AI Article Synopsis

  • The study investigates how drug effects in rats differ based on their activity levels during electroencephalography (EEG) recordings, proposing an automatic detection method for active and inactive states.
  • Researchers developed a precise state-detection system that correctly classified behavior over 90% of the time, revealing significant differences in brain activity patterns depending on the rat's locomotion state.
  • The findings showed that drug effects, particularly from ketamine and DOI, were more pronounced during inactive states, suggesting this method could enhance our understanding of how drugs affect brain function across species.

Article Abstract

Quantitative electroencephalography from freely moving rats is commonly used as a translational tool for predicting drug-effects in humans. We hypothesized that drug-effects may be expressed differently depending on whether the rat is in active locomotion or sitting still during recording sessions, and proposed automatic state-detection as a viable tool for estimating drug-effects free of hypo-/hyperlocomotion-induced effects. We aimed at developing a fully automatic and validated method for detecting two behavioural states: active and inactive, in one-second intervals and to use the method for evaluating ketamine, DOI, d-cycloserine, d-amphetamine, and diazepam effects specifically within each state. The developed state-detector attained high precision with more than 90% of the detected time correctly classified, and multiple differences between the two detected states were discovered. Ketamine-induced delta activity was found specifically related to locomotion. Ketamine and DOI suppressed theta and beta oscillations exclusively during inactivity. Characteristic gamma and high-frequency oscillations (HFO) enhancements of the NMDAR and 5HT modulators, speculated associated with locomotion, were profound and often largest during the inactive state. State-specific analyses, theoretically eliminating biases from altered occurrence of locomotion, revealed only few effects of d-amphetamine and diazepam. Overall, drug-effects were most abundant in the inactive state. In conclusion, this new validated and automatic locomotion state-detection method enables fast and reliable state-specific analysis facilitating discovery of state-dependent drug-effects and control for altered occurrence of locomotion. This may ultimately lead to better cross-species translation of electrophysiological effects of pharmacological modulations.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6806018PMC
http://dx.doi.org/10.1111/ejn.14373DOI Listing

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