Neurocognitive decline is a health problem that is associated with ageing. More often than not, age-related cognitive decline may be indicative of the onset of mild cognitive impairment (MCI), or even more severe neurocognitive disorders such as Alzheimer's and Parkinson's disease-both of which will eventually lead to dementia. Cognitive decline and neurocognitive disorders can often lead to the gross deterioration in one's quality of life. Depending on the severity and duration of the onset of the neurocognitive decline, patients may experience anything from forgetfulness or learning difficulties, to major issues such as a decreased capacity for decision-making, confusion, disorientation, communication problems, and social behavioral issues. All of these issues could impede one's ability to care for one's self, which may also lead to the increased reliance and burden on caretakers.

On a global scale, it is estimated that about 46.8 million people suffer from dementia or other dementia subtypes. That number is expected to increase by 68% over the next 30 years. The current economic burden of dementia and other dementia subtypes is evaluated at $818 billion, with projections expecting cost to rise to $2 trillion by the year 2030. In Singapore specifically, the estimated cost of dementia was reported at $1.4 billion per year, with costs expecting to rise in tandem with Singapore's rapidly aging population. Given the impact and impending threats of neurocognitive decline, it is clear that intentional efforts to combat neurocognitive decline is necessary.

To date, experts in the field have yet to identify specific causes of neurocognitive decline. This is due to the heterogeneity of neurocognitive decline and the diseases associated with it. As such, it has been challenging to find definitive causes and cures for neurocognitive decline. That said, there are several risk factors associated with neurocognitive decline and dementia. Risk factors such as age and genetics are fairly predictive of neurocognitive decline, but are, by nature, unmodifiable. However, risk factors such as, but not limited to, cardiovascular problems, physical activity, cognitive training, and social engagement are possible and much easier to modify. Hence, there has been a preponderance of interventions in the field that targets those specific modifiable risk factors with the intention of manipulating current or future neurocognitive outcomes. For example, cognitive training (CT) has been a target for interventions that promote the delay and/or prevention of neurocognitive decline. Over the past few decades, CT programs in the field have evolved to computerized, gamified, and self-manned versions that usually target specific areas of cognition such as memory, attention, decision-making, inhibition, or a combination of those areas.

Similarly, physical activity (PA) has also been a target for interventions that promote the delay and/or prevention of neurocognitive decline. Studies with PA-specific interventions have also shown to positively influence neurocognitive function in patients with mild cognitive impairment, as well as those who are at risk of developing Alzheimer's Disease. Evidence also show that PA can delay the effects of neurocognitive decline in patients with existing cognitive decline, dementia, and other dementia subtypes.

Interestingly, there has been a recent surge of interventions in the field that amalgamates both PA and CT elements. This shift in direction in the field acknowledges the symbiotic relationship between CT and PA with regards to neurocognitive outcome. Many of these studies set out to investigate the effects of 'exergaming' (a portmanteau of exercise and gaming) on neurocognitive function in the older adult population with varying neurocognitive capacity ranging from healthy to declining. Exergaming interventions have shown to improve the subjects' executive function and cognitive performance after the intervention period as compared to the subject controls. The effects of exergaming interventions were also able to delay the onset of mild cognitive impairment in healthy subjects as compared to the healthy controls in some studies. That said, such programs are still limited by factors such as poor personalization capabilities, substandard controls, and high attrition rates (lack of participant engagement). Additionally, studies of such nature are far and few between in Asia, making it unclear if similar results can be replicated in an Asian-majority demographic like Singapore.

To address these issues, the current study aims to use a novel personalized multimodal physical and cognitive brain computer interface (BCI) training system to delay and/or prevent neurocognitive decline, and enhance neurocognitive function. The investigators' proposed training system integrates a stationary cycling intervention and a corresponding personalized BCI cognitive training program. The BCI cognitive training program uses machine learning technologies and elderly-friendly user-interface/user-experience (UI/UX) game design to actively track individual neurocognitive status, provide feedback in real-time, and encourage older adults to persist in training for the long term. The investigators also seek to customize the program's UI/UX by employing locally-relevant materials to reduce accessibility barriers and increase participant engagement. For the purposes of this study, all instructions and interventions will be delivered in English. However, there are plans for future iterations of this program to include other local languages to facilitate the use of the program by non-English speaking Singaporean elderly.