pre-and post-training neuropsychological measures were
utilized as determinants of program success.
Results: Compared to controls, the intervention group displayed significant gains on
all outcome measures including: global (MMSE, p = .002), language (BN, p - .001), VS
(Rey-O, p = .011), memory (HVLT, p = .005), executive function (Animal, p = .001), mood
(GDS, p = .020) and functional ability (DAD, p = .008).
Conclusion: VS/VM cognitive training results in improved cognition, function and
mood beyond the outcomes of traditional intervention alone. Thus, this innovative type of
intervention shows promise for revolutionizing current stroke rehabilitation.

ii

TABLE OF CONTENTS
Abstract
Table of Contents
List of Tables
List of Figures
List of Appendices
Acknowledgement

ii
iii
v
vi
vii
viii

Introduction
Societal Burden Associated with Stroke
Secondary Stroke Overview

1
2
3

Best Practice for Stroke Care Units
Best Practice for Timing of Stroke Rehabilitation
Best Practice for Intensity of Therapy
British Columbia's Stroke Strategy

4
4
6
7
8

Stroke Best Care Practice

Literature Review on
V isuospatial/Visuomotor
Cognitive Training

9

Defining the Evaluation Process of Cognitive
Intervention
Remediation of Neglect and V isuospatial/Visuomotor
Deficits
Training Effectiveness of Visual Scanning
Training Effectiveness of Complex Visuospatial Skills
Video-Gaming Training Effectiveness
Visual Imagery Training Effectiveness
Visuospatial/Visuomotor
Cognitive Intervention

10
11
12
14
17
19
23

Cognitive Training Project Rationale
Summary of Project Elements
Objectives
Hypothesis

23
24
26
26

Participants
Study Recruitment Strategy
Procedure
Components of Cognitive Training Intervention
Neuropsychological Primary Outcome Measures

26
26
26
27
28
30

Method

iii

Results
Pre-Intervention Assessment Between Groups
Post-Intervention Differences Between Groups
Within Group Improvements
Magnitude of Improvement Between Groups
Training Outcome Measures
Discussion
Participant Improvements Within Group
Intervention Improvements on Trained Tasks
Unsuccessful Intervention Outcomes
Possible Mechanisms for Post-Intervention Success
Clinical Relevance
Limitations
Conclusions
Reference List

35
36
36
37
37
38
40
41
42
43
44
50
51
52
69

iv

List of Tables
Table 1.

Inclusion Criteria

54

Table 2.

Exclusion Criteria

55

Table 3.

Frequency Distribution for Intervention and Control Group on Stroke

56

Characteristics
Table 4.

Pre-treatment Comparability of the Intervention and Control Group

57

Table 5.

Post-treatment Outcome Measure Between Groups

58

Table 6.

Post-Treatment Cognitive Changes Within the Intervention Group

59

Table 7.

Post-Treatment Cognitive Changes Within the Control Group

60

Table 8.

Improvement Scores for Test in which Both Groups Showed Improvements

61

v

List of Figures
Figure 1.

Study Participant Flow Chart of Enrollment and Randomization

62

Figure 2.

Comparing Neuropsychological Changes Between the Groups from

63

Pre-intervention to Post-intervention
Figure 3. Post-intervention Differences Between the Groups in Neuropsychological

64

Domains
Figure 4. Comparing Magnitude of Neuropsychological Change Between Groups

65

from Pre-intervention to Post-intervention
Figure 5.

Improvements in Pac-Man High Score from Initial Weeks to Final Weeks

66

of Training
Figure 6.

Improvements in Pac-Man Duration of Play from Initial Weeks to Final

67

Weeks of Training
Figure 7.

Improvement in Block Design Duration of time from Initial Weeks to Final

68

Weeks

vi

List of Appendices
Appendix

Study Homework Booklet

Acknowledgements
I would like to express my appreciation to a number of people who enriched this
experience in several ways. First and foremost, I am sincerely grateful to Dr. William Tippett
whose active supervision made this research possible. Greatest thanks to my family and
partner, whose love and support I drew from on a daily basis. I would also like to give warm
regards to my committee members for their time and insightful comments on this thesis.
Special thanks to the staff at UHNBC and to the patients and caregivers who participated in
this project. Lastly, I offer gratitude to the research assistants who lent a hand throughout the
duration of this project.

viii

Introduction
Strokes lead to negative effects on brain structure and cognitive function (Gorelick, 2003).
The window of opportunity for intervening in some of these effects is time sensitive,
meaning that the longer a stroke goes untreated, the greater the chance of permanent
neurologic and cognitive damage (Cifu & Stewart, 1999; Feigenson, McDowell, Meese,
McCarthy, & Greenberg, 1977; Hayes & Carroll, 1986; Ottenbacher & Jannell, 1993;
Schallert, Fleming, & Woodlee, 2003). One of the major risk factors for stroke is
experiencing a previous one. An ischemic stroke occurs when there is low blood flow to a
core region which eventually infarcts, and this core is surrounded by an area of moderate
blood flow, called the ischemic penumbra (Astrup, Siesjo, & Symon, 1981). The ischemic
penumbra is at very high risk of infarction and thus secondary stroke is common (Lyden et
al., 2005). Generally, individuals who have experienced a stroke, and those with
cardiovascular risk factors (such as hypertension), are in the highest risk category for
recurrent stroke episodes, and are most likely to benefit from effective therapy (Gorelick,
2003). Furthermore, secondary strokes often have a higher rate of death and disability
because the areas of the brain already compromised by the first stroke are no longer as
resilient (Gorelick, 2003; Teasell, Bayona, Salter, Hellings, & Bitensky, 2006). Medical and
lifestyle strategies to combat the ravaging effects of stroke have been thoroughly
investigated. Research recommends avoidance of risk factors such as smoking (Nilsson et al.,
2009), heavy alcohol use (Daniel & Bereczki, 2004), and proper management of medical risk
factors such as hypertension (Barnett, 2002), diabetes (Najarian et al., 2006) and
hypercholesterolemia (Uchiyama et al., 2009). It is also well established that physical
exercise (Pang, Eng, Dawson, & Gylfadottir, 2006), stress reduction (Stead et al., 2008), and
1

proper nutrition are additional factors known to reduce damage caused by stroke or to
contribute to the prevention of a primary stroke (Gorelick, 2003). The concept that stroke
related repercussions are time sensitive does not apply to physical recovery only, but also
applies to cognitive recovery (Sachdev, Brodaty, Valenzuela, Lorentz, & Koschera, 2004).
Cognitive intervention, however, has not been a primary focus of attention. There is growing
interest in the potential for behavioural interventions, such as mental activity, to improve
cognitive function in vulnerable populations. One such area that is yet to be investigated is
the use of cognitive training as an intervention tool to improve cognition post-stroke.
Cognition is defined as the capacity for and expression of knowledge. It is demonstrated
when an individual can acquire and retain relevant information in such a way that it can be
applied in appropriate situations. Given both the relevance and prevalence of cognitive
impairment post-stroke, a need exists to investigate the prospect of a cognitive training
program designed for improving cognitive performance post-stroke. Currently no standard
cognitive treatment is recognized or available for post-stroke individuals to engage in during
their recovery phase.

Societal Burden Associated with Stroke
Stroke is the third leading cause of death in Canada. More than 50,000 strokes occur
annually and many victims are left with significant cognitive impairments and physical
disability (Teasell et al., 2006). Vascular cognitive impairment (VCI) affects up to two thirds
of stroke survivors (Madureira, Canhao, Guerreiro, & Ferro, 2000; Ballard, Rowan,
Stephens, Kalaria, & Kenny, 2003) and represents a substantial public health burden, with the
direct per-patient lifetime costs estimated to be approximately $10,000 for persons with mild
disease and $27,500 for persons with severe disease (Claesson, Linden, Skoog, &
2

Blomstrand, 2005; Heart and Stroke Foundation of BC and Yukon, 2000). Stroke related
deficits are also associated with indirect healthcare costs, impaired daily functional abilities
(Di et al., 2000; MacNeill & Lichtenberg, 1998), hospitalization and cognitive impairment
(Arfken, Lichtenberg, & Tancer, 1999; Lin et al., 2003; Tatemichi et al., 1994) and reduced
life expectancy (Cederfeldt, Gosman-Hedstrom, Perez, Savborg, & Tarkowski, 2010;
Claesson et al., 2005; Desmond et al., 2000; Hinkle, 2006; Prencipe et al., 1997; Ruchinskas
& Curyto, 2003; Wolfson et al., 2001; Zinn et al., 2004). Furthermore, an estimated one
quarter to one third of stroke patients will meet dementia criteria within 3 months of
experiencing stroke (Leys, Henon, Mackowiak-Cordoliani, & Pasquier, 2005; Tatemichi et
al., 1990). Evidence indicates that a stroke survivor has a 20% chance of having another
stroke within 2 years and this rate doubles every 10 years after the age of 65 (Heart Disease
and Stroke in Canada, 2006). Stroke numbers are expected to rise in 2011 when the first
baby-boomers will be age 65 (Heart Disease and Stroke in Canada, 2006; Teasell et al.,
2006). The implication of an expected rise in stroke is significant in light of the burden that is
associated with stroke related disability.

Secondary Stroke Overview
There are more than 300,000 stroke survivors in Canada and a major goal of therapy
for patients who have experienced stroke is to prevent recurrent stroke. Canadian secondary
stroke prevention focuses on improving access to stroke specialists in order to manage
vascular risk factors, improve physical mobility and promote public awareness on the
importance of healthy living (Tatemichi et al., 1990). Indeed, evidence indicates that patients
receiving professional advice on healthy living have a greater chance of preventing further
complications (Greenlund, Giles, Keenan, Croft, & Mensah, 2002). One of the most
3

widespread practices by physicians for secondary stroke prevention is the use of agents that
act to prevent blood occlusion [e.g., aspirin and angiotensin converting enzyme (ACE)
inhibitors]. Research on the effectiveness of blood pressure medication on the improvement
of cognition among stroke survivors has shown that this treatment is not effective in
preventing or improving cognitive decline in this population (Feigin, Ratnasabapathy, &
Anderson, 2005). Furthermore, there is evidence that pharmaceutical methods can sometimes
impede cognitive functioning. For example, using antihypertensives can affect attention and
executive functions and can be linked with ongoing neuropathological changes (Di et al.,
2000; Hadjiev & Mineva, 2008). This cognitive damage following pharmaceutical prevention
methods is problematic because stroke is already a major risk factor for dementia and can
expedite the conversion of existing cognitive impairment to dementia (Gamaldo et al., 2006;
Pendlebury & Rothwell, 2009). It has been noted that shortly after a first-ever stroke, 10% of
people may develop dementia (Teasell et al., 2006) and recurrent stroke can result in
dementia in one-third of patients (Pendlebury & Rothwell, 2009). As researchers, the
challenge is to target this at-risk population in the safest way possible.

Stroke Best Care Practice
Best Model of Stroke Care Units
Rehabilitation provides a means to alleviate the burden of disability associated with
stroke. However, given that rehabilitation is so resource-demanding, it is important that it be
executed in the most efficient and cost effective manner, in accordance with best scientific
and research based evidence (Teasell et al., 2006).
Specialized stroke rehabilitation units (which include both rehabilitative and acute
services) produce markedly better outcomes when compared with less organized stroke units,
4

such as mixed rehabilitation or general medicine wards (Govan et al., 2007; Stroke Unit
Trialists' Collaboration, 2001). Evaluations looking at differences between dedicated stroke
units and less organized stroke teams have elucidated some of the factors that contribute to
the advantages of specialized units. Within seven days of admission, patients on specialized
stroke units are assessed by social and occupational therapists and their medical needs are
more closely monitored compared to patients on general units (Evans et al., 2001). Other
studies have noted that this level of attentive care does not cease at 7 days, but persists
throughout the first four weeks of stroke, which is considered the most critical rehabilitation
period by physicians and researchers (Evans et al., 2001; Teasell et al., 2006). For example,
unlike general stroke units, specialized stroke units provide patients with an evaluation of
rehabilitation goals and long term discharge plans within 4 weeks of admission (Evans et al.,
2001; Indredavik, Bakke, Slordahl, Rokseth, & Haheim, 1999). Early monitoring is
imperative because complications are known to be common following stroke. Approximately
82% of stroke patients experience complications, the most common complications being falls
and urinary tract infections (Sorbello et al., 2009). One of the elements of stoke unit care that
has been associated with improved outcomes is the prevention of these complications.
Indredavik and colleagues (2008) followed 489 acute stroke patients in a specialized stroke
unit and found a significant reduction in the number and severity of complications compared
to patients in loose stroke settings. After the critical rehabilitation period, there are also
benefits to specialized stroke units in terms of rehabilitative services. In a retrospective study
Ang and collegues (2003) reported that acute patients of a specialized stroke unit benefited
by having shorter lengths of hospitalization and better overall functional abilities. The
authors speculated that the main reason for the improved outcome was due to the seamless
5

nature of specialized stroke care. For example, patients did not have to wait for a bed to
become available or be physically transferred before they could begin intensive therapy
(Ang, Chan, Heng, & Shen, 2003). Finally, in the long run, patients from specialized stroke
units are more likely to be adequately referred to follow-up clinics and more likely be put on
anticoagulation therapy at discharge (Barber, Langhorne, Rumley, Lowe, & Stott, 2004).
This is in accordance with best practice evidence showing that optimal prognosis is achieved
when there is an on-going process in place in which patients are referred to secondary stroke
prevention clinics at discharge (Sulch & Kalra, 2000).

Best Model for Timing of Stroke Rehabilitation
The results of several studies have suggested that soon after stroke, rehabilitation
should be initiated in order to maximize results (Feigenson et al., 1977; Gagnon, Nadeau, &
Tam, 2006; Hayes & Carroll, 1986; Paolucci et al., 2000). Early admission to stroke
rehabilitation is strongly correlated with improved functional outcomes, which is
demonstrated in both individual studies and meta-analysis. In a meta-analysis examining the
potential benefits of early intervention, Cifu and Stewart (1999) concluded that the literature
supports an intervention timeframe between 3 to 30 days post stroke for optimal functional
outcomes (Cifu & Stewart, 1999). Recently, Maulden et al. (2005) has confirmed the
necessity of early intervention, reporting that delaying the onset of rehabilitation was
associated with lower functional independence measure (FIM) scores and increased
hospitalization for patients with both moderate and severe strokes (Maulden, Gassaway,
Horn, Smout, & DeJong, 2005). The interval between stroke onset and admission to
rehabilitation is so time sensitive that delaying rehabilitation even for a few days is a
significant predictor of lower discharge FIM scores and longer hospitalization. In another
6

meta-analysis including 258 stroke patients, Salter et al (2006) found that time between a
stroke episode and admission to rehabilitation predicted the achievement of rehabilitation
potential (Salter et al., 2006). Most recently, Langhorne et al. (2010) examined the effects of
early mobilization on medical outcomes. They found that medical complications were lower
among subjects in the early mobilization group compared to the longer onset rehabilitation
group (Langhorne et al., 2010).

Best Model for Intensity of Therapy
When outlining the elements that contribute to optimal functional outcomes seen in
specialized stroke rehabilitation, the intensity of rehabilitation therapies is often mentioned.
Intensity is generally taken to mean the number of minutes per day of therapy or the number
of hours of consecutive therapy (Teasell et al., 2006). Generally, an intense rehabilitation
program is defined as 21 or more hours of therapy per week (Teasell & Foley, 2008),
whereas 4-8 hours per week would be considered a non-intensive program (Page, 2003).
Neuroimaging evidence suggests that increased intensity of rehabilitation results in greater
activation in various cortical areas, specifically the parietal region (Kalra & Langhorne,
2007). The results of 19 randomized controlled studies show that increasing the intensity of
physiotherapy results in both significant reduction of impairments and improvement in
activities of daily living (Askim et al., 2010; Di et al., 2003; Feys et al., 1998; Kwakkel,
Wagenaar, Twisk, Lankhorst, & Koetsier, 1999; Kwakkel, Kollen, & Wagenaar, 2002;
Langhammer, Lindmark, & Stanghelle, 2007; Langhammer, Stanghelle, & Lindmark, 2008;
Langhammer, Stanghelle, & Lindmark, 2009; Lincoln, Parry, & Vass, 1999; Logan, Ahern,
Gladman, & Lincoln, 1997; Parry, Lincoln, & Vass, 1999; Partridge et al., 2000; Pohl,
Mehrholz, Ritschel, & Ruckriem, 2002; Pohl et al., 2007; Richards et al., 1993; Slade,
7

Tennant, & Chamberlain, 2002; Sunderland et al., 1992; Sunderland et al., 1994; Werner &
Kessler, 1996). The benefit of augmenting therapy intensity has also been evaluated by
Kwakkel et al. (2004) in a 20 study meta-analysis that included many interventions:
occupational, physiotherapy, leisure therapy, home care and sensorimotor training (Kwakkel
et al., 2004). Regardless of therapy type, they found that intensity had a significant effect on
activities of daily living and functional outcome measures. Intensity of therapy has also been
linked to length of hospitalization. In a large cohort of stroke survivors (n = 23,824),
Wodchis et al. (2005) found that intensity of rehabilitation was positively associated with
expedited discharge in patients with an uncertain prognosis on admission (Wodchis et al.,
2005). This association was confirmed in a recent study by Jette et al. (2005) who found
higher intensity of therapy was associated with shorter hospitalization and higher likelihood
of functional independence and mobility (Jette, Warren, & Wirtalla, 2005). Importantly, the
benefit of increasing the intensity of therapy is maintained beyond the treatment phase. The
results of a meta-analysis which included 10 studies demonstrated that increased therapy
intensity had a positive effect on activities of daily living as measured by functional measures
(i.e., Barthel Index) and improvements were maintained over a 6-month period (Galvin,
Murphy, Cusack, & Stokes, 2008).

British Columbia's Stroke Strategy
The blueprint for British Columbia's Stroke Rehabilitation Service is composed of
several elements. Rehabilitation assessment is one of these elements (Stroke Report British
Columbia, 2000). It is suggested that within 48 hours of stroke, professionals should use
standardized assessment tools to evaluate the patient's impairment and determine if/when the
patient will be ready to begin post-acute rehabilitation. The cornerstone of post-acute
8

rehabilitation is typically restricted to physiotherapy, occupational and speech therapy. Once
the stroke survivor is ready to begin rehabilitation, the patient and their family work with the
unit to determine personal rehabilitation needs and develop a care plan. Recently, the Stroke
Strategy's Rehabilitation Report confirmed that stroke patients in British Columbia are
unable to access consistent healthcare, as constrained by resource availability. BC's limited
access to rehabilitation services has meant that some stroke survivors (including those in
northern regions such as Prince George) may not have the opportunity to participate in a
comprehensive stroke rehabilitation program and consequently may never reach their full
functional potential (Stroke Report British Columbia, 2000).
It is becoming increasingly clear that rural populations have a great need for specialty
physician services. Studies have found that physicians may be reluctant to work in rural areas
due to the nature of practice characteristics such as long hours, lengthy on-call schedules
(Kazanjian & Pagliccia N, 1996) and educational isolation (Rourke et al., 2005). It is
particularly challenging for small centres to identify and create stroke units and to provide
ongoing acute care. For example, University Hospital of Northern British Columbia
(UHNBC) currently offers no specialized stroke care unit or specialized secondary stroke
prevention clinics in which to discharge patients for follow-up care.

Literature Review on Visuospatial/Visuomotor Cognitive Training
Despite the prevailing incidence of cognitive deficits post stroke, rehabilitation of
stroke is heavily focused on assisting physical function. In exceptional cases in which
cognitive training is incorporated into rehabilitation, it is limited to very specific cognitive
tasks. Here we review the strides that have been made with regards to research on
visuospatial cognitive training. Visuospatial/visuomotor (VS/VM) abilities are those related
9

to understanding and conceptualizing visual representations and spatial relationships and the
ability to use this information to manually perform a task. First, a definition of how the
efficacy of a given training program is determined will be provided. This will be followed by
an overview of specific research studies that comprehensively demonstrate what is currently
known about visuospatial cognitive training from basic to more complex remediation.

Defining the Evaluation Process of Cognitive Intervention
An ideal way to evaluate cognitive training intervention is by a randomized controlled
trial. A randomized control trial is an experimental design where participants are randomly
assigned to a treatment group (experimental therapy) or a control group (placebo or standard
therapy) and then a comparison is made. In clinical practice, "pure" no-treatment control
conditions are impossible and unethical to establish. Therefore all patients regardless of
group assignment continue to receive standard care. The key of interventional studies, then,
is to look at pre/post interventional differences to determine whether the intervention offers
specific benefits above and beyond standard treatment. Therefore, the success of a treatment
is verified by comparing its benefits with those of the "best available" treatment (Cicerone,
2005). The best available treatment for post-stroke recovery is the combined application of
physiotherapy, occupational and speech therapy, along with any individualized
recommendations dictated by clinical experience and determined by the patient's clinical care
team (Lincoln, Whiting, Cockburn, & Bhavnani, 1985). With the use of exercise equipment
and aqua-fitness to train the affected limb, these conventional therapies are primarily
concerned with reducing impairments through compensatory mechanisms, and can be
classified as a "bottom-up" approach. This approach can be contrasted to the underlying
philosophy behind cognitive training in which the aim is to reverse disability by promoting
10

neural activity in a "top down" manner, thereby directly treating the effected organ: the brain.
Finally, most studies of cognitive rehabilitation have relied on neuropsychological outcome
measures to evaluate the success of treatment. Thus, comparison to baseline scores measured
before treatment is an effective way to evaluate improvement.

Remediation of Neglect and Visuospatial/Visuomotor Deficits
VS/VM impairments are a significant cause of disability after stroke. For example,
there is well-documented evidence that VS/VM impairments are a common consequence of
right hemisphere stroke (Byrd, Touradji, Tang, & Manly, 2004; Feldman et al., 2001;
Halligan, Burn, Marshall, & Wade, 1992; Huang & Wang, 2008; Lowery, Ragland, Gur,
Gur, & , 2004; Weintraub & Mesulam, 1988; Wilson, Cockburn, & Halligan, 1987; Lowery
et al., 2004; Tippett & Black, 2008; Lowery et al., 2004). VS/VM impairments typically cooccur with neglect (decreased awareness) for one side of the visual field, causing a patient to
act as if that side of sensory space does not exist. Even if patients have moderate or good
neurological recovery, neglect and VS/VM cognitive impairments account for the most
persistent and prominent consequence of right hemisphere brain injury (Cicerone, 2005).
Furthermore, the presence of unilateral neglect in subjects with right hemisphere stroke is
associated with greater functional disability and prolonged hospitalization (Katz, HartmanMaeir, Ring, & Soroker, 1999). For the remediation of neglect, the following review will
emphasize research studies that have focused on the improvement of basic abilities and
behaviours such as visual scanning (exercises that promote awareness of the neglected
hemisphere). In terms of VS/VM remediation, the following review will focus on studies that
have addressed the training of complex and high-level skills such as reading and writing that
depend on intact spatial relationships (Cicerone et al., 2000; Cicerone, 2005).
11

12

Training Effectiveness of Visual Scanning
Substantial efforts have gone into devising techniques for the rehabilitation of
neglect. Scanning training is classically the most popular rehabilitative approach (Gordon et
al., 1985; Weinberg et al., 1977). This technique relies on the observation that the majority of
problems encountered by neglect patients arise from a defective visual exploration strategy
(Smania, Bazoli, Piva, & Guidetti, 1997). Indeed, these patients demonstrate a reluctance to
explore the left hemispace and rather begin their scan from the right hemispace (Cheti,
Leblanc, & Lhermitte, 1973), moving the gaze vertically rather than horizontally (Chatterjee,
Mennemeier, & Heilman, 1992). Scanning training generally is composed of exercises that
aim at gradually amplifying the horizontal extension of the patient's visual scanning habits,
repairing their visual exploration tendencies. The following describes studies that have
focused on the efficacy of visual scanning training for the remediation of unilateral neglect
caused by right hemisphere damage.
Weinberg and colleagues (1977) compared standard rehabilitation with an
intervention that trained stroke patients to compensate for impaired scanning habits. People
in the standard rehabilitation sample (n =32) and the experimental group (n = 25) were at
least 4 weeks post insult. The experimental treatment group received 20 hours of training in
which visual material was incrementally used to enhance left-sided scanning. This training
required patients to acknowledge the neglected field by searching for stimuli presented to the
left visual field. The treatment group significantly improved on both specific scanning
measures and academic reading tests that were taken to rely on intact visual scanning
(Weinberg et al., 1977). Variations of this procedure and extensions of the design were
explored by Young and colleagues (1983). This research also compared a standard
13

rehabilitation control group (n = 14) with an experimental training group (n = 13) with the
objective of confirming the usefulness of scanning training to remediate neglect caused by
right hemisphere damage. The trained patients were required to complete a number of visual
cancellation tasks for 20 hours over a 4 week period. The experimental group significantly
improved on academic measures of reading and writing compared to controls (Young,
Collins, & Hren, 1983). In an effort to uncover new benefits of scanning training, Wiart and
colleagues (1997) used functional outcome measures (i.e., Functional Independence Measure)
to demonstrate that stroke patients who received visual scanning training (n = 11) not only
significantly reduced neglect but also improved on activities of daily living compared with
those who received traditional rehabilitation (n = 11) (Wiart et al., 1997). Improvement in
functional abilities also has significant implications as it relates to the potential for reducing
health care costs. Indeed, Kalra and colleagues (1997) compared standard stroke
rehabilitation to an intervention group that involved scanning training to demonstrate that
neglect patients who received the intervention produced significant improvements on spatial
exploration and had significantly shorter hospitalization compared to controls (Kalra, Perez,
Gupta, & Wittink, 1997). The results of these studies indicate that training in visual scanning
is required to reduce functional impairments in activities such as reading and driving
(Klavora et al., 1995). Furthermore, many other comparable studies (Butter & Kirsch, 1992;
Carter, Howard, & O'Neil, 1983; Gordon et al., 1985; Gouvier, Cottam, Webster, Beissel, &
Wofford, 1984; Kalra et al., 1997; Kerkhoff, Munssinger, Haaf, Eberlestrauss, & Stogerer,
1992; Kerkhoff, Munbinger, Eberle-Strauss, & Stogerer, 1992; Lincoln et al., 1985; Neistadt,
1992; Pantano et al., 1992; Pizzamiglio et al., 1992; Pommeranke & Markowitsch, 1989;
Robertson, Tegner, Tham, Lo, & Nimmo-Smith, 1995; Soderback, Bengtsson, Ginsburg, &
14

Ekholm, 1992; Taylor, Schaeffer, Blumenthal, & Grisell, 1971; Weinberg et al., 1979;
Weinberg, Piasetsky, Diller, & Gordon, 1982; Wiart et al., 1997; Young et al., 1983),
reaffirm the superiority of visual scanning training to conventional physical therapies alone.
Moreover, the superiority of scanning training to conventional rehabilitation is evident even
in persons without neglect and extends to those with a left hemispheric stroke. For example,
five studies (Carter et al., 1983; Lincoln et al., 1985; Neistadt, 1992; Taylor et al., 1971;
Weinberg et al., 1982) compared the effectiveness of visual scanning training with
conventional rehabilitation therapies for patients without evidence of unilateral neglect and
included a mix of right and left hemisphere stroke. The subjects who received visual
scanning training had significantly greater improvement after 3 to 4 weeks of treatment than
did subjects who received conventional stroke rehabilitation. Furthermore, scanning training
appears to be beneficial even in chronic (i.e., several years post-stroke) patients with neglect,
and this improvement applies to daily life conditions. For example, research conducted by
Dam et al (1993) and Paolucci (1996) has demonstrated that chronic neglect stroke patients
(including both left and right hemisphere stroke) who were given scanning treatment
achieved better motor and functional recovery than patients who underwent only motor
rehabilitation (Dam et al., 1993; Paolucci et al., 2000). Training in visual scanning is so
fundamental that the National Institutes of Health considers it a standard for remediation of
neglect (Cicerone, 2005) and the aformentioned studies suggest that it should be
implemented after right or left hemisphere stroke and for both acute or chronic cases.

Training Effectiveness of Complex Visuospatial Skills
For persons with visuospatial deficits associated with right hemisphere stroke,
additional training on more complex visuospatial tasks appears to enhance the benefits of
15

treatment and facilitate generalization to other visuospatial, academic, and functional
activities (e.g., reading, writing, walking). Studies focused exclusively on training complex
visuospatial skills are sparse and relatively dated. The following is a review of studies that
have addressed the remediation of visuospatial deficits.
Weinberg and colleagues (1979) assessed the training effects of complex visuospatial
skills for 50 subjects with right hemisphere stroke. The 30 subjects in the experimental
condition received 20 hours of training in reading, writing and calculation that depend on
intact visuospatial organization in addition to visual scanning training. The 20 subjects in the
control condition received an equivalent amount of standard rehabilitation. The subjects in
the intervention group significantly improved on visuospatial functional and academic tasks
relative to the control group. The benefits were most apparent among subjects with more
severe visuospatial impairments. The authors proposed that incorporating multiple treatment
levels into training (scanning plus visuospatial activities) produced more benefits and greater
generalized improvements than a single treatment program (i.e., scanning) (Weinberg et al.,
1979). Weinberg and colleagues (1982) continued to explore the usefulness of visuospatial
training by providing training designed to establish a systematic strategy for organizing
visual material (e.g., tips for picture copying). The study was for right hemisphere stroke
patients with visuospatial deficits without visual neglect, most of whom were more than 3
months post-stroke. Compared with conventional rehabilitation, the experimental treatment
produced benefits on measures of visual analysis (e.g., matching faces) and organization
(e.g., picture completion) (Weinberg et al., 1982). The claim of the effectiveness of
systematic treatment directed at multiple levels of visuospatial impairment was further
examined by Gordon et al. (1985). A comprehensive program of treatment for visuospatial
16

disturbances associated with right hemisphere stroke was developed by combining 3 types of
visuospatial techniques: (1) basic visual scanning, (2) somatosensory awareness and size
estimation, and (3) complex visuoperceptual organization (e.g., picture assembly). Among 77
acute right hemisphere stroke subjects receiving rehabilitation, 48 received the experimental
treatment and 29 received conventional rehabilitation. At rehabilitation discharge, the
experimental group showed greater improvement than the control group in all 3 areas of
visuospatial functioning. In addition, functional gains were shown by increased leisure
reading and increased performance in activities of daily living (Gordon et al., 1985). These
studies lend support that stroke patients on the whole may benefit from systematic training of
visuospatial skills as part of their acute rehabilitation.
Comparisons across the aforementioned studies producing positive effects in
visuospatial remediation and a few studies finding no effect (Edmans et al., 2009; Robertson,
Gray, Pentland, & Waite, 1990; Lincoln et al., 1985) suggest that effective training needs to
be relatively intense (i.e., daily) (Kwakkel, Wagenaar, Koelman, Lankhorst, & Koetsier,
1997; Kwakkel et al., 1999; Langhorne, Wagenaar, & Partridge, 1996; Tangeman, Banaitis,
& Williams, 1990; Taub et al., 1993; Teasell et al., 2006; Wolf, LeCraw, Barton, & Jann,
1989). Furthermore, the amount of improvement is associated with the intensity of
rehabilitation (Gladstone, Black, & Hakim, 2002; Langhorne et al., 1996; Nugent, Schurr, &
Adams, 1994; Smith et al., 1981; Teasell et al., 2006). A summation of all this research
indicates that effective treatment should involve 20 individual 1-hour sessions delivered on
separate days over a period of 4 weeks. Furthermore, the effects of short and intensive
treatment appear to be maintained in the long term (i.e., up to 1 year) (Wiart et al., 1997;
Diller & Gordon, 1981; Pizzamiglio et al., 1992).
17

Video-gaming Training Effectiveness
The use of video-gaming technology is emerging as a novel technique in
rehabilitation for stroke patients. Video games maintain the spirit of training (i.e., progressive
level of difficulty as performance improves) while offering enriched environments that may
maximize brain plasticity after stroke (Adamovich et al., 2004; Levin, 2011; Saposnik &
Levin, 2011). Among the existing studies that have utilized gaming systems with stroke
populations, the purpose has been to improve motor deficits with no focus on cognitive
outcome measures. However, the overriding consensus from these studies has been that
gaming systems keep patients motivated and engaged for long periods of time to allow the
brain to make full use of its ability to recuperate (Adamovich et al., 2004; Levin, Knaut,
Magdalon, & Subramanian, 2009; Saposnik et al., 2010; Saposnik & Levin, 2011). In a
recent randomized controlled trial, Saposnik and colleagues (2010) demonstrated that the use
of Wii training resulted in significantly better upper-body movement and improvement of
activities of daily living in 20 acute stroke patients compared to patients who received only
standard rehabilitation (Saposnik et al., 2010). Levin and colleagues (2010) have confirmed
these findings in a more elaborate study that delineated the specific benefits of 2-dimensional
(2D) and 3-dimensional (3D) virtual systems compared to conventional rehabilitation
protocols. Both 2D and 3D treatment was shown to be superior to conventional rehabilitation.
Arm mobility was most remarkable in patients treated with the 3D virtual reality system,
followed by those in the more modest 2D game system. Furthermore, improvement in upper
extremity function using videogames has also been demonstrated in patients who had spatial
neglect (Katz et al., 1999; Weiss, Bialik, & Kizony, 2003). Analogous studies examining the
benefits of gaming systems have supported their efficacy even in chronic stroke patients.
18

Adamovich and collegues (2010) trained 24 chronic stroke patients on a video game for 22
hours over a two-week period. The trained group significantly improved on reaction and
movement time compared to controls (Adamovich et al., 2004). Mapping of the brain using
functional magnetic resonance imaging (fMRI) suggested that this recovery may be due to
increased functional connections between motor and sensory regions (Adamovich, 2010).
Although there is limited evidence available on the effectiveness of video gaming in
the context of cognitive rehabilitation of stroke, research in normal aging has already
demonstrated that gaming has positive outcomes on visuospatial skills (Green & Bavelier,
2003), reaction time (Dustman, Emmerson, Steinhaus, Shearer, & Dustman, 1992; Gopher,
Weil, & Bareket, 1994), increased hand-eye coordination (Drew & Waters, 1986), mental
rotation and visual attention (Dye, Green, & Bavelier, 2009; Green & Bavelier, 2003). To
examine the influence of video game playing on regional cerebral blood volume, Hoshi and
Tamura (1997) measured cerebral hemoglobin concentrations using near-infrared
spectroscopy in six older adults. After only 14 seconds of game playing, they found a
significant increase in fronto-parietal haemoglobin levels (Hoshi & Tamura, 1997). In a study
using positron emission tomography (PET), Haier et al. (1992) observed regional glucose
metabolic changes in adults who engaged in a VS/VM task. In approximately 4 weeks of
daily practice, cortical glucose metabolism significantly decreased despite a 7-fold increase
in performance (Haier et al., 1992). These authors suggested that the use of video game
training worked to strengthen cortical circuits, resulting in decreased use of extraneous or
inefficient brain resources, thus liberating the brain to function more efficiently. Video­
games may also have an influence on increasing levels of cerebral oxygenation by regulating
physiologic parameters such as systemic arterial pressure. For example, Segal et al. (1991)
19

reported that playing video games significantly increased systolic and diastolic blood
pressure, heart rate, and oxygen consumption, which also facilitated an increase in
simultaneous cerebral hemoglobin changes in adults in the frontoparietal regions (Segal &
Dietz, 1991). Finally, using PET Koepp et al. (2008) has shown that engaging in videogames
produces a significant increase in brain dopamine levels compared to controls (Koepp et al.,
1998; Kopp, Rosser, & Wessel, 2008). This surge in dopamine is thought to play an
important role in learning following visuospatial training. On the forefront of this research
are Bao and colleagues (2001) who argue that the presence of dopamine is not only apparent,
but is necessary for fast and widespread visuospatial learning (Bao, Chan, & Merzenich,
2001).
For many brain injuries the rehabilitation process is very taxing and there is a
challenge in finding appealing and motivating intervention tools that will facilitate this
process. Videogame training may answer this challenge by providing the opportunity for
active learning while still permitting strict experimental control over stimulus delivery, as
well as the opportunity to individualize treatment needs while incrementally increasing the
task complexity (Rizzo, 2003; Schultheis & Rizzo, 2001).

Visual Imagery Training Effectiveness
Action observation can engage motor cortical activity in the absence of overt
movement. Such cortical activity is regulated by neurons, often noted as mirror neurons,
which fire when individuals watch others performing actions (Kandel, Schwartz, & Jessell,
2000). Recent studies have also shown that mirror neuron training performs an important role
in accelerating recovery of arm and leg function post-stroke by facilitating learning of
complex actions and through internal rehearsal of actions (Altschuler et al., 1999; Buccino,
20

Solodkin, & Small, 2006). Training stroke patients to imagine moving their affected arm
(e.g., motor imagery) has the potential to promote recovery of extremity function by
promoting neuroplasticity. For example, several fMRI studies of observation learning have
shown that watching someone else's action is associated with activation in the same parietal
and premotor regions that are used when actually producing the action (Decety et al., 1997;
Grezes & Costes, 1998; Grezes, Costes, & Decety, 1999). Two important findings from
neurophysiological studies provide evidence for neuroplasticity. First, recovery of hand
function after stroke is accompanied by a particular compensatory pattern of activity in the
motor cortex (Dijkerman, Ietswaart, Johnston, & MacWalter, 2004). Second, imagining
making hand movements simulates the same compensatory pattern of brain activity that is
seen accompanying actual recovery of hand function (Decety & Ingvar, 1990; Weiller, 1995).
Direct evidence for the efficacy of imagery training comes from a pilot study by Page and
colleagues (2000). The researchers gave chronic stroke patients (n = 16) a series of scripts
that described a variety of motor movements and required them to mentally rehearse the
scripts 3 hours/week for six weeks. At study completion, they found a significant
improvement in arm function in the trained stroke patients compared to controls who
received only conventional rehabilitation. Improvements also generalized to functional
measurements that were not directly trained but relied on similar brain regions (Page, 2000).
In a later study, Page et al. (2001) replicated these results on a sample of sub-acute (1 year
post-insult) stroke cases (n = 13) (Page, Levine, Sisto, & Johnston, 2001).
More support for the efficacy of imagery training has also been provided by
Dijkerman (2004) who compared each of two different types of imagery groups to a control
group. Chronic stroke patients in the experimental group (n = 10) who mentally rehearsed a
21

motor task were compared to a non-motor imagery group (n = 5), and a control group that
was not engaged in mental rehearsal (n = 5) (Dijkerman et al., 2004). On a daily basis, the
motor imagery group was required to practice imagining moving tokens with their affected
arm. The non-motor imagery group rehearsed visual imagery of previously seen pictures. All
three patient groups improved on the motor tasks. However, improvement was greater for the
motor imagery group, followed by non-motor imagery and then the control group.
Beyond physical remediation, there is also some precedent for the use of visual
imagery to alleviate neglect in stroke patients. Niemeier (1998) compared standard
rehabilitation with a novel technique to train acute stroke patients to imagine their eyes as
beams of a lighthouse, sweeping the horizon from left to right. After presenting a picture of a
lighthouse, the patients were required to use this imagery while performing functional
activities that require integrative VS/VM abilities such as dressing and eating. The
experimental (n = 16) and control groups (n = 15) were approximately 2 months post-insult
and were both composed of left and right hemisphere stroke patients. Post-treatment results
showed that the experimental group participants were significantly better than the controls in
performing tasks related to neglect (i.e., Mesulam Cancellation) and visual attention (i.e.,
Facility Rating Scale) (Niemeier, 1998). In a more elaborate study by Niemeier and
colleagues (2000), stroke patients were trained to use a variety of visual and motor imagery
techniques to remediate neglect. Visual imagery training required participants to explain a
familiar path by reporting the location of the buildings, roads, and other reference points
(e.g., signs, advertising posters). At post-treatment, the treatment group performed
significantly better on functional tasks (e.g., walking and wheelchair route-finding)
(Niemeier, 2000). Additional research conducted by Smania and colleagues (1997) utilized
22

motor imagery to train participants to imagine the affected arm positioned in one of several
given postures and then to describe the relative position of the contralateral arm. The study
delivered forty sessions, each lasting 50 minutes. Improvements in performance, which
persisted at 6 month follow-up, were reported on a range of neuropsychological (e.g., Letter
H Cancellation) and functional (e.g., reading) measures (Smania et al., 1997). Using a
slightly different research methodology, McCarthy and colleagues (2002) designed a study to
investigate whether imagined limb activation reduced the extent of neglect in two single case
studies. The study implemented an ABBABBA (counterbalancing) design where patients
were required to imagine making movements of the left arm during the intervention
conditions. Neglect was measured using neuropsychological measures. Performance during
intervention conditions were compared to baseline conditions. The results showed that
imagined activation of the left arm significantly reduced the symptoms of left-sided neglect
(McCarthy, Beaumont, Thompson, & Pringle, 2002).
Because inputs to the mirror neuron system are visual and auditory, this bypassing
strategy may offer an alternate access to motor networks independent of the affected primary
motor cortex. Accordingly, motor imagery-based intervention may prove particularly
beneficial in hemiplegic patients because it offers opportunities to directly activate cortical
areas representing a paralyzed limb which would not be activated otherwise (Sharma,
Pomeroy, & Baron, 2006). Finally, because the imitation network is engrained at a young age
and hardwired from past-life experiences, this form of training is presumed to come naturally
to patients.

23

Visuospatial/Visuomotor Cognitive Intervention Program
Cognitive Training Project Rationale
Nation-wide evidence suggests that within a few months of discharge, stroke
survivors often return to clinics or primary care physicians with complaints of cognitive
impairment (Cicerone, 2005). It has been reported that compared to healthy adults, stroke
survivors have up to a 10-fold relative risk of developing dementia, and this risk persists for
at least 3 to 5 years (Kokmen, Whisnant, O'Fallon, Chu, & Beard, 1996; Savva & Stephan,
2010; Ukraintseva, Sloan, Arbeev, & Yashin, 2006). Results from the Framingham study
showed that over a 10-year span, individuals with a stroke episode had twice the risk for
developing dementia compared to healthy age and gender matched controls (Elias et al.,
2004; Savva & Stephan, 2010; Ukraintseva et al., 2006). Stroke in relation to cognitive
dysfunction poses high risk, particularly in rural regions with limited access to speciality
services, and therefore cognitive intervention is a viable target that may help preserve
cognitive vitality. To my knowledge, there are currently no published studies examining the
efficacy of a comprehensive VS/VM training program to improve post-stroke cognitive
recovery, but given the evidence presented I have postulated that it could be a fruitful
approach. This idea is based on two well-supported findings. First, decaying brain volumes
caused by stroke weaken the brain's line of defence against ischemic attacks, resulting in a
cascade of pathological events and cognitive ramifications (Kase et al., 1998). However, the
use of cognitive intervention may promote neuroplasticity and may provide additional
facilitation of blood flow to the brain, thereby maximizing the brain's defence mechanisms.
For example, reperfusion to high risk areas, particularly the ischemic penumbra, may cause
the affected neurons to resume functioning thereby improving functional outcomes. The
24

previously mentioned studies in which Hoshi et al. (1997) and Haier et al (1992) observed
regional glucose metabolic changes in adults who engaged in VS/VM tasks and videogaming
is prime evidence of the potential of increased neuroplasticity and blood flow to the brain.
Second, it is possible that parietal lobe stimulation, through the use of a VS/VM training
program, may improve global cognitive and day-to-day functioning. Support for this idea
comes from Loewnstein et al. (2004) who included a visuomotor speed of processing task
and proposed that improved performance on functional tests (e.g., making change for a
purchase) was actually a result of the VM training (Loewenstein, Acevedo, Czaja, & Duara,
2004). Furthermore, the previously mentioned studies by Levin (2010) and Saposnik et al.
(2010) have demonstrated that videogames improve both mobility and cognitive ability in
post-stroke recovery. Collectively, these studies and others have suggested that a network of
connections between the parietal and other brain regions are important for VS tasks (Tippett
& Black, 2008; Tippett et al., 2009), and that a cognitive training program designed to
stimulate VS processes can act to strengthen the network, priming them for other cognitive
and functional tasks. It can be postulated that cognitive exercise acts like a buffer to increase
the capacity of the brain to endure neuropathological changes. This ability of the 'fitter brain'
to adapt to neurological stressors may result from the brain being "flexed" in the learning
process (Stern, 2009). Whether a post-stroke program focusing on VS and VM training can
flex the brain enough to improve compromised cognitive ability is not yet known.

Summary of Project Elements
The following is a summary of best practice principles for post stroke cognitive
recovery, and was utilized as the structure for this research. New interventional research
should strive to address these principles.
25

1. Randomized control trials looking at pre/post interventional differences are the most
widespread methodological design to determine whether an intervention offers specific
benefits above and beyond standard treatment (Cicerone, 2005).
2. To maximize the efficacy of treatment, training needs to be relatively intense (i.e., daily)
(Gladstone et al., 2002; Teasell et al., 2006).
3. Visual scanning training is necessary for the remediation of neglect caused by right
hemisphere stroke and its incorporation into conventional therapy is more effective for
improving cognition and functional abilities than conventional therapy alone (Wiart et al.,
1997).
4. The superiority of scanning training to conventional rehabilitation is evident even in stroke
patients without neglect and extends to those with a left hemispheric stroke (Neistadt, 1992).
5. For persons with stroke involving visuospatial deficits, additional training on more complex
visuospatial tasks (i.e., treatment designed to establish a systematic strategy for organizing
visual material) appears to enhance the benefits of treatment (Gordon et al., 1985).
6. Video gaming has the ability to promote brain plasticity (e.g., cortical reorganization, blood
reperfusion) after stroke and has been linked to improvement in physical mobility. Research
is absent with regards to its effectiveness in post stroke cognitive recovery (Levin, 2011;
Saposnik et al., 2010).
7. Visual imagery of hand movement simulates the same brain region that accompanies actual
hand movement and has also been linked to remediation of neglect symptoms (Dijkerman et
al., 2004).

26

Objectives
The goal of this study was to investigate whether the incorporation of
visuospatial/visuomotor (VS/VM) cognitive training to standard stroke therapy is an effective
tool for improving acute post-stroke recovery.

Hypotheses
Brain training that focuses on VS/VM activities effectively improves acute poststroke recovery in that it provides widespread benefits to cognition (e.g., memory, language),
function (e.g., activities of daily living) and mood (e.g., depression) that supersedes what is
offered by standard therapy alone.

Method
Participants
The performance of nine right-handed primary stroke participants in the experimental
group (5 male, 4 female, mean age at stroke 65 ± 9.31) was compared to that of nine righthanded stroke participants in the control group (6 male, 3 female, mean age at stroke 67 ±
7.81). Mean number of years of public education was 9 ± 2.07 for the experimental group
and 10 ± 1.45 for the control group. Mean days since stroke was 14.78 ± 2.94 for the
experimental group and 16.66 ±4.18 for the control group. Participants were recruited from
UHNBC and met the inclusion and exclusion criteria outlined in Tables 1 and 2 respectively.
Table 3 presents the frequency distribution for the groups on stroke characteristics as per
physician identified.

Study Recruitment Strategy
Initial screening for participants was obtained and agreed upon by physician referral.
When these potential participants entered a safe post-stroke window (i.e., were medically
27

stable), they were approached and provided with background information on the study. After
the patient provided informed consent, thorough chart examination was completed to verify
that the patient met the inclusion/exclusion criteria. It was taken into consideration that some
stroke participants may have had significant cognitive impairment at recruitment. For this
reason, a conservative method to ensure proper consent/assent of persons who possibly
lacked the capacity to provide full consent was followed. In addition to the patient's consent,
the consent of a close family member was obtained for participants who scored less than 20
on the MMSE (a level that raises the possibility that the patient may be unable to provide
consent). A copy of the signed consent was given to participants and family member/proxy
for their information and their records.

Procedure
Participants underwent neuropsychological testing at baseline and at follow-up (at
completion of the cognitive intervention program). The neuropsychological examinations
were used to determine the levels of cognitive ability in the areas of attention, language,
visuospatial skills, executive function and memory. A self-reported measure of depression
was also completed by each participant. Measures to determine pre-training and post-training
functional status were completed by the patient's caregiver. All participants (n = 18)
continued to receive standard stroke treatment already in place. This was a randomized
control trial involving a 1:1 random allocation of each participant into either the experimental
or control condition. The experimental group (n = 9) additionally received specialized
VS/VM training and the other half (n = 9) served as controls receiving only standard
treatment. The flow of participants for the study is shown in Figure 1. The randomized
control design of the project addressed best practice principle #1. Training for the
28

experimental group occurred in hospital for 1 hour, 5 days/week for 4 weeks. The intensity of
this project addressed best practice principle #2. The groups were matched as closely as
possible (e.g., age, gender, education, clinical factors) by making frequent demographic
comparisons as participants joined the study. Patient recruitment was conducted for 7
months. Implementing training during the patient's hospitalization rendered close to 100%
compliance with only 3 missed sessions overall across all participants (due to conflicting
medical appointments), which were subsequently made-up. Only one patient who was
approached to participate in the study declined the invitation, and participants that were
enrolled all reached their target completion date.

Components of Cognitive Training Intervention
A comprehensive stroke intervention program was developed by integrating 4 types
of previously evaluated perceptual remediation techniques: visual scanning, video-gaming,
visual imagery training, and complex VS/VM construction. The complete intervention
program collectively addressed best practice principles #3-7.

Visuospatial scanning. Five-to-ten minutes of each training session was devoted to
the Mesulam Cancellation Test (Mesulam, 1985). Cancellation tests are one of the most
popular tools for evaluating visuospatial attention, visual scanning patterns, and neglect
problems (Byrd et al., 2004; Halligan et al., 1992; Lowery et al., 2004; Weintraub &
Mesulam, 1988). For this task, the patient was required to circle a certain "target symbol"
amongst a host of distracters. This task required active scanning and trunk movement to the
left and right sides of the visual field. The targets were varied with respect to stimulus shape,
set sizes, and array layouts, thus making this task appropriate for training purposes

29

(Friedman, 1992; Halligan et al., 1992; Wilson et al., 1987). This component of training
addressed best practice principles # 3-4.

Complex vtsuospatial construction. Fifteen-to-twenty minutes of each training
session was devoted to Block Design [Wechsler Adult Intelligence Scale (WAIS)-IV] which
is a task that required patients to assemble blocks to match a model drawing. This activity
was used to train complex, high-level visuospatial skills (Wechsler, 2008). This component
of training addressed best practice principle # 5.

Complex VS/VM activity. Fifteen-to-twenty minutes of each training session was
devoted to playing the commercially available game "Pac-Man". This video-game
encapsulates visually guided ability and requires a substantial degree of VM control to
navigate its virtual environment. Furthermore, the VM demand automatically increases as
one's performance improves. This component of training addressed best practice principle #
6.

Mirror neuron training. Fifteen minutes of each training session required patients to
observe others engaging in motor activities (e.g., watching a tennis match). Patients were
encouraged to verbalize each action that they were imagining (e.g., serving) in order to verify
their engagement in the absence of overt movement. This component of training addressed
best practice principle # 7.

Weekend maintenance homework booklet. Throughout the duration of training,
maintenance stimulation was achieved by workbook activities comprised of visuospatial,
visuoconstructive and visuomotor tasks (e.g., mazes, "correct rotation", "find the
differences". See Appendix A). Participants were encouraged to engage in these tasks for 2
hours over the weekend. Each participant kept a log of their hours and at the beginning of
30

each week and completion of homework was monitored and checked for correctness. If a
component was incorrectly completed, it was returned on the following weekend and the
patient was asked to try again.

Standard treatment. In addition to VS/VM cognitive training, standard
rehabilitation was provided for all participants. Standard stroke therapy encompassed
physiotherapy, occupational therapy and speech therapy. These treatments aim to address
common consequences of stroke such as paralysis, functional disability, social handicap and
aphasia (World Health Organziation, 1993). Physiotherapy is concentrated on improving
controlled movement and muscle strength and alleviating spasticity and contractures
(Langhorne et al., 1996). Occupational therapy assesses how sensory and motor deficits
impact independent functioning and then aims to decrease disability due to these impairments
(Donkervoort, Dekker, Stehmann-Saris, & Deellman, 2001). Speech therapy makes use of
auditory stimuli (e.g., music), and visual stimuli (e.g., drawings) to improve language
impairment (Roth F.P. & Worthington C.K., 2010).

Neuropsychological Primary Outcome Measures
The neuropsychological test battery was selected to index all major cognitive domains
(executive, language, visuospatial and memory) and was composed of tests that have been
recently suggested to be sensitive measures for stroke by the National Institute of
Neurological Disorders and Stroke and the Canadian Stroke Network (Nyenhuis et al., 2009).
The battery required a reasonably short time period to administer (approximately 60
minutes), and had a sufficient range of difficulty (floor & ceiling effects) for patients. All
patients were administered this battery pre-intervention and post-intervention.

31

Executive domain: Animal Naming Test. Animal Naming is a common executive
category fluency test (Barr & Brandt, 1996), chosen because of its large standardization
samples (Crossley, D'Arcy, & Rawson, 1997; Kozora & Cullum, 1995; Seines et al., 1991),
its high reliability (test re-test ICC = .90) (Abwender, Swan, Bowerman, & Connolly, 2001)
and its prior use in stroke studies (Canning, Leach, Stuss, Ngo, & Black, 2004). Studies have
reported that it is useful in differentiating Alzheimer's disease from vascular dementia
patients (Canning et al., 2004). The patient is required to list as many animals as possible in
one minute and the score is the number of correct responses.

Attention domain. Trail Making Test. Trail making measures a variety of abilities
including visuomotor, working memory and executive set shifting (Reitan & Wolfson, 1993).
It has several standardization samples (Heaton, Miller, Taylor, & Grant, 2004; Ivnik, Malec,
Smith, Tangalos, & Petersen, 1996; Seines et al., 1991) and has demonstrated sensitivity to
VCI (O'Sullivan, Morris, & Markus, 2005; Padovani et al., 1995). It possesses high
consistency (Cronbach alpha = .96) (Kopp et al., 2008) high reliability (test re-test r = .96)
(Reynolds, 2006). Trails A presents numbers from 1 - 25, and the patient is required to
connect the numbers in ascending order. Trails B, presents circles that include both numbers
(1-13) and letters (A - L) and patient is required to connect the circles in an ascending
order, alternating between the numbers and letters (i.e., 1-A-2-B-3-C). Both trails A and B
are scored for time to completion.

Processing speed domain. Digit Symbol (DS). Digit Symbol is part of the WAIS- III
and measures executive and processing speed. This test has a large national standardization
sample (Wechsler, 1997) and it possesses high reliability (test re-test ICC = .87; inter-rater
ICC = .74) (Hinton-Bayre & Geffen, 2005). This test has been used in several studies
32

involving individuals with VCI(Mendez, Cherrier, & Perryman, 1997; Padovani et al., 1995;
Tei et al., 1997; Wechsler, 1997) and is sensitive to vascular pathology (O'Sullivan et al.,
2005). The patient is required to match symbol-number pairs and the score is the number of
correct pairs produced in two minutes.

Language domain. Boston Naming Test (BN). BN is the most frequently used
confrontation language naming test (Goodglass, Kaplan, & Barresi, 2001). Many normative
studies are available (Ivnik et al., 1996; Tombaugh & Hubley, 1997; Welch, Doineau,
Johnson, & King, 1996) and it has been used in many studies containing subjects with
potential VCI (Waite, Broe, Grayson, & Creasey, 2001). It possesses high internal
consistency (Cronbach alpha = .90) (Graves, Bezeau, Fogarty, & Blair, 2004) and high
reliability (test re-test r = .91) (Flanagan & Jackson, 1997). Patients are required to name the
item in the picture and the score is the number of items correctly named.

Visuospatial domain. Rey-Osterrieth Complex Figure Copy (REY-C). This
frequently used visuoconstruction task is brief, inexpensive and relatively culture and
language free (Rey, 1941). Several standardization samples are available (Chiulli, Haaland,
Larue, & Garry, 1995; Stern et al., 1994). The test has been used with vascular patient groups
(Diamond, DeLuca, & Kelley, 1997). It possesses high consistency (Cronbach alpha = .94)
(Tupler, Welsh, Asare-Aboagye, & Dawson, 1995) and high reliability (test re-test r = .94)
(Deckersbach et al., 2000). Patients are required to copy a complicated picture and a score is
given based on location and accuracy of picture parts (Stern et al., 1994).

Memory domain. Hopkins verbal learning test (HVLT). HVLT is a popular verbal
memory task that includes three learning trials and a 20 minute delayed recall condition
(Brandt & Benedict, 2001). The HVLT has been used in studies of vascular patients (De
33

Jager, Hogervorst, Combrinck, & Budge, 2003). It possesses reliability (r = .50) that is
comparable to test-retest correlations reported for other tests of verbal memory (e.g., Logical
Memory subtest of the Wechsler Memory Scale-Revised, California Verbal Learning Test)
(Rasmusson, Bylsma, & Brandt, 1995). The sum of items recalled across the three learning
trials provides the total acquisition score and represents short term verbal memory. The
number of items recalled upon delay represents long term memory integrity.
Rey-Osterrieth Complex Figure Delayed Recall (REY-D). This visual memory
drawing condition of the Complex Figure (Rey, 1941) occurs 20 to 25 minutes after the
initial copy condition. Patients are required to draw free-hand what they remember from the
initial diagram presentation. Chiulli et al. (1995) scoring criteria were used. This test
possesses high internal consistency (Cronbach alpha = .90) (Rapport, Charter, Dutra,
Farchione, & Kingsley, 1997) and high reliability (test re-test r = .90) (Deckersbach et al.,
2000).

Attention domain. Digit span. Digit span is the most common test used for
measuring attention and short term working memory (Lezak, 1995). It consists of seven pairs
of random number sequences that the examiner reads aloud. The patient is required to repeat
the numbers in the same order presented (digit forward) or to repeat the numbers in reverse
order (digit backward). Both tests possess strong reliability (test-retest r = .89) and
widespread validity (Kaufman, McLean, & Reynolds, 1991). The WAIS standard scoring
system was used.

Screening/Global domain. Mini-mental State Examination (MMSE). The 30-point
MMSE is a popular general cognitive screening examination (Folstein, Folstein, & McHugh,
1975). It is known for quantitatively assessing the severity of cognitive impairment
34

(Tombaugh & Mclntyre, 1992). Internal consistency is strong (inter-rater IIC = .90) (Molloy
& Standish, 1997). This quick-to-administer test examines a broad range of ability including:
orientation, word recall, working memory, naming, repetition, comprehension and drawing.
A score of greater than 17 was required to meet criteria for study entry
Boston Diagnostic Aphasia Examination (BDAE). This auditory comprehension test
was used to screen for significant receptive aphasia (Benton & Hamsher, 1987). In the test,
patients are instructed to follow certain instructions and the total score is the number of
correctly executed responses. A score of greater than 10 was required to meet criteria for
study entry.
Montreal cognitive assessment (MOCA). This quick-to-administer test is composed
of a five word immediate recall, delayed recall and recognition task, a six item orientation
(e.g., to time and place) and a one letter phonemic (letter f) fluency task. This test was chosen
because of its widespread assessment of cognitive ability and because it demonstrates high
test-retest reliability (r = 0.92) and internal consistency (Cronbach alpha = 0.83) (Nasreddine
et al., 2005).

Neuropsychiatric/Depressive domain.
Geriatric depression scale (GDS).
The GDS is a widely used self-report depression inventory. The score is the number
of reported items that signify pathology. It was used as a detailed index for mood and
represents a valid and reliable measure of depression (Yesavage et al., 1982).

Functional/Activities of daily living (ADL).
Informant questionnaire for cognitive decline in the elderly, short form (IQCODE).

35

The short form is a 16-item scale that is completed by a proxy and compares current
cognitive function to pre-stroke cognitive abilities. Each item is a five-point Likert scale and
the total score is the sum of the points across the 16 items. This form demonstrates high
reliability (test-retest = .97) and validity (Jorm, 1994; Jorm, 2004).
Disability assessment for dementia (DAD).
The DAD (Gelinas, Gauthier, Mclntyre, & Gauthier, 1999) measures both basic and
instrumental activities of daily living (IADL) in patients with cognitive impairment and
dementia. It possesses high internal consistency (Cronbach's alpha = .96) and reliability (test
re-test ICC = .96; inter-rater ICC = .95) and has been used in several clinical trials assessing
dementia agents (Erkinjuntti et al., 2003; Feldman et al., 2001; Orgogozo, Small, Hammond,
Van, & Schwalen, 2004; Suh et al., 2006).
Barthel.
The Barthel is a popular stroke instrument (Foulkes, Wolf, Price, Mohr, & Hier,
1988) that measures basic ADLs. It is both a valid (Graham, Emery, & Hodges, 2004;
Loewen & Anderson, 1990) and reliable (Collin, Wade, Davies, & Home, 1988) measure of
disability in the stroke population.

Results
The results of this study were evaluated using multivariate analysis of variance
(MANOVA) for all measures at pre-intervention and post-intervention. Non-significant
group differences at pre-intervention combined with significant group differences at postintervention would be indicative of intervention success. One-way analysis of variance
(ANOVA) was used on demographic variables to confirm that the participant groups were
equal at baseline. It was also important to evaluate the changes occurring within each patient
36

group, so a repeated measures analysis from pre-intervention to post-intervention was
conducted for each group. Effect sizes were used to interpret all significant p-values.

Pre-intervention Assessment Between Groups
In order to confirm that the groups were comparable prior to the experimental
intervention, a one-way ANOVA was conducted between patient groups (experimental
versus control) on all demographic tests. There were no significant between-group
differences on any of the demographic measures: age (F(l) = 0.40, p = .538), education (F(l)
= 0.63, p = .440) or days since stroke (F(l) = 1.23, p = .285). MANOVA results for
neuropsychological pre-treatment means, standard error, F- value and

between the groups

are presented in Table 4. There were no significant between-group differences observed on
any of the neuropsychological measures. Therefore, the two groups were equal at baseline.

Post-Intervention Differences Between Groups
To evaluate cognitive differences between groups at post-intervention, MANOVA
was conducted between patient groups on all neuropsychological measures.
Neuropsychological post-treatment means, standard error, F-value, df and effect sizes
between the groups are presented in Table 5. A main between-group effect was observed on
all the measures except Line Orientation, Digit Forward, Digit Backward, Digit Symbol,
Trails A and Trails B. However, Digit Backward, Digit Symbol and Trails B are significantly
different when using ANOVA (Digit Backward, F(l, 16) = 4.30, p < .05; Digit Symbol,
F(l,16) = 4.24, p < .05; Trails B F(l,16) = 4.17, p < .05). All significant between-group
differences at post-intervention were accompanied by large effect sizes, ranging from 0.97 to
2.22. Figure 2 compares the means for the MMSE, Boston Naming, Rey Copy, HVLT Delay,
Digit Backward, Digit Symbol and DAD to illustrate the extent of post-intervention
37

differences between the groups in functioning and in each neuropsychological domain
(global, language, visuospatial, verbal memory, processing speed and activities of daily
living, respectively).

Within Group Improvements
An analysis examining the treatment effects within each group was conducted to
evaluate cognitive changes within the groups from pre-intervention to post-intervention.
Repeated measures analysis was performed for both groups. This type of analysis benefits
from the fact that each subject serves as their own control, providing a way to reduce
variability so that the analysis can focus more precisely on treatment effects. Pre-treatment
and post-treatments means, standard error, F-value, df and effect sizes for both groups are
presented in Tables 6 and 7. Within group analysis showed that the intervention group
significantly improved on every outcome measure from pre-intervention to post-intervention.
Furthermore, all improvements were accompanied with large effect sizes, ranging from .40 to
2.35. The control group showed select improvement from pre-intervention to postintervention on: Animals, HVLT, Digit Symbol, Apathy and Barthel test scores.
Improvements were accompanied with small effect sizes, ranging from 0.23 to 0.35. There
were no significant improvements on the remaining tests. Figure 3 compares group changes
from pre-intervention to post-intervention on the MMSE, Boston Naming, Rey Copy and
Digit Symbol. These tests are the most telling in their illustration of how the experimental
group showed improvement whereas the control remained the same.

Magnitude of Improvement Between Groups
Having found that there were significant improvements in both groups for Animals,
HVLT, Digit Symbol, Apathy and Barthel test scores, the next step was to discover whether
38

the intervention group improved significantly more than the control. Change scores (i.e.,
improvement) were calculated by subtracting baseline scores from post-treatment. Next, the
improvements between the two groups were compared using independent r-tests. The
experimental group improved significantly more than the control group on each test: Animals
(f(8) = 5.00, p = .001), HVLT (r(8) = 8.74, p < .001), Digit symbol (t(8) = 5.86, p < .001),
Apathy (f(8) = 5.13, p = .001) and Barthel (f(8) = .95, p < .001). Table 8 compares the mean
improvement for each test between the groups and their significance level. Figure 4 shows
the mean change for each test to illustrate the difference in the magnitude of improvement
between the groups.

Training Outcome Measures
To evaluate the performance of the experimental group on the specific training
measures, an analysis was completed for Pac-Man, Block Design and the Mesulam
Cancellation task. Enhanced performance on trained tasks from initial weeks (weeks 1-2) to
final weeks (weeks 3-4) provides unique information about learning by the intervention
group.

Pac-man task.
For participants engaging in training, high scores as well as duration of play (i.e.,
keeping Pac-man alive) was documented in each training session. Longer duration time
suggests that the participant was improving at the task (e.g., due to improvement in following
rules and avoidance maneuvering). The analysis utilized paired Mests to compare the group's
overall high scores and duration played between weeks 1-2 and weeks 3-4. Significantly
higher scores were observed on weeks 3-4 versus weeks 1-2 (t(8) = 2.73,/? = .026). Figure 5
displays high-scores for initial weeks (1-2) to final weeks (3-4) of training. Likewise, paired

/-test for overall duration of time played showed significantly longer time from weeks 1-2 to
weeks 3-4 (/(8) = 5.62, p = .001). Figure 6 shows that participants increased their duration of
play from weeks 1-2 to weeks 3-4.

Block Design task.
For participants engaging in training, a record was taken of how long it took to
assemble blocks to match a series of model images. The analysis utilized paired Mests to
compare the group's overall duration on this task between weeks 1-2 and weeks 3-4. Shorter
duration time signified that the participant was improving at the task. Significant differences
were observed by faster assembly time from weeks 1-2 to weeks 3-4 (f(8) = 8.01, p = < .001;
See Figure 7).

Mesulam Cancellation task.
For participants engaging in training, a record was taken of how many target items
were found on the left (60 targets) and right (60 targets) visual field over a period of 7
minutes. Paired /-test analysis was used to compare the participant's mean scores from initial
weeks versus final weeks for both left (M = 35.93, SD = 18.64 versus M = 52.36, SD = 10.98)
and right (M = 41.68, SD = 12.88 versus M = 52.81, SD = 9.54) visual fields. Significant
differences between weeks 1-2 and weeks 3-4 was found for the group for both the left (r(8)
= 5.51, p < .01) and the right (t(8) = 3.34, p < .05) visual search fields. Of particular interest
were the performance improvements of two neglect patients (participants #1 and #2) to
determine if there were significant improvement in their ability to locate targets in their
neglected visual field (i.e., left visual field). For participant #1 and #2, individual paired ttests were used to compare their overall number of targets on the left side between weeks 1-2
and weeks 3-4. Left side targets at weeks 1-2 versus weeks 3-4 for participant #1 (M = 11.70,
40

SD = 10.13 versus M = 40.80, SD = 6.44) was significant on Mest analysis (t(9) = 8.66, p <
.001). Likewise, left side targets at weeks 1-2 versus weeks 3-4 for participant #2 (M = 7.50,
SD = 9.59 versus M = 25.20, SD = 10.96) was significant on Mest analysis (t(9) = 7.42, p <
.001).

Homework booklet.
Each participant followed the instructions to complete paper and pencil VS/VM
activities for 2 hours over the weekend. Compliance to this component of the program was
100%. With the help of the caregivers, the participants were able to keep a log of their hours,
thus making it possible to confirm completion and check for accuracy at the start of each
week. On the rare occasion that a task was incorrectly completed (occurring only a few times
collectively), the incorrect pages were added to the booklets on the following weekend and
the patient was asked to try again. There was no instance in which pages were returned for a
third time.

Discussion
The goal of this research was to determine if VS/VM training is an effective
intervention tool for improving acute post-stroke cognitive recovery. The intervention for the
experimental group was delivered as intended. Intervention occurred for 1 hour/day, 5
days/week for 4 weeks and involved a number of VS/VM training techniques such as visual
scanning, video-gaming, visual imagery, complex block construction and weekend
maintenance homework assignments. As hypothesized, the results of this randomized control
trial showed that the incorporation of cognitive training into conventional rehabilitative
treatment was more effective in improving cognition, function and mood than conventional
treatment alone. Control patients, receiving only standard rehabilitative treatment, were
41

consistently outperformed by the intervention group who engaged in the VS/VM training
procedure. Results showed that the experimental group performed better on all the following
cognitive domains: global, visuoconstructive, language, visual memory, verbal memory,
executive function, processing speed, depression, and activities of daily living. Although it
was readily apparent that the participant groups were different at post-intervention, it is also
important to evaluate and understand the process of change occurring within each group.

Participant Improvements Within Groups
Cognitive improvements occurred in both groups throughout the 4-week study period.
The intervention group made significant improvements in all domains and the controls made
selective improvements in short term memory and processing speed. Such changes are to be
expected, given that approximately 16% of stroke patients with cognitive impairment
spontaneously improve (Teasell et al., 2006). Spontaneous recovery is learning due to
functional and structural reorganization in the brain that naturally occurs weeks to months
following stroke (Saposnik et al., 2010; Teasell et al., 2006). Based on the values associated
with spontaneous recovery (i.e., 16%) and the number of participants in this study (i.e., 18),
one could expect this phenomenon to possibly affect only 2 or 3 of these individuals.
Conversely, the results here demonstrate significant improvements, both within
experimental group and between experimental and control group, that far exceeded 2 to 3
individuals, making spontaneous recovery an unlikely explanation. Even if spontaneous
recovery is thought to be a significant factor involved in recovery, then it must be equally
applied to both groups with comparable pre-treatment baseline. However, the fact that the
magnitude of improvements made by the intervention group were significantly greater than
the improvements made by the control group provides solid evidence to argue that there was
42

a specific intervention effect that could not be attributed to spontaneous recovery. Also, the
significant difference in the magnitude of improvements seen between the intervention and
control groups informs us that without cognitive training, patients are not reaching their full
potential, even if progress is observed. For example, although control patients showed
improvement on short term memory and processing speed, these improvements paled in
comparison to the improvements seen in the intervention group. However, because these
improvements were common in both groups, it seems reasonable to speculate that these
domains are the most responsive to rehabilitation efforts. This speculation originates from
clinical research showing that memory is relatively preserved in stroke patients (Kalaria &
Ballard, 2001), thus possibly making standard care somewhat successful for patient
improvements. However, the present study showed that these improvements were nowhere
near the level of improvement observed in patients that engaged in the VS/VM cognitive
training procedure.

Intervention Improvements on Trained Tasks
Increased training ability was observed on all tasks throughout the course of the
intervention. Experimental participants demonstrated improvements in Pac-Man high score,
duration of Pac-Man play and block design construction. Enhanced performance on training
can be taken as proof of learning, which suggests that the generation of new neuronal
connections was likely occurring (Belichenko, Mattsson, & Johansson, 2001; Greenwood &
Parasuraman, 2010; Hadjiev & Mineva, 2008; Mazmanian, Kreutzer, Devany, & Martin,
1993). Furthermore, the program showed promise in alleviating symptoms of neglect, as two
patients with severe left-sided neglect showed significant improvement on the Mesulam
cancellation tasks at program conclusion. Additional anecdotal evidence for alleviating
43

symptoms of neglect was evident in the participants' ability to correctly complete the
activities in their homework book as this involves tasks that heavily relied on intact scanning
abilities.
It is challenging to untangle the unique contribution that motor imagery added to the
overall outcome of the study. Research examining the neurophysiological bases of motor
imagery is what provided the theoretical justification to incorporate this form of training into
the program. Evidence from a number of sources has been used to suggest that motor
imagery involves the same neural mechanisms as are involved in the preparation and
planning of actual movements (Decety & Ingvar, 1990; Decety, 1996; Feltz & Landers,
1983; McCarthy et al., 2002; Richards et al., 1993; Tatemichi et al., 1994; Tyszka, Grafton,
Chew, Woods, & Colletti, 1994). On this basis, it can be deduced that mental practice of
motor skills may have helped participants improve at transitioning between sensory
preparation and motor action. This refinement in sensory-motor transition may have provided
a beneficial effect on the actual performance of motor activity such as playing Pac-Man. A
final argument for the use of motor imagery for stroke rehabilitation is the evident free time
that patients spend in non-rehabilitative activities and the need to design rehabilitation tasks
that they can perform safely alone (Bernhardt, Chan, Nicola, & Collier, 2007). Motor
imagery could provide a means for allowing patients to spend more time in rehabilitationrelated activity.

Unsuccessful Intervention Outcomes
Using a MANOVA to evaluate post-intervention group differences, there were non­
significant differences for Line Orientation, Digit Forward, Digit Backward, Digit Symbol,
Trails A and Trails B. However, an evaluation of these tests using ANOVA showed that
44

Digit Backward, Digit Symbol and Trails B were significantly different. Therefore, at postintervention only two domains, visuospatial (Line Orientation) and attention (Digit Forward
and Trails A), were consistently not significantly different between the groups. One
explanation for these non-significant group differences can be suggested by taking an indepth look at the properties of the tests used. That is, the visuospatial and attention tests that
were used were either extremely sensitive to right hemisphere damage (i.e., Line Orientation)
or not sensitive enough (i.e., Digit Forward and Trails A), making it difficult to detect
between group differences. A test that is non-sensitive to right hemisphere functioning may
require more than 4 weeks of training to show improvement whereas tests that are very
sensitive may not be able to detect true changes between participant group. In any case, on
the basis of the observed effect sizes for Line Orientation, Digit Forward, Digit Backward,
Digit Symbol, Trails A and Trails B, significant MANOVA post-intervention differences
would nonetheless be found with a sample size of 60, 32, 22, 20, 60,24 (respectively).
Therefore, these few non-significant results, which would be better powered with the accrual
of subjects into the program, are marginal in light of the vast improvements produced in a
short period of 4 weeks.

Possible Mechanisms for Post-Intervention Success
It is important to explore the theoretical underpinnings that may explain why VS/VM
training was so effective. Cognitive training is an example of a behaviour that promotes
neuronal activity and results in improved cognitive function (Greenwood & Parasuraman,
2010). There are 3 mechanism that can be highlighted that may have played a role in the
success of the intervention: (1) brain derived neurotrophic factors (BDNF), (2) cortical
reorganization and (3) synaptogenesis.
45

Brain derived neurotrophic factors. The success of cognitive intervention may be
attributable to neurotrophic enhancement of BDNF. BDNF is a protein produced in the
subgranular zone of the hippocampus that promotes neuron growth and prevents neuronal
apoptosis (Durany et al., 2000; Zhang et al., 2002). The hippocampus is essential for learning
and memory and thus enhancement of the hippocampus is key for overall improved cognitive
performance. On the basis of other studies, intervention activities most likely facilitated
increased BDNF production, fostering greater post-stroke cognitive recovery by enhancing
neuron survival and axon regeneration. Researchers have reported that when learning occurs,
as was demonstrated by the intervention participants, the expression of BDNF is
subsequently enhanced. For example, studies on rats have demonstrated that compared to
controls, rats that are trained on VS radial mazes show significantly elevated BDNF protein
levels in the hippocampus (Hall, Thomas, & Everitt, 2000; Kesslak, So, Choi, Cotman, &
Gomez-Pinilla, 1998). Furthermore, increases in the expression of BDNF are reported to
occur immediately after VS maze learning, and are thought to be responsible for superior VS
retention seen in the trained rats compared to their control counterparts (Ma, Wang, Wu,
Wei, & Lee, 1998). Upregulation of BDNF after VS training has been replicated in monkeys
(Tokuyama, Okuno, Hashimoto, Xin, & Miyashita, 2000). Furthermore, the findings from
monkeys have been expanded to show that VM training (i.e., learning how to use tools) also
results in BDNF surges in several areas of the cortex, such as the temporal and parietal lobe
(Ishibashi et al., 2002). VS learning is believed to directly increase the signalling between
BDNF and it's receptor Tyrosine Kinase B (TrkB), resulting in receptor autophosphorylation
and subsequent activation of downstream signal transduction pathways (Yamada, Mizuno, &
Nabeshima, 2002). In fact, the connection between VS learning and TrkB phosphorylation is
46

so tight that they are reported to move in parallel without any changes in the phosphorylation
of closely related receptors, TrkA or TrkC (Mizuno et al., 2003). Furthermore, the use of
antisense oligonucleotide to block the expression of BDNF results in impaired spatial
performance and the complete elimination of TrkB phosphorylation (Mizuno et al., 2003).
Collectively, these finding supports the link between VS learning and the activity of BDNF
pathways. The presence of BDNF can then enhance cognitive abilities through its intricate
role in synaptic strength, learning and memory (Yamada, Mizuno, & Nabeshima, 2002).
Further research into the neurotrophic mechanism of cognitive training is warranted (and
necessary) to support the involvement of BDNF.
Antidepressant effects were another observed benefit of specialized training in the
experimental group. Evidence of why this may have occurred could also be linked to an
increase in BDNF. Research has shown that there is an inverse link between BDNF and
depression (Durany et al., 2000; Schmidt & Duman, 2010). One of the findings in this project
that fits most tightly with the notion of BDNF was the rate of depression observed at postintervention. It was shown that the intervention group was significantly less depressed than
the controls at post-intervention. Thus, the antidepressant effect post intervention may have
been a reflection of BDNF increases that may have occurred as described above.
Furthermore, the presence of BDNF has been linked to adult neuroplasticity (Large et
al., 1986; Yan et al., 1997) which is a convincing explanation for why the benefits of a
specific VS/VM training program generalized to several cognitive domains that were not a
focus of intervention (e.g., executive and functional activities). Such a generalizing influence,
particularly to executive and functional abilities, has significant implications regarding the
prevention of vascular dementia because impairments in these two domains are considered its
47

hallmarks (Levin, 2011). Our ability to rapidly intervene on the leading symptoms of
vascular dementia could mean the difference between the development of this disease or its
prevention.
Aside from hippocampal and parietal expression of BDNF, it is known that astrocytes
are also a source of BDNF (Dougherty, Dreyfus, & Black, 2000). Astrocytes play an
important protective role in regulating the blood brain barrier (Abbott, Ronnback, &
Hansson, 2006) and an important healing role in CNS injury by phagocytising cellular debris,
and thus after a stroke episode, they are intensely recruited to the site of injury (White &
Jakeman, 2008). Therefore strategies that potentially increase levels of astrocyte BDNF (such
as the current project) may thereby dramatically elevate BDNF to the injured region,
simultaneously harnessing the beneficial roles of both astrocytes and BDNF that are needed
to foster neuronal survival and regrowth.

Cortical reorganization. Apart from neurotrophic explanations, the success of
cognitive intervention may also be attributable to enhancement of cortical neuroplasticity.
Neuroplasticity refers to changes at the neuronal level that can be stimulated by experience
(Chen, Rex, Sanaiha, Lynch, & Gall, 2010) and it is thought to enable the lesioned brain to
reorganize itself after damage (Wingfield & Grossman, 2006). Evidence that cortical
reorganization occurs following stroke is demonstrated when remote neurons assist or take
over function (Ro et al., 2006; Taub, Uswatte, & Elbert, 2002). For example, studies utilizing
fMRI to address post-stroke neuroplasticity and cognitive performance show that intact
cognitive performance is associated with compensatory activation in ipsilateral (Cao,
Vikingstad, George, Johnson, & Welch, 1999; Feydy et al., 2002) and homologous
contralateral regions (Carey et al., 2002; Lee et al., 2009). Therefore, there is a need for
48

compensatory processes in stroke brains, such that more cortical resources are needed to
carry out a task that fewer regions can do in normal brains.
VS/VM cognitive training may have allowed the intervention group to access the
additional resources necessary for intact performance (i.e., training induced functional
reorganization) whereas the control group may not have received this opportunity. The
specific plastic response that would be expected to occur in response to the current VS/VM
(i.e., parietal) training program would be increased compensatory activation in premotor
regions. Compensatory prefrontal activation would be expected because of the dense
projections from parietal to prefrontal regions. For example, parietal areas 5 and 7 are known
to project to supplementary premotor areas (Kandel et al., 2000). The reason for such
interconnectedness between the parietal and frontal region is because the parietal association
area is critical for integrating different sensory modalities which must be directed and used
by prefrontal regions to plan motor behaviour. Research has also shown that learning is
associated with increases in premotor activity even within a single session of practice
(Weissman, Woldorff, Hazlett, & Mangun, 2002), thus making a 4 week training program
ample time to induce the functional reorganization that I have proposed here.

Synaptogenesis. A final factor that may have played a role in the success of this
cognitive intervention may be the formation of new neuronal connections via synaptogenesis.
Recent evidence shows that the formations and remodeling of dendritic spines are induced by
cognitive training (Greenwood & Parasuraman, 2010). The presence of new dendrites is a
meaningful finding because they are thought to be one of the key players in neurogenesis,
with the potential to allow for structural plasticity (Crick, 1982; Geinisman, Morrell, &
deToledo-Morrell, 1989), and compensation of functional losses that are associated with
49

stroke. For example, studies using rat models of cerebral ischemia have shown that poststroke exposure to enriched environments can increase synaptogenesis (Belichenko et al.,
2001) and can significantly improve functional outcomes (Grabowski, Sorensen, Mattsson,
Zimmer, & Johansson, 1995). Synaptogenesis following exposure to enriched environments
has also been reported to occur even weeks after stroke (Johansson, 1996). Furthermore, such
increases in dendritic spines have been confirmed as "active" members in the cortical
network, expressing postsynaptic potentials and spontaneous action potentials (Kokoeva,
Yin, & Flier, 2005; Song, Stevens, & Gage, 2002) and receiving inputs from the established
neuronal network (Toni et al., 2008). Synaptic plasticity would be expected in our
intervention participants because when learning occurs, the process of synaptogenesis is
initiated (Greenwood & Parasuraman, 2010) and then the connection between newly formed
synapses are consolidated by long term potentiation (LTP). LTP is a long-lasting increase in
synaptic efficacy that is induced by learning and facilitates the wiring of neurons (Whitlock,
Heynen, Shuler, & Bear, 2006). Accordingly, the following is a proposed model for the role
of cognitive training in synaptogenesis and LTP: newly formed synapses between cells that
are believed to be induced by intervention learning would not yet be expected to have
meaningful connections and would mainly contain a few NMDA (N-methyl D-aspartate) and
AMPA (a-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid) glutamatergic receptors
(Richards, Clark, & Clarke, 2007). However, daily practice of the training activities may
have helped newly liberated synapses to coincide (i.e., fire together) and in turn strengthen
(i.e., wire together). When the new pre-synaptic neuron releases glutamate that coincides
with the firing of a post-synaptic neuron, its NMDA receptors are activated via calcium
(Ca2+) entering the cell (Muller, Nikonenko, Jourdain, & Alberi, 2002). The resulting
50

increase in Ca2+ influx triggers a cascade of events that eventually leads to an increase in the
number of AMPA receptors inserted into the membrane (Richards et al., 2007). As a result,
the next time this pre-synaptic neuron releases glutamate, the excitatory post-synaptic
potentials will be bigger; and thus LTP is established, cortical synaptic activity is amplified
and cognitive abilities improve.

Clinical Relevance
The findings from this study have important clinical relevance for informing and
shaping stroke rehabilitation towards the implementation of cognitive exercise into routine
practice. Importantly, cognitive intervention programs can be implemented safely among
individuals in the acute stroke phase without negative effects on participation in conventional
stroke rehabilitation, as evidenced by the success of this program. Furthermore, the fact that
there were no problems with participants completing all components of the program
(including the homework booklet), and that there were no dropouts, provides a good
benchmark for the feasibility of such a program.
Effect sizes are an important tool that can supplement standard statistical testing and
can facilitate the interpretation of research findings in clinical setting. An effect size
represents the magnitude of change between two groups. It tells us how meaningful
differences are between groups (Zakzanis, 2001). An effect size of .5 has been outlined in the
literature as the minimal threshold level at which research findings begin to reach clinical
significance (Donkervoort et al., 2001). The effect sizes that accompanied our findings far
exceed this criterion, indicating that there were strong meaningful differences between the
groups. Furthermore, the fact that the cognitive intervention therapy was only a subsection of
the total rehabilitation process, yet still produced such large effect sizes, makes an even
51

stronger case for its efficacy. The clinically important findings observed in this study are
relevant to both physicians and patients. Physicians can interpret the study's clinically
important outcomes as a therapeutic effect or a meaningful change in the prognosis of stroke.
As for the patients, a clinically important change would represent a meaningful reduction in
their symptoms or improvement in post-stroke function that would lead to improved quality
of life.

Limitations
Aside from test sensitivity determinants that may have contributed to the non­
significant post-intervention findings in visuospatial and attention abilities, it is important to
note that the effects of location and severity of brain damage are also relevant to
understanding the dynamic process occurring in acute stroke recovery. Visuospatial and
attention abilities have been documented as the most persistent cognitive impairments arising
from vascular etiology (Graham et al., 2004) and imaging analysis may be able to indicate if
these intervention outcomes are related to severity and location of stroke. Imaging analysis
was beyond the scope of the current project, but future research looking at the neurological
factors in relation to intervention outcomes would enhance our understanding of cognitive
rehabilitation and allow us to develop more effective cognitive intervention programs.
It is also important to note that the use of change scores does not control for the
possibility that change scores may be correlated with baseline values, thus complicating the
interpretation of results. Some researchers have suggested alternative approaches of analysis
(e.g., Analysis of Covariance) (Vickers & Altman, 2001) but the general caveat is having a
large enough sample size. Although the sample size of the current project did not afford such
alternative analysis, similar studies involving randomized control trials with a restricted
52

sample provides precedence that the use of change scores is appropriate in this scenario
(Altman & Bland, 1999; Donkervoort et al., 2001).
Methodological limitations of this study can be identified but they should be
evaluated under the lens that this was a pilot project. For example, this study examined the
beneficial outcome of incorporating VS/VM training into standard stroke therapy against
standard therapy alone as the control group. Accordingly, it can be argued that a drawback to
this study design is that the control group did not receive an equivalent amount of time for
regular activity as the intervention group. An optimal solution would be for the control group
to receive some additional but non-active/sham treatment that is equivalent in duration to the
experimental intervention. Another methodological limitation that should be addressed in
future projects is that the researcher who did the pre- and post-intervention testing was not
blind to the participants' group assignment.

Conclusion
There is no universally accepted cognitive treatment for stroke. The value of
rehabilitation aimed at assisting post-stroke cognitive recovery is becoming well recognized,
but strategies designed to address cognitive dysfunction is by comparison poorly developed.
This project constituted a step towards understanding the potential benefits of a focused
VS/VM training program to affect cognitive change and provided evidence that engaging in
early cognitive intervention influences faster recovery through improved cognitive, mood and
functional abilities. To this end, the primary objectives of this study were met.
Cognitive training programs, such as the one piloted here, may assist in broadening
the scope of rehabilitation beyond a physical focus and may assist in addressing the present
gaps in rehabilitation service, brain training. Ultimately, the ability to treat stroke-related
53

cognitive dysfunction may translate into a reduction in the occurrence of post-stroke
cognitive impairment, reduced burden on health care and a greater quality of life for poststroke individuals.

Table 1.
Patient Inclusion Criteria

Criteria

Description

Demographic

Sufficient English language skill for psychological tests.

Psychosocial

Availability of a caregiver knowledgeable about the participant's past
and recent medical history.

Stroke

Stroke as indicated by primary physician, with neuroimaging evidence
of symptomatic cerebral infarction.
Medically stable/managed (e.g., hypertension, blood lipid levels).

55

Table 2.
Patient Exclusion Criteria

Criteria
Psychological

Description
Moderately severe dementia defined by a Mini-Mental State score of < 17.
Severe receptive/expressive aphasia, as measured by a score of < 10 on the
Boston Diagnostic Aphasia Examination.

Medical

Previous/current medical/psychiatric conditions (e.g., epilepsy, dementia,
brain tumor, traumatic brain injury or substance abuse).
Metabolic or endocrine disorders.

Medication

Recent use of cognitive enhancing agents (e.g., cholinesterase inhibitors).
Current or past history of treatment with psychoactive medications.

56

Table 3.
Frequency Distribution for Intervention and Control Group on Stroke Characteristics

Intervention
(n = 9)
5

Control
( n = 9)
4

Right Frontal

1

1

Right Cerebellar

1

0

Right Unspecified

3

3

4

5

Left Frontal

1

1

Left Unspecified

3

4

Hemorrhage

1

2

Infarction

8

7

Previous stroke

0

1

Hemiplegia/hemiparesis

9

9

Characteristic
Total Right CVA

Total Left CVA

Type of stroke

Note. CVA = Cerebrovascular Accident

57

Table 4.
Pre-treatment Neuropsychological Comparability of the Intervention and Control Groups

Neuropsychological Test
Global/Screening
MMSE
MOCA
BDAE
Language
Boston Naming
Visuospatial/V isuoconstructive
Line Orientation
Rey Copy
Clock
Visuospatial Memory
Rey Delay
Verbal Memory
HVLT
HVLT Delay
Working Memory
Digit Forward
Digit Backward
Processing Speed
Digit Symbol
Trails A
Executive Functioning
Animal Naming Test
Trails B
Neuropsychiatric/Behavioural
GDS
Apathy Evaluation Scale
Activities of Daily Living
IQCODE
Barthel
DAD
*p < .05

Intervention
M (SD)

Pre-treatment
Control
M (SD)

F

df

20.67 (2.35)
17.11(2.57)
12.89(1.27)

19.00 (3.64)
16.11(3.33)
12.33 (0.87)

1.33 1,16
0.51 1,16
1.18 1,16

38.89 (7.08)

41.11 (5.30)

0.57 1,16

6.33 (4.85)
10.67 (5.10)
5.22 (2.49)

7.00 (4.89)
13.11 (7.03)
4.00 (2.40)

0.08 1,16
0.71 1,16
1.13 1,16

1.67 (3.31)

3.22 (4.58)

0.68 1,16

11.22 (2.33)
2.56(1.88)

10.22 (4.38)
2.00 (2.06)

0.37 1,16
0.36 1,16

5.11 (1.27)
4.00(1.12)

5.44(1.13)
3.00(1.80)

0.35 1,16
2.00 1,16

7.33 (5.39)
145.00(101.00)

9.88 (9.40)
136.11 (100.62)

0.50 1,16
0.04 1,16

10.56(1.42)
257.22 (65.72)

10.78 (1.64)
273.67 (64.14)

0.10 1,16
0.29 1,16

26.67 (9.19)
20.89 (9.70)

23.56 (8.73)
25.11 (4.62)

61.00 (5.33)

64.56 (6.10)
39.44 (8.08)
17.11 (4.07)

0.54 1,16
1.39 1,16
1,16
1.73 1,16
0.56 1,16
0.24 1,16

34.44 (18.45)

18.33 (6.34)

58

Table 5.
Post-treatment Neuropsychological Comparability of the Intervention and Control Groups

Neuropsychological Test
Global/Screening
MMSE**
MOCA*
BDAE*
Language
Boston Naming**
Visuospatial/V isuoconstructive
Line Orientation
Rey Copy**
Clock**
Visuospatial Memory
Rey Delay*
Verbal Memory
HVLT**
HVLT Delay**
Working Memory
Digit Forward
Digit Backward
Processing Speed
Digit Symbol
Trails A
Executive Functioning
Animal Naming**
Trails B
Neuropsychiatric/Behavioural
GDS*
Apathy Evaluation Scale**
Activities of Daily Living
IQCODE**
DAD**
* p < .05. **p<.01.

Post-treatment
Intervention
Control
M (SD)
M (SD)

F

df

Cohen
d

26.00 (2.45)
21.78 (2.99)
14.11(0.93)

19.22 (4.87)
15.89 (6.11)
12.67 (1.22)

13.93 1,16
6.74 1,16
7.95 1,16

1.76
1.22
1.33

52.22 (5.42)

42.22(4.18)

19.19 1,16

2.07

13.11 (6.33)
24.33 (7.21)
8.88 (1.96)

10.44 (7.94)
14.22 (5.76)
4.44 (2.92)

0.62 1,16
8.26 1,16
14.35 1,16

0.47
1.55
0.98

9.33 (5.00)

4.44 (4.85)

4.43

1,16

0.99

18.67 (4.09)
5.11(1.76)

11.78(4.82)
2.33 (2.29)

10.69 1,16
8.31 1,16

1.54
1.36

6.67 (1.41)
4.89 (1.45)

5.67 (1.66)
3.22 (1.92)

1.90
4.31

1,16
1,16

0.65
0.98

21.44 (9.57)
109.11(90.81)

12.11(9.66)
133.78(101.60)

4.24
0.30

1,16
1,16

0.97
0.46

14.56(1.94)
201.56 (77.36)

11.67(1.80)
270.89 (66.31)

10.69 1,16
4.17 1,16

1.54
0.96

11.67 (5.43)
11.11 (6.33)

20.67 (7.14)
23.44 (4.67)

7.16 1,16
22.12 1,16

1.26
2.22

51.11 (6.15)
28.89(11.01)

65.22 (8.74)
16.56 (5.15)

15.68 1,16
9.27 1,16

1.87
1.43

59

Table 6.
Post-Treatment Cognitive Changes Within the Intervention Group

Outcome Measure

Pre-treatment
Mean (SD)

Post-treatment
Mean (SD)

F

df

Cohen
d

MMSE**

20.67 (2.35)

26.00 (2.45)

85.33

1,8

2.22

Clock**

5.22 (2.49)

8.88 (1.96)

17.93

1.8

1.63

MOCA**

17.11 (2.57)

21.78 (2.99)

31.34

1,8

1.68

BDAE*

12.89(1.27)

14.11 (0.93)

6.91

1,8

1.10

Boston**

38.89 (7.08)

52.22 (5.42)

22.54

1.8

2.11

Animals**

10.56(1.42)

14.56(1.94)

25.04

1,8

2.35

Rey Copy**

10.67 (5.10)

24.33 (7.21)

76.41

1,8

2.18

Rey Delay**

1.67 (3.31)

9.33 (5.00)

54.23

1.8

1.80

Line Orientation*

6.33 (4.85)

13.11 (6.33)

6.93

1,8

1.45

HVLT**

11.22(2.33)

18.67 (4.09)

76.41

1,8

2.23

HVLT Delay**

2.56(1.88)

5.11 (1.76)

21.16

1.8

1.40

Digit Forward**

5.11 (1.27)

6.67 (1.41)

14.26

1,8

1.16

Digit Backward**

4.00(1.12)

4.89(1.45)

11.64

1,8

0.68

Digit Symbol**

7.33 (5.39)

21.44 (9.57)

34.39

1.8

1.81

Trails A*

145.00(101.00)

109.11 (90.81)

6.03

1,8

0.40

Trails B*

257.22 (65.72)

201.56 (77.36)

5.51

1,8

0.78

GDS**

26.67 (9.19)

11.67(5.43)

24.70

1.8

1.98

Apathy**

20.89 (9.70)

11.11 (6.33)

26.32

1,8

1.19

IQCODE**

61.00 (5.33)

51.11 (6.15)

24.37

1,8

1.71

Barthel**

34.44 (18.45)

61.67 (24.75)

35.44

1.8

1.25

DAD*

18.33 (6.34)

28.89(11.01)

9.41

1,8

1.17

* p < .05. ** p < .01.
60

Table 7.
Post-Treatment Cognitive Changes Within the Control Group

Outcome Measure

Pre-treatment
Mean (SD)

Post-treatment
Mean (SD)

F

df

Cohen
d

MMSE

19.00 (3.64)

19.22 (4.87)

0.11

1,8

0.08

Clock

4.00 (2.40)

4.44 (2.92)

1.73

1,8

0.16

MOCA

15.89 (3.33)

16.11 (6.11)

0.04

1,8

0.04

BDAE

12.33 (0.87)

12.67 (1.22)

2.00

1,8

0.32

Boston

41.11 (5.30)

42.22(4.18)

2.17

1,8

0.23

Animals**

10.78(1.64)

11.67(1.80)

19.69

1,8

0.51

Rey Copy

13.11 (7.03)

14.22 (5.76)

1.13

1,8

0.17

Rey Delay

3.22 (4.58)

4.44 (4.85)

1.56

1,8

0.25

Line Orientation

7.00 (4.89)

10.44 (7.94)

5.61

1,8

0.52

HVLT**

10.22 (4.38)

11.78(4.82)

17.04

1,8

0.33

HVLT Delay

2.00 (2.06)

2.33 (2.29)

4.00

1,8

0.15

Digit Forward

5.44(1.13)

5.67 (1.66)

1.00

1,8

0.16

Digit Backward

3.00(1.80)

3.22 (1.92)

1.00

1,8

0.11

Digit Symbol**

9.88 (9.40)

12.11(9.66)

16.50

1,8

0.23

Trails A

136.11(100.62)

133.78(101.60)

3.92

1,8

0.02

Trails B

273.67 (64.14)

270.89 (66.31)

3.87

1,8

0.40

GDS

23.56 (8.73)

20.67 (7.14)

5.26

1,8

0.36

Apathy*

25.11 (4.62)

23.44 (4.67)

6.67

1,8

0.35

IQCODE

64.56 (6.10)

65.22 (8.74)

0.27

1,8

0.08

Barthel**

39.44 (8.08)

42.78 (7.95)

25.00

1,8

0.41

DAD

17.11 (4.07)

16.56 (5.15)

0.14

1,8

0.11

* p< .05. ** p< .01.
61

Table 8.
Improvement Scores for Test in which Both Groups Showed Improvements
Change from Baseline
Intervention
Mean (SD)

Control
Mean (SD)

Difference Between Group
Mean (95% CI)
p

Animals

4.00 (2.39)

.89 (.60)

3.11 (1.36,4.86)

.002

HVLT

7.44 (2.55)

1.56(1.13)

5.89 (3.91,7.86)

.001

Digit Symbol

14.11 (7.22)

2.22(1.64)

11.89 (6.66, 17.12)

.001

Apathy

-9.78 (5.72)

-1.67(1.94)

-8.11 (-12.38, -3.86)

.001

Barthel

27.22 (13.72)

8.33 (5.00)

18.89 (8.57, 29.21)

.001

Assessed for
eligibility (n = 18)

18 randomly
allocated

9 allocated to
experimental group

9 allocated to
control group

Pre-treatment
Outcome measures
(n = 9)

Pre-treatment
Outcome measures
(n = 9)

Intervention:
Conventional therapy
with VS/VM training
fn = 9)

Control:
Conventional therapy
alone
(n = 9)

Post-treatment
Outcome measures
(n = 9)

Post-treatment
Outcome measures
(n = 9)

Figure 1. Study participant flow chart of enrollment and randomization

Post-Intervention Group Differences

x/x

• Experimental
• Control
MMSE

Boston REY Copy
Naming

HVLT

Digit
Backwaid

Dgit
Symbol

DAD

NeuropsychologicalTe st

Figure 2. Comparing neuropsychological changes between groups from preintervention to post-intervention. Error bars represent standards error of the
measurement. Post-intervention differences between the groups are seen in each
neuropsychological domain. * p < .05. ** p < .01.

64

Comparison of Within Group Improvements
60
50
40

1 Experimental

30

2 Control

20
10

0

li
1

MMSE

2

M
1

2

Boston Naming

1

2

ReyCopy

1

• Pre-Intervention
* Post-Intervention

2

Digit Symbol

Neuropsychological Test
Figure 3. Post-intervention differences between the groups in neuropsychological
domains. Error bars represent standard error of the mean. Experimental group
showed cognitive improvement whereas the control remained the same. *** p < .001.

65

Magnitude of Change from Baseline Between Groups
35
30

<u 25
3
0>

20

& 15

9

LJL_

•Experimental

—

u 10
5

0

• Control

***

Animals

HVLT

Digit Symbol

Apathy

Brnlhel

Neuropsychological Tests

Figure 4. Comparing magnitude of neuropsychological change between groups from
pre-intervention to post-intervention. Error bars represent standard error of the mean.
Experimental group improved significantly more than the control group. * p < .05,
**p<.01.

66

Experimental Group Pac-Man High Score
12000
10000

• Weeks 1-2
• Weeks 3-4

3

4
5
Participant

Figure 5. Improvements in Pac-man high score from initial weeks to final weeks of
training. Error bars represent standard error of the mean. Each participant
significantly increased their high-score from initial weeks to final weeks of training.
* p < .05, ** p < .01.

67

Experimental Group Average Length of Play on Pac-Man
70
60
50
72

"g

40

£

30

o

CO

**
**

"Weeks 1-2
• Weeks 3-4

*

liJii

20

10

0
1

2

3

4

5

6

7

8

9

Participant

Figure 6. Participant improvements in Pac-man duration of play from initial weeks to
final weeks of training. Error bars represent standard error of the mean. Each
participant significantly increased duration of time played from weeks 1-2 to weeks
3-4. * p < .05, ** p < .01.

68

Experimental Group Block Design Completion Time

• Weeks 1-2
a Weeks 3-4

Participant

Figure 7. Participant improvements in block design duration of time from initial
weeks to final weeks. Error bars represent standard error of the mean. Each
participant showed faster assembly time from weeks 1-2 to weeks 3-4. * p < .05,
** p< .01.

69

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Appendix

111

Draw your way through this maze

112

If you were to turn this image 90 degreesclockwise, how would it look?

The two following pictures are not alike.
Find all differences between the left and right pictures.
Circle the differences on the right picture.

114