| 1. |
- Gorbach, Tetiana, 1991-, et al.
(författare)
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A Hierarchical Bayesian Mixture Model Approach for Analysis of Resting-State Functional Brain Connectivity : An Alternative to Thresholding
- 2020
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Ingår i: Brain Connectivity. - : Mary Ann Liebert. - 2158-0014 .- 2158-0022. ; 10:5, s. 202-211
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Tidskriftsartikel (refereegranskat)abstract
- This article proposes a Bayesian hierarchical mixture model to analyze functional brain connectivity where mixture components represent "positively connected" and "non-connected" brain regions. Such an approach provides a data-informed separation of reliable and spurious connections in contrast to arbitrary thresholding of a connectivity matrix. The hierarchical structure of the model allows simultaneous inferences for the entire population as well as for each individual subject. A new connectivity measure, the posterior probability of a given pair of brain regions of a specific subject to be connected given the observed correlation of regions' activity, can be computed from the model fit. The posterior probability reflects the connectivity of a pair of regions relative to the overall connectivity pattern of an individual, which is overlooked in traditional correlation analyses. This article demonstrates that using the posterior probability might diminish the effect of spurious connections on inferences, which is present when a correlation is used as a connectivity measure. In addition, simulation analyses reveal that the sparsification of the connectivity matrix using the posterior probabilities might outperform the absolute thresholding based on correlations. Therefore, we suggest that posterior probability might be a beneficial measure of connectivity compared with the correlation. The applicability of the introduced method is exemplified by a study of functional resting-state brain connectivity in older adults.
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| 2. |
- Nordin, Kristin, et al.
(författare)
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DyNAMiC: A prospective longitudinal study of dopamine and brain connectomes : A new window into cognitive aging
- 2022
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Ingår i: Journal of Neuroscience Research. - : Wiley. - 0360-4012 .- 1097-4547. ; 100:6, s. 1296-1320
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Tidskriftsartikel (refereegranskat)abstract
- Concomitant exploration of structural, functional, and neurochemical brain mechanisms underlying age-related cognitive decline is crucial in promoting healthy aging. Here, we present the DopamiNe, Age, connectoMe, and Cognition (DyNAMiC) project, a multimodal, prospective 5-year longitudinal study spanning the adult human lifespan. DyNAMiC examines age-related changes in the brain’s structural and functional connectome in relation to changes in dopamine D1 receptor availability (D1DR), and their associations to cognitive decline. Critically, due to the complete lack of longitudinal D1DR data, the true trajectory of one of the most age-sensitive dopamine systems remains unknown. The first DyNAMiC wave included 180 healthy participants (20–80 years). Brain imaging included magnetic resonance imaging assessing brain structure (white matter, gray matter, iron), perfusion, and function (during rest and task), and positron emission tomography (PET) with the [11C]SCH23390 radioligand. A subsample (n = 20, >65 years) was additionally scanned with [11C]raclopride PET measuring D2DR. Age-related variation was evident for multiple modalities, such as D1DR; D2DR, and performance across the domains of episodic memory, working memory, and perceptual speed. Initial analyses demonstrated an inverted u-shaped association between D1DR and resting-state functional connectivity across cortical network nodes, such that regions with intermediate D1DR levels showed the highest levels of nodal strength. Evident within each age group, this is the first observation of such an association across the adult lifespan, suggesting that emergent functional architecture depends on underlying D1DR systems. Taken together, DyNAMiC is the largest D1DR study worldwide, and will enable a comprehensive examination of brain mechanisms underlying age-related cognitive decline.
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| 3. |
- Pedersen, Robin, et al.
(författare)
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When functional blurring becomes deleterious : Reduced system segregation is associated with less white matter integrity and cognitive decline in aging
- 2021
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Ingår i: NeuroImage. - : Elsevier BV. - 1053-8119 .- 1095-9572. ; 242
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Tidskriftsartikel (refereegranskat)abstract
- Healthy aging is accompanied by progressive decline in cognitive performance and concomitant changes in brain structure and functional architecture. Age-accompanied alterations in brain function have been characterized on a network level as weaker functional connections within brain networks along with stronger interactions between networks. This phenomenon has been described as age-related differences in functional network segregation. It has been suggested that functional networks related to associative processes are particularly sensitive to age-related deterioration in segregation, possibly related to cognitive decline in aging. However, there have been only a few longitudinal studies with inconclusive results. Here, we used a large longitudinal sample of 284 participants between 25 to 80 years of age at baseline, with cognitive and neuroimaging data collected at up to three time points over a 10-year period. We investigated age-related changes in functional segregation among two large-scale systems comprising associative and sensorimotor-related resting-state networks. We found that functional segregation of associative systems declines in aging with exacerbated deterioration from the late fifties. Changes in associative segregation were positively associated with changes in global cognitive ability, suggesting that decreased segregation has negative consequences for domain-general cognitive functions. Age-related changes in system segregation were partly accounted for by changes in white matter integrity, but white matter integrity only weakly influenced the association between segregation and cognition. Together, these novel findings suggest a cascade where reduced white-matter integrity leads to less distinctive functional systems which in turn contributes to cognitive decline in aging.
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