| 1. |
- Dima, Danai, et al.
(författare)
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Subcortical volumes across the lifespan : Data from 18,605 healthy individuals aged 3-90 years.
- 2022
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Ingår i: Human Brain Mapping. - : Wiley. - 1065-9471 .- 1097-0193. ; 43:1, s. 452-469
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Tidskriftsartikel (refereegranskat)abstract
- Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.
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| 2. |
- Frangou, Sophia, et al.
(författare)
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Cortical thickness across the lifespan : Data from 17,075 healthy individuals aged 3-90 years
- 2022
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Ingår i: Human Brain Mapping. - : John Wiley & Sons. - 1065-9471 .- 1097-0193. ; 43:1, s. 431-451
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Tidskriftsartikel (refereegranskat)abstract
- Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.
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| 3. |
- Bärgman, Jonas, et al.
(författare)
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Quantitative Driver Behavior Modelling forActive Safety Assessment Expansion (QUADRAE)
- 2021
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- In-vehicle technologies are essential for vehicle safety. This project, Quantitative Driver Behavior Modeling for Active Safety Assessment Expansion (QUADRAE), addresses two crucial components of the technology development process: driver models and simulation methodology. Together, they have provided the industrial partners with state-of-the-art tools for system development and testing, facilitating the development of innovative technologies to improve traffic safety. The main objectives of the project were to:develop and validate models of driver behavior needed in current and future simulation tools for virtual testing of active safety and automationcarry out prioritized virtual tests to estimate the safety benefit of a system, tune system parameters, and explore potential outcomes in scenarios when the system is activelearn more about the best methods for performing virtual testing using driver modelsAs a result of the project, the partners now have an established virtual simulation framework using Predictive Processing (PP) as a general paradigm for modeling driver behavior. The modeling, based on the latest knowledge and ideas about human behavior in driving, draws on extensive research using volunteer drivers as study participants. Data from both controlled experiments and naturalistic driving were used to develop and validate the models. These models are already being used by the industry partners as part of their virtual safety assessment toolchain, to develop advanced driver support systems. The data will continue to be used by the project partners in industry and academia to develop future driver models (which will, in turn, foster improved driver support systems).
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| 4. |
- Innamaa, Satu, et al.
(författare)
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Methodological challenges related to real-world automated driving pilots
- 2019
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Ingår i: ITS World Congress Proceedings.
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Konferensbidrag (refereegranskat)abstract
- This paper discusses the methodological challenges related to automated driving (AD) pilots in the realworld, providing an overview of some of the solutions offered by the L3Pilot project. Although theoverall methodology defined for Field Operational Tests (FOTs) has been developed quite extensivelyfor driver support systems, our efforts in the L3Pilot project show that the evaluation process can beadapted to suit the needs of AD pilot projects, as long as some caveats related to the pilot nature of ADstudies are acknowledged. The AD pilots currently in place around the world provide important insightsinto t he impacts of AD on their us ers, other road us ers and the societ y at large. However, as thes e s yst emsmature, large-scale FOTs will be needed as (closer to) ex-post evaluation, to verify the assessed impacts.This paper outlines the challenges and offers some solutions for working towards that goal.
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| 5. |
- Kaufmann, Tobias, et al.
(författare)
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Common brain disorders are associated with heritable patterns of apparent aging of the brain
- 2019
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Ingår i: Nature Neuroscience. - : Nature Publishing Group. - 1097-6256 .- 1546-1726. ; 22:10, s. 1617-
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Tidskriftsartikel (refereegranskat)abstract
- Common risk factors for psychiatric and other brain disorders are likely to converge on biological pathways influencing the development and maintenance of brain structure and function across life. Using structural MRI data from 45,615 individuals aged 3-96 years, we demonstrate distinct patterns of apparent brain aging in several brain disorders and reveal genetic pleiotropy between apparent brain aging in healthy individuals and common brain disorders.
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| 6. |
- Lin, Che-Tsung, 1979, et al.
(författare)
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Data Augmentation via Neural-Style-Transfer for Driver Distraction Recognition
- 2022
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Ingår i: The 8th International Conference on Driver Distraction and Inattention.
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Konferensbidrag (refereegranskat)abstract
- According to the National Highway Traffic Safety Administration, 3142 people were killed in motor vehicle crashes involving distracted drivers in 2019. Naturalistic driving datasets (NDD) have been widely used to study distracting activities while driving, with the aim of improving road safety. However, the time required to annotate videos to identify distracting activities is a major issue for research using NDD. Although full automation of the annotation process is not possible, the use of image classifiers is a way forward to hasten the classification of distractions and therefore the analysis of NDD. This paper presents the results obtained by applying image classifier to the publicly available Distracted Driver Dataset (DDD) and a sample of frames extracted from the EuroFOT and DriveC2X dataset. The results show that using ResNet-50 pretrained on Imagenet and Stylized Imagenet produces the highest accuracy on both DDD and our EuroFOT and DriveC2X datasets. The accuracy of the image classifier will now be tested on a different sample of the Swedish EuroFOT dataset, before using the image classifier for detecting distracting activities in other NDD. The faster identification of distracting activities will considerably hasten the future analyses of NDD.
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| 10. |
- Streubel, Thomas, 1985, et al.
(författare)
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Driver interaction with automated vehicles in real traffic
- 2022
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- While automated vehicles are expected to have a great positive impact on traffic safety, the interaction between manual driven vehicles and automated vehicles remains unknown until their introduction in real traffic. Some of the challenging interactions occur in cut-in (manual driven car enters lane in front of automated vehicle) and rear-end approaching scenarios (manual driven car approaches automated vehicle from behind). Here, a change in occurrence for the first scenario and discrepancy of expected behavior (e.g., higher speed) in the second scenario can potentially lead to an increase of risk.
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