Notes

Anatomical and also well-designed examination discloses TENM4 contributes to schizophrenia.
To understand the neural mechanism of repetitive transcranial magnetic stimulation (rTMS), the after-effects following one session or multiple days of stimulation have been widely investigated. However, the relation between the short-term effect (STE) and long-term effect (LTE) of rTMS is largely unknown. This study aims to explore whether the after-effects of 5-day rTMS on supplementary motor area (SMA) network could be predicted by one-session response. A primary cohort of 38 healthy participants underwent five daily sessions of real or sham continuous theta-burst stimulation (cTBS) on the left SMA. Resting-state functional magnetic resonance imaging (fMRI) data were acquired at the first (before and after the first stimulation) and sixth experimental day. The SMA connectivity changes after the first cTBS and after 5 days of stimulation were defined as STE and LTE, respectively. Compared to the baseline, significant STE and LTE were found in the bilateral paracentral gyrus (ParaCG) after real stimulation, suggesting shared neural correlates of short- and long-term stimulations. Region-of-interest analysis indicated that the resting-state functional connectivity between SMA and ParaCG increased after real stimulation, while no significant change was found after sham stimulation. Leave-one-out cross-validation indicated that the LTE in ParaCG could be predicted by the STE after real but not sham stimulations. In an independent cohort, the after-effects of rTMS on ParaCG and short- to long-term prediction were reproduced at the region-of-interest level. These imaging evidences indicate that one-session rTMS can aid to predict the regions responsive to long-term stimulation and the individualized response degree. Copyright © 2020 Ji, Sun, Liu, Wei, Li, Wu, Zhang, Yu, Bai, Zhu, Tian and Wang.A hallmark feature of Alzheimer's disease (AD) and other Tauopathies, like Frontotemporal Dementia with Parkinsonism linked to chromosome 17 (FTDP-17), is the accumulation of neurofibrillary tangles composed of the microtubule-associated protein Tau. As in AD, symptoms of FTDP-17 include cognitive decline, neuronal degeneration, and disruptions of sleep patterns. However, mechanisms by which Tau may lead to these disturbances in sleep and activity patterns are unknown. To identify such mechanisms, we have generated novel Drosophila Tauopathy models by replacing endogenous fly dTau with normal human Tau (hTau) or the FTDP-17 causing hTauV337M mutation. This mutation is localized in one of the microtubule-binding domains of hTau and has a dominant effect. Analyzing heterozygous flies, we found that aged hTauV337M flies show neuronal degeneration and locomotion deficits when compared to wild type or hTauWT flies. Furthermore, hTauV337M flies are hyperactive and they show a fragmented sleep pattern. These changes in the sleep/activity pattern are accompanied by morphological changes in the projection pattern of the central pacemaker neurons. These neurons show daily fluctuations in their connectivity, whereby synapses are increased during the day and reduced during sleep. Synapse formation requires cytoskeletal changes that can be detected by the accumulation of the end-binding protein 1 (EB1) at the site of synapse formation. Whereas, hTauWT flies show the normal day/night changes in EB1 accumulation, hTauV337M flies do not show this fluctuation. This suggests that hTauV337M disrupts sleep patterns by interfering with the cytoskeletal changes that are required for the synaptic homeostasis of central pacemaker neurons. Copyright © 2020 Cassar, Law, Chow, Giebultowicz and Kretzschmar.Itinerant dynamics of the brain generates transient and recurrent spatiotemporal patterns in neuroimaging data. Characterizing metastable functional connectivity (FC) - particularly at rest and using functional magnetic resonance imaging (fMRI) - has shaped the field of dynamic functional connectivity (DFC). Mainstream DFC research relies on (sliding window) correlations to identify recurrent FC patterns. Recently, functional relevance of the instantaneous phase synchrony (IPS) of fMRI signals has been revealed using imaging studies and computational models. In the present paper, we identify the repertoire of whole-brain inter-network IPS states at rest. Moreover, we uncover a hierarchy in the temporal organization of IPS modes. We hypothesize that connectivity disorder in schizophrenia (SZ) is related to the (deep) temporal arrangement of large-scale IPS modes. Hence, we analyze resting-state fMRI data from 68 healthy controls (HC) and 51 SZ patients. Seven resting-state networks (and their sub-components) ans is less efficient, less smooth, and more restricted in SZ subjects, compared to the HC. Finally, a regression analysis confirms the diagnostic value of the defined IPS measures for SZ identification, highlighting the distinctive role of metastate proportion. Our results suggest that the proposed IPS features may be used for classification studies and for characterizing phase synchrony modes in other (clinical) populations. Copyright © 2020 Zarghami, Hossein-Zadeh and Bahrami.Background Auditory deprivation alters cortical and subcortical brain regions, primarily linked to auditory and language processing, resulting in behavioral consequences. Neuroimaging studies have reported various degrees of structural changes, yet multiple variables in deafness profiles need to be considered for proper interpretation of results. To date, many inconsistencies are reported in the gray and white matter alterations following early profound deafness. The purpose of this study was to provide the first systematic review synthesizing gray and white matter changes in deaf individuals. Methods We conducted a systematic review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement in 27 studies comprising 626 deaf individuals. Results Evidence shows that auditory deprivation significantly alters the white matter across the primary and secondary auditory cortices. The most consistent alteration across studies was in the bilateral superior temporal gyri. Furthermore, reductions in the fractional anisotropy of white matter fibers comprising in inferior fronto-occipital fasciculus, the superior longitudinal fasciculus, and the subcortical auditory pathway are reported. The reviewed studies also suggest that gray and white matter integrity is sensitive to early sign language acquisition, attenuating the effect of auditory deprivation on neurocognitive development. Conclusions These findings suggest that understanding cortical reorganization through gray and white matter changes in auditory and non-auditory areas is an important factor in the development of auditory rehabilitation strategies in the deaf population. Copyright © 2020 Simon, Campbell, Genest, MacLean, Champoux and Lepore.Introduction Developing a machine learning-based approach which could provide quantitative identification of major depressive disorder (MDD) is essential for the diagnosis and intervention of this disorder. However, the performances of traditional algorithms using static functional connectivity (SFC) measures were unsatisfactory. In the present work, we exploit the hidden information embedded in dynamic functional connectivity (DFC) and developed an accurate and objective image-based diagnosis system for MDD. Methods MRI images were collected from 99 participants including 56 healthy controls and 43 MDD patients. DFC was calculated using a sliding-window algorithm. A non-linear support vector machine (SVM) approach was then used with the DFC matrices as features to distinguish MDD patients from healthy controls. The spatiotemporal characteristics of the most discriminative features were then investigated. Results The area under the curve (AUC) of the SVM classifier with DFC measures reached 0.9913, while this value is only 0.8685 for the algorithm using SFC measures. Spatially, the most discriminative 28 connections distributed in the visual network (VN), somatomotor network (SMN), dorsal attention network (DAN), ventral attention network (VAN), limbic network (LN), frontoparietal network (FPN), and default mode network (DMN), etc. Notably, a large portion of these connections were associated with the FPN, DMN, and VN. Temporally, the most discriminative connections transited from the cortex to deeper regions. Conclusion The results clearly suggested that DFC is superior to SFC and provide a reliable quantitative identification method for MDD. Our findings may furnish a better understanding of the neural mechanisms of MDD as well as improve accurate diagnosis and early intervention of this disorder. Copyright © 2020 Yan, Xu, Liu, Zheng, Liu, Li, Wei, Zhang, Lu and Li.Stuttering is a DSM V psychiatric condition for which there are no FDA-approved medications for treatment. A growing body of evidence suggests that dopamine antagonist medications are effective in reducing the severity of stuttering symptoms. Stuttering shares many similarities to Tourette's Syndrome in that both begin in childhood, follow a similar male to female ratio of 41, respond to dopamine antagonists, and symptomatically worsen with dopamine agonists. In recent years, advances in the neurophysiology of stuttering have helped further guide pharmacological treatment. selleck kinase inhibitor A newer medication with a novel mechanism of action, selective D1 antagonism, is currently being investigated in FDA trials for the treatment of stuttering. D1 antagonists possess different side-effect profiles than D2 antagonist medications and may provide a unique option for those who stutter. In addition, VMAT-2 inhibitors alter dopamine transmission in a unique mechanism of action that offers a promising treatment avenue in stuttering. This review seeks to highlight the different treatment options to help guide the practicing clinician in the treatment of stuttering. Copyright © 2020 Maguire, Nguyen, Simonson and Kurz.INTRODUCTION Previous research has indicated that weight control behaviors are linked to cigarette smoking, whether these relationships extend to electronic cigarettes (e-cigarettes) is unknown. This study aims to examine the association between weight control behaviors and current e-cigarette usage among middle and high school students in China. METHODS Based on the 2017 Zhejiang Youth Risk Behavior Survey, 17359 students were included and relevant data involving e-cigarette and weight control behaviors were collected via self-reported questionnaires. Logistic regression models were used to examine the associations between trying to control weight, specific weight control behaviors and current e-cigarette usage. Odds ratios (ORs) and their 95% confidence intervals (CIs) are reported. RESULTS Of the 17359 students, 374 (2.15%) were current e-cigarette users. No significant association was observed between trying to control weight and current e-cigarette usage (OR=1.01; 95% CI 0.81-1.28). Significant associations were found between current e-cigarette usage and unhealthy weight control behaviors of eating less food, fewer calories (OR=1.74; 95% CI 1.33-2.27), as well as taking laxatives (OR=3.34; 95% CI 2.11-5.27), taking diet pills (OR=2.63; 95% CI 1.72-4.02) and going without eating for 24 hours or more (OR=2.74; 95% CI 1.86-4.04). CONCLUSIONS A positive association was found between unhealthy weight control behaviors and current e-cigarette usage in adolescents. Specific education programs on unhealthy weight control behaviors should be considered in adolescents. © 2020 Wang M. et al.
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