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Christine Ecker

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5 papers
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5

YNICL Journal 2022 Journal Article

In-depth characterization of neuroradiological findings in a large sample of individuals with autism spectrum disorder and controls

  • Sara Ambrosino
  • Hasnaa Elbendary
  • Maarten Lequin
  • Dominique Rijkelijkhuizen
  • Tobias Banaschewski
  • Simon Baron-Cohen
  • Nico Bast
  • Sarah Baumeister

BACKGROUND: Autism spectrum disorder (ASD) is a group of neurodevelopmental conditions associated with quantitative differences in cortical and subcortical brain morphometry. Qualitative assessment of brain morphology provides complementary information on the possible underlying neurobiology. Studies of neuroradiological findings in ASD have rendered mixed results, and await robust replication in a sizable and independent sample. METHODS: We systematically and comprehensively assessed neuroradiological findings in a large cohort of participants with ASD and age-matched controls (total N = 620, 348 ASD and 272 controls), including 70 participants with intellectual disability (47 ASD, 23 controls). We developed a comprehensive scoring system, augmented by standardized biometric measures. RESULTS: There was a higher incidence of neuroradiological findings in individuals with ASD (89.4 %) compared to controls (83.8 %, p = .042). Certain findings were also more common in ASD, in particular opercular abnormalities (OR 1.9, 95 % CI 1.3-3.6) and mega cisterna magna (OR 2.4, 95 % CI 1.4-4.0) reached significance when using FDR, whereas increases in macrocephaly (OR 2.0, 95 % CI 1.2-3.2), cranial deformities (OR 2.4, 95 % CI: 1.0-5.8), calvarian / dural thickening (OR 1.5, 95 % CI 1.0-2.3), ventriculomegaly (OR 3.4, 95 % CI 1.3-9.2), and hypoplasia of the corpus callosum (OR 2.7, 95 % CI 1.1-6.3) did not survive this correction. Furthermore, neuroradiological findings were more likely to occur in isolation in controls, whereas they clustered more frequently in ASD. The incidence of neuroradiological findings was higher in individuals with mild intellectual disability (95.7 %), irrespective of ASD diagnosis. CONCLUSION: There was a subtly higher prevalence of neuroradiological findings in ASD, which did not appear to be specific to the condition. Individual findings or clusters of findings may point towards the neurodevelopmental mechanisms involved in individual cases. As such, clinical MRI assessments may be useful to guide further etiopathological (genetic) investigations, and are potentially valuable to fundamental ASD research.

YNIMG Journal 2013 Journal Article

Effects of age and gender on neural networks of motor response inhibition: From adolescence to mid-adulthood

  • Katya Rubia
  • Lena Lim
  • Christine Ecker
  • Rozmin Halari
  • Vincent Giampietro
  • Andrew Simmons
  • Michael Brammer
  • Anna Smith

Functional inhibitory neural networks mature progressively with age. However, nothing is known about the impact of gender on their development. This study employed functional magnetic resonance imaging (fMRI) to investigate the effects of age, sex, and sex by age interactions on the brain activation of 63 healthy males and females, between 13 and 38years, performing a Stop task. Increasing age was associated with progressively increased activation in typical response inhibition areas of right inferior and dorsolateral prefrontal and temporo-parietal regions. Females showed significantly enhanced activation in left inferior and superior frontal and striatal regions relative to males, while males showed increased activation relative to females in right inferior and superior parietal areas. Importantly, left frontal and striatal areas that showed increased activation in females, also showed significantly increased functional maturation in females relative to males, while the right inferior parietal activation that was increased in males showed significantly increased functional maturation relative to females. The findings demonstrate for the first time that sex-dimorphic activation patterns of enhanced left fronto-striatal activation in females and enhanced right parietal activation in males during motor inhibition appear to be the result of underlying gender differences in the functional maturation of these brain regions.

YNIMG Journal 2012 Journal Article

Individual differences in brain structure underpin empathizing–systemizing cognitive styles in male adults

  • Meng-Chuan Lai
  • Michael V. Lombardo
  • Bhismadev Chakrabarti
  • Christine Ecker
  • Susan A. Sadek
  • Sally J. Wheelwright
  • Declan G.M. Murphy
  • John Suckling

Individual differences in cognitive style can be characterized along two dimensions: ‘systemizing’ (S, the drive to analyze or build ‘rule-based’ systems) and ‘empathizing’ (E, the drive to identify another's mental state and respond to this with an appropriate emotion). Discrepancies between these two dimensions in one direction (S>E) or the other (E>S) are associated with sex differences in cognition: on average more males show an S>E cognitive style, while on average more females show an E>S profile. The neurobiological basis of these different profiles remains unknown. Since individuals may be typical or atypical for their sex, it is important to move away from the study of sex differences and towards the study of differences in cognitive style. Using structural magnetic resonance imaging we examined how neuroanatomy varies as a function of the discrepancy between E and S in 88 adult males from the general population. Selecting just males allows us to study discrepant E-S profiles in a pure way, unconfounded by other factors related to sex and gender. An increasing S>E profile was associated with increased gray matter volume in cingulate and dorsal medial prefrontal areas which have been implicated in processes related to cognitive control, monitoring, error detection, and probabilistic inference. An increasing E>S profile was associated with larger hypothalamic and ventral basal ganglia regions which have been implicated in neuroendocrine control, motivation and reward. These results suggest an underlying neuroanatomical basis linked to the discrepancy between these two important dimensions of individual differences in cognitive style.

YNIMG Journal 2010 Journal Article

Investigating the predictive value of whole-brain structural MR scans in autism: A pattern classification approach

  • Christine Ecker
  • Vanessa Rocha-Rego
  • Patrick Johnston
  • Janaina Mourao-Miranda
  • Andre Marquand
  • Eileen M. Daly
  • Michael J. Brammer
  • Clodagh Murphy

Autistic spectrum disorder (ASD) is accompanied by subtle and spatially distributed differences in brain anatomy that are difficult to detect using conventional mass-univariate methods (e. g. , VBM). These require correction for multiple comparisons and hence need relatively large samples to attain sufficient statistical power. Reports of neuroanatomical differences from relatively small studies are thus highly variable. Also, VBM does not provide predictive value, limiting its diagnostic value. Here, we examined neuroanatomical networks implicated in ASD using a whole-brain classification approach employing a support vector machine (SVM) and investigated the predictive value of structural MRI scans in adults with ASD. Subsequently, results were compared between SVM and VBM. We included 44 male adults; 22 diagnosed with ASD using “gold-standard” research interviews and 22 healthy matched controls. SVM identified spatially distributed networks discriminating between ASD and controls. These included the limbic, frontal-striatal, fronto-temporal, fronto-parietal and cerebellar systems. SVM applied to gray matter scans correctly classified ASD individuals at a specificity of 86. 0% and a sensitivity of 88. 0%. Cases (68. 0%) were correctly classified using white matter anatomy. The distance from the separating hyperplane (i. e. , the test margin) was significantly related to current symptom severity. In contrast, VBM revealed few significant between-group differences at conventional levels of statistical stringency. We therefore suggest that SVM can detect subtle and spatially distributed differences in brain networks between adults with ASD and controls. Also, these differences provide significant predictive power for group membership, which is related to symptom severity.