Ian Michael Goodyer

The paper introduces dGAMLSS, a distributed algorithm for fitting GAMLSS models to construct population reference charts without sharing patient data.

This study identifies two ASD subgroups with distinct brain morphology using cross-cultural datasets, highlighting key brain regions associated with subgroup characteristics and autistic traits.

The paper examines how morphometric similarity in brain regions changes during adolescence, finding distinct developmental patterns in paralimbic versus neocortical areas.

The paper investigates how resilient functioning in adolescents exposed to childhood adversity relates to structural brain network topology, finding lower nodal degree in specific brain regions associated with higher resilience.

The paper introduces brain charts as a standardized resource for benchmarking brain morphology across the human lifespan using MRI data from a large and diverse cohort.

The paper uses manifold learning to analyze longitudinal structural connectome data, showing expansion in transmodal regions during adolescence and linking it to cognitive outcomes.

The paper investigates how prior beliefs influence perception in early psychosis, finding differences in reliance on cognitive and perceptual priors between prodromal, psychotic, and control groups.

This study shows childhood socio-economic disadvantage is linked to reduced myelin growth in adolescence and young adulthood, with some protective effects from parental education and positive parenting.

The paper assesses reinforcement learning deficits in psychosis risk groups and finds they are not linked to schizophrenia polygenic risk in the general population.

The paper links schizotypy-related magnetization in adolescent cortex to schizophrenia risk genes using MRI and gene expression data.

The paper investigates how precision-weighting of prediction error signals in the superior frontal cortex affects learning, is influenced by dopamine, and is impaired in psychosis.

The paper identifies two modes of brain-behavior covariation in adolescents and young adults using canonical correlation analysis, linking brain connectivity to psychometric, IQ, and demographic data.

The paper links compulsivity and impulsivity to distinct patterns of fronto-striatal myelination during adolescence using longitudinal MRI data.

This study identifies a bi-factor model to fractionate impulsive and compulsive problem behaviors in young adults and finds distinct antecedents for each phenotype.

The paper identifies two modes of brain functional connectivity change during adolescence: conservative and disruptive, with distinct patterns in primary and association cortex.

This study shows that positive memory specificity in adolescents at risk for depression reduces vulnerability to depression by lowering cortisol and negative self-cognitions.

The paper introduces morphometric similarity networks to map cortical organization and shows they predict cognitive variation across individuals.

The paper constructs structural covariance networks from MRI data and links them to transcriptomic networks, finding coupling between network topology and gene expression in supragranular layers.

The paper introduces latent change score models for analyzing developmental changes in brain and behavior using longitudinal data, showing correlated brain-behavior changes and sex differences in cortical thinning.

The paper examines age-related changes in structural brain networks during adolescence, finding decreased structural correlation and changes in nodal degree in association cortex.

This study shows that compulsivity is linked to reduced metacognitive ability and slower perceptual decision making.