Jon̈athan R. Polimeni

This paper measures blood velocity response timing across the vascular network using dynamic PC-fMRA, showing arterial and venous responses with distinct temporal delays.

This study shows that hemodynamic oscillations during sleep coordinate directional CSF flow in the subarachnoid space and ventricles, enhancing fluid transport.

This study characterizes human cerebral cortex metabolic connectivity using PET-FDG data, finding a superior-inferior gradient driven by low-frequency signals.

This paper introduces FCG, a technique that corrects spatiotemporal-varying phase errors in EPI using an MLP, improving image quality on high-performance systems.

This paper introduces a method to measure high-resolution cardiac-locked brainstem velocity using DENSE MRI at 7T, revealing a double-peak pattern of motion.

This study uses MRI to show neural activity drives directional CSF flow in the subarachnoid space near activated brain regions in awake humans.

The paper examines the relationship between fMRI-based network metrics and glucose metabolism across different brain states and diseases, finding state- and network-dependent metabolic associations.

The paper characterizes the auditory cortex's function through dynamic coactivation patterns identified in fMRI data, showing consistency between resting-state and task conditions.

This paper develops a biophysical model to simulate fMRI responses in mice and humans, revealing species-specific hemodynamic differences and conserved vascular asymmetries.

This paper compares eight BOLD fMRI simulation approaches, finding that most are accurate but some are biased, with intravascular signal differences affecting results.

This study shows high-frequency fMRI signals are linked to brain states and can predict spontaneous neural activity using machine learning.

The paper examines the temporal and spatial patterns of BOLD-fMRI responses in the cerebral cortex, finding that peak responses vary by location and that middle cortical layers show early activity.

This study examines age-related changes in fMRI signatures of autonomic physiology, finding slower respiratory responses and faster cardiac responses with aging, with a notable turning point after age 60.

This study uses 7 Tesla fMRI to examine BOLD responses in newborns and adults, showing depth-dependent changes in cortical activity related to development.

This paper introduces a phase-contrast MRI technique to quantify slow cerebrospinal fluid flow in the human brain, showing cardiac pulsation drives brain-wide flow more than respiration.

This paper tests T1-weighted fMRI with iron oxide nanoparticles and UTE imaging at 9.4T to detect functional hyperaemia in mouse visual cortex, showing positive signal changes in both parenchyma and pial surface.

This study uses EEG-PET-MRI to show how hemodynamic and metabolic dynamics change during wakefulness and NREM sleep, revealing coupled temporal patterns and distinct network activity.

The paper maps individual auditory cortex subareas using functional network analysis and fMRI, showing high intraindividual reproducibility and meaningful interindividual variability.

This paper introduces a method to distinguish BOLD and non-BOLD signals in fMRI by analyzing cross-cortical depth delay patterns, demonstrating its effectiveness with visual task data.

This study introduces a new fMRA method to measure dynamic blood velocity responses in human posterior cerebral arteries during visual stimulation, showing a 10% increase in velocity and indicating neurovascular coupling.

This study shows that incorrect baseline modeling in fPET-FDG can create false metabolic activity patterns, affecting GLM analyses.

VesselBoost is a Python tool for segmenting small blood vessels in human MRA data using deep learning and data augmentation to overcome labeling challenges.

This paper investigates how anatomical and vascular features of the human brain affect the temporal specificity of fMRI signals in the primary visual cortex.

This paper demonstrates the feasibility of predicting resting-state fMRI functional connectivity and BOLD fluctuation amplitudes using biophysical models of macrovascular anatomy at 3 Tesla.

This study uses multilayer network analysis to examine functional connectivity across cortical depths in resting-state 7T fMRI, finding that superficial layers dominate information transfer while deeper layers drive clustering, particularly in frontotemporal and limbic regions.

This study uses 7T fMRI to compare brain activity during speech production and perceptual categorization, finding that left motor networks are involved in both tasks.

This study uses high-resolution MRI to show that thin and thick stripes in human V2 have lower myelination compared to surrounding gray matter.

The paper evaluates and corrects slice-direction geometric distortion in high-resolution 7T EPI using reversed slice-select gradient acquisitions and gradient reversal-based correction.

This study uses fast fMRI to identify a temporal sequence of thalamic activity during transitions in behavioral arousal states, linking thalamic dynamics to wakefulness and sleep.

This study demonstrates that high-resolution 7T time-of-flight MRI can image pial arteries in vivo, showing that resolution, not blood flow speed, limits visualization of these vessels.