Increased Basal Ganglia Modulatory Effective Connectivity Observed in Resting-State fMRI in Individuals With Parkinson's Disease.

Alterations to interactions between networked brain regions underlie cognitive impairment in many neurodegenerative diseases, providing an important physiological link between brain structure and cognitive function. Previous attempts to characterize the effects of Parkinson's disease (PD) on network functioning using resting-state functional magnetic resonance imaging (rs-fMRI), however, have yielded inconsistent and contradictory results. Potential problems with prior work arise in the specifics of how the area targeted by the diseases (the basal ganglia) interacts with other brain regions.

Reproductive success of Eastern Bluebirds (Sialia sialis) varies with the timing and severity of drought.

Drought affects avian communities in complex ways. We used our own and citizen science-generated reproductive data acquired through The Cornell Lab of Ornithology's NestWatch Program, combined with drought and vegetation indices obtained from governmental agencies, to determine drought effects on Eastern Bluebird (Sialia sialis L.) reproduction across their North American breeding range for the years 2006-2013.

Effect of Dopaminergic Medications on Blood Oxygen Level-Dependent Variability and Functional Connectivity in Parkinson's Disease and Healthy Aging.

Both functional connectivity (FC) and blood oxygen level-dependent (BOLD) signal variability (SD) are methods that are used for examining the physiological state of the brain. Although they are derived from signal changes and are related, a few studies have explored their relationship. Here, we examined the relationship between SD and FC within the default mode network (DMN) in healthy aging participants and those with Parkinson's disease (PD) ON and OFF dopaminergic medications.

Characterizing cross-subject spatial interaction patterns in functional magnetic resonance imaging studies: A two-stage point-process model.

We develop a two-stage spatial point process model that introduces new characterizations of activation patterns in multisubject functional Magnetic Resonance Imaging (fMRI) studies. Conventionally multisubject fMRI methods rely on combining information across subjects one voxel at a time in order to identify locations of peak activation in the brain. The two-stage model that we develop here addresses shortcomings of standard methods by explicitly modeling the spatial structure of functional signals and recognizing that corresponding cross-subject functional signals can be spatially misaligned.