BACKGROUND: Long-term alcohol abuse is associated with change in behavior, brain structure, and brain function. However, the nature of these changes is not well understood. In this study, we used network science to analyze a nonhuman primate model of ethanol self-administration to evaluate functional differences between animals with chronic alcohol use and animals with no exposure to alcohol. Of particular interest was how chronic alcohol exposure may affect the resting state network. METHODS: Baseline resting state functional magnetic resonance imaging was acquired in a cohort of vervet monkeys. Animals underwent an induction period where they were exposed to an isocaloric maltose dextrin solution (control) or ethanol in escalating doses over three 30-day epochs. Following induction, animals were given ad libitum access to water and a maltose dextrin solution (control) or water and ethanol for 22 h/d over 12 months. Cross-sectional analyses examined region of interests in hubs and community structure across animals to determine differences between drinking and nondrinking animals after the 12-month free access period. RESULTS: Animals were classified as lighter (<2.0 g/kg/d) or heavier drinkers (≥2.0 g/kg/d) based on a median split of their intake pattern during the 12-month ethanol free access period. Statistical analysis of hub connectivity showed significant differences in heavier drinkers for hubs in the precuneus, posterior parietal cortices, superior temporal gyrus, subgenual cingulate, and sensorimotor cortex. Heavier drinkers were also shown to have less consistent communities across the brain compared to lighter drinkers. The different level of consumption between the lighter and heavier drinking monkeys suggests that differences in connectivity may be intake dependent. CONCLUSIONS: Animals that consume alcohol show topological differences in brain network organization, particularly in animals that drink heavily. Differences in the resting state network were linked to areas that are associated with spatial association, working memory, and visuomotor processing.
BACKGROUND: Long-term alcohol abuse is associated with change in behavior, brain structure, and brain function. However, the nature of these changes is not well understood. In this study, we used network science to analyze a nonhuman primate model of ethanol self-administration to evaluate functional differences between animals with chronic alcohol use and animals with no exposure to alcohol. Of particular interest was how chronic alcohol exposure may affect the resting state network. METHODS: Baseline resting state functional magnetic resonance imaging was acquired in a cohort of vervet monkeys. Animals underwent an induction period where they were exposed to an isocaloric maltose dextrin solution (control) or ethanol in escalating doses over three 30-day epochs. Following induction, animals were given ad libitum access to water and a maltose dextrin solution (control) or water and ethanol for 22 h/d over 12 months. Cross-sectional analyses examined region of interests in hubs and community structure across animals to determine differences between drinking and nondrinking animals after the 12-month free access period. RESULTS: Animals were classified as lighter (<2.0 g/kg/d) or heavier drinkers (≥2.0 g/kg/d) based on a median split of their intake pattern during the 12-month ethanol free access period. Statistical analysis of hub connectivity showed significant differences in heavier drinkers for hubs in the precuneus, posterior parietal cortices, superior temporal gyrus, subgenual cingulate, and sensorimotor cortex. Heavier drinkers were also shown to have less consistent communities across the brain compared to lighter drinkers. The different level of consumption between the lighter and heavier drinking monkeys suggests that differences in connectivity may be intake dependent. CONCLUSIONS: Animals that consume alcohol show topological differences in brain network organization, particularly in animals that drink heavily. Differences in the resting state network were linked to areas that are associated with spatial association, working memory, and visuomotor processing.
Authors: Jared A Rowland; Jennifer R Stapleton-Kotloski; Greg E Alberto; April T Davenport; Robert J Kotloski; David P Friedman; Dwayne W Godwin; James B Daunais Journal: Drug Alcohol Depend Date: 2017-05-30 Impact factor: 4.492
Authors: Qawi K Telesford; Arian Ashourvan; Nicholas F Wymbs; Scott T Grafton; Jean M Vettel; Danielle S Bassett Journal: Hum Brain Mapp Date: 2017-06-24 Impact factor: 5.038
Authors: Jared A Rowland; Jennifer R Stapleton-Kotloski; Greg E Alberto; April T Davenport; Phillip M Epperly; Dwayne W Godwin; James B Daunais Journal: Front Behav Neurosci Date: 2021-06-02 Impact factor: 3.558