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Abstract:
Corpus callosum dysgenesis (CCD) is one of the most common congenital neurological malformations. Despite being a clear and identifiable structural alteration in brain white matter connectivity, our understanding of the impact of CCD on cognition and behaviour is incomplete. To address this, we administered a range of cognitive tasks to CCD and neurotypical (NT) participants, along with collecting psychometric measures of non-verbal abstract reasoning, trust, suggestibility, paranoia, and autistic-like traits. The tasks assessed metacognition and decision-making. Here we present our psychometric findings that better characterise the phenotype of CCD and the initial results of the cognitive tests. Using an unsupervised machine learning algorithm over all psychometric dimensions to estimate covariational differences between NT and CCD participants, we demonstrate that CCD participants are best defined by their propensity for suggestibility and gullibility after controlling for autistic-like traits, age, sex, and non-verbal abstract reasoning. Converging with prior evidence, we also found that CCD versus NT participants have a sharper, negative psychometric curve on increasingly difficult non-verbal abstract reasoning items; relative to their own performance, those with CCD find more difficult items even harder than NT participants. Finally, we present preliminary data on the impact of CCD on metacognition and decision-making versus NT participants, showing that those with CCD have lower metacognitive sensitivity, and are less able to consider increasing costs on exploratory behaviour. Taken together, our work provides an improved phenotypic characterisation of CCD and more broadly provides insight into the role of the corpus callosum on cognitive function.
