Contributions of human amygdala nuclei to resting-state networks.

The amygdala is a brain region with a complex internal structure that is associated with psychiatric disease. Methodological limitations have complicated the study of the internal structure of the amygdala in humans. In the current study we examined the functional connectivity between nine amygdaloid nuclei and existing resting-state networks using a high spatial-resolution fMRI dataset.

Daily-Life Physical Activity of Healthy Young Adults Associates With Function and Structure of the Hippocampus.

Previous research on Physical Activity (PA) has been highly valuable in elucidating how PA affects the structure and function of the hippocampus in elderly populations that take part in structured interventions. However, how PA affects the hippocampus in younger populations that perform PA during daily-life activities remains poorly understood. In addition, this research has not examined the impact of PA on the internal structure of the hippocampus.

Medial temporal lobe contributions to resting-state networks.

The medial temporal lobe (MTL) is a set of interconnected brain regions that have been shown to play a central role in behavior as well as in neurological disease. Recent studies using resting-state functional magnetic resonance imaging (rsfMRI) have attempted to understand the MTL in terms of its functional connectivity with the rest of the brain. However, the exact characterization of the whole-brain networks that co-activate with the MTL as well as how the various sub-regions of the MTL are associated with these networks remains poorly understood.

Functional connectivity of the hippocampus and its subfields in resting-state networks.

Many neuroimaging studies have shown that the hippocampus participates in a resting-state network called the default mode network. However, how the hippocampus connects to the default mode network, whether the hippocampus connects to other resting-state networks and how the different hippocampal subfields take part in resting-state networks remains poorly understood. Here, we examined these issues using the high spatial-resolution 7T resting-state fMRI dataset from the Human Connectome Project.