Author

Alasdair L. A. Vance

Royal Children's HospitalORCID 0000-0002-7471-9769Unclaimed 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· 3 Assay:imaging· 3 Research Focus:differential expression· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:deep learning· 1

Frequent Co-Authors

Timothy J. SilkiD· 3 shared Alysa E. DoyleiD· 2 shared Anastasia ChristakouiD· 2 shared Andreas Jochen FallgatteriD· 2 shared Andreas ReifiD· 2 shared Annette ConzelmanniD· 2 shared Anouk SchranteeiD· 2 shared Astri Johansen LundervoldiD· 2 shared

Activity by Year

2021-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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3 shared papersNeuroscience

Timothy J. SilkORCID

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Author profile →

3 papers

Recent·Most cited

Distinct Neural Profiles of Frontoparietal Networks in Boys with ADHD and Boys with Persistent Depressive Disorder

Veronika Vilgis, Debbie Marianne Yee, Timothy J. Silk, Alasdair L. A. Vance

The paper uses MVPA to compare neural profiles of frontoparietal networks in boys with ADHD, PDD, and TD, finding differences in working memory processing.

Cognitive Affective & Behavioral Neuroscience · Mar 29, 2022Peer-reviewedNeuroscience

Analysis of structural brain asymmetries in Attention-Deficit/Hyperactivity Disorder in 39 datasets

Merel C. Postema, Martine Hoogman, Sara Ambrosino, Philip J. Asherson, Tobias Banaschewski, Cibele Edom Bandeira, Baranov Aa, Claiton H.D. Bau, Sarah Baumeister, Ramona Baur‐Streubel, Mark A. Bellgrove, Joseph Biederman, Janita Bralten, Daniel Brandeis, Silvia Brem, , Neda Jahanshad

This study analyzes structural brain asymmetries in ADHD using 39 datasets, finding small effects that do not meet study-wide significance thresholds.

Journal of Child Psychology and Psychiatry · Mar 22, 2021Peer-reviewedNeuroscience

Evidence for Similar Structural Brain Anomalies in Youth and Adult Attention-Deficit/Hyperactivity Disorder: A Machine Learning Analysis

Yanli Zhang‐James, Emily C. Helminen, Jinru Liu, The ENIGMA-ADHD Working Group, Geraldo F. Busatto, Anna Calvo, Mara Cercignani, Tiffany M. Chaim‐Avancini, Matt C. Gabel, Neil Andrew Harrison, Luisa Lázaro, Sara Lera‐Miguel, Mario Rodrigues Louzã, Rosa Nicolau, Pedro G. P. Rosa, , Susanne Walitza

This study uses machine learning to show that structural brain anomalies in ADHD are similar in children and adults, supporting continuity of the disorder's pathophysiology.

Translational Psychiatry · Feb 1, 2021Peer-reviewedBioinformatics