The effects of video-game training on broad cognitive transfer in multiple sclerosis: A pilot randomized controlled trial.

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The effects of video-game training on broad cognitive transfer in multiple sclerosis: A pilot randomized controlled trial a

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Alisha Janssen , Aaron Boster , HyunKyu Lee , Beth Patterson & Ruchika Shaurya a

Prakash a

Department of Psychology, The Ohio State University, Columbus, OH, USA

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Department of Neurology, The Ohio State University Medical Center, Columbus, OH, USA c

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Brain Plasticity Institute, San Francisco, CA, USA Published online: 07 Apr 2015.

To cite this article: Alisha Janssen, Aaron Boster, HyunKyu Lee, Beth Patterson & Ruchika Shaurya Prakash (2015) The effects of video-game training on broad cognitive transfer in multiple sclerosis: A pilot randomized controlled trial, Journal of Clinical and Experimental Neuropsychology, 37:3, 285-302, DOI: 10.1080/13803395.2015.1009366 To link to this article: http://dx.doi.org/10.1080/13803395.2015.1009366

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Journal of Clinical and Experimental Neuropsychology, 2015 Vol. 37, No. 3, 285–302, http://dx.doi.org/10.1080/13803395.2015.1009366

The effects of video-game training on broad cognitive transfer in multiple sclerosis: A pilot randomized controlled trial Alisha Janssen1, Aaron Boster2, HyunKyu Lee3, Beth Patterson1, and Ruchika Shaurya Prakash1 1

Department of Psychology, The Ohio State University, Columbus, OH, USA Department of Neurology, The Ohio State University Medical Center, Columbus, OH, USA 3 Brain Plasticity Institute, San Francisco, CA, USA

Journal of Clinical and Experimental Neuropsychology 2015.37:285-302.

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(Received 7 July 2014; accepted 14 January 2015) Background: Multiple sclerosis (MS) is a neurodegenerative disease of the central nervous system that results in diffuse nerve damage and associated physical and cognitive impairments. Of the few comprehensive rehabilitation options that exist for populations with lower baseline cognitive functioning, those that have been successful at eliciting broad cognitive improvements have focused on a multimodal training approach, emphasizing complex cognitive processing that utilizes multiple domains simultaneously. Method: The current study sought to determine the feasibility of an 8-week, hybrid-variable priority training (HVT) program, with a secondary aim to assess the success of this training paradigm at eliciting broad cognitive transfer effects. Capitalizing on the multimodal training modalities offered by the Space Fortress platform, we compared the HVT strategy-based intervention with a waitlist control group, to primarily assess skill acquisition and secondarily determine presence of cognitive transfer. Twenty-eight participants met inclusionary criteria for the study and were randomized to either training or waitlist control groups. To assess broad transfer effects, a battery of neuropsychological tests was administered pre- and post-intervention. Results: The results indicated an overall improvement in skill acquisition and evidence for the feasibility of the intervention, but a lack of broad transfer to tasks of cognitive functioning. Participants in the training group, however, did show improvements on a measure of spatial short-term memory. Conclusions: The current investigation provided support for the feasibility of a multimodal training approach, using the HVT strategy, within the MS population, but lacked broad transfer to multiple domains of cognitive functioning. Future improvements to obtain greater cognitive transfer efficacy would include a larger sample size, a longer course of training to evoke greater game score improvement, the inclusion of only cognitively impaired individuals, and integration of subjective measures of improvement in addition to objective tests of cognitive performance. Keywords: Multiple sclerosis; Cognitive training; Space Fortress; Randomized control trial; Skill acquisition.

Relapsing-remitting multiple sclerosis (RRMS) is one of the most frequently diagnosed neurodegenerative disease afflicting adults during the prime years of their societal contribution. The disease

course is characterized by a heterogeneous profile of symptoms, including significant cognitive decline in approximately 50% of diagnosed individuals (Fischer et al., 2014). Decrements in

We would like to thank the members of the Clinical Neuroscience Laboratory for their tireless efforts towards the collection, organization, and analysis of these data. Those individuals involved include Frank Dossman, Danielle Rickert, Kimberley Rolley, Basam Rashwan, Angeline De Leon, Brian Shannon, Sarah Murtha, Matt Grover, Aishwarya Balasubramaniyan, Allison Londeree, and Taylor Wong. We would also like to thank the members of the department that contributed to the research design and analysis of this project, Charles Emery and Dirk Bernhardt-Walther. No potential conflict of interest was reported by the author(s). Address correspondence to: Ruchika Shaurya Prakash, Department of Psychology, The Ohio State University, 139 Psychology Building, 1835 Neil Avenue, Columbus, OH 43210, USA (E-mail: [email protected]).

© 2015 Taylor & Francis


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cognitive functioning significantly predict overall quality of life within this population (Amato, Ponziani, Siracusa, & Sorbi, 2001; Cutajar et al., 2000; Gold, Schulz, Mönch, Schulz, & Heesen, 2003). While primary disease modifying treatments slow the accumulation of brain lesions associated with cognitive decline progression, there is still a lack of specific treatments to reverse broad cognitive impairment (Patti et al., 2013). The ubiquitous decline of cognitive functioning observed in the multiple sclerosis (MS) population, along with its impact on overall quality of life and the lack of impairmentspecific pharmacological or behavioral interventions, point to a critical issue within this literature and necessitate feasibility research for behavioral interventions to improve and ameliorate MS-related cognitive decline (Benito-León, Morales, & RiveraNavarro, 2002; Rao et al., 1991). One feasible option for behavioral treatment is cognitive training to ameliorate progressive degeneration or even improve decrements in cognitive functioning. While cognitive training has been a vibrant area of research in non-clinical populations, there is considerable debate on the most efficacious approach, as well as the magnitude of observed transfer effects. The magnitude of effect is based on the presence of near or broad transfer, with broad effects being the desired goal in most studies. Broad transfer effects are conceptualized as the effect of training on tasks significantly different from those that were trained, while near transfer would improve performance on tasks that are more similar to the intervention. Those programs that have been most successful in community participants focus on complex multimodal training to produce broad transfer effects (Basak, Boot, Voss, & Kramer, 2008; Chiappe, Conger, Liao, Caldwell, & Vu, 2013; Legault, Allard, & Faubert, 2013). In contrast, those programs that train each dimension separately, utilizing tasks localized to one or two functions in a repeated practice regimen, have exhibited little or no effect of transfer (Chooi & Thompson, 2012; Dahlin, Nyberg, Bäckman, & Neely, 2008; Olson & Jiang, 2004). The repeated practice approach may be lacking broad transfer efficacy due to the focus on training of cognitive processes independently and lack of integrative training that forces interaction of cognitive processes (Green, Pouget, & Bavelier, 2010). In contrast, multimodal training strategies, such as the intervention proposed here, employ the complex integration of cognitive processes to induce processing speed improvements associated with broad transfer effects (Green et al., 2010).

Given the transfer effects observed through the use of multimodal training, there has been a burgeoning interest in the use of videogames as a highly feasible and cognitively integrative avenue to investigate learning strategies and their efficacy for broad cognitive transfer (Basak et al., 2008; Chiappe et al., 2013). Space Fortress is one such videogame that requires players to manage overlapping component tasks that target multiple cognitive domains simultaneously in their interaction and integration within a broad performance goal (Donchin, Fabiani, & Sanders, 1989; Mané & Donchin, 1989). A full game description follows in the Method section of this manuscript. Over the years, this game has been employed to test the efficacy of various learning strategies, which include, full-emphasis training (FET), variable priority training (VPT), and hybrid-variable priority training (HVT), a combination platform of VPT and part-task training (Boot et al., 2010; Gopher, Well, & Bareket, 1994; Lee, Boot, et al., 2012). FET is essentially a repeated practice implementation of the Space Fortress game and, consequently, the least successful intervention in eliciting learning gains due to its lack of complex task integration (Boot et al., 2010). Variable priority training allows for the full game to be simplified by revolving the emphasized goal onto different game components within the context of the full game, eliciting significantly greater learning gains and cognitive transfer for populations with lower baseline cognitive abilities (Boot et al., 2010; Gopher et al., 1994). Combining both part-task training and VPT, HVT was designed to capitalize on the advantages of the two approaches. The HVT strategy focuses initially on training processes in isolation that play a supportive role in higher order cognitive functioning, such as processing speed, attention, and working memory storage (part-task training). VPT training then allows for sub-component integration of these processes within the larger task, while still limiting overall cognitive workload. Table 1 depicts the training breakdown of the HVT strategy by session and illustrates the first wave of parttask training to improve isolated functions, followed by a second wave of VPT to integrate those isolated functions in the context of a complex, multimodal training environment. Based on Green and colleagues’ theory of performance gains (Green et al., 2010), we hypothesized that a training program utilizing both incremental and integrative training strategies might improve processing speed, attention, and working memory capacity early in the intervention, thereby providing support from these cognitive components as

SPACE FORTRESS TRAINING IN MULTIPLE SCLEROSIS TABLE 1 Overview of training programs Training descriptor


Part-task training

1 2 3 4 5 6 7 8 9 10 11

13 14 15 16

Three full emphasis games Slow down a ship Aiming Aiming and firing Navigating a ship in Trajectory 1 Navigating a ship in Trajectory 2 Navigating a ship in Trajectory 3 Navigating a ship in big hexagon Navigating a ship in small hexagon Navigating a ship in hexagon and aiming Navigating a ship in hexagon, aiming, and firing Navigating a ship in hexagon, aiming and firing on the shooting fortress Ship control only Mine control only Bonus control only Three full emphasis games

1 2 3 4 5 6

Total score emphasis—3 games Points score emphasis—2 games Control score emphasis—2 games Velocity score emphasis—2 games Speed score emphasis—2 games Total score emphasis—3 games

12

Variable priority training

Note. Details of the hybrid variable priority training (HVT) program, which included 10 one-hour sessions of part-task training and 10 one-hour sessions of variable priority training (VPT).

building blocks for later skill acquisition and increasing likelihood of training feasibility. Specifically, VPT and HVT interventions have proven most successful at eliciting skill acquisition and subsequent transfer in similar cohorts with lower processing speed, attention, and working memory abilities (Gopher et al., 1994). Individuals with RRMS represent a cohort with lower than average processing speed abilities and thus a population that would experience more efficient rates of learning from a multimodal training platform, particularly given the current dearth of cognitive training interventions eliciting broad transfer effects in this population. Evidence of narrow transfer has been observed for elaborative rehearsal and mnemonic strategy implementations to tasks of long-term memory in individuals with RRMS (Chiaravalloti, DeLuca, Moore, & Ricker, 2005; Mendozzi et al., 1998). However, even fewer options have been substantiated to provide broad transfer effects to multiple domains of cognitive functioning (Plohmann et al., 1998; Solari et al., 2004; Vogt et al., 2009). Those interventions that have been successful at eliciting learning gains in the RRMS population through the use of cognitive training have shown evidence of near transfer to

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one or two tasks within the same domain as the training paradigm, with no evidence of broad transfer to multiple domains of cognitive functioning (Flavia, Stampatori, Zanotti, Parrinello, & Capra, 2010; Vogt et al., 2009). Specifically, a recent investigation in the MS literature, utilizing previous research based on single-domain training designs and individually tailored paradigms, was ultimately unsuccessful at eliciting broad transfer to tasks outside the trained domain and exhibited no effect on patients’ perception of improved functioning (Amato et al., 2014). Thus, the current investigation hopes to build upon previous evidence of cognitive training utility in the MS population to provide feasibility for the use of multimodal videogame-based learning strategies as a possible behavioral platform to induce broad cognitive transfer. However, as the first study to implement the Space Fortress platform and HVT training strategy in a clinical population and taking into consideration the broad profile of cognitive deficits observed in the MS population, our primary aim was to the test feasibility of the HVT strategy to induce incremental learning gains. The specific study aims included: (1) Determine the feasibility of an eight-week cognitive training program for individuals with MS, relative to a waitlist control group. Our hypothesis predicted greater improvement of game play scores over the course of the intervention in the training group as compared to participants in the control group. (2) Determine the effect of an HVT strategy on broad cognitive transfer. We predicted that individuals in the training group would show significant improvement, as compared to the waitlist control participants, on tasks that comprise Rao’s Brief Repeatable Battery (BRB) from pre- to post-training (Rao, 1990).

METHOD Participants Participants were recruited from the local community via advertisements in the media, NARCOMS (North American Research Commission on MS), promotional flyers, Research Match (researchmatch.org), the National MS Society (nationalmssociety.org), and the Multiple Sclerosis Treatment Center affiliated with the research laboratory’s larger institution. Participants were selected based on a priori inclusionary criteria, including: 20/40 visual acuity or better; dominant right-handedness


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Figure 1. A visual overview of the specific details of the study from recruitment to completion. RRMS = relapsing-remitting multiple sclerosis; EDSS = expanded disability status scale; MSFC = multiple sclerosis functional composite; HVT = hybrid variable priority training.

as measured by the Edinburgh Handedness Inventory (Oldfield, 1971); absence of depression as measured by a score of 18 or less on the Beck Depression Inventory–II (Beck, Steer, & Brown, 1996); absence of relapse and corticosteroid use for the last 30 days; age 30–59 years; a score higher than 23 on the Mini Mental Status Examination (MMSE; Folstein, Folstein, & McHugh, 1975); videogame usage of less than 4 hours/week; absence of any other neurological or psychological disorders; and a score greater than 1 on the Expanded Disability Status Scale (EDSS; Kurtzke, 1983). Consent to collect protected health information was obtained from every participant to verify diagnosis and disease duration. The University Institutional Review Board approved the study, and all participants provided informed consent. Assessment procedures Screening session Individuals that exhibited an interest in study participation were asked to contact the laboratory and were subsequently screened by phone to ensure study eligibility. During this screening, participants

provided demographic information on age, gender, and education, as well as clinical variables including diagnosis, duration of illness, psychiatric and neurological history, current health status, and videogame usage. Those participants that met eligibility criteria over the phone were invited to the laboratory for pre-training assessment sessions. A flow chart of study procedures and session descriptions is presented in Figure 1. Pre- and post-training sessions Each participant underwent two pre- and two post-training assessments. The first assessment was conducted to ensure that individuals met all inclusionary and exclusionary criteria that could not be collected during the phone screen. This session included the administration of the MMSE (Folstein et al., 1975) and the Beck Depression Inventory–II (Beck et al., 1996). The co-author, A.B., a neurologist specializing in MS, also administered the Expanded Disability Status Scale (Kurtzke, 1983). The first assessment also included an introduction to the Space Fortress game. Data from this session were later used as the first time-point for the statistical analysis of skill acquisition. Each


SPACE FORTRESS TRAINING IN MULTIPLE SCLEROSIS

participant was shown instructional videos outlining all rules, tips for success, and instructions for the Space Fortress game. To ensure that each participant understood the rules governing the Space Fortress game, a 15-question quiz was administered directly after the instructional videos, and further clarification was provided, if necessary. Participants then completed six full-emphasis games, the last three of which were used for data analysis purposes to represent Time 1 skill acquisition. After eligibility was verified, a second neuropsychological assessment session was conducted to establish a cognitive baseline for each participant. The Wechsler Test of Adult Reading (WTAR), a baseline intelligence estimate (Wechsler, 2001), and the BRB (Rao, 1990) were administered to assess a variety of cognitive domains including attention, memory, processing speed, working memory, and executive functioning. The tests that comprise this battery included: Paced Auditory Serial Addition Test (PASAT). This task was an assessment of working memory functioning, processing speed, and simple arithmetic. Participants were auditorily presented with digits at the rate of 3 s/digit for one condition and 2 s/digit for the second condition. Participants were instructed to add each number heard to the number previously heard and to report the sum out loud. Response accuracy was the primary outcome measure, calculated separately for 2- and 3-s conditions. Selective Reminding Task (SRT). This task was a multi-trial memory assessment of encoding and retrieval processes for verbal stimuli in short- and long-term memory. The SRT involved verbal presentation of 12 words, followed by a series of recall trials. After each trial, participants were selectively reminded of words that were not recalled in the previous trial and were directed to recall the entire list of 12 words again. This procedure was repeated for six trials or until the participant recalled all 12 words. Delayed recall was administered approximately 11 min later and required each participant to freely recall as many words as possible, without cueing. The primary outcome measures were assessed by three dependent variables: long-term storage (LTS), identified by two consecutive recalls of the word; consistent long-term retrieval (CLTR), referring to a word that is recalled consistently for all subsequent trials in the task; and delayed recall, an uncued free recall test of any 12 words remembered after an 11-minute delay. The long-term storage score allows for the assessment of encoding success, while the consecutive long-

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term retrieval score is a measure of retrieval success from immediate memory. 10/36 Spatial Recall Task. This was a task of short-term and long-term spatial memory. A checkerboard was placed in front of each participant for 10 s with a particular pattern displayed. The participant was asked to replicate the pattern, from memory, on an empty checkerboard. Three total trials of the same pattern were administered or until the participant attained a perfect score. After a 15-min delay, the participant was asked to recall the pattern, without cueing, to test delayed recall accuracy. Accuracy was the primary outcome variable for immediate and delayed conditions. Oral Symbol Digit Modalities Test (SDMT). Participants were presented with a key at the top of the page including numbers matched to geometric shapes. The bottom portion of the page contained only geometric shapes with blank spaces below. Participants were asked to verbalize the numbers that corresponded to the geometric shapes, as quickly as possible. The experimenter recorded answers for the participant to remove variability associated with upper motor neuron injury. Participants were given 90 s to complete as many trials as possible, while preserving accuracy. The number of correctly generated responses was the primary outcome measure. Word List Generation Task (WLGT). This was a task of verbal fluency and executive functioning. Each participant was provided with a letter of the alphabet and was instructed to generate as many words as they could think of in 60 s that began with that letter. Three trials of differing letters were completed with the number of correct generated responses across all three trials as the primary outcome measure. Following the eight-week cognitive training period, assessments were repeated to obtain post-training data for analysis of transfer effects within a two-week time window of the 8-week study period completion. A detailed flow chart of the study procedure is provided in Figure 1. Intervention procedures Randomization and blinding A list of random numbers were generated prior to the start of the study and kept in a passwordprotected excel file, accessible only to the study coordinator. As individuals completed the assessments, their names were added to this list, in


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order, by the study coordinator, to ensure complete randomization. The study coordinator was responsible for generating the randomization sequence, enrolling participants, and assigning their group placement. Those participants in the waitlist control group were informed of their future ability to participate in the cognitive training after the 12 weeks of data collection had commenced, although no individuals accepted this invitation. Admission to the study was completed on a rolling basis as participants became available from September, 2011, to May, 2013. The trial was completed when an n of 28 participants was reached. All investigators and key personnel who performed assessments were blinded to group assignment except for the study coordinator and research assistants administering the training sessions. Participants that became aware of other individuals participating in the study were asked not to share the details of their group assignment. Key assessment personnel that became aware of a participant’s group assignment were prohibited from completing any further assessments with that participant. Participants were encouraged to remain within their testing rooms at all times and were otherwise escorted by unblinded personnel to ensure that their group assignment remained blinded to the assessors. Training and assessment rooms, while housed within the laboratory, were completely closed off to outside personnel and were identified during assessment and training sessions as occupied. All additional computer files containing group assignment, including training data, were kept on one computer and were password protected at all times. Space Fortress game In this study, we employed the videogame Space Fortress as a platform to implement the HVT strategy. We chose this game primarily for its success in lending itself flexibly to various training strategies (Boot et al., 2010; Lee, Boot, et al., 2012). Space Fortress was designed by cognitive psychologists to examine the influence of various training strategies on skill acquisition rates (Mané & Donchin, 1989). Figure 2 is a static illustration of the Space Fortress game, depicting the Space Fortress in the center of two hexagons. The player, using a joystick, navigates their spaceship in a frictionless environment, shooting missiles at the Space Fortress to destroy it, while simultaneously monitoring and collecting bonus points that appear at the bottom of the screen and constantly dealing with diamond-shaped foe or friend mines that appear on the screen. Details of this game have been published extensively (Boot et al., 2010;

Figure 2. A static image of the Space Fortress videogame highlighted in the current study as a platform for testing the efficacy of the HVT approach in RRMS individuals. PNTS = points; CNTRL = control; VLCTY = velocity; VLNER = vulnerability; IFF = identify friend or foe; INTRVL = millisecond interval between double clicks. To view a color version of this figure, please see the online issue of the Journal.

Gopher et al., 1994; Lee, Boot, et al., 2012; Lee, Voss, et al., 2012; Stern et al., 2011), and thus here we simply highlight the total score and the four subscores derived from the game. The total score awarded to the participant is a sum of four subscores: control, points, speed, and velocity. The control subscore is calculated from the participant’s maintenance of spaceship movements within the two hexagons. The points subscore is determined from the number of bonuses obtained and missile interactions with the Space Fortress. Speed subscores are derived from the player’s ability to maintain an attentional set composed of three letters and identify mines corresponding to those letters during the game. Finally, the velocity subscore is a reflection of the player’s spaceship speed; going fast subtracts from the score, and going slow contributes to the score.

Experimental and control group protocols For the period of the intervention, participants were asked to notify the experimenters of any sudden adjustments in their medical therapies or significant lifestyle changes and stressors. Participants that suffered a relapse or began corticosteroid use after randomization complied with study protocol and withdrew participation to ensure safety while



attending study appointments and preserve study integrity due to the impact of relapse and related treatment on cognitive functioning (two participants in the HVT group). Study participation also required completion of the training or waitlist control period within a 10-week window. Those participants that could not comply with this deadline were omitted from final data analyses, due to confounding variance from a differential training or waitlist time course (one participant from each study group). Hybrid-variable priority training strategy (experimental group). For the purpose of the current study, we utilized the HVT strategy. The first 10 one-hour training sessions required participants to practice part-task training. This learning approach divided the Space Fortress game into 14 part tasks, each about 2 min long, which focused on different aspects of the game, outlined in Table 1. Each participant first completed three full-emphasis games, or games that were not altered from the original Space Fortress format, followed by 14 part-task games, and, finally, another three fullemphasis games. The next 10 one-hour sessions consisted of a variable priority training (VPT) strategy. This strategy highlighted different aspects of the game, with varying emphasis on each subscore to minimize overall cognitive load, while integrating previously trained part-tasks. Participants completed six variable priority games, with a varying, counterbalanced emphasis order of points, control, speed, velocity, and total scores, bookended by three full emphasis games at the beginning and end of each session. Further details of the part-task and variable priority training sessions can be found in Table 1. A total duration of 20 one-hour sessions was chosen based on previous literature detailing significant skill acquisition in young adult participants after only 10 hours of training (Lee, Boot, et al., 2012). Thus, 20 hours was deemed sufficient to elicit skill acquisition and substantiate HVT strategy feasibility in a population with a lower cognitive baseline. Skill acquisition data were also collected for both groups after 10 hours of training to verify previous accounts of training success after 10 training hours in the current population. Waitlist control group. Control group participants were contacted every two weeks to ensure good health and compliance with study guidelines. Participants were requested to refrain from engaging in any other experimental trials and were required to attend two training sessions at Weeks 4 and 8 to obtain comparison game-play data for

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skill acquisition analysis. Control session included three full-emphasis games, followed by a distractor task for 34 min to ensure equal fatigue levels across groups for comparison data. The participant then completed the final three full-emphasis games. A visual depiction of the intervention procedures can be found in Figure 1.

Data analyses Statistical analyses of skill acquisition data Analyses were completed using the Statistical Package for the Social Sciences (SPSS Version 20). Statistical significance was based on an a priori determined p-value of .05. An initial series of independent samples t-tests were conducted to identify any significant covariates, including clinical and demographic variables and initial game performance. Group differences for gender were determined via chi-square analysis. No significant covariates were identified. Space Fortress performance was based on the average score of the last three full-emphasis games for each session. There were three time points for each individual representing pre-training, Week 4, and Week 8 of the intervention. All data collected from game play were tested for multivariate normality of analysis of variance (ANOVA) residuals and multivariate outliers. One participant was excluded from the final analysis of the points’ subscore due to outlier effects, exemplified by a score greater than 3.5 standard deviations below the mean. All other scores for this participant were within 3.5 standard deviations from the mean and were maintained in all other skill acquisition analyses. Our first hypothesis assessing intervention feasibility was tested by conducting a repeated measures ANOVA for total score: the composite of all four subscores, with time (pre-training, Week 4, and Week 8) as the within-subject factor and group (training, control) as the between-subjects factor. Significance was based on the F-test of the Group × Time interaction. To examine the independent effects of each subscore on the outcome of the total score ANOVA, repeated measures ANOVAs were completed on each of the four subscores, with significance based on the F-value of the Time × Group interaction. We inspected each of the analyses for violations of sphericity using the Mauchly’s test of significance, and Greenhouse–Geisser corrections were applied wherever violations of the hypothesized and observed variance/covariance pattern was noted.

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Statistical analyses of neuropsychological data All behavioral data were tested for multivariate normality of ANOVA residuals. No scores were classified as multivariate outliers. There was an error in SDMT data collection during pre-training assessment for one participant in the control group, requiring imputation. Missing data was accounted for by calculating an average of the individual’s z-standardized scores on other measures of the BRB at pre-training and back-transforming that average to compute the SDMT raw score. The secondary study aim of transfer effect to sub-domains tapped by the five tests of the BRB was analyzed using repeated measures multivariate analyses of variance (MANOVAs). We adopted a categorization described by Sepulcre and colleagues, to assess domain-specific improvements observed as a function of training (Sepulcre et al., 2006). Specifically, PASAT and SDMT dependent variables were analyzed via repeated measures MANOVA, testing the effect of the HVT strategy on the attention/executive domain. Verbal memory and visual memory transfer were determined via repeated measures MANOVA for SRT and 10/36 spatial recall variables, respectively. Finally, verbal fluency was examined through repeated measures ANOVA analysis of change in WLGT score. Given the pilot nature of this study, and primary aim to determine feasibility within a completely novel treatment population, a correction for multiple comparisons was not made.

RESULTS Participant characteristics Demographics Table 2 displays group-level statistics of demographic characteristics. Independent samples t-tests, and chi-square tests, when applicable, were

performed to ensure that no statistically significant differences existed between experimental groups at baseline for all individuals that met final study criteria. The final N was 28, with 14 participants completing the training condition and 14 completing the waitlist control condition. Participant attrition Fifty individuals with RRMS were recruited in total from the aforementioned sites and materials. A flowchart of study adherence and attrition can be found in Figure 3, which depicts the number of individuals who were lost at each stage of the screening, assessment, and intervention process. Sixteen individuals were excluded from study participation during the assessment process due to Beck Depression Inventory scores (10 individuals), EDSS scores (2 individuals), relapse during the assessment process (1 individual), and MMSE scores (1 individual). Two individuals passed the phone screening and were scheduled for subsequent appointments, but chose not to attend the pre-training sessions. Thirty-four individuals were randomized for inclusion in the intervention process. Four participants were lost to attrition during the course of the intervention process. Reasons for attrition from the training group were circumscribed to clinical relapse during the training period (2 individuals). Two individuals were lost from the waitlist control group due to issues with scheduling and time commitments. Two additional individuals completed the training period (one from each of the groups) within 12 weeks and the post-training session within 14 weeks, but were excluded from final analyses based on prolonged training duration (more than 10 weeks). This resulted in 17% attrition from the study after randomization. An analysis of clinical, demographic, and cognitive differences between completers and noncompleters is reported in Table 3. Specifically, we

TABLE 2 Demographic variables

Group Training (n = 14) Control (n = 14) Inferential Statistics P-values

Age (years) 49.43 (6.4) 44.93 (8.8) t = 1.55 .13

Gender 4 males 3 males χ2 = 0.19 .66

Education (years)

EDSS

Disease duration (years)

WTAR

BDI–II

16.57 (2.3) 16.21 (1.7)

2.86 (1.3) 2.68 (1.4)

13.00 (6.7) 10.93 (7.4)

108.46 (8.1) 109.64 (8.0)

6.5 (5.7) 5.57 (3.9)

t = 0.47 .64

t = 0.36 .72

t = 0.77 .45

t = –0.38 .71

t = 0.50 .62

Note. A display of demographic and clinical variable means for both groups with standard deviations in parentheses. The last two rows of the table illustrate the results of independent samples t-tests of group differences at pre-training. There were no significant differences between the two groups on any of the demographic or clinical variables. EDSS = Expanded Disability Status Scale; WTAR = Wechsler Test of Adult Reading; BDI–II = Beck Depression Inventory–II.

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Figure 3. Outlines how individuals were chosen for participation in the study based on inclusionary/exclusionary criteria, as well as attrition rates once individuals were randomized. An attrition rate of less than 17% provides support for the feasibility of a hybridvariable priority intervention. RRMS = relapsing-remitting multiple sclerosis; EDSS = expanded disability status scale; MMSE = MiniMental Status Examination; HVT = hybrid variable priority training.

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JANSSEN ET AL. TABLE 3 Completers versus noncompleters


Variables Demographic variables

Age (years) Gender Education (years)

Clinical variables

EDSS Disease duration (years) WTAR BDI–II

Cognitive variables

PASAT 3 s PASAT 2 s SDMT SRT-LTS SRT-CLTR SRT-Delayed 10/36-Correct 10/36-Delayed WLG

Completers (n = 28)

Noncompleters (n = 6)

Inferential statistics

47.18 (7.87) 7 males 16.39 (1.99)

37.67 (4.23) 0 males 15.33 (2.42)

t = 2.85** χ2 = 1.89 t = 1.14

2.77 11.96 109.07 6.04

(1.30) (7.05) (7.91) (4.80)

2.25 5.00 100.50 9.83

(0.82) (4.20) (13.38) (6.71)

t t t t

= = = =

0.93 2.32* 2.11* –1.64

43.64 33.68 43.10 47.43 38.25 8.57 21.14 7.36 27.46

(12.32) (12.16) (11.22) (18.30) (22.39) (2.82) (5.92) (2.83) (7.74)

36.67 26.67 42.17 54.33 49.50 9.67 17.17 7.00 28.50

(13.59) (8.04) (10.40) (13.53) (17.94) (1.97) (7.20) (2.68) (5.32)

t t t t t t t t t

= = = = = = = = =

1.24 1.34 0.19 –0.87 –1.15 –0.90 1.44 0.28 –0.31

Notes. A display of demographic, clinical, and cognitive variable means for study completers versus noncompleters with standard deviations in parentheses. The last column of the table illustrates the results of independent samples t-tests of participant differences at baseline. EDSS = Expanded Disability Status Scale; WTAR = Wechsler Test of Adult Reading; BDI–II = Beck Depression InventoryII; PASAT = Paced Auditory Serial Addition Test; SDMT = Oral Symbol Digit Modalities Test; SRT = Selective Reminding Task; LTS = long-term storage; CLTR = consistent long-term retrieval; WLG = Word List Generation Task. *p < .05; **p < .01.

observed that those individuals that completed the study were significantly older, with longer disease duration and higher intelligence estimate. Given the well-documented correlation between disease progression and employment in the MS population, it is unsurprising that noncompleters were younger with a shorter disease duration (Hakim et al., 2000; Beatty, Blanco, Wilbanks, Paul, & Hames, 1995). However, the demographic composition of individuals lost to follow-up represents a commonly observed phenomenon in intervention and longitudinal studies and the limitations to external validity posed by laboratory-based investigations (Larners et al., 2012). The final analyses included 28 individuals who met all inclusionary criteria and completed the intervention within the designated time

window without clinical relapse or therapeutic corticosteroid use.

Skill Acquisition Results Table 4 displays the results of the repeated measures ANOVAs conducted on the Space Fortress game data. In support of our first hypothesis, the test of total score, a composite of all four subscores, was significant at F(1.29, 25) = 9.96, p = .0005, η2 = .28, signifying greater skill acquisition in our training group than in control participants. Figure 4 reveals a significant difference between groups beginning at Week 4,

TABLE 4 Skill acquisition results Group

Total

Points

Control

Speed

Velocity

Training

Time 1 Time 2 Time 3

–3328.69 (1071.55) –1199.29 (2219.38) 181.80 (3407.54)

–1597.13 (923.83) –1182.49 (1264.45) –245.61 (1158.64)

–956.64 (537.93) –180.33 (836.43) 326.58 (806.99)

–97.62 (155.71) 170.48 (188.81) 342.98 (303.20)

–508.33 (419.20) 174.67 (854.21) 467.75 (940.65)

Control

Time 1 Time 2 Time 3

–3491.33 (729.34) –2942.50 (1376.34) –2618.05 (1732.99)

–1758.90 (473.79) –1592.33 (515.89) –1337.79 (418.02)

–1023.43 (429.26) –833.98 (579.52)) –819.93 (776.36)

–145.00 (85.04) –96.19 (125.41) –31.67 (205.84)

–564.00 (349.24) –420.00 (563.19) –428.67 (688.53)

F-value Partial eta2

9.96** .28

5.03* .17

12.68** .33

11.76** .31

6.59** .20

Notes. Displays Space Fortress score results for test of the composite total score, as well as each independent subscore analysis. Mean values for pre-training (Time 1), Week 4 (Time 2), and Week 8 (Time 3) are presented with standard deviation values in parentheses. The last two rows display the results of the F-test and the obtained effect size in partial eta2. *p < .05; **p < .01.

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Figure 4. A graphical representation of Space Fortress game analyses results. Time is displayed on the x-axis, while game score values are displayed on the y-axis. *p < .05; **p < .01. To view a color version of this figure, please see the online issue of the Journal.

t(21.71) = 2.50, p = .02, and continuing through to Week 8, t(26) = 2.74, p = .01. Further analyses of subscore changes were conducted to determine the specific improvements in various components of the Space Fortress game. A

repeated measures ANOVA of the points subscore was significant, F(2, 24) = 5.03, p = .01, η2 = .17, indicating learning from pre-training to Week 8 on these skills. The difference in points subscore between the training and waitlist control group,


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in contrast to the total score, was not significant at Week 4, t(16.51) = 0.58, p = .57, but was significant at Week 8, t(14.88) = 3.21, p = .01, with the training participants performing better than the control participants. Results of the repeated measures ANOVA for the control subscore illustrated an overall skill acquisition gain in the training group, as compared to waitlist controls, F(2, 25) = 12.68, p = .0005, η2 = .33. In contrast to the points subscore, there was evidence of significantly better performance in the training group on the control subscore at Week 4, t(23.1) = 2.40, p = .03, and Week 8, t(26) = 3.83, p = .0005, compared to controls. The control subscore measures a participant’s ability to keep the ship on the screen and within the hexagon boundaries, relying on basic cognitive processes such as mental and motoric processing speed, and dexterity with the joystick. The speed score is an analysis of mine control and the ability to maintain an attentional set consisting of a three-letter string and monitor for scoring opportunities related to the mine control goal. This subscore significantly improved in the training group, relative to the control group, F(2, 25) = 11.76, p = .0005, η2 = .31. A breakdown of this effect at Week 4 and Week 8 illustrated a significant difference between groups at both time points, t(26) = 4.40, p = .0005, and t(26) = 3.83, p = .0005. An analysis of the velocity subscore, or the player’s ability to fly the ship at low speeds, was significant after eight weeks of training, relative to

pre-training, F(1.49, 25) = 6.59, p = .01, η2 = .20. Further analyses of each time point revealed evidence for significant group differences at Week 4, t(22.51) = 2.18, p = .04, and at Week 8, t(26) = 2.88, p = .01. A graphical representation of the total score and subscore improvements can be found in Figure 4.

Brief Repeatable Battery results Table 5 displays the results of the repeated measures MANOVAs that were conducted with each of the four sub-domains of the BRB. We did not find an effect of the training program on attention/ executive functioning, as evidenced by a nonsignificant Group × Time interaction, F(3, 24) = 0.69, p = .57, η2 = .08. Surprisingly, an analysis of the verbal memory revealed a marginally significant effect in favor of the control group, F(3, 24) = 2.58, p = .08, η2 = .24. Specifically, univariate analyses of each score separately indicated a significant effect in favor of the control group on long-term storage, F(1, 26) = 4.82, p = .04, η2 = .16, and consecutive long-term retrieval, F(1, 26) = 5.03, p = .03, η2 = .16, with trending significance for delayed recall, F(1, 26) = 3.62, p < .1, η2 = .12. We did, however, find a significant effect of the intervention, in the direction of the training group, on measures of visual memory, with the overall MANOVA being significant, F(2, 25) = 4.25, p = .03, η2 = .25. In here, we found the Group ×

TABLE 5 Brief Repeatable Battery results Training Group Attention/executive PASAT 2s PASAT 3s SDMT Verbal memory SRT LTS SRT CLTR SRT Delayed Visual memory 10/36 Correct 10/36 Delayed Verbal fluency WLG

Control

Inferential statistics

Pre

Post

Pre

Post

MANOVA F

Partial eta2

33.93 (12.10) 44.21 (12.88) 43.79 (11.68)

35.36 (14.03) 48.86 (13.45) 45.07 (12.09)

33.43 (12.67) 43.07 (12.19) 42.43 (11.15)

34.14 (12.70) 45.64 (10.63) 40.21 (10.85)

0.69

.08

50.43 (17.18) 44.71 (19.79) 9.07 (2.65)

47.36 (19.77) 39.43 (21.14) 8.86 (2.41)

44.43 (19.52) 31.79 (23.67) 8.07 (3.00)

51.14 (11.29) 38.29 (20.53) 9.29 (2.02)

2.58†

.24

18.79 (5.95) 7.07 (3.27)

22.00 (6.15) 7.57 (3.01)

23.50 (5.03) 7.64 (2.41)

19.43 (6.78) 6.50 (3.57)

4.25*

.25

28.43 (7.31)

27.79 (9.25)

26.50 (8.30)

28.07 (6.12)

0.96

.04

Notes. A display of Brief Repeatable Battery (BRB) results for both groups for the two time points. Mean values are presented for pre and post time points with standard deviation values in parentheses. The last two rows illustrate the results of the multivariate analysis of variance (MANOVA) F-test and the obtained effect size in partial eta2. PASAT = Paced Auditory Serial Addition Test; SDMT = Oral Symbol Digit Modalities Test; SRT = Selective Reminding Task; LTS = long-term storage; CLTR = consecutive longterm retrieval; 10/36 = 10/36 Spatial Recall; WLG = Word List Generation Test. *p < .05; †p < .1.



Time interaction for the immediate recall on the 10/36 spatial recall task, F(1, 26) = 6.68, p = .02, η2 = .21, to be significant, after controlling for significant differences in pre-training scores. However, a delayed version of the 10/36 Spatial Recall exhibited no significant effects of transfer to measures of long-term spatial memory, F(1, 26) = 1.21, p = .28, η2 = .05. Higher order functions, as measured by the verbal fluency demands of the word-list generation task, also exhibited non-significant results, F(1, 26) = 0.96, p = .34, η2 = .04.

DISCUSSION The empirical examination of feasible and easily disseminable cognitive rehabilitation strategies for reducing broad cognitive deficits and improving overall quality of life has become a topic of great interest to the MS community. In this study, we tested the feasibility of a HVT strategy to elicit skill acquisition in individuals with MS. The secondary aim was to investigate the impact of the HVT strategy on broad measures of cognition. The results of our eight-week Space Fortress training intervention provide evidence for the feasibility of this intervention, with significant effects on skill acquisition, despite negligible effects of cognitive transfer. Specifically, we saw an improvement in total game score, for the training group. This substantiates previous findings of successful learning and skill acquisition in the RRMS population (Amann et al., 2011). However, given that our control comparison was a waitlist control group, these results were expected. The decision to implement a waitlist control group, as opposed to an active control, was based on the primary goal of determining intervention feasibility within an MS cohort. Despite the previous implementation of the HVT strategy in healthy young and older adult populations, this is the first trial to assess feasibility in a clinical, neurodegenerative disease sample. Future research, testing the efficacy of the HVT training strategy, relative to another training strategy, such as full-emphasis training (FET), would validate whether greater skill acquisition was achieved as a function of HVT training, within the MS population. Specifically, implementation of an FET control group would match participants on exposure to the game and allow for a more direct observation of the effects of specific learning strategies on skill acquisition. More recent studies of skill acquisition have observed changes in the functional neural correlates of skill learning before cognitive impairment is detectable (Amann et al.,

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2011). Therefore, it is possible that changes in the functional organization of the brain have also been affected, as a consequence of the training intervention, before objective behavioral change could be detected. Thus, a significant effect of training on skill acquisition could represent the first necessary steps for behavioral changes associated with transfer effects, once adequate skill level is achieved. Additional improvements to the current training platform would be necessary to determine whether these associations would hold true. Further analyses of sub-component scores revealed an improvement in all targeted measures of skill acquisition within the larger Space Fortress game, further supporting the feasibility of this intervention in the MS population. Improvement on the points subscore was likely associated with each participant’s focus on this subscore throughout their game play due to its close association with the superordinate goal of the game and the integral role it plays in subsequent skill acquisition on other subscores. Significant improvement on the speed subscore, a reflection of the player’s ability to deal efficiently with mines as they appear on the screen, likely equates to the ability to maintain an attentional set of three letters in short-term memory storage throughout game play and monitor for opportunities to apply maintained information according to mine control goals. Thus, this could suggest an enhancement of attentional capacities within the game context as a function of training. However, further analysis through the use of near-transfer computerized tasks of divided attention and working memory would be necessary to validate the effects outside of the Space Fortress paradigm. The control subscore represents a player’s ability to keep their ship within the two hexagons presented on the screen and fly in a clockwise direction. This requires manual dexterity and small, incremental movements that are difficult for individuals with multiple sclerosis to execute (Benedict et al., 2011). Similarly, the velocity subscore also requires incremental joystick movements to keep the player’s ship flying at a low velocity throughout game play. Both measures of control and velocity equate to manual joystick maneuvering changes as a function of the training program, and improvement in both these scores suggests the possibility of enhanced motor control in the Space Fortress game environment in the training participants. However, a task to assess changes in motor control, as a function of the intervention, would be necessary to ascertain the validity of these transfer effects. The secondary aim of this study was to investigate the transfer effects of multimodal training to


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broader measures of cognition, commonly associated with functional impairment in the RRMS disease course. Our results suggest that the current training program did not produce significant improvements on tasks requiring a wide array of cognitive functioning abilities, such as those comprising the Brief Repeatable Battery (Rao, 1990). This result was surprising, especially given previous investigations of significant near transfer effects in both young adult (Lee, Boot, et al., 2012) and older adult populations (Stern et al., 2011). Employing the HVT strategy, Lee and colleagues found near transfer effects on tasks of working memory and visual reasoning after 30 hours of training in both HVT and FET groups (Lee, Boot, et al., 2012). Similarly, in a study by Stern et al., with older adults, the authors found that 36 hours of VPT training, over the course of 12 weeks, resulted in significant transfer to letter– number sequencing, a measure of working memory and processing speed as part of the Wechsler Adult Intelligence Scale, Fourth Edition (Stern et al., 2011). Thus, given these previous investigations, we initially hypothesized a significant improvement on tasks of broader cognition in our sample of MS participants. One interpretation for the lack of such transfer effects could be the limited gain in Space Fortress performance in our sample of RRMS participants, as compared to the studies

cited above. While participants in the experimental group showed significantly better performance than participants in the waitlist control group, their overall performance on the Space Fortress game was still substantially lower than participants in the Lee, Boot, et al. (2012) study. In Figure 5, we plot the total score obtained by participants in the Lee, Boot, et al. study with 20 hours of training, in comparison to our participants at the end of 20 hours of training, showing that MS individuals trained with the same HVT Space Fortress program fall substantially short of scores attained in a cognitively healthy population during normal game play. In other words, it is possible that, due to limited gains in skill acquisition, RRMS participants did not elicit the cognitive transfer effects observed in other studies. Future endeavors of the HVT training paradigm as a rehabilitation tool for MS-related cognitive impairment would do well to implement a training strategy program of at least 40 hours or greater to produce similar effect sizes to those observed in young adult populations. Another possible explanation for the lack of transfer results observed in the current study could be the inclusion of individuals with RRMS who did not exhibit clinically significant deficits in cognitive processing, defined by a difference of 1.5 standard deviations or greater below their age-

Figure 5. An illustration of game score differences after 20 hours of training in a group of 25 young adult participants as compared to a group of 14 relapsing-remitting multiple sclerosis (RRMS) participants. Data on young adults were adapted with permission from Lee, Boot, et al. (2012). The young adult sample is stratified by high scorers versus low scorers to illustrate the difference in skill acquisition based on initial performance level. RRMS patients appear to score below the young adult sample at every time point. HVT = hybrid variable priority training. To view a color version of this figure, please see the online issue of the Journal.



matched peers (Lezak, Howieson, Loring, Hannay, & Fischer, 2004). Evidence within the MS population illustrates the most robust and reliable results in cognitive rehabilitation for those individuals who were cognitively impaired at the start of training, with markedly better results for moderately to severely impaired patients (Chiaravalloti et al., 2005). Indeed, a previous investigation by Foss and colleagues comparing studies that illustrate transfer effects to studies that fail to find such benefits attributed the variance in transfer effects to differing levels of baseline cognitive processing, with ceiling effects at baseline hypothesized to underlie the failure to find significant transfer effects (Foss, Fabiani, Mané, & Donchin, 1989; Whitlock, McLaughlin, & Allaire, 2012). In our study, we did not specifically select participants with impaired cognitive processing, nor did we provide them with the same amount of training time as that implemented in previous studies that observed cognitive transfer, due to our primary aim of feasibility (Lee, Boot, et al., 2012; Stern et al., 2011). Participant selection was completed under the assumption that all included participants would show some cognitive decrements as a function of their clinically definite RRMS diagnosis. Thus, the current investigation was hypothesized to exhibit higher external validity if transfer effects were observed in a general population of RRMS patients. From our previous analysis of skill acquisition gains, it is clear that some level of cognitive impairment was affecting skill acquisition, but a clinically significant level of cognitive impairment was not present for all participants. Future endeavors with this multifaceted, complex retraining perspective would benefit from stratifying participants based on cognitive impairment and examining the differential impact of training on cognitively impaired versus cognitively unimpaired individuals with the aforementioned lengthening of the training period. Finally, and critically, the non-significant effects of the intervention on broad transfer were likely the result of our limited sample size. Given the novelty of a videogame training paradigm, our primary aim was to determine feasibility of the intervention in a clinical population. Utilizing the effect sizes provided in the current analysis and a more targeted battery of cognitive tasks, a larger sample size with a significant degree of cognitive impairment would be more appropriate to achieve broad transfer effects. Specifically, future investigations might benefit from including those tasks eliciting the greatest improvement in the current intervention to shape subsequent power analyses.

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The addition of subjective measures of improvement would also be a valuable tool to extend the implications of transfer results to a practical context. These measurements would allow for a better understanding of which functional dimensions individuals perceive as most critical to their daily lives and evaluate whether those were impacted by the intervention. Subjective measures of improvement could prove both complementary and informative in regards to the successful deployment of treatment strategies and general efforts to improve quality of life for MS individuals. Despite these limitations, transfer effects were observed for measures of visual memory as illustrated by significant improvement in the training group on 10/36 spatial recall measures. This task required participants to observe a checkerboard design with a randomized dot pattern of 10 circles for 10 s, followed by an immediate recall trial. Pattern presentation and subsequent immediate recall was repeated for three trials or until the participant got all 10 circle placements correct. Delayed recall was evaluated 15 min later, without additional cueing. Notably, previous investigations of “expert” gamers have illustrated greater aptitude with visual short-term memory adaptability and changes (Boot, Kramer, Simons, Fabiani, & Gratton, 2008). It is possible that the complex and demanding environment of the HVT learning strategy transferred to a better ability to hold visual information in short-term memory while manipulating other objects in the environment and maintaining concurrent executive demands. However, this result was not corrected for multiple comparisons, and thus replication would be necessary to have confidence in the veridicality of the observed result. Surprisingly, we found trending results in favor of the waitlist control group for verbal memory domain measuring immediate sustained storage and retrieval as part of the Selective Reminding Test. The SRT, designed to differentiate between the processes involved in memory functioning, has three main dependent variables: long-term storage, consecutive long-term retrieval, and delayed recall. Participants successfully recalling a word on two consecutive trials earn a score for that word on the measure of long-term storage, thus suggesting that an inability to recall the word on subsequent trials was largely a result of retrieval failure, rather than a failure of storage. CLTR is a measure of retrieval from long-term memory and representative of successful long-term storage and retrieval mechanisms. The current results provided evidence that control participants, post-training, performed better on the combination of storage and retrieval


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measures, than did training participants. While these results are surprising, considering that control participants did not specifically receive any training, the cognitive intervention implemented in this study did not target long-term memory storage. Thus, we did not predict specific training-related improvements on this measure of long-term retrieval, given the nature of the intervention. The improvement of control participants, while perplexing, could possibly be a result of practice effects with the SRT paradigm. The lack of transfer effects observed in the current study does aid in pointing out some significant areas for improvement and future development of this rehabilitation strategy, while also providing a feasible platform for future training endeavors. First, the observed behavioral transfer effects could be improved by a larger sample size and longer training schedule to induce skill acquisition at or above the level of healthy younger adults. We would propose an additional 20 hours of training to increase the total training hours to 40 over the course of a 12-week intervention period. It would also be important to limit future trials to individuals that display a significant cognitive impairment, specifically using the standardized, normbased cutoffs provided by the MACFIMS (Multiple Assessment of Cognitive Functioning in Multiple Sclerosis) battery (Benedict et al., 2006). In addition, previous research has provided functional neural correlates of cognitive change during computerized cognitive retraining programs (Parisi et al., 2014; Sastre-Garriga et al., 2011). The addition of functional neuroimaging to our study of cognitive rehabilitation could elucidate the neural correlates of behavioral change, as well as provide evidence of improvement before behavioral effects are elicited.

CONCLUSIONS The significant effect of the HVT strategy on skill acquisition in this sample lends support to our rehabilitation program and the feasibility of the Space Fortress HVT strategy in producing learning gains within the RRMS population. While limited effects of transfer to broad measures of cognition were observed, significant improvement on shortterm spatial memory suggest an effect in the positive direction for working memory functions that act as a building block in broader cognitive functioning gains. Several study limitations were identified for future research endeavors, including an increase in study duration, inclusion of individuals with a defined cognitive impairment profile, and a

larger subject sample size. For future research, we would also propose the addition of functional and structural neuroimaging to provide additional insights into the efficacy of such complex cognitive training programs as a disseminable rehabilitation tool within the RRMS population.

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