Brain and cognitive ageing: The present, and some predictions (…about the future)

Abstract

Experiencing decline in one's cognitive abilities is among the most feared aspects of growing old [53]. Age-related cognitive decline carries a huge personal, societal, and financial cost both in pathological ageing (such as dementias) and also within the non-clinical majority of the population. A projected 152 million people worldwide will suffer from dementia by 2050 [3]. The early stages of cognitive decline are much more prevalent than dementia, and can still impose serious limitations of performance on everyday activities, independence, and quality of life in older age [5], [60], [80]. Cognitive decline also predicts poorer health, adherence to medical regimens, and financial decision-making, and can herald dementia, illness, and death [6], [40]. Of course, when seeking to understand why some people experience more severe cognitive ageing than others, researchers have turned to the organ of thinking for clues about the nature, possible mechanisms, and determinants that might underpin more and less successful cognitive agers. However, that organ is relatively inaccessible, a limitation partly alleviated by advances in neuroimaging. Here we discuss lessons for cognitive and brain ageing that have come from neuroimaging research (especially structural brain imaging), what neuroimaging still has left to teach us, and our views on possible ways forward in this multidisciplinary field.

Keywords: Brain ageing; Diffusion MRI; Epidemiology; Longitudinal studies; Review; Structural MRI.

Fig. 1

Individual differences in brain structural ageing hallmarks. a) Different participants, ordered from top left to bottom right by severity of global atrophy (parenchymal volume fraction: total brain volume / intracranial volume). MRI-visible markers include global cerebral atrophy, cortical thinning, and ventricular enlargement alongside sulcal widening as CSF (black) replaces brain tissue. b) T2 FLAIR sequence shows increasing severity of white matter hyperinensities (volume increasing from top left to bottom right). Participants from this figure come from the Lothian Birth Cohort 1936 wave 2: community-dwelling adults aged ∼ 73 years at time of scanning. Participants between panels do not correspond. c) Longitudinal total brain volume measurements from 3189 individuals in UK Biobank (Field ID: 20510) with local polynomial regression lines (loess) for females (red) and males (blue). d) Longitudinal white matter hyperintensity volume measurements from 3152 individuals in UKB Biobank (Field ID: 25781) with local polynomial regression lines (loess) for females (red) and males (blue). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)