Basal Forebrain Cholinergic Activity Modulates Isoflurane and Propofol Anesthesia. Luo Tian-Yuan,Cai Shuang,Qin Zai-Xun,Yang Shao-Cheng,Shu Yue,Liu Cheng-Xi,Zhang Yu,Zhang Lin,Zhou Liang,Yu Tian,Yu Shou-Yang Frontiers in neuroscience Cholinergic neurons in the basal forebrain (BF) have long been considered to be the key neurons in the regulation of cortical and behavioral arousal, and cholinergic activation in the downstream region of the BF can arouse anesthetized rats. However, whether the activation of BF cholinergic neurons can induce behavior and electroencephalogram (EEG) recovery from anesthesia is unclear. In this study, based on a transgenic mouse line expressing ChAT-IRES-Cre, we applied a fiber photometry system combined with GCaMPs expression in the BF and found that both isoflurane and propofol inhibit the activity of BF cholinergic neurons, which is closely related to the consciousness transition. We further revealed that genetic lesion of BF cholinergic neurons was associated with a markedly increased potency of anesthetics, while designer receptor exclusively activated by designer drugs (DREADD)-activated BF cholinergic neurons was responsible for slower induction and faster recovery of anesthesia. We also documented a significant increase in δ power bands (1-4 Hz) and a decrease in β (12-25 Hz) power bands in BF cholinergic lesioned mice, while there was a clearly noticeable decline in EEG δ power of activated BF cholinergic neurons. Moreover, sensitivity to anesthetics was reduced after optical stimulation of BF cholinergic cells, yet it failed to restore wake-like behavior in constantly anesthetized mice. Our results indicate a functional role of BF cholinergic neurons in the regulation of general anesthesia. Inhibition of BF cholinergic neurons mediates the formation of unconsciousness induced by general anesthetics, and their activation promotes recovery from the anesthesia state. 10.3389/fnins.2020.559077

Non-Contact Sleep Stage Detection Using Canonical Correlation Analysis of Respiratory Sound. Xue Biao,Deng Boya,Hong Hong,Wang Zhiyong,Zhu Xiaohua,Feng David Dagan IEEE journal of biomedical and health informatics Respiratory sound is able to differentiate sleep stages and provide a non-contact and cost-effective solution for the diagnosis and treatment monitoring of sleep-related diseases. While most of the existing respiratory sound-based methods focus on a limited number of sleep stages such as sleep/wake and wake/rapid eye movement (REM)/non-REM, it is essential to detect sleep stages at a finer level for sleep quality evaluation. In this paper, we for the first time study a sleep stage detection method aiming at classifying sleep states into four sleep stages: wake, REM, light sleep, and deep sleep from the respiratory sound. In addition to extracting time-domain features, frequency-domain features of respiratory sound, non-linear features of snoring sound are devised to better characterize snoring-related signals of respiratory sound. To effectively fuse the three sets of features, a novel feature fusion technique combining the generalized canonical correlation analysis with the ReliefF algorithm is proposed for discriminative feature selection. Final stage detection is achieved with popular classifiers including decision tree, support vector machines, K-nearest neighbor, and the ensemble classifier. To evaluate our proposed method, we built an in-house dataset, which is comprised of 13 nights of sleep audio data from a sleep laboratory. Experimental results indicate that our proposed method outperforms the existing related ones and is promising for large-scale non-contact sleep monitoring. 10.1109/JBHI.2019.2910566

An evidence-based approach to psychopharmacology for posttraumatic stress disorder (PTSD) - 2022 update. Psychiatry research Algorithms for posttraumatic stress disorder were published by this team in 1999 and 2011. Developments since then warrant revision. New studies and review articles from January 2011 to November 2021 were identified via PubMed and analyzed for evidence supporting changes. Following consideration of variations required by special patient populations, treatment of sleep impairments remains as the first recommended step. Nightmares and non-nightmare disturbed awakenings are best addressed with the anti-adrenergic agent prazosin, with doxazosin and clonidine as alternatives. First choices for difficulty initiating sleep include hydroxyzine and trazodone. If significant non-sleep PTSD symptoms remain, an SSRI should be tried, followed by a second SSRI or venlafaxine as a third step. Second generation antipsychotics can be considered, particularly for SSRI augmentation when PTSD-associated psychotic symptoms are present, with the caveat that positive evidence is limited and side effects are considerable. Anti-adrenergic agents can also be considered for general PTSD symptoms if not already tried, though evidence for daytime use lags that available for sleep. Regarding other pharmacological and procedural options, e.g., transcranial magnetic stimulation, cannabinoids, ketamine, psychedelics, and stellate ganglion block, evidence does not yet support firm inclusion in the algorithm. An interactive version of this work can be found at www.psychopharm.mobi. 10.1016/j.psychres.2022.114840