Bart Larsen

The paper shows that neural timescale flexibility adapts to task demands, is hierarchically organized, and develops through two stages in youth.

The paper introduces a multimodal MRI dataset to evaluate myelin-sensitive imaging methods across test-retest acquisitions and metrics.

The paper analyzes the Drosophila connectome to reveal hierarchical community structures and identifies functional circuit archetypes.

The paper identifies menarche as an inflection point for mental health and brain development in adolescent females using longitudinal data.

The paper introduces a scalable method to estimate basal ganglia brain tissue iron using fMRI data, validated across developmental datasets and applicable to large-scale repositories.

This study identifies two axes of white matter development in human cortico-cortical tracts using diffusion MRI across three datasets, revealing non-uniform maturation patterns.

The paper estimates heritability of subcortical brain volumes in adolescents using a multi-site cohort, finding high heritability in cerebellum cortex and hippocampus.

The paper develops a framework using optimal control theory to estimate brain structure-function interactions from MRI data, showing correlations between self-inhibition parameters and neural timescales across species.

The paper identifies robust sex differences in personalized functional brain network topography in youth, linked to X-linked genes and brain regions involved in psychiatric disorders.

This paper introduces DELSSOME, a deep learning framework that accelerates biophysical brain circuit model optimization, enabling faster parameter estimation and lifespan trajectory analysis of cortical E/I ratios.

This paper introduces multi-echo acquisition and thermal denoising methods to improve precision functional MRI in adults, children, and newborns, showing increased signal-to-noise ratio and reliability.

This study shows that optimizing study design, such as increasing age variability and adding longitudinal measurements, improves replicability and effect sizes in brain-wide association studies.

The paper shows thalamocortical connections develop along a sensorimotor-association gradient in youth, linking structural connectivity to cortical plasticity and environmental sensitivity.

The paper examines how functional connectivity develops along the sensorimotor-association axis during childhood to adolescence, finding that sensorimotor connectivity increases while association connectivity decreases, reinforcing cortical hierarchy.

This study identifies white matter fiber covariance networks in youth, showing their development aligns with executive function and hierarchical cortical maturation patterns.

This study uses network control theory to examine how alprazolam affects persistence energy during emotion processing in schizophrenia relatives, revealing compensatory mechanisms and neuromodulatory relationships.

The paper estimates the whole-cortex excitation-inhibition ratio using fMRI and shows it declines during youth, with lower ratios linked to better cognitive performance in children.

This study evaluates six compressed sensing diffusion spectrum imaging (CS-DSI) schemes, finding they provide accurate and reliable white matter structure measures with up to 80% reduced scan time compared to full DSI.

This study tracks cortical activity propagations in youth, finding increased top-down propagations with cognitive control demands and development.

This study links individual differences in delay discounting to specific patterns of dorsal prefrontal cortex connectivity in youth using resting-state fMRI.

This study shows that dopamine release in the ventral striatum is linked to reward learning, not just reward processing, using combined PET and fMRI in humans.

The paper defines personalized functional networks in children to predict cognitive differences, finding that fronto-parietal network representation correlates with general cognition.

The paper shows that intrinsic brain activity decreases along a sensorimotor-association cortical axis during human development, with reduced activity in disadvantaged youth.

ModelArray is an R package for efficient statistical analysis of fixel data, supporting linear and nonlinear models with reduced memory usage.

The paper examines how individual differences in functional brain network topography relate to psychopathology dimensions in youth using machine learning and fMRI data.

The paper analyzes multi-scale functional brain networks in youths to identify developmental patterns of network re-organization and their cognitive implications.

This study uses MRI to track changes in GABA and glutamate levels in the prefrontal cortex across adolescence, finding increased balance between these neurotransmitters.

This study examines how cerebral blood flow and fMRI fluctuations are coupled in youth, finding age-related decreases, sex differences, and links to executive function.

This study uses pharmacological fMRI to show a reduction in the excitation:inhibition ratio in association cortex during adolescence, linked to psychopathology.

This study examines how neighborhood socioeconomic status affects executive system activation during a working memory task in youth and identifies mediating brain activity patterns.