Shella Dawn Keilholz

This paper introduces a platform combining wide-field optical imaging and fMRI to study neuronal infraslow dynamics underlying functional connectivity.

The paper examines altered attention network dynamics in resting-state fMRI of individuals with high smartphone addiction scores using dynamic functional connectivity methods.

This study shows behavior shapes cortical network dynamics differently across frequencies and signal types in awake mice.

This paper introduces a method to analyze directional brain network organization using fMRI data, identifying strength and duration signatures of neural influence across species and conditions.

The paper investigates the neural origins of quasi-periodic patterns in resting-state fMRI using combined calcium imaging and fMRI, finding a time-locked correlation between neural activity and BOLD signals.

This study examines the relationship between neural and hemodynamic functional connectomes across time scales using simultaneous wide-field optical imaging and resting-state functional MRI.

This study evaluates how scan duration, TR, and frequency bands affect the reliability of functional connectivity patterns derived from rs-fMRI using QPPs and cPCA.

This study uses QPP and cPCA to analyze spatiotemporal network changes in AD progression, identifying early disruptions in specific brain networks and showing their potential as biomarkers.

This study uses an ODE model to separate rest and task signals in fMRI data, showing task-specific dynamics are subsets of rest dynamics and improving reaction time predictions.

This study compares functional connectivity and spatiotemporal dynamics in individuals with idiopathic hypersomnia, narcolepsy type 1, and healthy controls, finding significant differences in key networks post-nap.

This paper analyzes dynamic functional connectivity in fMRI data across attentional tasks to identify a spectrum of network relationships tracking external to internal attention.

QPPLab detects, analyzes, and visualizes large-scale quasiperiodic spatiotemporal patterns in brain activity, offering customizable tools and automated workflows for diverse datasets.

The paper examines variations in large-scale spatiotemporal brain activity patterns across different brain states using resting-state fMRI data from humans and rats.

The paper examines how arousal correlates with cortical voltage and hemodynamic signals in mice, finding distinct spatial and frequency-dependent patterns.

This study compares two dynamic functional connectivity methods in musicians, finding increased DMN-VIS and DMN-FPN correlations in improvisational musicians, replicating and expanding previous findings.

This study shows that time-varying functional connectivity between brain networks predicts fluctuations in sustained attention during a finger-tapping task.

This study investigates how optogenetic stimulation of the locus coeruleus affects global spatiotemporal patterns in rats using resting-state fMRI.

This paper investigates how systematic and random visual stimulation affects infraslow quasiperiodic spatiotemporal patterns (QPP) of whole-brain activity and finds distinct impacts on QPP waveform characteristics and frequency.

This paper uses Neural ODE to estimate initial conditions for brain network models to synchronize simulations with fMRI data, showing agreement between short-term and long-term parameterizations.

This study identifies widespread brain-body co-fluctuations across multiple physiological systems and shows they are linked to autonomic nervous system activity.

This paper identifies three spatiotemporal patterns that unify diverse resting-state functional MRI phenomena into a parsimonious framework of global brain organization.

This study identifies five brain states during suspenseful film viewing, showing four differ in frequency at suspense peaks compared to valleys.

This study uses a convolutional variational autoencoder to model spatiotemporal trajectories in resting-state fMRI data, revealing a small number of orthogonal patterns that capture key features of brain activity.

This study compares topological and traditional metrics for segmenting brain states from fMRI data, finding topological methods more accurate and generalizable.

The paper identifies spatiotemporal patterns of brain activity that propagate along macroscale gradients and contribute to functional connectivity.

This study uses prediction correlation on resting-state fMRI data to analyze spatiotemporal functional interactions within and between large-scale brain networks, revealing distinct connectivity patterns.

The paper shows that resting brain fluctuations in mice are intrinsically linked to visual response dynamics through quasiperiodic patterns.

The paper examines the relationship between BOLD and neural activity using simultaneous rs-fMRI and LFP recordings in rats, finding that high-amplitude LFP events drive BOLD signals and co-activation patterns.

This study examines how quasi-periodic patterns (QPPs) of low-frequency neural activity contribute to functional connectivity in the brain, showing differences between resting-state and task-performing individuals.

This study identifies quasi-periodic patterns in brain activity that contribute to functional connectivity differences in ADHD, showing reduced QPP contributions in key networks.