Differential Patterns of Gyral and Sulcal Morphological Changes During Normal Aging Process

Lin, Hsin; Huang, Chu-Chung; Chou, Kun Hsien; Yang, Albert C.; Lo, Chun Yi Zac; Tsai, Shih Jen; Lin, Ching Po

doi:10.3389/fnagi.2021.625931

Cited by 17 publications

(16 citation statements)

References 72 publications

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“…However, while mean curvature is useful to distinguish convex from concave shapes, this binary discrimination is insufficient to analyze the true topology of the cortex. It is not the case that negative and positive mean curvature strictly denote gyri and sulci, respectively, although this has been used previously as a heuristic (Lin et al, 2021). Both gyri and sulci have vertices with both positive and negative mean curvature (Figures 8 and 10a).…”

Section: Mean Curvaturementioning

confidence: 99%

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Cortical thickness systematically varies with curvature and depth in healthy human brains

Demirci

Holland

2022

Human Brain Mapping

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Cortical thickness varies throughout the cortex in a systematic way. However, it is challenging to investigate the patterns of cortical thickness due to the intricate geometry of the cortex. The cortex has a folded nature both in radial and tangential directions which forms not only gyri and sulci but also tangential folds and intersections.In this article, cortical curvature and depth are used to characterize the spatial distribution of the cortical thickness with much higher resolution than conventional regional atlases. To do this, a computational pipeline was developed that is capable of calculating a variety of quantitative measures such as surface area, cortical thickness, curvature (mean curvature, Gaussian curvature, shape index, intrinsic curvature index, and folding index), and sulcal depth. By analyzing 501 neurotypical adult human subjects from the ABIDE-I dataset, we show that cortex has a very organized structure and cortical thickness is strongly correlated with local shape. Our results indicate that cortical thickness consistently increases along the gyral-sulcal spectrum from concave to convex shape, encompassing the saddle shape along the way. Additionally, tangential folds influence cortical thickness in a similar way as gyral and sulcal folds; outer folds are consistently thicker than inner.

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Section: Mean Curvaturementioning

confidence: 99%

“…It is important to consider cortical thickness not as a global property of an entire brain, but rather a local, spatially varying property. For instance, thinning in Alzheimer's disease is systematically nonuniform, with sulci thinning and degenerating more than gyri (Lin et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Cortical thickness systematically varies with curvature and depth in healthy human brains

Demirci

Holland

2022

Human Brain Mapping

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“…The gyrification cluster in the pre/postcentral gyrus showed the opposite relationship with step length (Figure 4), where increasing gyrification was associated with less asymmetry in step length. Since sulcal depth is generally larger in younger adults (Lin et al, 2021) and gyrification is higher in younger adults (Lamballais et al, 2020), the current results might seem to suggest conflicting findings for step length. That is, the healthier brain metric (more sulcal depth and more gyrification) had differing relationships with step length asymmetry.…”

Section: Discussionmentioning

confidence: 66%

Neural correlates of gait adaptation in younger and older adults

Fettrow

Hupfeld

Hass

et al. 2022

Preprint

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Mobility decline is a major concern for older adults.A key component of maintaining mobility with advancing age is the ability to learn and adapt to the environment.The split-belt treadmill paradigm is an experimental protocol that tests the ability to adapt to a dynamic environment.Here we examined the magnetic resonance imaging (MRI) derived structural neural correlates of individual differences in adaptation to split-belt walking for younger and older adults.We have previously shown that younger adults adopt an asymmetric walking pattern during split-belt walking, particularly in the medial-lateral (ML) direction, but older adults do not.We collected \emph{T}$_1$-weighted and diffusion-weighted MRI scans to quantify brain morphological characteristics (i.e.in the gray matter and white matter) on these same participants.We investigated two distinct questions: 1) Are there structural brain metrics that are associated with the ability to adopt asymmetry during split-belt walking; and 2) Are there different brain-behavior relationships for younger and older adults? Given the growing evidence that indicates the brain has a critical role in the maintenance of gait and balance,we hypothesized that brain areas commonly associated with locomotion (i.e. basal ganglia, sensorimotor cortex, cerebellum) would be associated with ML asymmetry and that older adults would show more associations between split-belt walking and prefrontal brain areas.We identified multiple brain-behavior associations.More gray matter volume in the superior frontal gyrus and cerebellar lobules VIIB and VIII, more sulcal depth in the insula, more gyrification in the pre/post central gyri, and more fractional anisotropy in the corticospinal tract and inferior longitudinal fasciculus corresponded to more gait asymmetry.These associations did not differ between younger and older adults.This work progresses our understanding of how brain structure is associated with balance during walking, particularly during adaptation.

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“…For example, when creating the FE mesh, we uniformly inflate the WM surface to create a GM layer which results in a fairly homogeneous GM thickness across the brain. In reality, the gray matter layer is characterized by thickness differences between sulci and gyri (Lin et al, 2021) and varies across the brain (Fischl and Dale, 2000). We chose this approach due to the necessity to avoid self-contact between GM folds in order to capture sulcal widening during atrophy.…”

Section: Limitationsmentioning

confidence: 99%

Brain Shape Changes Associated With Cerebral Atrophy in Healthy Aging and Alzheimer’s Disease

Blinkouskaya

Weickenmeier

2021

Front. Mech. Eng.

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Both healthy and pathological brain aging are characterized by various degrees of cognitive decline that strongly correlate with morphological changes referred to as cerebral atrophy. These hallmark morphological changes include cortical thinning, white and gray matter volume loss, ventricular enlargement, and loss of gyrification all caused by a myriad of subcellular and cellular aging processes. While the biology of brain aging has been investigated extensively, the mechanics of brain aging remains vastly understudied. Here, we propose a multiphysics model that couples tissue atrophy and Alzheimer’s disease biomarker progression. We adopt the multiplicative split of the deformation gradient into a shrinking and an elastic part. We model atrophy as region-specific isotropic shrinking and differentiate between a constant, tissue-dependent atrophy rate in healthy aging, and an atrophy rate in Alzheimer’s disease that is proportional to the local biomarker concentration. Our finite element modeling approach delivers a computational framework to systematically study the spatiotemporal progression of cerebral atrophy and its regional effect on brain shape. We verify our results via comparison with cross-sectional medical imaging studies that reveal persistent age-related atrophy patterns. Our long-term goal is to develop a diagnostic tool able to differentiate between healthy and accelerated aging, typically observed in Alzheimer’s disease and related dementias, in order to allow for earlier and more effective interventions.

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Differential Patterns of Gyral and Sulcal Morphological Changes During Normal Aging Process

Cited by 17 publications

References 72 publications

Cortical thickness systematically varies with curvature and depth in healthy human brains

Cortical thickness systematically varies with curvature and depth in healthy human brains

Neural correlates of gait adaptation in younger and older adults

Brain Shape Changes Associated With Cerebral Atrophy in Healthy Aging and Alzheimer’s Disease

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