Jacob Tanner

The paper examines how the brain adapts to novelty using fMRI data from repeated movie viewings, finding reduced brain activity dimensionality and links to intelligence and arousal.

The paper analyzes high-amplitude events in edge time series across the human lifespan, finding age-related changes in their patterns and associations with cognitive phenotypes.

The paper introduces edge community entropy as a measure of neural dedifferentiation in aging, showing it correlates with age and fluid cognition, particularly in older adults.

This study identifies bursty dynamics and modular subgraphs in mouse and human brain networks, showing cross-species consistency in co-fluctuation patterns and anatomical connectivity.

The paper analyzes brain network events during movie-watching, identifying three synchronization classes and their distinct characteristics.

This study identifies hierarchical co-fluctuation patterns in brain activity using fMRI data from two dense-sampling studies, revealing multi-scale organization of brain systems.

This paper introduces a method to weight anatomical brain connectivity data using multi-modal MRI data and evaluates its performance on the Human Connectome Project dataset.

This study compares edge-centric and sliding window methods for analyzing time-varying functional brain networks in ASD and healthy controls, finding distinct dynamic patterns in co-fluctuations.

The paper investigates local brain system events and their contributions to global events, revealing distinct co-fluctuation patterns and their spatial distribution during resting-state and movie-watching scans.

The paper investigates cortico-subcortical interactions using edge communities and finds distinct coupling patterns between subcortical regions and cortical systems.

This paper introduces an edge-centric model to harmonize multi-relational network datasets by integrating connectivity estimates into a unified representation, revealing mesoscale architecture and node-level properties.