Regional Cortical Thickness Predicts Top Cognitive Performance in the Elderly

Abstract

While aging is typically associated with cognitive decline, some individuals are able to diverge from the characteristic downward slope and maintain very high levels of cognitive performance. Prior studies have found that cortical thickness in the cingulate cortex, a region involved in information processing, memory, and attention, distinguish those with exceptional cognitive abilities when compared to their cognitively more typical elderly peers. Others major areas outside of the cingulate, such as the prefrontal cortex and insula, are also key in successful aging well into late age, suggesting that structural properties across a wide range of areas may better explain differences in cognitive abilities. Here, we aim to assess the role of regional cortical thickness, both in the cingulate and the whole brain, in modeling Top Cognitive Performance (TCP), measured by performance in the top 50th percentile of memory and executive function. Using data from National Alzheimer’s Coordinating Center and The 90 + Study, we examined healthy subjects aged 70–100 years old. We found that, while thickness in cingulate regions can model TCP status with some degree of accuracy, a whole-brain, network-level approach out-performed the localist, cingulate models. These findings suggests a need for more network-style approaches and furthers our understanding of neurobiological factors contributing to preserved cognition.

Superficial white matter across the lifespan: volume, thickness, change, and relationship with cortical features

“…The brain is known to undergo significant changes during the lifespan. Studies of brain volume, white and gray matter tissue volume (Fan et al, 2019; Fjell and Walhovd, 2010; Hedman et al, 2012; Lebel et al, 2012; Pfefferbaum et al, 1992; Scahill et al, 2003; Steffener, 2021), cortical thickness (Dominguez et al, 2021; Frangou et al, 2022; Habeck et al, 2020; Hou et al, 2021), microstructure measures (Beck et al, 2021; Fan et al, 2019; Lebel et al, 2012; Storsve et al, 2016), and myelination (Grydeland et al, 2019) have described patterns of neuroanatomical variation that provide insight into the biological sequelae of development and aging. For example, well characterized waves of brain growth occur, with gray matter volume increasing until middle childhood (~ 6 years), followed by volume decreases from young adulthood and into late adulthood, while white matter reaches peak volume in adulthood (20-40 years), again leveling off and decreasing into late adulthood, with both tissues experiencing accelerated atrophy during late adulthood (Bethlehem et al, 2022; Hedman et al, 2012; Lebel et al, 2012; Scahill et al, 2003).…”

“…For example, features such as SWM volume or thickness of the SWM sheet below the cortex have not been characterized. Unlike the cortical thickness and cortical volume metrics that have been thoroughly investigated, are easily quantified using standard toolsets (Destrieux et al, 2010; Fischl, 2012), and have proven strong associations with cognition, aging, and disease (Dickie et al, 2020; Dominguez et al, 2021; Fjell and Walhovd, 2010; Frangou et al, 2022; Gao et al, 2018; Habeck et al, 2020; Hou et al, 2021; Mattsson et al, 2018; Meyer et al, 2019; Racine et al, 2018; Roe et al, 2021; Steffener, 2021; Storsve et al, 2016; Tustison et al, 2019; Vogt et al, 2019), SWM thickness and SWM volume have not been investigated or quantified. Towards this end, we study three high-quality datasets that span the human lifespan (ages 5-100, N=2421 subjects), and implement advances and innovations in SWM tractography.…”

Defining exceptional cognition in older adults: A systematic review of cognitive super‐ageing

“…More females were included in cognitively high-performing than control cohorts in six of these studies 11,18,19,28,49,53 while education levels were significantly higher in six cognitively high performing cohorts compared with controls. [11][12][13]15,28,49 Rates of hypertension and diabetes were higher in the cognitively average than the super-ageing cohort in one study but not significantly so. 43 [64][65][66] Processing speed has been shown to decline from the third decade of life while memory performance may begin to decline in the 50s and executive function especially after age 70 but more complex reasoning capabilities beginning around age 45.…”

“…One study selected performers in the top 20th percentile on a memory composite score 45 and one study those in the 50th percentile for episodic memory and executive function. 28 Most studies relied on cross-sectional assessment of cognition with only nine requiring maintenance of exceptional performance over time and one study further characterising participants by stable, worsened or improved performance at follow up. 14 Baran et al required 'supernormals' to maintain a positive mean slope of executive function and episodic memory performance over a 5-year period.…”

“…5,19 Episodic memory performance has frequently been selected as a marker of cognitive super-ageing 5,26 with executive function, processing speed and composite cognitive scores less commonly utilised. 14,27,28 Some studies have also identified individuals without cognitive decline over time.…”