John Suckling A

This study examines uncertainty processing in humans using computational models and neurochemical data, finding links between neurotransmitter levels and prediction errors in reversal learning.

The paper examines sex differences in brain structure at birth in newborns, finding larger brain volumes in males and specific regional differences in gray and white matter volumes between sexes.

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

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

This paper introduces a framework for neuroimaging using concentration inequalities to improve model validation and hypothesis testing with small sample sizes.

The paper shows that the Hurst exponent from fMRI BOLD signals indexes synaptic excitation-inhibition ratio, revealing sex-specific E:I imbalance in autistic mice medial prefrontal cortex.

This study examines the boundary sharpness coefficient (BSC) as a measure of cortical microstructure in ASD, finding age, sex, and regional differences in BSC that correlate with clinical measures.

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

This paper develops a deep learning framework to segment the paracingulate sulcus from MRI scans and estimate segment lengths, achieving a Dice score over 0.77.

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.

This study investigates dopaminergic modulation of prediction error responses in OCD using fMRI and computational modeling, finding bidirectional remediation of exaggerated cingulate signaling with dopamine agonists and antagonists.

This paper identifies distinct neuroanatomical patterns of gray matter changes associated with hallucination status in psychiatric versus neurodegenerative disorders through meta-analyses and systematic reviews.

This study shows focal brain tumours create global, non-linear functional gradients, affecting network robustness and complexity beyond the tumour site.