19 research outputs found

    Neurobiology of rodent self-grooming and its value for translational neuroscience

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    Self-grooming is a complex innate behaviour with an evolutionarily conserved sequencing pattern and is one of the most frequently performed behavioural activities in rodents. In this Review, we discuss the neurobiology of rodent self-grooming, and we highlight studies of rodent models of neuropsychiatric disorders-including models of autism spectrum disorder and obsessive compulsive disorder-that have assessed self-grooming phenotypes. We suggest that rodent self-grooming may be a useful measure of repetitive behaviour in such models, and therefore of value to translational psychiatry. Assessment of rodent self-grooming may also be useful for understanding the neural circuits that are involved in complex sequential patterns of action.National Institutes of Health (U.S.) (Grant NS025529)National Institutes of Health (U.S.) (Grant HD028341)National Institutes of Health (U.S.) (Grant MH060379

    Acetylcholine: Definition

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    Real-time detection of neural oscillation bursts allows behaviourally relevant neurofeedback

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    Neural oscillations as important information carrier in the brain, are increasingly interpreted as transient bursts rather than as sustained oscillations. Short (<150 ms) bursts of beta-waves (15-30 Hz) have been documented in humans, monkeys and mice. These events were correlated with memory, movement and perception, and were even suggested as the primary ingredient of all beta-band activity. However, a method to measure these short-lived events in real-time and to investigate their impact on behaviour is missing. Here we present a real-time data analysis system, capable to detect short narrowband bursts, and demonstrate its usefulness to increase the beta-band burst-rate in rats. This neurofeedback training induced changes in overall oscillatory power, and bursts could be decoded from the movement of the rats, thus enabling future investigation of the role of oscillatory bursts. Karvat et al. describe a real-time digital signal-processing method to detect neural oscillations in the form of short and narrowband bursts. Using this real-time method, they show that neurofeedback increases burst-related behaviours and that these bursts can be decoded from the movements of the rats
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