| Autor: |
Angela M. Henricks, Emily D. K. Sullivan, Lucas L. Dwiel, Karina M. Keus, Ethan D. Adner, Alan I. Green, Wilder T. Doucette |
| Jazyk: |
angličtina |
| Rok vydání: |
2019 |
| Předmět: |
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| Zdroj: |
Biology of Sex Differences, Vol 10, Iss 1, Pp 1-10 (2019) |
| Druh dokumentu: |
article |
| ISSN: |
2042-6410 |
| DOI: |
10.1186/s13293-019-0276-0 |
| Popis: |
Abstract 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 |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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