Caterina Gratton

The paper shows that functional brain networks remain stable in healthy young adults over years, suggesting persistent individual brain organization.

The paper uses precision fMRI to reveal individual-specific, fragmented, and interdigitated network patches in the lateral prefrontal cortex, showing conserved motifs and distinct functional boundaries not visible in group-averaged data.

This study evaluates the feasibility and reliability of precision resting state functional connectivity (RSFC) in Parkinson's disease (PD) and finds it produces reliable, stable network measures comparable to healthy controls.

This study maps brain networks in children using precision neuroimaging, finding less inter-individual variability compared to adults.

This study examines longitudinal stability of mood-related resting-state networks in youth with bipolar-I/II disorder, finding reduced within-person stability in BD compared to healthy controls.

The paper introduces the Network Correspondence Toolbox (NCT) to evaluate spatial correspondence between novel neuroimaging results and existing brain atlases, enabling standardized reporting and comparison across studies.

The paper defines the parietal memory network (PMN) using high-resolution fMRI and finds it extends beyond traditional regions to include multiple cortical areas.

This paper identifies two distinct forms of variation in human functional brain networks: border shifts and ectopic intrusions, which differ in location, network associations, and behavioral predictions.

The paper investigates how the cingulo-opercular network contributes to decision-making under ambiguity using fMRI and behavioral tasks.

The paper investigates the relationship between brain hubs and inter-individual variability, finding that group hubs defined by participation coefficient are consistent across individuals, while other hub measures show higher correspondence to individual variability.

This paper introduces a method to disentangle non-local network input from task-induced changes in functional connectivity using BOLD fMRI signals and demonstrates its effectiveness in distinguishing task types.

The paper examines hemispheric differences in network variants from resting-state fMRI data, finding asymmetries in variant locations and their relation to lateralized traits.

The paper reveals that motor cortex contains inter-effector regions connected to the Cingulo-opercular network, alternating with effector-specific areas, suggesting a dual system for motor control and whole-body coordination.

This paper identifies two distinct sub-systems within the cingulo-opercular network using fMRI data, showing differential roles in task control and other cognitive/motor functions.

The paper examines whether high cofluctuation 'events' in fMRI data uniquely drive functional connectivity or arise from sampling variability in a static signal.

This paper shows that individual-specific features of brain states during tasks are more robust than cross-subject features, using fMRI data from single-person datasets.

The paper develops a precision functional brain atlas to capture individual-specific network topography and demonstrates its utility in generating reproducible statistical maps of brain function.

The paper identifies distinct functional connectivity patterns in the hippocampus, showing anterior regions connect to the default mode network and posterior regions connect to the parietal memory network, supporting different cognitive processes.

The paper probabilistically maps human functional brain networks to identify regions of high inter-subject consensus across multiple datasets.

The paper shows network variants identified from task data are similar to those from rest states, supporting their trait-like nature.

This paper identifies and removes high-frequency motion artifacts in single-band fMRI data, improving motion estimates and reducing data loss without biasing functional connectivity.

This paper develops a band-stop filter to correct respiratory artifacts in MRI motion estimates, improving data quality and demonstrating real-time implementation.

The paper introduces a new set of functionally-defined brain regions that better represent subcortex and cerebellum, validated across datasets and combined with cortical regions to improve functional network analysis.

This paper introduces a multi-layer network method to analyze brain network modularity across individuals and time, revealing scale-specific variability linked to cognitive performance.

This study identifies age-specific functional connectivity differences in Tourette syndrome between children and adults using MRI, showing altered developmental trajectories in affected brain networks.