Researchers have been investigating a variety of behavioral interventions, including exercise, to improve cognitive function and decrease risk of progression to dementia among individuals with MCI (e.g., Kramer et al., 1999; Colcombe and Kramer, 2003; Studenski et al., 2006; Angevaren et al., 2008; Baker et al., 2010; Geda et al., 2010; Martin et al., 2011). Physical exercise has garnered significant support in the literature for its potency in effecting cognitive benefits (e.g., Colcombe and Kramer, 2003). While the literature examining the relationship between physical exercise and cognitive benefit is not without issues (e.g., recent Cochrane Reviews; Forbes et al., 2015; Young et al., 2015, which focused on dementia and normative older adults, respectively), it is widely accepted that exercise benefits cognition, particularly executive function among symptomatic individuals, that are yet early in their cognitive decline (e.g., MCI), the very population on which this study focused (e.g., Colcombe and Kramer, 2003; Etnier and Chang, 2009; Geda et al., 2010; Gates, 2013; Hess et al., 2014; Zheng et al., 2016). Indeed, pre-clinical persons, ranging from asymptomatic older adults to those with early MCI, may experience the greatest benefit from exercise, due to the relatively preserved brain structures and functions (in contrast with more progressed dementia) that can support and supply components needed to realize neuroplasticity as triggered by exercise (e.g., Colcombe et al., 2004; Kramer and Erickson, 2007; Ahlskog et al., 2011; Teixeira et al., 2016). However, knowing that physical exercise may be good for one's body and brain may not be enough to induce regular practice of exercise. Most older adults do not meet the guideline from the American College of Sports Medicine (ACSM) which now recommends 45 min per day, 5–7 days per week, including vigorous exercise (Chodzko-Zajko et al., 2009).

In a previous randomized clinical trial (Anderson-Hanley et al., 2012), we aimed to induce a thorough dose of exercise (Vidoni et al., 2015) by assigning older adults to an exergame¹. We expected that the engagement of a stimulating exergame would motivate regular exercise, therefore allowing older adults to achieve maximum cognitive benefit. Three months of pedaling a virtual-reality-enhanced stationary ergometer, displaying scenic bike tours which we referred to as a “cybercycle” (see Figure 1), was compared with a traditional stationary bike. In the end, the cybercycle condition yielded significantly greater cognitive benefit, as hypothesized. However, surprisingly, it was not due to a difference in dose; we found instead that both the cybercycle and traditional cyclists has been similarly adherent (e.g., no significant difference between groups in miles, minutes, power, heart rate, etc.).

This unexpected finding raised the possibility that the screen display was providing benefit, beyond that of basic entertainment or motivation. We theorized the enhanced form of exercise was yielding findings much like those of the environmental enrichment literature (e.g., animals provided with greater physical and mental stimulation experience enhanced brain function; Pusic et al., 2016); thus it seems more (even two types at once) is generally better, although to a point. In humans the complexity of experience and the diversity of type, timing and compounding of “enrichment” makes this considerably challenging to study as a unique phenomenon. It seemed that for our participants, by interacting with the tour stimuli on screen (e.g., changing pedaling speed yielded a change in speed of scenery moving by), they were certainlyengaged in some additional amount of cognitive processing beyond the control condition. This layered cognitive stimulation may have combined with the physical exercise required of the exergame to create a “two-for-one” impact that resulted in the observed additional cognitive benefit for participants. Hence, we hypothesized that participants experienced better neuropsychological outcomes because of the potentially synergistic phenomena created by combining a type of “mental exercise” that was interactive with physical exercise (Anderson-Hanley et al., 2012; Frantzidis et al., 2014).

Several areas of the research literature speak to the possible validity of this hypothesized compounding or synergistic effect. As previously mentioned, there is a robust literature documenting the cognitive benefits of physical exercise. There is also a growing literature on cognitive training that purports significant effects (Willis et al., 2006; Karr et al., 2014; Toril et al., 2014; Wang et al., 2014; Huntley et al., 2015; Train the Brain Consortium, 2017). However, in our view, the claims are less convincing due to problems with reporting, limited generalizability, and other reasons that have been cited in various critiques of the literature and related “brain training” industry (e.g., Owen et al., 2010; Muijden et al., 2012; Redick et al., 2013; Boot and Kramer, 2014; Simons et al., 2016; Zokaei et al., 2016). Indeed, a Cochrane Review of 11 RCTs concluded there was “no indication of any significant benefits from cognitive training” (Bahar-Fuchs et al., 2013, p. 1). Nevertheless, considering some “mixed” results on the potential benefits of cognitive training, and as well as the animal literature on neurobiological impact of cognitive enrichments (reviewed below), there is potential for mental challenge to have its own benefit on cognition. Although perhaps it is most effectively implemented as part of a more naturalistic intervention, as when integrated with physical activity that taps additional neural mechanisms.

One way to examine this possibility further is to evaluate the body of literature that encompasses the cognitive effects of interventions with multiple components (e.g., cognitive training and physical exercise). Often these are referred to as:

Indeed, there is a vast literature on “dual-task” experiments and interventions (Kramer et al., 1985; Hiyamizu et al., 2012; Kramer and Wong et al., 2015; Hosseini et al., 2017), which sometimes focus on the limitations of human abilities to manage two separate (non-interactive tasks) at once (e.g., walking and counting numbers backwards). Traditionally, the aim of dual-task training might focus on interference effects (Al-Yahya et al., 2011) and improving physical outcomes (e.g., decreasing falls) for impaired individuals (e.g., post-stroke), especially while managing dual tasks. More recently, studies have examined cognitive outcomes in dual tasks wherein there is more naturalistic interactivity (as in the cybercycle scenario above; Anderson-Hanley et al., 2012; as well as other interactive modalities such as dance: Foster, 2013; Kattenstroth et al., 2013; Dhami et al., 2015; Schoene et al., 2015; Burzynska et al., 2017; Marquez et al., 2017; Müller et al., 2017; Rehfeld et al., 2017). These recent studies seem to be converging on a similar cognitive-enhancing phenomenon that lends empirical support to the synergistic hypothesis outlined above and in part, elsewhere (Fissler et al., 2013). Recent reviews of the literature on the cognitive benefits of exergaming for older adults conclude the preliminary evidence is promising (Smith et al., 2010; Schoene et al., 2013; Bamidis et al., 2014; Barry et al., 2014; Chao et al., 2014; Ogawa et al., 2016; Zhu et al., 2016; Zilidou et al., 2016), but further research of the effects of these interactive interventions and the impact of specific components (e.g., passive stimulation vs. active cognitive training, aerobic vs. non-aerobic activity, etc.) is necessary.

We have previously hypothesized that the benefits of interactive physical and cognitive exercise may increase with increased mental effort and our lab published a pilot trial as a precursor to this present RCT, the Aerobic and Cognitive Exercise Study pilot (ACES-pilot; Barcelos et al., 2015). The ACES-pilot sought to investigate whether greater cognitive challenge while exergaming would yield differential outcomes in executive function and generalize to everyday functioning. Sixty-four community-dwelling older adults (mean age = 82) were randomly assigned to pedal a stationary bike, while interactively engaging on-screen with: (1) a low cognitive demand task (pedaling a steering along a virtual bike tour, referred to as exer-tour), or (2) a high cognitive demand task (pedaling and steering to chase dragons and score points in a 3D video game, referred to as exer-score). Executive function (indices from Trails, Stroop and Digit Span) was assessed before and after a single-bout and 3-month exercise intervention. A significant group × time interaction after 3 months of exergaming (Stroop; among 20 adherents). Those in the high cognitive demand group performed better than those in the low cognitive dose condition. Self-reported everyday function improved across both exercise conditions. These pilot data indicated that for older adults, cognitive benefit while exergaming increased concomitantly with higher doses of interactive mental challenge (Barcelos et al., 2015). The present study aims to replicate and extend that finding to MCI.

It is our hypothesis that interactivity can produce greater cognitive effects due to synergistic processes that compound or magnify the benefit in a non-linear way, perhaps by activation and utilization of neurobiological substrate of the mind-body interface that is evolutionarily adapted for success in naturalistic tasks (in this case, goal-directed motion through 3D space). While theory and research connecting cognitive processes to neurobiological pathways triggered by exercise in humans is expanding rapidly, there are indications of important links with various biomarkers (e.g., brain-derived neurotrophic factor [BDNF], insulin-like growth factor [IFG-1]; Cotman et al., 2007; Knaepen et al., 2010), including expression of microRNA (miRNA) in circulating exosomes (Pusic et al., 2016; Bertoldi et al., 2017), and brain structure and function (e.g., gray and white matter regions: Colcombe et al., 2006; hippocampus; Thomas et al., 2012; Erickson et al., 2015; Sexton et al., 2016). Animal models have more plainly linked certain differential, compounding or synergistic cognitive benefits with neurobiological phenomenon when both physical and mental exercise are provided (e.g., in laboratory mice exposed to enriched environments with physical and/or cognitive challenges; Greenough et al., 1999; Churchill et al., 2002; Olson et al., 2006; Galvan and Bredesen, 2007; Fabel et al., 2009; Voss et al., 2013; Jessberger and Gage, 2014). These studies and others, detail a variety of mechanisms and impacts linking mental and physical exercise to improved neuronal and brain health (e.g., via increased cerebral perfusion, neurogenesis, angiogensis, synaptogenesis; Greenough et al., 1999; Gage, 2002; Trachtenberg et al., 2002; Tsai et al., 2016; Kleemeyer et al., 2017), even detailing specific differential benefits (Black et al., 1990; Olson et al., 2006; Suo et al., 2016) such as cell proliferation with physical exercise, and cell survival with mental exercise (Van Praag et al., 2005; van Praag, 2008).

Since only a tiny fraction of older adults exercise at levels recommended by the ACSM and American Heart Association (AHA; Chodzko-Zajko et al., 2009), and physician recommendation appears to do little to change sedentary behaviors (Grandes et al., 2009), the novel exergame utilized in this study holds the promise of increasing compliance by virtue of the distracting components of the virtual reality environment and the interactive and challenging features of the videogame. Besides being a potentially effective way of engaging older adults in exercise, the present RCT augments prior research by exploring the neuropsychological benefits of interactive cognitive and physical training combined, rather than focusing on either alone (Colcombe and Kramer, 2003; Anguera et al., 2013), or in tandem, but lacking interactivity (Fabre et al., 2002; Oswald et al., 2006; Kraft, 2012; Suzuki et al., 2012; Hotting and Roder, 2013; Shatil, 2013; González-Palau et al., 2014; Satoh et al., 2014; Shah et al., 2014; Suo et al., 2016). By examining the neuropsychological effects some of the components separately (e.g., physical exercise and mental exercise alone), this study attempts to tease apart the unique contributions of each component to any benefit to cognition, as well as the potentially differential effect of low- vs. high-cognitive demands. The present research specifically examines the benefits of these behavioral interventions for community-dwelling older adults with or at risk for MCI and thus, attempts to extend previous findings to this more vulnerable population.

Finally, this RCT examines potential underlying mechanisms of effects of combined physical and mental exercise on cognition through the collection of neurobiological and neuroimaging data. Prior research has begun to clarify the role a number of biomarkers (primarily from serum, CNS, or saliva) that change in accord with exercise interventions and appear to be linked improvements in brain health that and/or promote improvements in cognition. For example, exercise has been shown to yield: increases in Brain-Derived Neurotrophic Factor (BDNF; Cotman et al., 2007; Coelho et al., 2013a; Leckie et al., 2014; Vaughan et al., 2014; Dinoff et al., 2016; Maass et al., 2016) and variable responses of insulin-like growth factor 1 (IGF-1; Lorens-Martín et al., 2009). Research linking traditional physical exercise and cognition in older adults has identified BDNF and IGF-1 as biomarkers linking cognitive function and healthy aging (Voss et al., 2010; Bellar et al., 2011; Erickson et al., 2012; Hotting and Roder, 2013; Phillips et al., 2014; Szuhany et al., 2014; Geerlings et al., 2015; Lara et al., 2015; Maass et al., 2016). BDNF plays an important role in neuronal growth and survival, it modulates neurotransmitters, and is involved in the cascade to promote neuronal plasticity, while IGF-1 has also been implicated as a mechanism in exercise-induced neuronal plasticity (Voss et al., 2010; Brown et al., 2013; Phillips et al., 2015; Maass et al., 2016). Cotman et al. (2007) has presented a model in which exercise induces activity of BDNF and IGF-1 in multiple pathways that facilitate: (a) learning, (b) neurogenesis, and (c) angiogenesis. Furthermore, some research has found increases in vascular endothelial growth factor with exercise (VEGF; Vital et al., 2014). While growth factors are typically said to increase with exercise, there are number of reports of decreases in inflammatory markers: C-reactive protein and Interleukin-6 (CRP and IL6; Thielen et al., 2016; Monteiro-Junior et al., 2017). Additionally, recent progressive research has also been examining the potential for circulating exosomes to serve as early markers of neuropathology, such as AD, to act as delivery vehicles for potentially reparative miRNA expressions, and even to play a positive role the neurbiological effects of exercise (e.g., Zhang et al., 2014; Kumar and Reddy, 2016; Pusic et al., 2016; Batistela et al., 2017; Bertoldi et al., 2017). Some promising research has pointed to miRNA-9 and miRNA-193 as linked to benefit in neurobiological processes such that they play a therapeutic role in dementia (e.g., Russell et al., 2013; Párrizas et al., 2015; Li et al., 2016; Riancho et al., 2017).

In sum, exercise appears to be able to trigger or enhance the function of complex cascades of neurobiological processes that have sometimes been linked to cognitive benefits or other expressions of brain or CNS health. It is likely that a number of those processes act on neurophysiological substrate to foster improved brain health that leads to improved cognition; some of those mediating phenonmena may even be visible through structural imaging.

Structural changes in certain regions of the brain have been found to follow exercise and are often linked to concomitant changes in cognition; for example, increases in the hippocampus (Lorens-Martín et al., 2009; Erickson et al., 2011), as well as the anterior cingulate cortex, dorsal lateral prefrontal cortex, and more broadly the prefrontal cortex (ACC, DLPC, and PFC; Gordon et al., 2008; Erickson et al., 2011; Weinstein et al., 2012; Curlik and Shors, 2013; Hayes et al., 2013; Nishiguchi et al., 2015; ten Brinke et al., 2015; Jonasson et al., 2017; Li et al., 2017). While the body of research has been growing with respect to linking physical exercise and cognition via biomarkers, scant literature has yet explored how these indicators and mechanisms react in the case of combined or interactive mental and physical exercise interventions in humans, wherein there might be somewhat differential or compounding beneficial effects given a two-for-one intervention (for a promising exception, see Eggenberger et al., 2016). The present study aims to address a number of these gaps and replicate or extend other findings in the literature.

This study is a partial replication and extension of the ACES-pilot (Barcelos et al., 2015) and it was hypothesized that, similar to that which was found in that prior pilot study: physical exercise interactive with effortful cognitive challenge (exer-score; Figure 2), would produce greater cognitive benefit than physical exercise that was interactive with relatively passive cognitive processing (exer-tour). We expected this previously observed phenomenon to extend to MCI specifically. The primary aim of the trial was for community-dwelling older adults with or at risk for MCI to engage their assigned intervention regularly for 6 months (longer than the ACES-pilot, which extended only to 3 months). Baseline to 6-month intervention (exer-tour vs. exer-score) were hypothesized to yield these effects:

All study procedures were approved by the appropriate Institutional Review Boards (i.e., including the PI's institution and the three medical centers where the study was conducted; see section Author Notes). Older adults with a diagnosis of MCI were initially sought via referrals from neurology and neuropsychology at three medical centers in a specific region of upstate New York where participants were to exercise (using a cybercyle placed at each center's physical therapy clinic). However, given difficulties enrolling patients (especially due to travel requirements, but also due to challenges targeting patients with MCI before progression to dementia), further IRB approval was obtained to expand recruitment by locating additional cybercycles at several more locations around the region (e.g., retirement communities, YMCAs, etc.) for a total of 14 sites. Enrollment was thus expanded to include self-referred community-dwelling older adults, aiming to include especially those that might be undiagnosed (because symptoms had not affected function), but yet who might meet criteria for, or could be said to be at risk for MCI (e.g., thus those that would meet screening criteria for MCI, herein referred to as “screened as MCI” or sMCI²). Participants were recruited using fliers, newspaper ads, and information sessions. The timeline for the conduct of the study was 2014–2016. Volunteers (n = 220; see CONSORT Figure 3 for details) were screened by phone and were excluded if they had known neurologic disorders (e.g., Alzheimer's, Parkinson's, or seizures) or functional limitations that would restrict participation in cognitive testing or exercise. After reviewing the informed consent form (ICF) and answering all questions, a signed document was obtained from all participants and their surrogate, if appropriate, based on the Impaired Decision Making Capacity screen (IDMC; Karlawish, 2008). Physician approval (PCP and if applicable, cardiologist) was obtained for all participants to engage in exercise as assigned. Enrollees (n = 111) were community-dwelling older adults with a mean age of 78.1 (SD = 9.9), who were predominantly female (66%), well educated (average years of education = 16.2, SD = 2.4) Causasians (three individuals self-reported minority ethnic/racial status). Participants scored on average 23.7 (SD = 3.1) on the Montreal Cognitive Assessment (MoCA; 30-point multidimensional scale, with higher scores indicative of better global cognitive function; Nasreddine et al., 2005; Freitas et al., 2012; Julayanont et al., 2014), such that 75% of enrollees were categorized at meeting screening criteria for sMCI (“screened as MCI” based on MoCA < 26; Nasreddine et al., 2005).

To provide an additional point of comparison of the relative effect of physical exercise alone vs. interactively combined with mental exercise, archival data was culled from our prior Cybercycle Study. In that study, 33 participants were randomly assigned to a traditional exercise or “pedal-only” condition in which participants pedaled a stationary bike (in many cases the same model as used in the present study), but without the virtual reality display (see below for between group comparisons at baseline; for additional details see Anderson-Hanley et al., 2012, 2014; Dimitrova et al., 2016).

Participants were initially randomly assigned to one of three conditions for 6 months: (1) exer-tour: physical exercise interactive with relatively passive, low cognitive load, virtual scenic bike tour; or (2) exer-score: physical exercise interactive with a relatively effortful, high cognitive demand, videogame (see Figure 2 for sample screen shots); or (3) game-only: the same videogame operated by a joystick or keyboard (no physical exercise was required). Exercise participants pedaled a virtual reality enhanced, recumbent stationary bike (Expresso S3R, from Interactive Fitness Holdings, LLC). Individuals in the exer-tour condition pedaled through various virtual scenic bike tours while steering along the path (but without significant consequence for not steering; that is the bike would coast along the curb and one could pass through other riders fluidly). Those in the exer-score condition pedaled through a scenic landscape where the goal was to score points by collecting different colored coins and corresponding colored dragons. Throughout the videogame (either exer-score or game-only), participants could navigate through bonus items to increase their speed and score, while avoiding penalties (e.g., steering into water). The exer-tour condition was presumed to require less mental engagement than the videogame conditions, as the game called for scoring and thus, potentially effortful planning, tracking, multi-tasking, and strategizing (a validity check of this assumption was confirmed by those in the exer-score condition who reported expending significantly greater “mental effort” than those in the exer-score condition; see Table 1). Participants were provided “thank you gifts” (e.g., water- bottle, mug, etc.) at each of evaluation (baseline, 3-month, and 6-month).

Given difficulty retaining participants in the game-only condition (due to preference for active/physical exercise, boredom once started, etc.), the protocol was again adjusted, with IRB approval, to allow randomly assigned game-only participants to switch to the exer-score condition at the 3-month mid-point evaluation. Additionally, game-only participants were also recruited separately with modest periodic remuneration provided. Upon enrollment, participants were phone screened for eligibility and administered the Impaired Decision-Making Capacity structured interview (IDMC; Veterans Administration Medical Center (VAMC), 2007) and provided informed consent (co-signed by a surrogate or legally-authorized representative as applicable and/or per the IDMC). Once scheduled for an initial evaluation, participants were mailed the ICF, demographic, health and fitness history questionnaires. If they were willing, an MRI (3T) of the brain was scheduled. At the baseline evaluation, a saliva sample was collected (passive drool), and they were administered a neuropsychological test battery (specified below). Individuals were trained in the use of the equipment for their assigned condition and underwent a single bout of exercise for 20 min. Participants were asked to maintain a target heart rate level, which was calculated using the Karvonen equation (McAuley et al., 2011) and measured via steering hand-grips built into the cybercycle (displayed on screen for participant monitoring and captured by onboard computer for later data extraction and analysis). Post-testing was conducted following the single bout⁴ (SB) of exercise.

Following the baseline (BL) evaluation, individuals were instructed to exercise for at least 20 min at least twice a week, and to gradually increase exercise duration to 45 min and frequency to at least three to five times per week until the 3-month (3M) mid-point evaluation, and then maintain that pattern though a 6-month (6M) final evaluation. Participants were instructed to aim toward their individualized specific target heart rate (per above) throughout the intervention period. Participants were also asked to document their exercise sessions on log pages provided in a binder and used to calculate adherence statistics (e.g., frequency, heart rate average, etc.); additionally, the computer onboard the cybercycle captured similar data which was used for spot verification. A final evaluation, including repeat neuropsychological, biomarker, and neuroimaging assessments, was conducted at the end of the 6-month intervention period.

The following biomarker and neuroimaging data were collected from some willing and able participants, who comprised a small subset of the enrolled participants. Due to the small and incomplete sample, we report these as pilot data to examine comparisons that were planned a priori and provide tentative findings, which may be useful in directing future research.

Biomarker samples were sought from all participants, but not all were willing or able to provide saliva samples (data from completers was available from a maximum of n = 16 for analysis).¹¹ Target analytes included: BDNF, CRP, IGF-1, IL-6, and VEGF. Due to low concentrations of IGF-1 in the samples collected, the assay results were below the limit of detection on too many samples and this assay was excluded from analyses. Partial correlations (controlling for age and sex; Table 4) were conducted to examine the change from baseline to 6M in biomarkers related to change in the primary outcome measure, executive function (StroopA/C) which, per above, changed significantly with the intervention. Similarly, change in biomarkers were correlated with a secondary outcome that was impacted significantly by both interventions, was verbal memory, and we chose to focus on delayed verbal memory specifically (ADAS errors), since one of the more salient cognitive functions to impact for MCI patients. Finally, the exercise dose, based on average number of rides, was examined for association with the biomarkers change to evaluated the possibility of a dose effect. Exercise dose (rides) was found to correlate significantly with an increase in BDNF (r = 0.50, p = 0.04). Delayed recall errors showed a trend toward a moderate inverse correlation with increased VEGF such that better memory performance tended to coincide with increasing VEGF (r = −0.42, p = 0.08). Exosome analyses revealed a significant positive correlation between miRNA-9 expression with improved StroopA/C performance (r = 0.98, p = 0.002).

Neuroimaging (3T structural MRI) was grant-funded and sought from all participants, but not all were willing or able to undergo imaging (data from completers was available from a maximum of n = 8 for analysis). Partial correlations, just as described above, are reported in Table 5. Greater exercise dose (number of rides over 6M) was positively correlated with increasing PFC (r = 0.80, p = 0.003) and ACC (right; r = 0.70, p = 0.05; Figure 6). Verbal memory (delayed recall) errors were inversely related to increasing DLPFC, such that improvement in memory corresponded to increasing volume (r = −0.80, p = 0.01; Figure 6).

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer DM and handling Editor declared their shared affiliation.