| 1. |
- Anjomshoae, Sule, 1985-, et al.
(author)
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Explaining graph convolutional network predictions for clinicians : an explainable AI approach to Alzheimer’s disease classification
- 2024
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In: Frontiers in Artificial Intelligence. - : Frontiers Media S.A.. - 2624-8212. ; 6
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Journal article (peer-reviewed)abstract
- Introduction: Graph-based representations are becoming more common in the medical domain, where each node defines a patient, and the edges signify associations between patients, relating individuals with disease and symptoms in a node classification task. In this study, a Graph Convolutional Networks (GCN) model was utilized to capture differences in neurocognitive, genetic, and brain atrophy patterns that can predict cognitive status, ranging from Normal Cognition (NC) to Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD), on the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Elucidating model predictions is vital in medical applications to promote clinical adoption and establish physician trust. Therefore, we introduce a decomposition-based explanation method for individual patient classification.Methods: Our method involves analyzing the output variations resulting from decomposing input values, which allows us to determine the degree of impact on the prediction. Through this process, we gain insight into how each feature from various modalities, both at the individual and group levels, contributes to the diagnostic result. Given that graph data contains critical information in edges, we studied relational data by silencing all the edges of a particular class, thereby obtaining explanations at the neighborhood level.Results: Our functional evaluation showed that the explanations remain stable with minor changes in input values, specifically for edge weights exceeding 0.80. Additionally, our comparative analysis against SHAP values yielded comparable results with significantly reduced computational time. To further validate the model's explanations, we conducted a survey study with 11 domain experts. The majority (71%) of the responses confirmed the correctness of the explanations, with a rating of above six on a 10-point scale for the understandability of the explanations.Discussion: Strategies to overcome perceived limitations, such as the GCN's overreliance on demographic information, were discussed to facilitate future adoption into clinical practice and gain clinicians' trust as a diagnostic decision support system.
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| 2. |
- Fjell, Anders M., et al.
(author)
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Poor Self-Reported Sleep is Related to Regional Cortical Thinning in Aging but not Memory Decline-Results From the Lifebrain Consortium
- 2021
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In: Cerebral Cortex. - : Oxford University Press. - 1047-3211 .- 1460-2199. ; 31:4, s. 1953-1969
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Journal article (peer-reviewed)abstract
- We examined whether sleep quality and quantity are associated with cortical and memory changes in cognitively healthy participants across the adult lifespan. Associations between self-reported sleep parameters (Pittsburgh Sleep Quality Index, PSQI) and longitudinal cortical change were tested using five samples from the Lifebrain consortium (n = 2205, 4363 MRIs, 18-92 years). In additional analyses, we tested coherence with cell-specific gene expression maps from the Allen Human Brain Atlas, and relations to changes in memory performance. "PSQI # 1 Subjective sleep quality" and "PSQI #5 Sleep disturbances" were related to thinning of the right lateral temporal cortex, with lower quality and more disturbances being associated with faster thinning. The association with "PSQI #5 Sleep disturbances" emerged after 60 years, especially in regions with high expression of genes related to oligodendrocytes and S1 pyramidal neurons. None of the sleep scales were related to a longitudinal change in episodic memory function, suggesting that sleep-related cortical changes were independent of cognitive decline. The relationship to cortical brain change suggests that self-reported sleep parameters are relevant in lifespan studies, but small effect sizes indicate that self-reported sleep is not a good biomarker of general cortical degeneration in healthy older adults.
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| 3. |
- Grydeland, Håkon, et al.
(author)
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Self-reported sleep relates to microstructural hippocampal decline in beta-amyloid positive Adults beyond genetic risk
- 2021
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In: Sleep. - : Oxford University Press. - 0161-8105 .- 1550-9109. ; 44:11
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Journal article (peer-reviewed)abstract
- Study Objectives: A critical role linking sleep with memory decay and beta-amyloid (A beta) accumulation, two markers of Alzheimer's disease (AD) pathology, may be played by hippocampal integrity. We tested the hypotheses that worse self-reported sleep relates to decline in memory and intra-hippocampal microstructure, including in the presence of A beta.Methods: Two-hundred and forty-three cognitively healthy participants, aged 19-81 years, completed the Pittsburgh Sleep Quality Index once, and two diffusion tensor imaging sessions, on average 3 years apart, allowing measures of decline in intra-hippocampal microstructure as indexed by increased mean diffusivity. We measured memory decay at each imaging session using verbal delayed recall. One session of positron emission tomography, in 108 participants above 44 years of age, yielded 23 A beta positive. Genotyping enabled control for APOE epsilon 4 status, and polygenic scores for sleep and AD, respectively.Results: Worse global sleep quality and sleep efficiency related to more rapid reduction of hippocampal microstructure over time. Focusing on efficiency (the percentage of time in bed at night spent asleep), the relation was stronger in presence of A beta accumulation, and hippocampal integrity decline mediated the relation with memory decay. The results were not explained by genetic risk for sleep efficiency or AD.Conclusions: Worse sleep efficiency related to decline in hippocampal microstructure, especially in the presence of A beta accumulation, and A beta might link poor sleep and memory decay. As genetic risk did not account for the associations, poor sleep efficiency might constitute a risk marker for AD, although the driving causal mechanisms remain unknown.
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| 4. |
- Josefsson, Maria, 1979-, et al.
(author)
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A Bayesian semiparametric approach for inference on the population partly conditional mean from longitudinal data with dropout
- 2023
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In: Biostatistics. - : Oxford University Press. - 1465-4644 .- 1468-4357. ; 24:2, s. 372-387
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Journal article (peer-reviewed)abstract
- Studies of memory trajectories using longitudinal data often result in highly non-representative samples due to selective study enrollment and attrition. An additional bias comes from practice effects that result in improved or maintained performance due to familiarity with test content or context. These challenges may bias study findings and severely distort the ability to generalize to the target population. In this study we propose an approach for estimating the finite population mean of a longitudinal outcome conditioning on being alive at a specific time point. We develop a flexible Bayesian semi-parametric predictive estimator for population inference when longitudinal auxiliary information is known for the target population. We evaluate sensitivity of the results to untestable assumptions and further compare our approach to other methods used for population inference in a simulation study. The proposed approach is motivated by 15-year longitudinal data from the Betula longitudinal cohort study. We apply our approach to estimate lifespan trajectories in episodic memory, with the aim to generalize findings to a target population.
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| 5. |
- Koch, Elise, et al.
(author)
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Sex-specific effects of polygenic risk for schizophrenia on lifespan cognitive functioning in healthy individuals
- 2021
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In: Translational Psychiatry. - : Springer Nature. - 2158-3188. ; 11:1
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Journal article (peer-reviewed)abstract
- Polygenic risk for schizophrenia has been associated with lower cognitive ability and age-related cognitive change in healthy individuals. Despite well-established neuropsychological sex differences in schizophrenia patients, genetic studies on sex differences in schizophrenia in relation to cognitive phenotypes are scarce. Here, we investigated whether the effect of a polygenic risk score (PRS) for schizophrenia on childhood, midlife, and late-life cognitive function in healthy individuals is modified by sex, and if PRS is linked to accelerated cognitive decline. Using a longitudinal data set from healthy individuals aged 25–100 years (N = 1459) spanning a 25-year period, we found that PRS was associated with lower cognitive ability (episodic memory, semantic memory, visuospatial ability), but not with accelerated cognitive decline. A significant interaction effect between sex and PRS was seen on cognitive task performance, and sex-stratified analyses showed that the effect of PRS was male-specific. In a sub-sample, we observed a male-specific effect of the PRS on school performance at age 12 (N = 496). Our findings of sex-specific effects of schizophrenia genetics on cognitive functioning across the lifespan indicate that the effects of underlying disease genetics on cognitive functioning is dependent on biological processes that differ between the sexes.
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| 6. |
- Nyberg, Lars, et al.
(author)
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Educational attainment does not influence brain aging
- 2021
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In: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 118:18
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Journal article (peer-reviewed)abstract
- Education has been related to various advantageous lifetime outcomes. Here, using longitudinal structural MRI data (4,422 observations), we tested the influential hypothesis that higher education translates into slower rates of brain aging. Cross-sectionally, education was modestly associated with regional cortical volume. However, despite marked mean atrophy in the cortex and hippocampus, education did not influence rates of change. The results were replicated across two independent samples. Our findings challenge the view that higher education slows brain aging.
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| 7. |
- Nyberg, Lars, 1966-, et al.
(author)
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Individual differences in brain aging : heterogeneity in cortico-hippocampal but not caudate atrophy rates
- 2023
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In: Cerebral Cortex. - : Oxford University Press. - 1047-3211 .- 1460-2199. ; 33:9, s. 5075-5081
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Journal article (peer-reviewed)abstract
- It is well documented that some brain regions, such as association cortices, caudate, and hippocampus, are particularly prone to age-related atrophy, but it has been hypothesized that there are individual differences in atrophy profiles. Here, we document heterogeneity in regional-atrophy patterns using latent-profile analysis of 1,482 longitudinal magnetic resonance imaging observations. The results supported a 2-group solution reflecting differences in atrophy rates in cortical regions and hippocampus along with comparable caudate atrophy. The higher-atrophy group had the most marked atrophy in hippocampus and also lower episodic memory, and their normal caudate atrophy rate was accompanied by larger baseline volumes. Our findings support and refine models of heterogeneity in brain aging and suggest distinct mechanisms of atrophy in striatal versus hippocampal-cortical systems.
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| 8. |
- Pudas, Sara, 1983-
(author)
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Brain characteristics of memory decline and stability in aging : Contributions from longitudinal observations
- 2013
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Doctoral thesis (other academic/artistic)abstract
- Aging is typically associated with declining mental abilities, most prominent for some forms of memory. There are, however, large inter-individual differences within the older population. Some people experience rapid decline whereas others seem almost spared from any adverse effects of aging. This thesis examined the neural underpinnings of such individual differences by using longitudinal observations of episodic memory change across 15-20 years, combined with structural and functional magnetic resonance imaging of the brain. Study I found significant correlations between volume and activity of the hippocampus (HC), and memory change over a 6-year period. That is, individuals with decline in HC function also had declining memory. In contrast, Study II showed that successfully aged individuals, who maintained high memory scores over 15-20 years, had preserved HC function compared to age-matched elderly with average memory change. The successful agers had HC activity levels comparable to those of young individuals, as well as higher frontal activity. Study III revealed that individual differences in memory ability and brain activity of elderly reflect both differential age-related changes, and individual differences in memory ability that are present already in midlife, when age effects are minimal. Specifically, memory scores obtained 15-20 years earlier reliably predicted brain activity in memory-relevant regions such as the frontal cortex and HC. This observation challenges results from previous cross-sectional aging studies that did not consider individual differences in cognitive ability from youth. Collectively the three studies implicate HC and frontal cortex function behind heterogeneity in cognitive aging, both substantiating and qualifying previous results from cross-sectional studies. More generally, the findings highlight the importance of longitudinal estimates of cognitive change for fully understanding the mechanisms of neurocognitive aging.
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| 9. |
- Ronat, Lucas, et al.
(author)
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Revised temperament and character inventory factors predict neuropsychiatric symptoms and aging-related cognitive decline across 25 years
- 2024
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In: Frontiers in Aging Neuroscience. - : Frontiers Media S.A.. - 1663-4365. ; 16
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Journal article (peer-reviewed)abstract
- Introduction: Personality traits and neuropsychiatric symptoms such as neuroticism and depression share genetic overlap and have both been identified as risks factors for development of aging-related neurocognitive decline and Alzheimer’s disease (AD). This study aimed to examine revised personality factors derived from the Temperament and Character Inventory, previously shown to be associated with psychiatric disorders, as predictors of neuropsychiatric, cognitive, and brain trajectories of participants from a population-based aging study.Methods: Mixed-effect linear regression analyses were conducted on data for the full sample (Nmax = 1,286), and a healthy subsample not converting to AD-dementia during 25-year follow-up (Nmax = 1,145), complemented with Cox proportional regression models to determine risk factors for conversion to clinical AD.Results: Two personality factors, Closeness to Experience (CE: avoidance of new stimuli, high anxiety, pessimistic anticipation, low reward seeking) and Tendence to Liabilities (TL: inability to change, low autonomy, unaware of the value of their existence) were associated with higher levels of depressive symptoms, stress (CE), sleep disturbance (TL), as well as greater decline in memory, vocabulary and verbal fluency in the full sample. Higher CE was additionally associated with greater memory decline across 25 years in the healthy subsample, and faster right hippocampal volume reduction across 8 years in a neuroimaging subsample (N = 216). Most, but not all, personality-cognition associations persisted after controlling for diabetes, hypertension and cardiovascular disease. Concerning risks for conversion to AD, higher age, and APOE-ε4, but none of the personality measures, were significant predictors.Conclusion: The results indicate that personality traits associated with psychiatric symptoms predict accelerated age-related neurocognitive declines even in the absence of neurodegenerative disease. The attenuation of some personality effects on cognition after adjustment for health indicators suggests that those effects may be partly mediated by somatic health. Taken together, the results further emphasize the importance of personality traits in neurocognitive aging and underscore the need for an integrative (biopsychosocial) perspective of normal and pathological age-related cognitive decline.
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| 10. |
- Samrani, George, et al.
(author)
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Healthy Middle-Aged Adults Have Preserved Mnemonic Discrimination and Integration, While Showing No Detectable Memory Benefits
- 2022
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In: Frontiers in Psychology. - : Frontiers Media S.A.. - 1664-1078. ; 12
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Journal article (peer-reviewed)abstract
- Declarative memory abilities change across adulthood. Semantic memory and autobiographic episodic knowledge can remain stable or even increase from mid- to late adulthood, while episodic memory abilities decline in later adulthood. Although it is well known that prior knowledge influences new learning, it is unclear whether the experiential growth of knowledge and memory traces across the lifespan may drive favorable adaptations in some basic memory processes. We hypothesized that an increased reliance on memory integration may be an adaptive mechanism to handle increased interference from accumulating memory traces and knowledge across adulthood. In turn, this may confer an improved ability for integration, observable in middle-age, before the onset of major aging-related declines. We further tested whether the hypothesized increase would be associated with previously observed reductions in memory discrimination performance in midlife. Data from a sample of healthy middle-aged (40–50 years, n = 40) and younger adults (20–28 years, n = 41) did not support the hypothesis of improved integration, as assessed by an associative inference paradigm. Instead, age-equivalent performance on both integration and discrimination measures were observed [Bayes factors (BFs)10 = 0.19–0.25], along with expected higher verbal knowledge and slower perceptual speed for middle-aged [(BFs)10 = 8.52–73.52]. The results contribute to an increased understanding of memory processing in midlife, an understudied portion of the lifespan, and suggest that two core episodic memory processes, integration and discrimination, can be maintained in healthy middle-aged adults.
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