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Hyper-reactivity to sensory input is a common and debilitating symptom in individuals with autism spectrum disorders (ASD), but the neural basis underlying sensory abnormality is not completely understood. Here we examined the neural representations of sensory perception in the neocortex of a Shank3B−/− mouse model of ASD. Male and female Shank3B−/− mice were more sensitive to relatively weak tactile stimulation in a vibrissa motion detection task. In vivo population calcium imaging in vibrissa primary somatosensory cortex (vS1) revealed increased spontaneous and stimulus-evoked firing in pyramidal neurons but reduced activity in interneurons. Preferential deletion of Shank3 in vS1 inhibitory interneurons led to pyramidal neuron hyperactivity and increased stimulus sensitivity in the vibrissa motion detection task. These findings provide evidence that cortical GABAergic interneuron dysfunction plays a key role in sensory hyper-reactivity in a Shank3 mouse model of ASD and identify a potential cellular target for exploring therapeutic interventions.Chen, Deister et al. show that Shank3B-knockout mice display hypersensitivity to tactile sensory stimulation and that dysfunction of interneurons in somatosensory cortex contributes to the sensory hyper-reactivity in this mouse model of autism.

With the continuous development of intelligent transportation systems (ITSs), traffic flow prediction methods have become the cornerstone of this technology. This paper comprehensively reviews the traffic flow prediction methods used in ITSs and divides them into three categories: statistics-based, machine learning-based, and deep learning-based methods. Although statistics-based methods have lower data requirements and machine learning methods have faster calculation speeds, this paper concludes that deep learning methods have the best overall effect after a comprehensive analysis of the principles, advantages, limitations, and practical applications of each method. Deep learning methods can overcome many limitations that traditional statistical methods and machine learning methods cannot surpass, such as the ability to model complex nonlinear relationships. Experimental results show that hybrid neural networks are significantly superior to traditional methods in terms of their prediction accuracy and generalization abilities. By combining multiple models and techniques, hybrid neural networks can improve the accuracy of traffic flow prediction under different conditions. Although deep learning methods have achieved remarkable success in short-term prediction, challenges still exist, such as the generalization of models in different traffic scenarios and the difficulty of long-term traffic flow prediction. Finally, this paper discusses future research directions and anticipates the future development of ITS technology.

The ability to target and manipulate specific neuronal populations is crucial for understanding brain function. In this report, the authors describe a novel virus that restricts gene expression to telencephalic GABAergic interneurons, allowing for morphological visualization, activity monitoring and functional manipulation of interneurons in mice and in non-genetically tractable species. A fundamental impediment to understanding the brain is the availability of inexpensive and robust methods for targeting and manipulating specific neuronal populations. The need to overcome this barrier is pressing because there are considerable anatomical, physiological, cognitive and behavioral differences between mice and higher mammalian species in which it is difficult to specifically target and manipulate genetically defined functional cell types. In particular, it is unclear the degree to which insights from mouse models can shed light on the neural mechanisms that mediate cognitive functions in higher species, including humans. Here we describe a novel recombinant adeno-associated virus that restricts gene expression to GABAergic interneurons within the telencephalon. We demonstrate that the viral expression is specific and robust, allowing for morphological visualization, activity monitoring and functional manipulation of interneurons in both mice and non-genetically tractable species, thus opening the possibility to study GABAergic function in virtually any vertebrate species.

Background: Students with Autism Spectrum Disorder (ASD) commonly demonstrate prominent social communication deficits, symptoms of attention-deficit/hyperactivity disorder, and chronic irritability. These challenges hinder academic progress and frequently persist despite educational, behavioral, and medical interventions. An assistive smartglasses technology may aid these individuals, especially if the technology is efficacious in ecologically-valid school settings. This study explored the feasibility and efficacy of Empowered Brain, a computerized smartglasses intervention designed as a socio-emotional behavioral aid for students with ASD. Methods: This two-part six-week study involved four school children with ASD from a public elementary school. The study incorporated an initial three-week feasibility stage followed by a three-week controlled longitudinal efficacy stage. Both stages involved the use of a twice-daily socio-emotional intervention with the smartglasses. Educators completed pre-intervention and post-intervention Aberrant Behavioral Checklist (ABC) ratings at the start of the feasibility stage, and weekly during the efficacy stage. Primary outcome measures were improvements in the ABC subscales of irritability, hyperactivity, and social withdrawal. Results: Students in both feasibility and efficacy stages demonstrated improvements (decreases) in irritability, hyperactivity, and social withdrawal compared to a baseline period and control periods, respectively. Participants in the controlled efficacy stage demonstrated decreased ABC subscale scores of 90% for irritability, 41.6% for hyperactivity, and 45.6% for social withdrawal. An intervention exposure-response improvement in irritability and hyperactivity was found during the efficacy stage. Educators rated the technology as superior or vastly superior compared to other assistive technologies. Conclusion: A substantial number of school children with ASD demonstrate chronic and impairing cognitive and behavioral challenges. This study provides evidence that Empowered Brain, a smartglasses-based socio-emotional aid for autism, is both feasible and efficacious in improving symptoms of social withdrawal, irritability, and hyperactivity in students with autism. The improvement is demonstrated as part of a longitudinal school-based intervention. Further studies involving larger samples and incorporation of randomized controlled trial methodology are underway to further elucidate the impact of this technology.

There is considerable demand for special education services for the over half a million students with autism in the United States. While assistive technology may augment educational services, its implementation is often prevented by a number of practical and attitudinal barriers. These barriers are especially pertinent for the newest and thus least familiar digital systems, such as computerized smartglasses loaded with specialized software modules. Computerized smartglasses are a technology that has already been shown to have an ability to deliver educational interventions through augmented reality. With this in mind, we sought to understand how school educators received and assessed the practicality of a smartglasses-based educational intervention in a single-subject study. The intervention was designed to aid with attention and social educational learning in autism. The intervention was delivered twice a day during a two-week study on a 13-year-old student with autism who was attending a mainstream middle school in Massachusetts. Three different school educators delivered the intervention: the student’s general education teacher, special education teacher, and paraprofessional. Educators recorded their attitudes, the practicality of the technology, and its impact on the student and their classroom through the use of a digital log and a series of in-person interviews. Overall, the school educators experienced a positive view of the smartglasses. The smartglasses intervention was found to be logistically practical to implement, easily usable by both the educator and student, and not time-consuming to learn or implement. Educators also identified the experience as being fun for the student, and felt that the student demonstrated improvement in his verbal and non-verbal skills. There were no adverse effects on the other students or the classroom, and the technology did not result in a distraction. These findings suggest that social skills interventions delivered by smartglasses may be practical, useful, and may lead to improvements in social communication skills. Further research on smartglasses may help to clarify the future role for augmenting special education in students with autism.

Nat. Neurosci. 19, 1743–1749 (2016); published online 31 October 2016; corrected after print 29 November 2016 In the version of this article initially published, authors Joshua S. Grimley, Anne-Rachel Krostag and Ajamete Kaykas were missing. These authors have been inserted into the author list after Jianhua Chu; they are at the Allen Institute for Brain Science, Seattle, Washington, USA, and performed experiments related to hESCs.

The electricity marketing management information system realizes the whole process of management from accepting customers’ electricity application to electricity bill recovery and from business processing to decision support. The electricity marketing management information system is a modern management tool for electric electricity enterprises to go to the market, expand the market, increase supply, expand sales, and provide customers with high-quality services. This paper has completed the following work: (1) described the development of domestic and foreign electricity marketing management information system and provided a theoretical basis for the design scheme proposed later. (2) The construction of the marketing system should focus on eight key points, establish a service-oriented architecture, plan the hardware platform in combination with the principles of advanced and practicality, and at the same time, apply multisensors to the marketing technology support system to improve the efficiency of data interaction. (3) According to the characteristics of the application software of the electricity marketing management information system, the software that runs between the components of the distributed, enterprise-wide C/S application or within the components is adopted. The performance of the software and hardware of the system is tested experimentally, and the results show that the electricity marketing information system has good performance.