Author

Eva Hilland

University of OsloORCID 0000-0002-7102-8372Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 5 Approach:statistical model· 4 Assay:imaging· 3 Research Focus:benchmarking· 2 Approach:machine learning (classical)· 2 Research Focus:clustering· 1 Research Focus:differential expression· 1 Research Focus:dimensionality reduction· 1

Frequent Co-Authors

Luigi A. MaglanociD· 5 shared Nils Inge LandrøiD· 5 shared Rune JonasseniD· 5 shared Lars Tjelta WestlyeiD· 4 shared Tobias KaufmanniD· 4 shared Ole A. AndreasseniD· 2 shared A. SchmidtiD· 1 shared Aldo Córdova‐PalomeraiD· 1 shared

Activity by Year

2018-2026 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 39 mutual co-author links

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5 shared papersNeuroscience

Luigi A. MaglanocORCID

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Author profile →

5 papers

Recent·Most cited

Thalamic Nuclei Volumes Across Psychiatric and Neurological Disorders: A Multi-Site Magnetic Resonance Imaging Study

Verónica Mäki-Marttunen, Stener Nerland, Kjetil Nordbø Jørgensen, Einar August Høgestøl, Jaroslav Rokicki, Dag Alnæs, Stefan Borgwardt, B. Boye, Jan K. Buitelaar, Erlend Bøen, Simon Červenka, Annette Conzelmann, Sophie Erhardt, Barbara Franke, Elisabeth Gulowsen Celius, , Torbjørn Elvsåshagen

This study compares thalamic nucleus volumes across multiple psychiatric and neurological disorders using MRI, finding significant volume reductions in specific regions associated with different conditions.

Translational Psychiatry · May 13, 2026Peer-reviewedNeuroscience

Exploring the Links between Specific Depression Symptoms and Brain Structure: A Network Study

Eva Hilland, Nils Inge Landrø, Brage Kraft, Christian Krog Tamnes, Eiko I. Fried, Luigi A. Maglanoc, Rune Jonassen

This study models a network of depression symptoms and brain structures to explore their associations and clarify biological and symptomatic heterogeneity in depression.

Psychiatry and Clinical Neurosciences · Dec 20, 2019Peer-reviewedNeuroscience

Predicting cognitive and mental health traits and their polygenic architecture using large-scale brain connectomics

Luigi A. Maglanoc, Tobias Kaufmann, Dennis van der Meer, André F. Marquand, Thomas Wolfers, Rune Jonassen, Eva Hilland, Ole A. Andreassen, Nils Inge Landrø, Lars Tjelta Westlye

This study uses machine learning on brain connectomics data to predict cognitive and mental health traits and their polygenic scores in a large population sample.

Biological Psychiatry · Oct 29, 2019Peer-reviewedNeuroscience

Multimodal fusion of structural and functional brain imaging in depression using linked independent component analysis

Luigi A. Maglanoc, Tobias Kaufmann, Rune Jonassen, Eva Hilland, Dani Beck, Nils Inge Landrø, Lars Tjelta Westlye

This study fuses structural and functional brain imaging data in depression using linked independent component analysis but finds limited associations with case-control status and symptom loads.

Human Brain Mapping · Oct 1, 2019Peer-reviewedNeuroscience

Data-driven clustering reveals a link between symptoms and functional brain connectivity in depression

Luigi A. Maglanoc, Nils Inge Landrø, Rune Jonassen, Tobias Kaufmann, Aldo Córdova‐Palomera, Eva Hilland, Lars Tjelta Westlye

The paper identifies symptom-based subgroups in depression and anxiety using clustering and finds distinct static brain connectivity patterns associated with these subgroups.

Biological Psychiatry Cognitive Neuroscience and Neuroimaging · May 29, 2018Peer-reviewedNeuroscience