Combined T1-weighted MRI and diffusion MRI tractography of paraventricular, locus coeruleus, and dorsal vagal complex connectivity in brainstem-hypothalamic nuclei.

Background: Current multimodal neuroimaging plays a critical role in studying clinical conditions such as cardiovascular disease, major depression, and other disorders related to chronic stress. These conditions involve the brainstem-hypothalamic network, specifically the locus coeruleus (LC), dorsal vagal complex (DVC), and paraventricular nucleus (PVN) of the hypothalamus, collectively referred to as the "DVC-LC-PVN circuitry." This circuitry is strongly associated with the norepinephrine (NE) and epinephrine (E) neurotransmitter systems, which are implicated in the regulation of key autonomic functions, such as cardiovascular and respiratory control, stress response, and cognitive and emotional behaviors.

Objectives: To develop a methodology for delineating the DVC-LC-PVN circuitry in the human brain using multimodal neuroimaging.

Methods: We combined structural T1-weighted morphometric magnetic resonance imaging (MRI) and diffusion MRI-based tractography to map the DVC-LC-PVN circuitry in the human brain. This methodology was applied to a pilot sample of brain datasets from five healthy adult subjects obtained from the publicly available Human Connectome Project repository and to one post-mortem human dataset.

Results: The DVC-LC-PVN circuitry was delineated in vivo in five human subjects and one ultra-high resolution post-mortem dataset, allowing for refined anatomical observations.

Conclusion: NE and E neurotransmitter systems engender substantial interest in both basic and clinical neuroscience due to their roles in the regulation of key autonomic functions, such as cardiovascular and respiratory control, stress responses, and cognitive and emotional behaviors. As demonstrated in this study, multimodal neuroimaging techniques provide a valuable approach for mapping small brainstem and hypothalamic structures and complex circuitries such as the DVC-LC-PVN circuitry.