Adolescence is the peak period for the incidence of anxiety disorders. Recent findings have revealed the immaturity of neural networks underlying emotional regulation in this population. Brain vulnerability to anxiety in adolescence is related to the unsynchronised development of anxiety‐relevant brain functional systems. However, our current knowledge on brain deficits in adolescent anxiety is mainly borrowed from studies on adults. Understanding adolescent‐specific brain deficits is essential for developing biomarkers and brain‐based therapies targeting adolescent anxiety. This article reviews and compares recent neuroimaging literature on anxiety‐related brain structural and functional deficits between adolescent and adult populations, and proposes a model highlighting the differences between adolescence and adulthood in anxiety‐related brain networks. This model emphasises that in adolescence the emotional control system tends to be hypoactivated, the fear conditioning system is immature, and the reward and stress response systems are hypersensitive. Furthermore, the striatum’s functional links to the amygdala and the prefrontal cortex are strengthened, while the link between the prefrontal cortex and the amygdala is weakened in adolescence. This model helps to explain why adolescents are vulnerable to anxiety disorders and provides insights into potential brain‐based approaches to intervene in adolescent anxiety disorders.

Orthographic processing is crucial in reading. For the Chinese language, sub-lexical processing has already taken place at radical level. Previous literature reported early position-specific radical representations and later position-general radical representations, implying a possible separating process of abstract position information irrespective of radicals per se from radical representations during orthographic processing. However, it remains largely unclear whether the abstract pattern of spatial arrangement of radicals can be rapidly extracted, and if so, whether this extraction takes place at the visual cortex, the very first processing center. As the visual cortex is documented to actively participate in orthographic processing, it may also play a role in the possible extraction of abstract orthographic patterns of Chinese characters. Hence, we hypothesize that abstract orthographic patterns of Chinese characters are covertly extracted at the visual cortex during reading. In this study, we investigated whether the visual cortex could rapidly extract abstract structural patterns of Chinese characters, using the event-related potential (ERP) technique. We adopted an active oddball paradigm with two types of deviant stimuli different only in one feature, structural or tonal, from standard stimuli; in each of the two sessions, subjects focused conscious attention on one feature and neglected the other. We observed that the ERPs recorded at occipital electrodes responded differentially to standard and structural deviant stimuli in both sessions, especially within the time range of the occipital P200 component. Then, we extracted three source waves arising from different levels of the visual cortex. Early response differences (from 88 to 456 ms after stimulus onset) were observed between the source waves, probably arising from left primary/secondary and bilateral associative visual cortices, in response to standard and deviant stimuli that violated abstract structural patterns, whether subjects focused their attention on the character structure or not. This suggests rapid extraction of abstract structural patterns of Chinese characters in the visual cortex, no matter the abstract structural pattern was explicit or implicit to subjects. Note that the source waves arising from right primary/secondary visual cortices in response to standard and structural deviant stimuli did not differ at all, indicating that this extraction of the abstract structural pattern of Chinese characters was left-lateralized. Besides, no difference was observed between source waves originating from any level of the visual cortex to standard and deviant stimuli that violated abstract tonal patterns, until 768 ms when a late effect related to conscious detection of targets occurred at higher levels of the visual cortex. Note that at late stages (later than 698 ms after stimulus onset), responses arising from bilateral associative visual cortices to standard and target stimuli differed for both sessions, no matter the structural or tonal feature was attended to. Our findings support the primitive intelligence of visual cortex to rapidly extract abstract orthographic patterns of Chinese characters that might be engaged in further lexical processing. Our findings also suggest that this rapid extraction can take place implicitly during reading.

Background Neuroimaging techniques provide rich and accurate measures of brain structure and function, and have become one of the most popular methods in mental health and neuroscience research. Rapidly growing neuroimaging research generates massive amounts of data, bringing new challenges in data collection, large-scale data management, efficient computing requirements and data mining and analyses. Aims To tackle the challenges and promote the application of neuroimaging technology in clinical practice, we developed an integrated neuroimaging cloud (INCloud). INCloud provides a full-stack solution for the entire process of large-scale neuroimaging data collection, management, analysis and clinical applications. Methods INCloud consists of data acquisition systems, a data warehouse, automatic multimodal image quality check and processing systems, a brain feature library, a high-performance computing cluster and computer-aided diagnosis systems (CADS) for mental disorders. A unique design of INCloud is the brain feature library that converts the unit of data management from image to image features such as hippocampal volume. Connecting the CADS to the scientific database, INCloud allows the accumulation of scientific data to continuously improve the accuracy of objective diagnosis of mental disorders. Results Users can manage and analyze neuroimaging data on INCloud, without the need to download them to the local device. INCloud users can query, manage, analyze and share image features based on customized criteria. Several examples of 'mega-analyses' based on the brain feature library are shown. Conclusions Compared with traditional neuroimaging acquisition and analysis workflow, INCloud features safe and convenient data management and sharing, reduced technical requirements for researchers, high-efficiency computing and data mining, and straightforward translations to clinical service. The design and implementation of the system are also applicable to imaging research platforms in other fields.