Taylor A. Chamberlain

The paper investigates how the brain forms connections between new information and existing schemas using the Method of Loci, finding that default mode network regions create conjunctive representations that evolve with expertise.

BIBSNet is a deep learning model for infant brain segmentation in MRI scans that outperforms JLF in accuracy and speed, with compatible outputs for further analysis.

This study shows that ongoing thoughts during rest are reflected in brain connectivity and predict individual behavioral differences.

The paper introduces Baby Open Brains (BOBs), an open-source repository of manually curated infant brain segmentations to improve reproducibility in neuroimaging research.

The paper examines brain-behavior relationships using fMRI data and finds that neural similarity does not always correlate with behavioral similarity across different domains.

The paper shows that functional brain networks predict sustained attention and working memory in children and adults, with WM networks changing more from preadolescence to adulthood.

This study shows propofol affects functional connectivity related to sustained attention, with specific impacts on attention networks compared to other brain networks.