The inaugural Indianapolis 500-Mile Race, one of the world’s most prestigious – and exhausting – car races, which is traditionally started by the command cited above, was held in 1911.

In the same year, Alois Alzheimer published his first more detailed scientific manuscript (Alzheimer, Reference Alzheimer1911) on presenile and senile dementing processes. Ten years before, the German neurologist had examined his 51-year-old female patient Auguste Deter in Frankfurt am Main for the first time, who was suffering, amongst other symptoms, from huge problems with memory and language. When he performed an autopsy of her brain in Munich five years later, he detected neurofibrillary tangles and plaques and presented these findings at a scientific psychiatric conference in Tübingen (Alzheimer, Reference Alzheimer1907). In 1910, Emil Kraepelin, Chair of the University Hospital for Psychiatry in Munich, proposed to call this illness alzheimer’s disease (AD) in the 8th edition of his psychiatry textbook (Kraepelin, Reference Kraepelin1909/1910).

More than 100 years have passed since and both races – the “Indi-500” and the search for a causal cure for AD – still continue today. Although diagnostic possibilities have increased substantially during the last decades, there is currently no cure in sight. Instead, it seems like the quest is going in circles that resemble the 200 laps of the annual car race.

In the last years, nonpharmacological interventions like music therapy, reminiscence therapy, occupational therapy, or sports therapy have been rediscovered by researchers and have recently been recommended as first-line treatment options by current guidelines (Nice 2018; Rabins et al., Reference Rabins, Rovner, Rummans, Schneider and Tariot2014).

We have learned that traditional cognitive remediation interventions that have proven effective in schizophrenic (Wykes et al., Reference Wykes, Huddy, Cellard, McGurk and Czobar2011) and, partly, in depressive individuals (Kim et al., Reference Kim, Bahk, Oh, Lee, Lee and Choi2018) cannot be transferred to dementia patients without modifications. The first meta-analysis (Sitzer et al., Reference Sitzer, Twamley and Jeste2006) found moderate effects for cognitive training to slow down cognitive decline, but when the authors considered only high-quality studies, this effect was dramatically smaller and no longer significant. Why was that so? The high-quality studies used attention-placebo control groups and it might be that dementia patients simply benefit from general cognitive stimulation. In other words, while training of specific cognitive functions was superior to treatment as usual, it was no more effective than any arbitrary cognitively stimulating activity. Therefore, the researchers wondered if cognitive stimulation in itself might be effective. And indeed, stable effects could be found (Woods et al., Reference Woods, Aguirre, Spector and Orrell2012). In a recent review about the evidence profile of cognitive training and stimulation, the WHO supports this view and adds that the type of stimulation (passive vs. active) might further modify this effect (WHO, 2019). Everyone who conducts cognitive groups for elderly people suffering from mild cognitive impairment (MCI) or dementia, has faced the problem of participants remaining passive and refraining from active participation and has wondered how to get them to be more engaged.

Gamification, on the other hand, defined as the use of game design elements in nongame contexts, is a feature that has proven to be highly engaging and to boost participant motivation (Lumsden et al., Reference Lumsden, Edwards, Lawrence, Coyle and Munafò2016). The term “serious gaming” has been coined to denote the use of video games developed for a primary purpose other than enjoyment. If the reader has any doubt about how engaging even quite simple game designs can be, it might be enlightening to watch a video of “Tennis for Two”, one of the first video games developed by William Hingbotham in 1958 (https://www.bnl.gov/about/history/firstvideo.php). This game was played by two players operating separate controllers connected to an analogue computer with an oscilloscope that served as a screen. When the game was first introduced at a visitor’s day of the Brookhaven National Laboratory, a huge queue of people lined up for a chance to try this new kind of entertainment.

But back to gamification in the present time. The benefits of gamification described by Lumsden and colleagues were mostly shown for adult or adolescent participants, samples that are not comparable to dementia or mild cognitive impairment patients. They were used to devices like computers, smartphones, or tablets, while the majority of the elderly patients that would qualify for such interventions have no such experience. Moreover, the cognitive deficits in MCI or mild dementia are more pronounced, which means that participants might be overstrained by gamified approaches.

However, recent data show that modern electronic devices (Øksnebjerg et al., Reference Øksnebjerg, Woods, Janbek and Waldemar2019; Jodrell and Astell, Reference Joddrell and Astell2016) – and even social robots (Chen et al. Reference Chen, Moyle, Jones and Petsky2020) – are usually accepted without problems by dementia patients and novel tasks generated with these devices are experienced as especially attractive (Astell et al., Reference Astell2016). Consequently, increasing engagement time – especially when studies focused on connecting participants by the use of technology (Du Toit et al., Reference Du Toit, Best and Lovarini2019) – and better recall during reminiscence therapy was found when touchscreen technology was used (Pringle and Somerville, Reference Pringle and Somerville2013). In a small study, we examined how elderly people with varying degrees of cognitive impairment would manage several group tasks developed by our workgroup for tablets that were interconnected by bluetooth (Trapp et al., Reference Trapp, Kilic, Röder, Lautenbacher and Hajak2019). Despite the fact that none of the participants had any experience with computers or touch screen devices, we found two main results: firstly, regardless of their degree of cognitive impairment, people enjoyed playing the tablet group games more than dealing with comparable paper and pencil tasks. Secondly, the learning curve in handling the touchscreen devices was independent of their degree of cognitive decline. Dementia patients learned to perform the swipe and tap operations as quickly as cognitively less impaired participants, although, of course, their performance was significantly poorer.

With these results in mind, would it not be fantastic if everyone working with elderly people suffering from MCI or dementia could immediately translate their expertise and creativity into gamified diagnostic or therapeutic tools? It is possible! By using modern game engines, any researcher who can plan an intervention and analyze study data is able to develop 2D or 3D games that realize their diagnostic or therapeutic ideas.

The contribution of Jin-Hyuck Park (Park, Reference Park2020) in this issue is based on the findings of an immersive virtual reality (VR) path integration test (Howett et al., Reference Howett2019) and represents an excellent and impressive example for such a straightforward approach. In the study of Howett and colleagues, participants had to successively walk to three markers in a VR environment and then, in the absence of any marker, back to the location they had started from. Euclidean distance between the participants’ estimate of the first location and its actual position was used to assess performance. Compared to participants without cognitive impairment, MCI patients performed more poorly. Even more interesting, MCI patients with positive cerebrospinal fluid biomarkers, and thus with an increased risk to develop dementia, performed significantly worse than biomarker-negative MCI subjects. The path integration test outperformed sophisticated neuropsychological measures with regard to classification of biomarker-positive and biomarker-negative MCI patients. Finally, performance in the path integration task correlated with relevant brain structures (volume of the total entorhinal cortex and the posterior medial entorhinal cortex where the grid cells – involved in spatial navigation – lie).

Park decided to use a similar VR paradigm where adults with MCI patients repeatedly had to find previously visited locations in a VR environment. As allocentric spatial cognition is more susceptible to decline in age and is especially impaired in MCI and AD patients (Wood et al., Reference Wood, Moodley, Lever, Minati and Chan2016), the allocentric load of the task was increased firstly because boundary cues (“rocks” and “water”) were used and secondly because participants had to navigate using a joystick instead of physically walking in a mapped out square with a VR headset on. The group receiving 24 training sessions improved significantly in a spatial cognition as well as a verbal memory test compared to a control group. Both cognitive domains have been found to be related to hippocampal function. Together with the grid cells of the medial EC, this brain structure is assumed to form the neural basis of cognitive maps.

Remarkably, both studies used the same game engine (Unity) to create their VR game paradigm and the VR task used by Park was not programmed by a computer scientist, but by one single occupational therapist with many years of clinical experience.

Therefore, readers may feel encouraged to follow this example and to pick a game engine that suits them best. (The Unity engine might be a good choice, but there are many more.) Let yourselves be inspired by the numerous examples and tutorials that can be found on the internet. And finally, start your engine to develop new and exciting diagnostic and therapeutic tools that can be used to mitigate cognitive decline in older people suffering from AD or MCI.