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Benzodiazepines (BZD) are one of the most frequently prescribed drugs worldwide. However, the cognitive effects of benzodiazepines in the elderly are highly debated. This systematic review and meta-analysis aims to explore the following two questions in the elderly population (i) Do BZD lead to any impairments in cognitive functions in elderly users? and (ii) Which specific cognitive domains are most affected by BZD use and abuse?

First, we performed a literature search following the PRISMA guidelines. Electronic databases, including PubMed, PsycINFO, EMBASE, Cochrane Library, and Web of Science were searched until May 14

, 2020. After selecting the relevant articles, we integrated the results of the selected studies with a standardized cognitive classification method. Next, we performed meta-analyses with the random-effects model on the cognitive results. Finally, we specifically examined the cognitive impairments of BZD in the abuse subgroup.

Of the included studies, eight of the thirteen had meta-anh as aging, testing tools, and abuse. Clinicians should be cautious when prescribing BZD for the elderly.

PROSPERO, identifier CRD42019124711.

PROSPERO, identifier CRD42019124711.Dementia is a syndrome of acquired cognitive impairment that leads to a significant decline in a patient’s daily life, ability to learn, and the ability to communicate with others. Dementia occurs in many diseases, including Alzheimer’s disease (AD), dementia with Lewy bodies, frontotemporal dementia, and Parkinson’s disease dementia (PDD). Although the analysis of biomarkers in the cerebrospinal fluid (CSF) and peripheral blood physicochemical analysis can indicate neurological impairment, there are currently no sensitive biomarkers for early clinical diagnosis of dementia or for identifying the cause of dementia. Previous studies have suggested that circulating micro (mi)RNAs may be used as biomarkers for diagnosing neurological disorders. However, miRNAs are susceptible to interference by other components in the peripheral circulation, bringing into question the diagnostic value of circulating miRNAs. Exosomes secreted by most cell types contain proteins, mRNAs, and miRNAs that are closely associated with changes in cellular functions. Exosome miRNAs (ex-miRNAs) are highly stable and resistant to degradation. Therefore, these may serve as useful biomarkers for the early clinical diagnosis of dementia. Here, we review studies of ex-miRNAs that commonly cause clinical dementia and explore whether ex-miRNAs may be used as early diagnostic biomarkers of dementia.Neuromodulation techniques such as deep brain stimulation (DBS) are a promising treatment for memory-related disorders including anxiety, addiction, and dementia. However, the outcomes of such treatments appear to be somewhat paradoxical, in that these techniques can both disrupt and enhance memory even when applied to the same brain target. In this article, we hypothesize that disruption and enhancement of memory through neuromodulation can be explained by the dropout of engram nodes. We used a convolutional neural network (CNN) to classify handwritten digits and letters and applied dropout at different stages to simulate DBS effects on engrams. We showed that dropout applied during training improved the accuracy of prediction, whereas dropout applied during testing dramatically decreased the accuracy of prediction, which mimics enhancement and disruption of memory, respectively. We further showed that transfer learning of neural networks with dropout had increased the accuracy and rate of learning. Dropout during training provided a more robust “skeleton” network and, together with transfer learning, mimicked the effects of chronic DBS on memory. Overall, we showed that the dropout of engram nodes is a possible mechanism by which neuromodulation techniques such as DBS can both disrupt and enhance memory, providing a unique perspective on this paradox.Despite the popularity of the continuous performance test (CPT) in the diagnosis of attention-deficit/hyperactivity disorder (ADHD), its specificity, sensitivity, and ecological validity are still debated. Pitstop 2 datasheet To address some of the known shortcomings of traditional analysis and interpretation of CPT data, the present study applied a machine learning-based model (ML) using CPT indices for the Prediction of ADHD.Using a retrospective factorial fitting, followed by a bootstrap technique, we trained, cross-validated, and tested learning models on CPT performance data of 458 children aged 6-12 years (213 children with ADHD and 245 typically developed children). We used the MOXO-CPT version that included visual and auditory stimuli distractors. Results showed that the ML proposed model performed better and had a higher accuracy than the benchmark approach that used clinical data only. Using the CPT total score (that included all four indices Attention, Timeliness, Hyperactivity, and Impulsiveness), as well as four control variables [age, gender, day of the week (DoW), time of day (ToD)], provided the most salient information for discriminating children with ADHD from their typically developed peers. This model had an accuracy rate of 87%, a sensitivity rate of 89%, and a specificity rate of 84%. This performance was 34% higher than the best-achieved accuracy of the benchmark model. The ML detection model could classify children with ADHD with high accuracy based on CPT performance. ML model of ADHD holds the promise of enhancing, perhaps complementing, behavioral assessment and may be used as a supportive measure in the evaluation of ADHD.Objective Osteonecrosis of the femoral head (ONFH) is a common condition that is encountered in clinical practice, and yet, little is known about its characteristics and manifestations in the brain. Therefore, in this study, we aimed to use resting-state functional magnetic resonance imaging (rs-fMRI) to investigate the spatial patterns of spontaneous brain activity in the brain of ONFH patients. Methods The study included ONFH patients and healthy controls. The pattern of intrinsic brain activity was measured by examining the amplitude of low-frequency fluctuations (ALFF) of blood oxygen level-dependent signals using rs-fMRI. Meanwhile, we also used Harris hip scores to evaluate the functional performance of ONFH patients and healthy controls. Result Ten ONFH patients and 10 health controls were investigated. We found global ALFF differences between the two groups throughout the occipital, parietal, frontal, prefrontal, and temporal cortices. In the ONFH patients, altered brain activity was found in the brain regions in the sensorimotor network, pain-related network, and emotion and cognition network. The results of the correlation investigations also demonstrated that the regions with ALFF changes had significant correlations with the functional performance of the patients evaluated by Harris hip scores. Conclusions Our study has revealed the abnormal pattern of brain activity in ONFH patients, and our findings could be used to aid in understanding the mechanisms behind the gait abnormality and intractable pain associated with ONFH at the central level.Aerobic, anaerobic, and strength exercises are known to improve various cognitive functions, such as executive functions, pattern separation, and working memory. High-intensity functional training (HIFT) is a form of physical activity that can be modified to any fitness level and elicits greater muscle recruitment than repetitive aerobic exercises, thereby improving cardiovascular endurance, strength, and flexibility. HIFT emphasizes functional, multi-joint movements via high-intensity interval training (HIIT) and muscle-strengthening exercises. It is yet unknown, however, whether HIFT affects cognitive functions in adolescents. To address this question, we subjected adolescents to 3 × 20 min training sessions/week of HIFT for 3 months. The effects of HIFT were tested on performance in (1) virtual reality (VR)-based spatial learning task; (2) computerized visual pattern separation; and (3) attention span. The control group performed a typical physical class three times per week. The effects on cognition were tested at baseline and following 3 months of HIFT. Three months into the intervention, the HIFT group achieved higher scores in the spatial learning task, pattern separation task, and in the attention span test, compared with controls. These data suggest that HIFT can potentially translate into improving school performance in adolescents.The purpose of the present study was to examine the influence of personality traits on the impact of emotional stimuli focusing on n-back task performance and brain activity changes. Previous neuroimaging studies have reported that individual differences in emotional processing can be attributed to personality traits, which is linked to the hemisphere-specific activity of the dorsolateral prefrontal cortex (DLPFC) in response to emotional stimuli. Thirty right-handed healthy young male participants were recruited in this study and classified into two groups, the behavioral inhibition system (BIS) group and behavioral activation system (BAS) group, based on their scores on the BIS/BAS scale. Participants saw six emotional images (two each with negative, neutral, and positive valence), which were selected from the International Affective Picture System and validated in a preliminary experiment. Then, a dual 2-back task that simultaneously employed auditory-verbal and visuospatial stimuli was conducted. Additiony performance, considering the personality traits to better understand individual differences in emotional processing.An earlier study in monkeys indicated that lesions to the mid-portion of the ventral orbitofrontal cortex (OFC), including Walker’s areas 11 and 13 (OFC11/13), altered the spontaneous scanning of still pictures of primate faces (neutral and emotional) and the modulation of arousal. Yet, these conclusions were limited by several shortcomings, including the lesion approach, use of static rather than dynamic stimuli, and manual data analyses. To confirm and extend these earlier findings, we compared attention and arousal to social and nonsocial scenes in three groups of rhesus macaques with restricted lesions to one of three OFC areas (OFC12, OFC13, or OFC14) and a sham-operated control group using eye-tracking to capture scanning patterns, focal attention and pupil size. Animals with damage to the lateral OFC areas (OFC12 and OFC13) showed decreased attention specifically to the eyes of negative (threatening) social stimuli and increased arousal (increased pupil diameter) to positive social scenes. In contrast, animals with damage to the ventromedial OFC area (OFC14) displayed no differences in attention or arousal in the presence of social stimuli compared to controls. These findings support the notion that areas of the lateral OFC are critical for directing attention and modulating arousal to emotional social cues. Together with the existence of face-selective neurons in these lateral OFC areas, the data suggest that the lateral OFC may set the stage for multidimensional information processing related to faces and emotion and may be involved in social judgments.