| 1. |
- Wegmann, Bertil, et al.
(författare)
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Bayesian modelling of effective and functional brain connectivity using hierarchical vector autoregressions
- 2024
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Ingår i: The Journal of the Royal Statistical Society, Series C. - : Oxford University Press. - 0035-9254 .- 1467-9876. ; 74:4, s. 835-856
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Tidskriftsartikel (refereegranskat)abstract
- Analysis of brain connectivity is important for understanding how information is processed by the brain. We propose a novel Bayesian vector autoregression hierarchical model for analysing brain connectivity within resting-state functional magnetic resonance imaging, and apply it to simulated data and a real data set with subjects in different groups. Our approach models functional and effective connectivity simultaneously and allows for both group- and single-subject inference. We combine analytical marginalization with Hamiltonian Monte Carlo to obtain highly efficient posterior sampling. We show that our model gives similar inference for effective connectivity compared to models with a common covariance matrix to all subjects, but more accurate inference for functional connectivity between regions compared to models with more restrictive covariance structures. A Stan implementation of our model is available on GitHub.
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| 2. |
- Bondesson, Lennart, 1944-, et al.
(författare)
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Pareto sampling versus Sampford and Conditional Poisson sampling
- 2006
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Ingår i: Scandinavian Journal of Statistics. - : Wiley InterScience. - 0303-6898 .- 1467-9469. ; 33:4, s. 699-720
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Tidskriftsartikel (refereegranskat)abstract
- Pareto sampling was introduced by Rosén in the late 1990s. It is a simple method to get a fixed size πps sample though with inclusion probabilities only approximately as desired. Sampford sampling, introduced by Sampford in 1967, gives the desired inclusion probabilities but it may take time to generate a sample. Using probability functions and Laplace approximations, we show that from a probabilistic point of view these two designs are very close to each other and asymptotically identical. A Sampford sample can rapidly be generated in all situations by letting a Pareto sample pass an acceptance–rejection filter. A new very efficient method to generate conditional Poisson (CP) samples appears as a byproduct. Further, it is shown how the inclusion probabilities of all orders for the Pareto design can be calculated from those of the CP design. A new explicit very accurate approximation of the second-order inclusion probabilities, valid for several designs, is presented and applied to get single sum type variance estimates of the Horvitz–Thompson estimator.
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| 3. |
- Davies, G., et al.
(författare)
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Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function
- 2018
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Ingår i: Nature Communications. - : Nature Publishing Group. - 2041-1723. ; 9:1
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Tidskriftsartikel (refereegranskat)abstract
- General cognitive function is a prominent and relatively stable human trait that is associated with many important life outcomes. We combine cognitive and genetic data from the CHARGE and COGENT consortia, and UK Biobank (total N = 300,486; age 16-102) and find 148 genome-wide significant independent loci (P < 5 × 10-8) associated with general cognitive function. Within the novel genetic loci are variants associated with neurodegenerative and neurodevelopmental disorders, physical and psychiatric illnesses, and brain structure. Gene-based analyses find 709 genes associated with general cognitive function. Expression levels across the cortex are associated with general cognitive function. Using polygenic scores, up to 4.3% of variance in general cognitive function is predicted in independent samples. We detect significant genetic overlap between general cognitive function, reaction time, and many health variables including eyesight, hypertension, and longevity. In conclusion we identify novel genetic loci and pathways contributing to the heritability of general cognitive function.
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| 4. |
- 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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| 5. |
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| 6. |
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| 7. |
- Gorbach, Tetiana, 1991-
(författare)
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Methods for longitudinal brain imaging studies with dropout
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- One of the challenges in aging research is to understand the brain mechanisms that underlie cognitive development in older adults. Such aging processes are investigated in longitudinal studies, where the within-individual changes over time are observed. However, several methodological issues exist in longitudinal analyses. One of them is loss of participants to follow-up, which occurs when individuals drop out from the study. Such dropout should be taken into account for valid conclusions from longitudinal investigations, and this is the focus of this thesis. The developed methods are used to explore brain aging and its relation to cognition within the Betula longitudinal study of aging.Papers I and II consider the association between changes in brain structure and cognition. In the first paper, regression analysis is used to establish the statistical significance of brain-cognition associations while accounting for dropout. Paper II develops interval estimators directly for an association as measured by partial correlation, when some data are missing. The estimators of Paper II may be used in longitudinal as well as cross-sectional studies and are not limited to brain imaging. Papers III and IV study functional brain connectivity, which is the statistical dependency between the functions of distinct brain regions. Typically, only brain regions with associations stronger than a predefined threshold are considered connected. However, the threshold is often arbitrarily set and does not reflect the individual differences in the overall connectivity patterns. Paper III proposes a mixture model for brain connectivity without explicit thresholding of associations and suggests an alternative connectivity measure. Paper IV extends the mixture modeling of Paper III to a longitudinal setting with dropout and investigates the impact of ignoring the dropout mechanism on the quality of the inferences made on longitudinal connectivity changes.
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| 8. |
- Koch, Elise, et al.
(författare)
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Polygenic Risk for Schizophrenia Has Sex-Specific Effects on Brain Activity during Memory Processing in Healthy Individuals
- 2022
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Ingår i: Genes. - : MDPI. - 2073-4425. ; 13:3
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Tidskriftsartikel (refereegranskat)abstract
- Genetic risk for schizophrenia has a negative impact on memory and other cognitive abilities in unaffected individuals, and it was recently shown that this effect is specific to males. Using functional MRI, we investigated the effect of a polygenic risk score (PRS) for schizophrenia on brain activation during working memory and episodic memory in 351 unaffected participants (167 males and 184 females, 25–95 years), and specifically tested if any effect of PRS on brain activation is sex-specific. Schizophrenia PRS was significantly associated with decreased brain activation in the left dorsolateral prefrontal cortex (DLPFC) during working-memory manipulation and in the bilateral superior parietal lobule (SPL) during episodic-memory encoding and retrieval. A significant interaction effect between sex and PRS was seen in the bilateral SPL during episodic-memory encoding and retrieval, and sex-stratified analyses showed that the effect of PRS on SPL activation was male-specific. These results confirm previous findings of DLPFC inefficiency in schizophrenia, and highlight the SPL as another important genetic intermediate phenotype of the disease. The observed sex differences suggest that the previously shown male-specific effect of schizophrenia PRS on cognition translates into an additional corresponding effect on brain functioning.
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| 9. |
- Lundquist, Anders, 1978-
(författare)
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A note on choosing sampling probabilities for conditional Poisson sampling
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- For conditional Poisson sampling the sampling probabilities and the achieved inclusion probabilities are not identical, which is a problem. We present a general method for choosing the sampling probabilities, which uses only the desired inclusion probabilities and transformations of them. We compare the performance of this new method to other reasonable choices of sampling probabilities.
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| 10. |
- Lundquist, Anders, 1978-
(författare)
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Balanced unequal probability sampling with maximum entropy
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- This paper investigates how to perform balanced unequal probability sampling with maximum entropy. Focus is on balancing conditions having the form of known marginal sums in a cross-stratification table. Since only marginal sums are fixed, the sample sizes for one or more cells in the table are random. The probability distribution for those sample sizes can be expressed explicitly but there are computational difficulties except for very small cases. Markov Chain Monte Carlo methods are proposed for obtaining good distribution approximations, as well as sample selection. Some large-sample Gaussian approximations are also considered. Iterative procedures for obtaining sampling probabilities yielding specified inclusion probabilities are discussed.
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