Author

Michael V. Lombardo

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Animal Behavior & Cognition· 1 Neuroscience· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Approach:statistical model· 2 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Assay:imaging· 1

Frequent Co-Authors

Amber N. V. RuigrokiD· 2 shared Bonnie Auyeung· 2 shared Simon Baron-Cohen· 2 shared Bhismadev ChakrabartiiD· 1 shared Carrie Allison· 1 shared Christine EckeriD· 1 shared Declan G. M. Murphy· 1 shared Edward T Bullmore· 1 shared

Activity by Year

2016-2016 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 39 mutual co-author links

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2 shared papersAnimal Behavior & Cognition

Amber N. V. RuigrokORCID

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Author profile →

2 papers

Recent·Most cited

Unsupervised data-driven stratification of mentalizing heterogeneity in autism

Michael V. Lombardo, Meng-Chuan Lai, Bonnie Auyeung, Rosemary J. Holt, Carrie Allison, Paula Smith, Bhismadev Chakrabarti, Amber N. V. Ruigrok, John Suckling, Edward T. Bullmore, MRC AIMS Consortium, Christine Ecker, Michael C. Craig, Declan G. M. Murphy, Francesca Happe, Simon Baron-Cohen

The paper identifies 5 distinct subgroups within autism spectrum conditions using clustering analysis on cognitive datasets, revealing varying levels of mentalizing impairments.

Scientific Reports · Oct 18, 2016Peer-reviewedAnimal Behavior & Cognition

Improving effect size estimation and statistical power with multi-echo fMRI and its impact on understanding the neural systems supporting mentalizing

Michael V. Lombardo, Bonnie Auyeung, Rosemary J Holt, Jack Waldman, Amber N. V. Ruigrok, Natasha Mooney, Edward T Bullmore, Simon Baron-Cohen, Prantik Kundu

This paper shows that removing non-BOLD artifacts using ME-ICA improves effect size and statistical power in mentalizing task-fMRI, particularly in cerebellar regions.

bioRxiv · Mar 23, 2016Neuroscience