Neuroimaging has provided salient information on the changing brain tissue macro and micro-structure, cortical and sub-cortical morphology and morphometry, and functional connectivity across the lifespan. Studies of volumetric change describe a non-linear pattern characterized by rapid growth of the brain’s white and gray matter throughout infancy and childhood, peaking in the second to fourth decades of life, followed by a slow but progressive decline throughout adulthood [1–8]. Tissue-wise and regional differences exist, with cortical gray matter reaching its maximal value during adolescence while global white matter volume is maximal between 30 and 40 years of age [2, 6, 8]. Subcortical structures, similarly, follow differential growth trajectories, with peak values occurring throughout the second decade of life [5, 7]. Overall, patterns are generally preserved between males and females [8, 9], though absolute volume is, on average, greater in males in large part due to their larger physical body and head size.
Patterns of brain change across the lifespan have further been associated with emerging and receding cognitive skills and abilities. Volume reductions in memory-related regions (e.g., hippocampus) have been associated with age-related memory changes among otherwise healthy older adults, as well as in mild cognitive impairment and Alzheimer’s disease [10–13]. More generally and beyond memory function, global and regional brain volumes have been associated with differential executive functioning skills [12, 14, 15], processing speed [16, 17], and general intelligence [18, 19].
Despite the utility of neuroimaging to the study of healthy aging and neurodegenerative disorders, MRI studies are expensive and often limited to specialized university imaging centers or larger research hospitals. As consequence, they typically have relatively small sample study sizes (n < 30) and rely on populations of convenience, i.e., geographically proximal participants who are able to travel independently or have nearby family members or other support. These factors can bias the study population towards particular sociodemographic phenotypes (e.g., higher socioeconomic and/or educational backgrounds, individuals living independently with lower disease burden, etc.) that may affect the generalizability of findings and conclusions. Large-scale neuroimaging initiatives such as the Alzheimer’s Disease Neuroimaging Initiative (ADNI) [20], the Human and Lifespan Connectome Projects [21, 22], and the UK Biobank [23] aim to provide study sizes large enough to avoid potential biases (or enable direct modeling of them). These large studies, however, are financially expensive and logistically complex, and still require participating individuals to travel to centralized imaging and research centers.
Over the past 5–10 years, internet and tabled-based tools have made scalable and remote cognitive assessments feasible [24–26]. This trend toward remote assessment has been further accelerated by the COVID-19 pandemic, which forced many research and healthcare centers to seek reliable and reproducible online alternatives to traditional in-person visits and assessments [25, 27, 28]. These tools offer the potential to reach beyond the traditional study populations and include participants from a wide range of geographic, demographic, and socioeconomic backgrounds. MindCrowd [29–32] is one such accessible and easy-to-use web-based platform for cognitive and demographic assessment, designed specifically to overcome challenges with small sample-size studies and to increase inclusive and diverse participation. Participants over 18 years of age are able to anonymously provide general background sociodemographic information (e.g., age, biological sex, education attainment, spoken and written languages, and country of residence). If willing, more granular data may also be provided, including details of medical, health, and lifestyle factors (e.g., marital status, handedness, race, ethnicity, number of daily prescription medications, a first-degree family history of dementia, and yes/no responses to the following: seizures, dizzy spells, loss of consciousness for more than 10 min, high blood pressure, smoking, diabetes, heart disease, cancer, stroke, alcohol/drug abuse, brain disease and/or memory problems). Participants can also optionally provide identifiable name and residential address information for follow-up studies, as well as indicate a willingness to provide biosample collections and participate in ancillary studies.
Cognitive assessment on MindCrowd consists of a simple visual reaction time (svRT) and a paired-associates learning (PAL) task. svRT and PAL are quick and sensitive tests of processing speed and associative episodic memory function, respectively. Past work has shown these cognitive functions are affected in the earliest stages of cognitive impairment and Alzheimer’s Disease (AD), but also reflect the general decline in cognitive performance in healthy aging. The ability to capture data from hundreds of thousands of participants at a relatively low cost and without time-consuming and intensive in-person visits has allowed the team behind MindCrowd to investigate the impact of diverse family, medical history, and genetic factors on cognitive performance across the adult lifespan [29, 32], and to identify potential cases of previously undiagnosed cases of cognitive impairment and dementia [31].
While reliable remote and internet-based cognitive assessments are becoming increasingly common, remote collection of MRI data has been impracticable due to the size and weight of common 1.5 and 3 Tesla (T) systems, as well as their electrical requirements, and helium and maintenance needs. Though semi-trailer 18-wheeler mounted 1.5T systems are broadly available throughout North America, Europe, and Asia, they share the size, weight, and electrical needs of their sited brethren, and are designed for institutional use as adjuncts to static systems installed at hospitals or clinics, or as semi-permeant solutions for smaller institutions. These systems require specially installed concrete parking pads and high voltage electrical supplies and are not designed for use at a participant’s home. However, advancements in MRI systems that operate at lower magnetic field strength (I.e., less than 100mT) with permanent or resistive magnet arrays present an alternative to conventional systems with the possibility of enabling “residential MRI” - truly remote neuroimaging performed at a participant’s home, assisted living facility, or other residential or convenient and nearby location (e.g., library, shopping center, etc.) [33]. While lower field systems are not replacements for higher field strength scanners, and currently offer a limited repertoire of imaging contrasts and methods, they do allow for high-quality anatomical imaging [34] and have shown replication of developmental patterns observed at higher field strength [35].
As much of the past work with low field scanners has focused on clinical applications (e.g., identification of pediatric hydrocephalus [36], multiple sclerosis [37], stroke [38], and other indications [39]), its utility in neuroscience research, such as associations between brain morphology and cognitive performance, remains unknown. Like remote cognitive assessments, the ability to reliably collect high-quality and information-rich MRI data at a participant’s home could bring new opportunities to the study of aging, cognitive decline, cognitive impairment, and dementia. Remote MRI would allow the inclusion of participants with mobility challenges or who lack transportation options, those who live long distances away from research centers and outside traditional recruitment areas, and those with competing family, work, or other time commitments. The reduced expense of low field strength MRI may further allow for increased study population size, improving statistical power and generalizability of study findings.
To this end, in this study we sought to determine the feasibility of combining remote cognitive assessment via MindCrowd with mobile low field MRI in a modified Ford Transit cargo “scan van” equipped with a 64mT MRI scanner [40] to (1) Determine the feasibility of collecting reliable remote MRI and cognitive data in adults and elderly individuals; and (2) Replicate previously reported associations between regional brain volumes and cognitive performance with an established cognitive assessment, PAL, with substantial normative data against which to compare.