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Sex differences in the ability of corticostriatal oscillations to predict rodent alcohol consumption

BACKGROUND: Although male and female rats differ in their patterns of alcohol use, little is known regarding the neural circuit activity that underlies these differences in behavior. The current study used a machine learning approach to characterize sex differences in local field potential (LFP) osc...

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Autores principales: Henricks, Angela M., Sullivan, Emily D. K., Dwiel, Lucas L., Keus, Karina M., Adner, Ethan D., Green, Alan I., Doucette, Wilder T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6918672/
https://www.ncbi.nlm.nih.gov/pubmed/31849345
http://dx.doi.org/10.1186/s13293-019-0276-0
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author Henricks, Angela M.
Sullivan, Emily D. K.
Dwiel, Lucas L.
Keus, Karina M.
Adner, Ethan D.
Green, Alan I.
Doucette, Wilder T.
author_facet Henricks, Angela M.
Sullivan, Emily D. K.
Dwiel, Lucas L.
Keus, Karina M.
Adner, Ethan D.
Green, Alan I.
Doucette, Wilder T.
author_sort Henricks, Angela M.
collection PubMed
description BACKGROUND: Although male and female rats differ in their patterns of alcohol use, little is known regarding the neural circuit activity that underlies these differences in behavior. The current study used a machine learning approach to characterize sex differences in local field potential (LFP) oscillations that may relate to sex differences in alcohol-drinking behavior. METHODS: LFP oscillations were recorded from the nucleus accumbens shell and the rodent medial prefrontal cortex of adult male and female Sprague-Dawley rats. Recordings occurred before rats were exposed to alcohol (n = 10/sex × 2 recordings/rat) and during sessions of limited access to alcohol (n = 5/sex × 5 recordings/rat). Oscillations were also recorded from each female rat in each phase of estrous prior to alcohol exposure. Using machine learning, we built predictive models with oscillation data to classify rats based on: (1) biological sex, (2) phase of estrous, and (3) alcohol intake levels. We evaluated model performance from real data by comparing it to the performance of models built and tested on permutations of the data. RESULTS: Our data demonstrate that corticostriatal oscillations were able to predict alcohol intake levels in males (p < 0.01), but not in females (p = 0.45). The accuracies of models predicting biological sex and phase of estrous were related to fluctuations observed in alcohol drinking levels; females in diestrus drank more alcohol than males (p = 0.052), and the male vs. diestrus female model had the highest accuracy (71.01%) compared to chance estimates. Conversely, females in estrus drank very similar amounts of alcohol to males (p = 0.702), and the male vs. estrus female model had the lowest accuracy (56.14%) compared to chance estimates. CONCLUSIONS: The current data demonstrate that oscillations recorded from corticostriatal circuits contain significant information regarding alcohol drinking in males, but not alcohol drinking in females. Future work will focus on identifying where to record LFP oscillations in order to predict alcohol drinking in females, which may help elucidate sex-specific neural targets for future therapeutic development.
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spelling pubmed-69186722019-12-20 Sex differences in the ability of corticostriatal oscillations to predict rodent alcohol consumption Henricks, Angela M. Sullivan, Emily D. K. Dwiel, Lucas L. Keus, Karina M. Adner, Ethan D. Green, Alan I. Doucette, Wilder T. Biol Sex Differ Research BACKGROUND: Although male and female rats differ in their patterns of alcohol use, little is known regarding the neural circuit activity that underlies these differences in behavior. The current study used a machine learning approach to characterize sex differences in local field potential (LFP) oscillations that may relate to sex differences in alcohol-drinking behavior. METHODS: LFP oscillations were recorded from the nucleus accumbens shell and the rodent medial prefrontal cortex of adult male and female Sprague-Dawley rats. Recordings occurred before rats were exposed to alcohol (n = 10/sex × 2 recordings/rat) and during sessions of limited access to alcohol (n = 5/sex × 5 recordings/rat). Oscillations were also recorded from each female rat in each phase of estrous prior to alcohol exposure. Using machine learning, we built predictive models with oscillation data to classify rats based on: (1) biological sex, (2) phase of estrous, and (3) alcohol intake levels. We evaluated model performance from real data by comparing it to the performance of models built and tested on permutations of the data. RESULTS: Our data demonstrate that corticostriatal oscillations were able to predict alcohol intake levels in males (p < 0.01), but not in females (p = 0.45). The accuracies of models predicting biological sex and phase of estrous were related to fluctuations observed in alcohol drinking levels; females in diestrus drank more alcohol than males (p = 0.052), and the male vs. diestrus female model had the highest accuracy (71.01%) compared to chance estimates. Conversely, females in estrus drank very similar amounts of alcohol to males (p = 0.702), and the male vs. estrus female model had the lowest accuracy (56.14%) compared to chance estimates. CONCLUSIONS: The current data demonstrate that oscillations recorded from corticostriatal circuits contain significant information regarding alcohol drinking in males, but not alcohol drinking in females. Future work will focus on identifying where to record LFP oscillations in order to predict alcohol drinking in females, which may help elucidate sex-specific neural targets for future therapeutic development. BioMed Central 2019-12-18 /pmc/articles/PMC6918672/ /pubmed/31849345 http://dx.doi.org/10.1186/s13293-019-0276-0 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Henricks, Angela M.
Sullivan, Emily D. K.
Dwiel, Lucas L.
Keus, Karina M.
Adner, Ethan D.
Green, Alan I.
Doucette, Wilder T.
Sex differences in the ability of corticostriatal oscillations to predict rodent alcohol consumption
title Sex differences in the ability of corticostriatal oscillations to predict rodent alcohol consumption
title_full Sex differences in the ability of corticostriatal oscillations to predict rodent alcohol consumption
title_fullStr Sex differences in the ability of corticostriatal oscillations to predict rodent alcohol consumption
title_full_unstemmed Sex differences in the ability of corticostriatal oscillations to predict rodent alcohol consumption
title_short Sex differences in the ability of corticostriatal oscillations to predict rodent alcohol consumption
title_sort sex differences in the ability of corticostriatal oscillations to predict rodent alcohol consumption
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6918672/
https://www.ncbi.nlm.nih.gov/pubmed/31849345
http://dx.doi.org/10.1186/s13293-019-0276-0
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