Jessica S. Flannery

The DIVA Study investigates intra-individual variability in brain and behavior across the menstrual cycle in premenopausal women using multimodal neuroimaging and physiological data.

This paper develops and evaluates methods for decoding functional connectivity gradients in fMRI data using meta-analytic techniques and k-means segmentation.

This paper decomposes brain activity during the cue-reactivity paradigm into subnetworks associated with attention, reward, and affective processes using meta-analytic and connectivity techniques.

This study identifies common and distinct brain regions associated with risky and ambiguous decision-making through meta-analyses of neuroimaging data from 151 studies.

The paper uses meta-analytic clustering to identify seven brain activity patterns associated with different aspects of reward processing and their corresponding behavioral profiles.

This study dissociates habenula activity linked with nicotine withdrawal from striatal activity linked with addiction severity using pharmacological fMRI.

This study identifies seven recurrent brain networks involved in naturalistic cognition through a meta-analysis of fMRI data using k-means clustering and functional decoding.