Functional connectivity of the human hypothalamus using meta-analytic connectivity modeling
Creators: name: Bottenhorn, Katherine L.
name: Robinson, Jennifer L.
Publisher: name: Zenodo
Year: 2014
Subjects: human hypothalamus
neuroimaging meta-analysis

description: <strong>Introduction:</strong> The human hypothalamus is an intersection between several neural systems and is implicated in numerous processes and disorders related to homeostasis. Despite its vital role in autonomic regulation, very few studies have assessed its neural connectivity and associated functional relationship with the rest of the brain. In this study, we examined the functional connectivity of the human hypothalamus using a robust meta-analytic technique. <strong>Methods:</strong> Functional connectivity of the human hypothalamus was assessed using meta-analytic connectivity modeling (MACM) methods, which capitalize on the rigorous coding structure of the BrainMap database. <em>ROI Selection.</em> Because there is no readily available hypothalamic ROI, we applied a replicable method of ROI generation using Mango’s Talairach Loader plugin. In addition to a bilateral hypothalamic ROI, left and right ROIs were also created in order to identify hemisphere-specific functional connectivity. <em>BrainMap Meta-Analysis.</em> To search for studies that included activation of the hypothalamus, we used Sleuth to query the BrainMap database, with the above ROIs. We imposed additional search criteria to limit our dataset to only those studies reporting activation in healthy populations. The results for the bilateral ROI included data from 34 papers, 494 subjects, and 42 experiments. The right hypothalamus results included data from 20 papers, 287 subjects, and 25 experiments. The left hypothalamus results included data from 17 papers, 257 subjects, and 20 experiments. <em>Activation Likelihood Estimation (ALE)</em>. ALE was performed on the coordinates included in the data generated by the BrainMap search. Analysis of these coordinates provided information about the convergence of regions of coactivation at the 99% confidence level. <em>Behavioral Analysis.</em> We used Mango, equipped with the Behavioral Analysis plug-in, which uses a brain ROI defined by the user in Talairach space as a target to perform regional behavioral analysis. The behavioral domains are representative of the spatial probability mapping of activation foci from the BrainMap database, indicative of the true probability distribution of each domain and sub-domain’s activation locations. <strong>Results:</strong> <em>ALE.</em> Coactivation with bilateral hypothalamus was identified in 17 regions of the brain, including the left insula, bilateral inferior frontal gyri, bilateral superior temporal gyri, bilateral parahippocampal gyri, and the right anterior cingulate.. Coactivation with the right hypothalamus was identified in bilateral thalami, bilateral superior temporal gyri, left parahippocampus, and the right amygdala. For the left hypothalamus, we identified coactivation in the left inferior and superior frontal gyri, the right middle frontal gyrus, the right parahippocampus, and the right anterior cingulate. <em>Behavioral Analysis. </em>Four behavioral domains were represented within the hypothalamus ROI, the most notable of which was Interoception. Among these behaviors identified were five sub-domains of interoception (sexuality, air-hunger, sleep, bladder, and hunger), which is consistent with the current literature concerning hypothalamic functions. <strong>Conclusions:</strong> Our data reveal distinct patterns of functional connectivity between the hypothalamus and regions of cognitive and emotional processes. Because of the intimate involvement of the hypothalamus with autonomic and neuroendocrine responses, these connectivity patterns may reveal potential regions of intervention for disorders that have known aberrant hypothalamic function such as post traumatic stress disorder, which is characterized by intense emotional responses that lead to distinct physiological responses. Future research should examine resting state and diffusion tensor imaging patterns to extend our understanding of the connectivity of this structure in relation to the rest of the brain.