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Robust pipelines for extensive analyses of large genetic and brain imaging datasets linked to complex human behavior

Petrovska, Jana. Robust pipelines for extensive analyses of large genetic and brain imaging datasets linked to complex human behavior. 2020, Doctoral Thesis, University of Basel, Faculty of Psychology.

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Official URL: https://edoc.unibas.ch/79005/

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Abstract

The rapid technological and methodological advances in genetics, molecular biology and brain imaging in the last decades have enabled the current wide-spread application of brain-wide and genome-wide analyses of potential biological substrates of complex behavioral traits, such as psychological processes and psychiatric disorders. This thesis addresses methodological and statistical issues emerging from the large scale, complexity and explorative nature of brain-wide and genome-wide analyses. Furthermore, it points out additional steps for increasing the confidence in findings resulting from such extensive analyses. It does so by introducing two studies investigating the genetic bases of depressive symptoms and the brain imaging underpinnings of recognition memory performance, respectively. In the first study we aggregated genome-wide data of genetic variation to groups of genes and used inferential statistics to associate them with depressive symptoms. We also replicated the results in an independent sample and used imagining genetics to validate and extend our findings. In the second study, we decomposed the voxel-wise brain activation contrast of looking at previously seen vs. new pictures into 12 brain networks, based of which we evaluated recognition memory performance using prediction analysis. We used stable and reproducible data-driven decomposition and we trained and tested our prediction model in different samples, insuring higher generalizability of our findings. These two studies offer additional insight into the biological underpinnings of complex behavioral traits. Importantly, the applied analyses were carefully tailored to the specific research questions and integrated into robust pipelines for replication and validation of the initial results.
Advisors:Papassotiropoulos, Andreas and de Quervain, Dominique J.-F.
Faculties and Departments:03 Faculty of Medicine > Bereich Psychiatrie (Klinik) > Erwachsenenpsychiatrie UPK > Molekulare Neurowissenschaften (Papassotiropoulos)
03 Faculty of Medicine > Departement Klinische Forschung > Bereich Psychiatrie (Klinik) > Erwachsenenpsychiatrie UPK > Molekulare Neurowissenschaften (Papassotiropoulos)
05 Faculty of Science > Departement Biozentrum > Services Biozentrum > Life Sciences Training Facility (Papassotiropoulos)
07 Faculty of Psychology > Departement Psychologie > Forschungsbereich Klinische Psychologie und Neurowissenschaften > Molecular Psychology (Papassotiropoulos)
UniBasel Contributors:Petrovska, Jana and Papassotiropoulos, Andreas and de Quervain, Dominique J.-F.
Item Type:Thesis
Thesis Subtype:Doctoral Thesis
Thesis no:13786
Thesis status:Complete
Number of Pages:137
Language:English
Identification Number:
  • urn: urn:nbn:ch:bel-bau-diss137861
edoc DOI:
Last Modified:04 Dec 2020 15:21
Deposited On:30 Nov 2020 12:26

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