Biology subjects

Visscher, K. M.

Publications and source records attributed to Visscher, K. M..

6 recordsLinked to original sources

bioRxiv2025

Your Brain Doesn't Look a Day Past 70! Cross-Sectional Associations with Brain-Predicted Age in the Cognitively-Intact Oldest-Old

The cognitively-intact oldest-old (85+) may be the most-resilient members of their birth cohort; due to survivorship effects (e.g., depletion of susceptibles), risk factors associated with brain aging biomarkers in younger samples may not generalize to the oldest-old. We evaluated associations between established aging-related risk factors and brain-predicted age difference (brainPAD) in a cross-sectional cognitively-intact oldest-old sample. Additionally, we evaluated brainPAD-cognition associations to characterize brain maintenance vs. cognitive reserve in our sample. Oldest-old adults (N = 206; 85-99 years; MoCA > 22 or neurologist evaluation) underwent T1-weighted MRI; brainPAD was generated with brainageR, such that more-positive brainPAD reflected relatively advanced brain aging. Sex, educational attainment, alcohol and smoking history, exercise history, BMI, cardiovascular and metabolic disease history, and anticholinergic medication burden were self-reported. Global cognitive z-score and coefficient of variation were derived from the NACC UDS 3.0 cognitive battery; crystallized-fluid discrepancy was derived from the NIH Toolbox Cognitive Battery. Mean brainPAD was -7.99 (SD: 5.37; range: -24.50, 6.03). Women showed more-delayed brain aging than men (B = -2.35, 95% CI = - 4.28, -0.41, p = 0.018). No other exposures were associated with brainPAD. BrainPAD was not associated with any cognitive variable. These findings suggest that cognitively-intact oldest-old adults may be atypically-resistant to risk factors associated with aging in younger samples, consistent with survivorship effects in aging. Furthermore, brainPAD may have limited explanatory value for cognitive performance in cognitively-intact oldest-old adults, potentially due to high cognitive reserve. Overall, our findings highlight the impact of survivorship effects on brain aging research. HighlightsO_LIBrain-predicted age difference was assessed in cognitively-intact oldest-old ([≥]85) C_LIO_LIMean brain-predicted age corresponded to an 8-year delay in brain aging C_LIO_LIBrain age in oldest-old was not associated with self-reported health history C_LIO_LIBrain age was not associated with cognitive performance C_LI

neuroscience↗

bioRxiv2024

Impact of deprivation and preferential usage on functional connectivity between early visual cortex and category-selective visual regions

Human behavior can be remarkably shaped by experience, such as the removal of sensory input. Many studies of conditions such as stroke, limb amputation, and vision loss have examined how the removal of input changes brain function. However, an important question has yet to be answered: when input is lost, does the brain change its connectivity to preferentially use some remaining inputs over others? In individuals with healthy vision, the central portion of the retina is preferentially used for everyday visual tasks, due to its ability to discriminate fine details. However, when central vision is lost in conditions like macular degeneration, peripheral vision must be relied upon for those everyday tasks, with certain portions receiving "preferential" usage over others. Using resting-state fMRI collected during total darkness, we examined how deprivation and preferential usage influence the intrinsic functional connectivity of sensory cortex by studying individuals with selective vision loss due to late stages of macular degeneration. We found that cortical regions representing spared portions of the peripheral retina, regardless of whether they are preferentially used, exhibit plasticity of intrinsic functional connectivity in macular degeneration. Cortical representations of spared peripheral retinal locations showed stronger connectivity to MT, a region involved in processing motion. These results suggest that long-term loss of central vision can produce widespread effects throughout spared representations in early visual cortex, regardless of whether those representations are preferentially used. These findings support the idea that connections to visual cortex maintain the capacity for change well after critical periods of visual development. HighlightsO_LIPortions of early visual cortex representing central vs. peripheral vision exhibit different patterns of connectivity to category-selective visual regions. C_LIO_LIWhen central vision is lost, cortical representations of peripheral vision display stronger functional connections to MT than central representations. C_LIO_LIWhen central vision is lost, connectivity to regions selective for tasks that involve central vision (FFA and PHA) are not significantly altered. C_LIO_LIThese effects do not depend on which locations of peripheral vision are used more. C_LI

neuroscience↗

bioRxiv2023

"Surviving and Thriving": Evidence for Cortical GABA Stabilization in Cognitively-Intact Oldest-Old Adults

Cortical GABA levels are reduced in older age; age-related differences in GABA may be associated with age-related cognitive change. The nature of age-related GABA differences in the highest-functioning stratum of the oldest-old (85+) population is not yet known. We extend our previously-reported Individual Participant Data Meta-Analysis of GABA levels (Porges et al., 2021) across the lifespan with four novel datasets sampling the cognitively-intact oldest-old. The slope of age-related GABA differences in cognitively-intact oldest-old adults flattens after roughly age 80. We interpret these findings as an effect of survivorship: inclusion in the study required intact cognition, and too great a reduction of GABA levels may not be compatible with neurophysiological function needed for intact cognition. This work contributes to a growing body of evidence suggesting that successful cognitive aging may require intact GABAergic function, as well as further characterizing successful aging amongst oldest-old adults.

neuroscience↗

bioRxiv2022

Larger and more dentated hippocampal structure is associated with better memory in the oldest-old.

Episodic memory is widely recognized as a critically important aspect of cognition that is often impacted by cognitive and brain aging. Prior work has shown that episodic memory is related to the presence of teeth-like folds on the dentate gyrus, called dentation. We hypothesized that episodic memory performance relates to overall hippocampal structure (i.e., dentation and volume) in an oldest-old cohort. We used data from the McKnight Brain Aging Registry, which consisted of cognitively healthy 85+-year-old adults. We conducted a canonical correlation analysis on 111 participants between a set of episodic memory tests and a set of characterizations of hippocampal structure. The analysis yielded a strong canonical correlation between episodic memory and hippocampal structure (r = 0.491, p = <0.001). The results suggest there is a connection between hippocampal morphology and function in the oldest-old. Our findings suggest that dentation may play an important role in relation to the individual differences observed in episodic memory performance among the oldest old and that hippocampal structure supports healthy cognitive aging. HighlightsO_LIWe characterized hippocampal dentation in a healthy oldest-old sample. C_LIO_LIHippocampal structure is related to episodic memory in healthy oldest-old adults. C_LIO_LIMemory functioning is related to both hippocampal volume and dentation. C_LI

neuroscience↗

bioRxiv2021

Fronto-parietal Network Segregation Predicts Maintained Cognition in the Cognitively Healthy Oldest-old (85+): evidence for dedifferentiation

Functional connections among groups of brain areas give insight into the brains organization. The cognitive effects of aging may relate to the brains large-scale organization. Examining the relationship between individual differences in brain organization and cognitive function in healthy older adults can help us understand how these networks support healthy cognitive aging. We investigated functional network segregation in 146 cognitively healthy participants aged 85+ in the McKnight Brain Aging Registry. We found that the segregation of the cortical association system and the segregation of individual networks within that system [the fronto-parietal network (FPN), cingulo-opercular network (CON) and default mode network (DMN)], were strong predictors of overall cognition and processing speed. We also provide a healthy oldest-old (85+) cortical parcellation that can be used in future work in this age group. This study shows that network segregation of the oldest-old brain is closely linked to cognitive performance. This work adds to the growing body of knowledge about differentiation in the aged brain by demonstrating that cognitive ability is associated with differentiated functional networks in very old individuals experiencing successful cognitive aging.

neuroscience↗

bioRxiv2020

The fronto-parietal network connects more strongly to central than peripheral V1

The functionality of central vision is different from peripheral vision. Central vision is used for fixation and has higher acuity that makes it useful for everyday activities such as reading and object identification. The central and peripheral representations in primary visual cortex (V1) also differ in how higher-order processing areas modulate their responses. For example, attention and expectation are top-down processes (i.e., high-order cognitive functions) that influence visual information processing during behavioral tasks. This top-down control is different for central vs. peripheral vision. Since functional networks can influence visual information processing in different ways, networks (such as the Fronto-Parietal (FPN), Default Mode (DMN), and Cingulo-Opercular (CON)) likely differ in how they connect to representations of the visual field across V1. Prior work indicated the central representing portion of V1 was more functionally connected to regions belonging to the FPN, and the far-peripheral representing portion of V1 was more functionally connected to regions belonging to the DMN. Our goals were 1) Assess the reproducibility and generalizability of retinotopic effects on functional connections between V1 and functional networks. 2) Extend this work to understand structural connections of central vs. peripheral representations in V1. 3) Examine the overlapping eccentricity differences in functional and structural connections of V1. We used resting-state BOLD fMRI and DWI to examine whether portions of V1 that represent different visual eccentricities differ in their functional and structural connectivity to functional networks. All data were acquired and minimally preprocessed by the Human Connectome Project. We identified central and far-peripheral representing regions from a retinotopic template. Functional connectivity was measured by correlated activity between V1 and functional networks, and structural connectivity was measured by probabilistic tractography and converted to track probability. In both modalities, differences between V1 eccentricity segment connections were compared by paired, two-tailed t-test. Dice Coefficients were used to determine spatial overlap between modalities. We found 1) Centrally representing portions of V1 are more strongly functionally connected to frontal regions than are peripherally representing portions of V1, 2) Structural connections also show stronger connections between central V1 and frontal regions, 3) Patterns of structural and functional connections overlaps in the lateral frontal cortex. In summary, the works main contribution is a greater understanding of higher-order functional networks connectivity to V1. There are stronger structural connections to central representations in V1, particularly for lateral frontal regions, implying that the functional relationship between central V1 and frontal regions is built upon direct, long-distance connections. Overlapping structural and functional connections reflect differences in V1 eccentricities, with central V1 preferentially connected to attention-associated regions. Understanding how V1 is functionally and structurally connected to higher-order brain areas contributes to our understanding of how the human brain processes visual information and forms a baseline for understanding any modifications in processing that might occur with training or experience.

neuroscience↗