Specific and general relationships between cortical thickness and cognition in older adults: a longitudinal study

Hou, Mingzhu; Chastelaine, Marianne de; Donley, Brian E.; Rugg, Michael D.

doi:10.1016/j.neurobiolaging.2020.11.004

Cited by 9 publications

(15 citation statements)

References 62 publications

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“…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).…”

Section: Discussionmentioning

confidence: 99%

“…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.…”

Section: Introductionmentioning

confidence: 99%

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

Schilling

Archer

Rheault

et al. 2022

Preprint

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Superficial white matter (SWM) represents a significantly understudied part of the human brain, despite comprising a large portion of brain volume and making up a majority of cortical structural connections. Using multiple, high-quality, datasets with large sample sizes (N=2421, age range 5-100) in combination with methodological advances in tractography, we quantified features of SWM volume and thickness across the brain and across the lifespan. We address four questions: (1) How does U-fiber volume change with age? (2) What does U-fiber thickness look like across the brain? (3) How does SWM thickness change with age? (4) Are there relationships between SWM thickness and cortical features? Our main findings are that (1) SWM volume shows unique volumetric trajectories with age that are distinct from gray matter and other white matter trajectories; (2) SWM thickness varies across the brain, with patterns robust across individuals and across the population at the region-level and vertex-level; (3) SWM shows nonlinear changes across the lifespan that vary across regions; and (4) SWM thickness is associated with cortical thickness and curvature. For the first time, we show that SWM volume follows a similar trend as overall white matter volume, peaking at a similar time in adolescence, leveling off throughout adulthood, and decreasing with age thereafter. Notably, the relative fraction of total brain volume of SWM continuously increases with age, and consequently takes up a larger proportion of total white matter volume, unlike the other tissue types that decrease with respect to total brain volume. This study represents the first characterization of SWM features across the lifespan and provides the background for characterizing normal aging and insight into the mechanisms associated with SWM development and decline.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Schilling

Archer

Rheault

et al. 2022

Preprint

View full text Add to dashboard Cite

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“…de Chastelaine et al, 2019;Hou et al, 2021). The MMSE was excluded from the PCA because (which was not certified by peer review) is the author/funder.…”

Section: Principal Components Analysismentioning

confidence: 99%

“…Analogously, associations between thickness and specific cognitive abilities are also largely eliminated after the variance shared across different cognitive measures is controlled for (Hou et al, 2021;Krogsrud et al, 2021;Tsapanou et al, 2019;Salthouse et al, 2015). Thus, findings indicative of selective associations between regional cortical thickness and domain-specific cognitive performance seem largely to reflect a single association between global cortical thickness and mean cognitive ability.…”

mentioning

confidence: 99%

“…Moreover, many studies reporting regionally specific associations between thickness and cognitive performance did not account for the strong correlations that exist between regional thickness measures. When this inter-dependency is accounted for, little evidence of regionally specific associations between cortical thickness and cognitive performance remains (Hou et al, 2021;Kranz et al, 2018;Krogsrud et al, 2021;Salthouse et al, 2015; but see Lee et al, 2016).…”

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confidence: 99%

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Cortical thickness, gray matter volume and cognitive performance: a cross-sectional study of the moderating effects of age on their inter-relationships

Chastelaine¹,

Srokova²,

Hou³

et al. 2022

Preprint

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In a sample comprising younger, middle-aged and older cognitively healthy adults (N = 375), we examined associations between mean cortical thickness, gray matter volume (GMV) and performance in four cognitive domains - memory, speed, fluency and crystallized intelligence. In almost all cases, the associations were moderated significantly by age, with the strongest associations in the older age group. An exception to this pattern was identified in a younger adult sub-group aged less than 23 yrs, when a negative association between cognitive performance and cortical thickness was identified. Other than for speed, all associations between structural metrics and performance in specific cognitive domains were fully mediated by mean cognitive ability. Cortical thickness and GMV explained unique fractions of the variance in mean cognitive ability, speed and fluency. In no case, however, did the amount of variance jointly explained by the two metrics exceed 7% of the total variance. These findings suggest that cortical thickness and GMV are distinct correlates of domain-general cognitive ability, that the strength and, for cortical thickness, the direction of these associations is moderated by age, and that these structural metrics offer only limited insights into the determinants of individual differences in cognitive performance across the adult lifespan.

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Superficial white matter across development, young adulthood, and aging: volume, thickness, and relationship with cortical features

et al. 2023

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Specific and general relationships between cortical thickness and cognition in older adults: a longitudinal study

Cited by 9 publications

References 62 publications

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

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

Cortical thickness, gray matter volume and cognitive performance: a cross-sectional study of the moderating effects of age on their inter-relationships

Superficial white matter across development, young adulthood, and aging: volume, thickness, and relationship with cortical features

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