Daniel A. Handwerker

This paper introduces pBOLD, a new fMRI quality metric that quantifies BOLD dominance in multi-echo scans, validates it on datasets, and shows its utility in predicting phenotypes.

This study investigates the neural mechanisms of afterimages using fMRI, finding that they engage widespread brain activity and specific cortical layers, challenging previous views on their origins.

This study shows that rapid neural information can be decoded from ultra-fast fMRI signals using multivariate pattern decoders, achieving significant accuracy within 2 seconds of stimulus onset.

Robust-tedana improves automated denoising of multi-echo fMRI data, enhancing both single-subject and group-level analysis accuracy.

This study maps neuroanatomical changes in a human brain from preconception to two years postpartum, revealing decreases in gray matter and increases in white matter integrity.

The paper shows that in-scanner experiences significantly affect resting-state functional connectivity measures in fMRI data.

The paper investigates the relationship between visual imagery vividness and afterimage perception, finding a positive correlation between imagery vividness and afterimage contrast and sharpness.

This commentary critiques Pang et al.'s 2023 study, arguing that their geometric mode approach to brain dynamics lacks specificity to brain shape and orientation, and does not sufficiently establish geometry as a more fundamental constraint than connectivity.

The paper argues against hiding subthreshold results in neuroimaging studies and proposes a 'highlighting' approach to improve reproducibility and understanding.

This paper evaluates manifold learning techniques for visualizing time-varying functional connectivity in fMRI data, finding that intrinsic dimension varies and methods differ in capturing subject and task information.

This paper identifies ultra-slow fMRI fluctuations in the fourth ventricle as a marker of drowsiness and shows their impact on functional connectivity during sleep.

This study uses fMRI to examine time-dependent brain activity during haptic 3D curve and roughness estimation, finding differential activation patterns in sensorimotor and higher-level regions.

This paper uses TBS and resting-state fMRI to show that disrupting the right posterior superior temporal sulcus reduces functional connectivity across the face-processing network, including between non-stimulated regions.

This study uses sub-millimeter fMRI to show that individual fingers have multiple mirrored representations in the motor cortex based on movement types, bridging invasive and non-invasive motor organization research.

The paper analyzes dynamic functional connectivity during rest and finds that distinct cognitive periods influence resting-state brain activity, which can be inferred from data without behavioral input.

The paper introduces BIDS, a standard for organizing MRI datasets to improve data sharing and processing.