Michael V. Lombardo
University of Cambridge
Developmental psychologyDefault mode networkPsychologyNeuroscienceCognitionCognitive psychologyMentalizationAutismAsperger syndromeNeurotypicalAutism spectrum disorderSex characteristicsFunctional magnetic resonance imagingTheory of mindEmpathyWhite matterPopulationAudiologyNeuroimagingResting state fMRIClinical psychologyMedicineBiology
Publications 132
#1Meng-Chuan Lai (U of T: University of Toronto)H-Index: 51
#2Michael V. Lombardo (University of Cambridge)H-Index: 56
Last. Simon Baron-Cohen (University of Cambridge)H-Index: 196
view all 10 authors...
Prior work has revealed sex/gender-dependent autistic characteristics across behavioural and neural/biological domains. It remains unclear whether and how neural sex/gender differences are related to behavioural sex/gender differences in autism. Here, we examined whether atypical neural responses during mentalizing and self-representation are sex/gender-dependent in autistic adults and explored whether ‘camouflaging’ (acting as if behaviourally neurotypical) is associated with sex/gender-depende...
34 CitationsSource
#1Martijn P. van den Heuvel (UU: Utrecht University)H-Index: 70
#1Martijn P. van den Heuvel (UU: Utrecht University)H-Index: 14
Last. Siemon C. de Lange (UU: Utrecht University)H-Index: 9
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We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain.
6 CitationsSource
#1Marianne Oldehinkel (Radboud University Nijmegen)H-Index: 10
#2Maarten Mennes (Radboud University Nijmegen)H-Index: 48
Last. Jan K. Buitelaar (Radboud University Nijmegen)H-Index: 142
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Abstract Background Resting-state functional magnetic resonance imaging–based studies on functional connectivity in autism spectrum disorder (ASD) have generated inconsistent results. Interpretation of findings is further hampered by small samples and a focus on a limited number of networks, with networks underlying sensory processing being largely underexamined. We aimed to comprehensively characterize ASD-related alterations within and between 20 well-characterized resting-state networks using...
36 CitationsSource
#1Joseph D. Buxbaum (ISMMS: Icahn School of Medicine at Mount Sinai)H-Index: 127
#2Simon Baron-Cohen (University of Cambridge)H-Index: 196
Last. Cynthia M. Schumann (UC Davis: University of California, Davis)H-Index: 24
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2 CitationsSource
#1Simon Baron-CohenH-Index: 3
#2Janine RobinsonH-Index: 5
Last. N nagra
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#1Michael V. Lombardo (University of Cambridge)H-Index: 56
#2Meng-Chuan Lai (University of Cambridge)H-Index: 51
Last. Simon Baron-Cohen (University of Cambridge)H-Index: 196
view all 3 authors...
Autism is a diagnostic label based on behavior. While the diagnostic criteria attempt to maximize clinical consensus, it also masks a wide degree of heterogeneity between and within individuals at multiple levels of analysis. Understanding this multi-level heterogeneity is of high clinical and translational importance. Here we present organizing principles to frame research examining multi-level heterogeneity in autism. Theoretical concepts such as ‘spectrum’ or ‘autisms’ reflect non-mutually ex...
102 CitationsSource
#1Eric Courchesne (UCSD: University of California, San Diego)H-Index: 116
#2Tiziano Pramparo (UCSD: University of California, San Diego)H-Index: 31
Last. Nathan E. Lewis (UCSD: University of California, San Diego)H-Index: 44
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Autism spectrum disorder (ASD) has captured the attention of scientists, clinicians and the lay public because of its uncertain origins and striking and unexplained clinical heterogeneity. Here we review genetic, genomic, cellular, postmortem, animal model, and cell model evidence that shows ASD begins in the womb. This evidence leads to a new theory that ASD is a multistage, progressive disorder of brain development, spanning nearly all of prenatal life. ASD can begin as early as the 1st and 2n...
95 CitationsSource
#1Michael V. Lombardo (University of Cambridge)H-Index: 56
#2Tiziano Pramparo (UCSD: University of California, San Diego)H-Index: 31
Last. Eric Courchesne (UCSD: University of California, San Diego)H-Index: 116
view all 11 authors...
Heterogeneity in early language development in autism spectrum disorder (ASD) is clinically important and may reflect neurobiologically distinct subtypes. Here, we identified a large-scale association between multiple coordinated blood leukocyte gene coexpression modules and the multivariate functional neuroimaging (fMRI) response to speech. Gene coexpression modules associated with the multivariate fMRI response to speech were different for all pairwise comparisons between typically developing ...
29 CitationsSource
#1Richard A.I. Bethlehem (University of Cambridge)H-Index: 15
#2Jakob Seidlitz (NIH: National Institutes of Health)H-Index: 19
Last. Michael V. Lombardo (UCY: University of Cyprus)H-Index: 56
view all 5 authors...
Understanding heterogeneity in neural phenotypes is an important goal on the path to precision medicine for autism spectrum disorders (ASD). Age is a critically important variable in normal structural brain development and examining structural features with respect to age-related norms could help to explain ASD heterogeneity in neural phenotypes. Here we examined how cortical thickness (CT) in ASD can be parameterized as an individualized metric of deviance relative to typically-developing (TD) ...
13 CitationsSource
#1Stuart J. Ritchie (Edin.: University of Edinburgh)H-Index: 32
#2Simon R. Cox (Edin.: University of Edinburgh)H-Index: 30
Last. Ian J. Deary (Edin.: University of Edinburgh)H-Index: 21
view all 18 authors...
Sex differences in the human brain are of interest for many reasons: for example, there are sex differences in the observed prevalence of psychiatric disorders and in some psychological traits that brain differences might help to explain. We report the largest single-sample study of structural and functional sex differences in the human brain (2750 female, 2466 male participants; mean age 61.7 years, range 44–77 years). Males had higher raw volumes, raw surface areas, and white matter fractional...
251 CitationsSource