Publications by authors named "Lauren M Aiani"

Article Synopsis
  • Researchers have developed an automated classifier, SWISC, that can accurately score sleep-wake states and seizures in mice, achieving over 93% accuracy.
  • Traditional manual scoring of EEG in mouse models is challenging due to high variability, necessitating large sample sizes and impractical workloads.
  • The classifier utilizes advanced machine-learning techniques, specifically a bidirectional long short-term memory (BiLSTM) network, and primarily relies on hippocampal signals, making it effective even without electromyogram data.
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Background: Narcolepsy type 1 (NT1, narcolepsy with cataplexy) is a disabling neurological disorder caused by loss of excitatory orexin neurons from the hypothalamus and is characterized by decreased motivation, sleep-wake fragmentation, intrusion of rapid-eye-movement sleep (REMS) during wake, and abrupt loss of muscle tone, called cataplexy, in response to sudden emotions.

Objective: We investigated whether subcortical stimulation, analogous to clinical deep brain stimulation (DBS), would ameliorate NT1 using a validated transgenic mouse model with postnatal orexin neuron degeneration.

Methods: Using implanted electrodes in freely behaving mice, the immediate and prolonged effects of DBS were determined upon behavior using continuous video-electroencephalogram-electromyogram (video/EEG/EMG) and locomotor activity, and neural activation in brain sections, using immunohistochemical labeling of the immediate early gene product c-Fos.

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Background: Mouse models are beneficial to understanding neural networks given a wide array of transgenic mice and cell-selective techniques. However, instrumentation of mice for neurophysiological studies is difficult. Often surgery is prolonged with experimental error arising from non-concurrent and variable implantations.

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Despite commercial availability of software to facilitate sleep-wake scoring of electroencephalography (EEG) and electromyography (EMG) in animals, automated scoring of rodent models of abnormal sleep, such as narcolepsy with cataplexy, has remained elusive. We optimize two machine-learning approaches, supervised and unsupervised, for automated scoring of behavioral states in orexin/ataxin-3 transgenic mice, a validated model of narcolepsy type 1, and additionally test them on wild-type mice. The supervised learning approach uses previously labeled data to facilitate training of a classifier for sleep states, whereas the unsupervised approach aims to discover latent structure and similarities in unlabeled data from which sleep stages are inferred.

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Rationale: Understanding the neurobiological mechanisms mediating dominance and competitive aggression is essential to understanding the development and treatment of various psychiatric disorders. Previous research suggests that these mechanisms are both sexually differentiated and influenced substantially by social experience. In numerous species, GABA receptors in the lateral septum have been shown to play a significant role in aggression in males.

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Social reward is critical for social relationships, and yet we know little about the characteristics of social interactions that are rewarding or the neural mechanisms underlying that reward. Here, we investigate the sex-dependent role of oxytocin receptors within the ventral tegmental area (VTA) in mediating the magnitude and valence of social reward. Operant and classical conditioning tests were used to measure social reward associated with same-sex social interactions.

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The rewarding properties of social interactions play a critical role in the development and maintenance of social relationships, and deficits in social reward are associated with various psychiatric disorders. In the present study, we used a novel Operant Social Preference (OSP) task to investigate the reinforcing properties of social interactions under conditions of high or low reward value, and high or low behavioral effort in male Syrian hamsters. Further, we investigated the role of oxytocin (OT) in a key structure of the mesolimbic reward system, the ventral tegmental area (VTA), in mediating the reinforcing properties of social interaction.

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Background: Social reward plays a critical role in the development of beneficial social relationships, and disorders of the mechanisms controlling social reward are involved in the etiology of many psychiatric diseases.

New Method: We present a novel operant social preference task to quantify social reward in rodents using an apparatus with three chambers separated by one-way vertical-swing doors. The experimental animal is placed in the larger chamber while the two smaller chambers either remain empty or contain a stimulus animal or other potential reward stimulus.

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