<b>Leveraging Whole Brain Imaging to Identify Brain Regions Involved in Alcohol Frontloading</b>
Creators: name: Ardinger, Cherish Elizabeth
Publisher: name: Purdue University Graduate School
Year: 2024
Subjects: classificationCode: 520202
subject: Behavioural neuroscience
classificationCode: 320904
subject: Computational neuroscience (incl. mathematical neuroscience and theoretical neuroscience)

description: Frontloading is an alcohol drinking pattern where intake is skewed toward the onset of access. The goal of the current study was to identify brain regions involved in frontloading using whole brain imaging. 63 C57Bl/6J (32 female and 31 male) mice underwent 8 days of binge drinking using drinking-in-the-dark (DID). Three hours into the dark cycle, mice received 20% (v/v) alcohol or water for two hours on days 1-7. Intake was measured in 1-minute bins using volumetric sippers, which facilitated analyses of drinking patterns. Mice were perfused 80 minutes into the day 8 DID session and brains were extracted and processed for iDISCO clearing and c-fos immunohistochemistry. For brain network analyses, day 8 drinking patterns were used to characterize mice as frontloaders or non-frontloaders using a change-point analysis described in our recent ACER publication (Ardinger et al., 2022). Groups were female frontloaders (n = 20), female non-frontloaders (n = 2), male frontloaders (n = 13) and male non-frontloaders (n = 8). There were no differences in total alcohol intake as a function of frontloading status. Water drinkers had an n of 10 for each sex. As only two female mice were characterized as non-frontloaders, it was not possible to construct a functional correlation network for this group. Following light sheet imaging, ClearMap2.1 was used to register brains to the Allen Brain Atlas and detect fos+ cells. Functional correlation matrices were calculated for each group from log<sub>10</sub> c-fos values. Euclidean distances were calculated from these R values and hierarchical clustering was used to determine modules (highly connected groups of brain regions) at a tree-cut height of 50%. In males, alcohol access decreased modularity (3 modules in both frontloaders and non-frontloaders) as compared to water drinkers (7 modules). In females, an opposite effect was observed. Alcohol access (9 modules) increased modularity as compared to water drinkers (5 modules). These results suggest sex differences in how alcohol consumption reorganizes the functional architecture of networks. Next, key brain regions in each network were identified. Connector hubs, which primarily facilitate communication between modules, and provincial hubs, which facilitate communication within modules, were of specific interest for their important and differing roles. In males, 4 connector hubs and 17 provincial hubs were uniquely identified in frontloaders (i.e., were brain regions that did not have this status in male non-frontloaders or water drinkers). These represented a group of hindbrain regions (e.g., locus coeruleus and the pontine gray) connected to striatal/cortical regions (e.g., cortical amygdalar area) by the paraventricular nucleus of the thalamus. In females, 16 connector and 17 provincial hubs were uniquely identified which were distributed across 8 of the 9 modules in the female alcohol drinker network. Only one brain region (the nucleus raphe pontis) was a connector hub in both sexes, suggesting that frontloading in males and females may be driven by different brain regions. In conclusion, alcohol consumption led to fewer, but more densely connected, groups of brain regions in males but not females, and recruited different hub brain regions between the sexes. These results suggest target brain regions for future studies to try to manipulate frontloading behavior and more broadly contribute to the literature on alcohol’s effect on neural networks.