Evelyn M. R. Lake

The paper uses Bayesian generative modeling to show the mouse brain's functional connectome has multiple co-dominant organizational configurations rather than a single structure.

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.

The paper introduces channel capacity as a measure of directed information transfer between brain regions and validates it across human and rodent neuroimaging datasets to assess its sensitivity, specificity, and temporal variability.

This paper introduces a biphasic acclimation protocol for simultaneous wide-field fluorescent Ca2+ imaging and fMRI in awake mice, showing convergent and divergent patterns in brain function between modalities.

The paper uses simultaneous calcium imaging and fMRI in mice to identify cell-type specific signals in the brain with high spatiotemporal resolution.

This paper develops a geometrically constrained framework to map brain regions across species and shows geometry influences regional organization through patterning molecules.

This study investigates the effects of repetitive mild closed-head injury on synaptic density and BOLD-fMRI signal homogeneity in mice, finding decreased synapse density and increased regional homogeneity.

The paper uses Ca2+ imaging and fMRI-BOLD in mice to compare functional network organization, finding overlapping but distinct patterns between modalities.

The paper uses fMRI to track functional connectivity changes in a mouse model of Alzheimer's disease over time and shows that mGluR5 modulator treatment reverses these deficits.

This study shows PTEN mutations cause ventriculomegaly and cortical network dysfunction through neural precursor and interneuron dysregulation, with mTORC1 inhibition offering therapeutic potential.

This study investigates how arousal levels affect brain network integration using resting state fMRI and pupillometry, showing decreased integration and variability at low arousal.

This paper uses bootstrap aggregating (bagging) to improve the generalizability of predictive models of fluid intelligence from functional connectivity data across different datasets.

The paper uses task-based functional MRI connectomes to predict cognitive phenotypes across psychiatric diseases and shows differences in connectomes by disease category and symptom severity.

This paper combines mesoscopic Ca2+ imaging and fMRI to study brain activity across spatiotemporal scales, finding correspondence between signals and stable connectivity matrices.

This study uses connectome-based predictive modeling on fMRI data to identify functional brain networks that predict social ability measures in autism spectrum disorder.