John D. E. Gabrieli

The paper uses fMRI to show that language network lateralization is adult-like by age 4, despite continued development of other language network features.

This study uses precision fMRI to show that face-sensitive brain regions in autistic adults are more variably located compared to neurotypical adults, with displacement linked to sociocommunicative challenges.

The paper examines dynamic fMRI correlates of adolescent rumination and finds that adult models do not generalize, suggesting developmental differences in neural correlates of rumination.

This study uses frequency-tagging and machine learning to separate neural responses to mixed melodies, showing that musicality improves top-down attention and reduces bottom-up distractions.

The paper identifies a reliable brain state associated with trait mindfulness in adolescents using dynamic functional connectivity analysis of fMRI data.

The paper uses connectome predictive modeling to identify neural correlates of trait mindfulness subscales in resting-state fMRI data from three samples.

This study shows that intensive reading interventions improve white matter plasticity in children with reading disabilities, specifically in brain tracts linked to reading.

This study uses personalized narratives in fMRI to show that children's interests enhance language processing in brain regions associated with reward and self-reference.

The paper investigates the relationship between fiber-specific white matter microstructure and reading skills in children and adolescents, finding a positive association between FDC and reading proficiency.

This study investigates white matter microstructural associations with reading ability in children, finding age-related FA increases but no overall correlations with reading skills.

This study investigates neural prediction error in dyslexia using EEG, finding reduced prediction error signals in dyslexic adults compared to controls during perceptual tasks.

This study improves automated white-matter tractography in lower-quality diffusion MRI data by training on high-quality Connectom data and manually annotated pathways.

This study examines how a family-based intervention affecting conversational turn-taking influences neuroplasticity and language development in young children.

The paper develops a functional brain network model to predict stimulus-independent, task-unrelated thought across different populations and contexts.

The paper investigates neural correlates of reading comprehension components in adults with and without dyslexia, finding group differences in brain activation patterns associated with fluency, comprehension, and decoding.

The paper investigates interhemispheric functional symmetry in human subcortical structures using fMRI data, finding that direct cortical connectivity correlates with stronger subcortical symmetry in some regions, while connectivity to symmetric cortical areas correlates with symmetry in others.

The paper identifies factors predicting better reading outcomes in kindergarten children at risk for dyslexia, focusing on neural, cognitive-linguistic, and socioeconomic factors.

This study identifies distinct neural activation patterns in pre-readers with a family history of dyslexia who later develop typical reading skills, suggesting protective mechanisms may be present before reading onset.

This paper identifies three functional territories in the human dentate nucleus using resting-state MRI, showing their unique contributions to default-mode, salience-motor, and visual brain networks.

LittleBrain visualizes cerebellar neuroimaging data along newly identified functional gradients to enhance topographical interpretation.

The paper tests the UCT theory by showing that cerebellar functional specialization is independent of microstructural variation, unlike the cerebral cortex.

The paper identifies two functional gradients in the cerebellum using diffusion map embedding on resting-state data, revealing a progression from motor to transmodal regions and task-unfocused to task-focused processing.

The paper analyzes cerebellar fMRI task activation and resting-state connectivity in a large cohort, revealing triple representations for non-motor cognitive and affective tasks.