Leveraging Neural Networks in Preclinical Alcohol Research

Smith, Lauren C.; Kimbrough, Adam

doi:10.3390/brainsci10090578

Cited by 8 publications

(4 citation statements)

References 229 publications

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“…Another limitation of the present study is the lack of direct comparisons between neural activation of each treatment. The approaches used within this study can be leveraged to study and better understand numerous cognitive states ( Smith and Kimbrough, 2020 ; Simpson et al, 2021 ). However, in the future assessing neural and network differences in more quantitative ways will be necessary.…”

Section: Discussionmentioning

confidence: 99%

Characterization of the Brain Functional Architecture of Psychostimulant Withdrawal Using Single-Cell Whole-Brain Imaging

Kimbrough

Kallupi

Smith

et al. 2021

eNeuro

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Numerous brain regions have been identified as contributing to withdrawal behaviors, but unclear is the way in which these brain regions as a whole lead to withdrawal. The search for a final common brain pathway that is involved in withdrawal remains elusive. To address this question, we implanted osmotic minipumps containing either saline, nicotine (24 mg/kg/day), cocaine (60 mg/kg/day), or methamphetamine (4 mg/kg/day) for 1 week in male C57BL/6J mice.After 1 week the minipumps were removed and brains collected 8 hours (saline, nicotine and cocaine) or 12 hours (methamphetamine) after removal. We then performed single-cell wholebrain imaging of neural activity during the withdrawal period when brains were collected. We used hierarchical clustering and graph theory to identify similarities and differences in brain functional architecture. Although methamphetamine and cocaine shared some network similarities, the main common neuroadaptation between these psychostimulant drugs was a dramatic decrease in modularity, with a shift from a cortical-to subcortical-driven network, including a decrease in total hub brain regions. These results demonstrate that psychostimulant withdrawal produces the drug-dependent remodeling of functional architecture of the brain and suggest that the decreased modularity of brain functional networks and not a specific set of brain regions may represent the final common pathway associated with withdrawal. Significance StatementA key aspect of treating drug abuse is understanding similarities and differences of how drugs of abuse affect the brain. In the present study we examined how the brain is altered during withdrawal from psychostimulants. We found that each drug produced a unique pattern of activity in the brain, but that brains in withdrawal from cocaine and methamphetamine shared 3 similar features. Interestingly, we found the major common link between withdrawal from all psychostimulants, when compared to controls, was a shift in the broad organization of the brain in the form of reduced modularity. Reduced modularity has been shown in several brain disorders, including traumatic brain injury, and dementia, and may be the common link between drugs of abuse.

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Section: Discussionmentioning

confidence: 99%

Characterization of the Brain Functional Architecture of Psychostimulant Withdrawal Using Single-Cell Whole-Brain Imaging

Kimbrough

Kallupi

Smith

et al. 2021

eNeuro

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“…Advancements in tissue clearing approaches coupled with immunolabeling have opened the door to the unbiased assessment of whole brain networks with single-cell resolution, for reviews, see (2,3). Immunolabeling-enabled imaging of solvent-cleared organs (iDISCO+) (4,5) with light sheet imaging is increasingly being utilized in the alcohol field (6)(7)(8)(9).…”

Section: Introductionmentioning

confidence: 99%

Sex Differences in Neural Networks Recruited by Frontloaded Binge Alcohol Drinking

Ardinger,

Chen,

Kimbrough

et al. 2024

Preprint

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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. Whole brain imaging was performed in 63 C57Bl/6J (32 female and 31 male) mice that underwent 8 days of binge drinking using the drinking-in-the-dark (DID) model. On days 1-7, three hours into the dark cycle, mice received 20% (v/v) alcohol or water for two hours. Intake was measured in 1-minute bins using volumetric sippers, which facilitated analyses of drinking patterns. On day 8 mice were perfused 80 minutes into the DID session and brains were extracted. Brains were then processed to stain for Fos protein using iDISCO+. Following light sheet imaging, ClearMap2.1 was used to register brains to the Allen Brain Atlas and detect Fos+ cells. For brain network analyses, day 8 drinking patterns were used to characterize mice as frontloaders or non-frontloaders using a recently developed change-point analysis. Based on this analysis the 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 in animals that frontloaded versus those that did not. Only two female mice were characterized as non-frontloaders, thus preventing brain network analysis of this group. Functional correlation matrices were calculated for each group from log10 Fos values. Euclidean distances were calculated from these R values and hierarchical clustering was used to determine modules (highly connected groups of brain regions). 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 for frontloaders) increased modularity as compared to water drinkers (5 modules). These results suggest sex differences in how alcohol consumption reorganizes the functional architecture of neural 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) functionally 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 frontloader 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 that alcohol frontloading leads to a reduction in network efficiency in male mice.

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“…While these and other models have generated important insight into key neurochemicals and circuits that contribute to alcohol dependence, existing studies are biased toward brain regions already established to play a role in addiction (12), leaving a wide knowledge gap concerning other potentially influential regions. The recent implementation of unbiased whole-brain approaches and graph theoretical methods has begun to bridge this gap (13). Network-based methods can provide insight into how the brain produces complex cognitive states and behaviors, Brain network reorganization in alcohol dependence… which arise from coordinated activity among groups or "communities" of brain regions (14).…”

Section: Introductionmentioning

confidence: 99%

Alcohol dependence modifies brain networks activated during abstinence and reaccess: a c-fos-based analysis in mice

Roland

Coelho

Haun

et al. 2022

Preprint

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High-level alcohol consumption causes neuroplastic changes in the brain that lead to negative affective and somatic symptoms when alcohol is withdrawn, promoting relapse drinking. We have some understanding of these plastic changes in defined brain circuits and cell types, but unbiased approaches are needed to explore broader patterns of adaptations. Here, we employed whole-brain c-fos mapping and network analysis to assess how brain-wide patterns of neuronal activity are altered during acute alcohol abstinence and reaccess in a well-characterized model of alcohol dependence. Mice underwent four cycles of chronic intermittent ethanol vapor exposure (CIE) with alternating weeks of voluntary alcohol drinking, and a subset of mice underwent forced swim stress (FSS) prior to drinking sessions to further escalate alcohol consumption. After four CIE cycles, brains were collected from mice in each group either 24 hours (abstinence) or immediately following a one-hour period of alcohol reaccess. Brains from CIE mice during acute abstinence displayed widespread neuronal activation relative to those from AIR mice, independent of FSS, and this increase in c-fos was reversed by reaccess drinking. For network analysis, mice were then classified as high or low drinkers (HD or LD). We computed Pearson correlations for all pairs of brain regions and used graph theoretical methods to identify changes in network properties associated with high-drinking behavior. Network modularity, a measure of network segregation into communities, was increased in HD mice after alcohol reaccess relative to abstinence. Within-community strength and diversity measures were computed for each region and condition, and highly coactive regions were identified. One high-diversity region, the cortical amygdala (COA), was further interrogated using a chemogenetic approach. COA silencing in CIE mice reduced voluntary drinking, validating our network analysis and indicating that this region may play an important but underappreciated role in alcohol dependence.

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Leveraging Neural Networks in Preclinical Alcohol Research

Cited by 8 publications

References 229 publications

Characterization of the Brain Functional Architecture of Psychostimulant Withdrawal Using Single-Cell Whole-Brain Imaging

Characterization of the Brain Functional Architecture of Psychostimulant Withdrawal Using Single-Cell Whole-Brain Imaging

Sex Differences in Neural Networks Recruited by Frontloaded Binge Alcohol Drinking

Alcohol dependence modifies brain networks activated during abstinence and reaccess: a c-fos-based analysis in mice

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