BAT can perform functional and genetic annotation for many neuroimaging results, either in 3D-volume space or 2D-surface space, in the form of clusters/regions or FCs (see Fig.1 for details). Advances in neuroimaging and sequencing techniques provide an unprecedented opportunity to map the function of brain regions and identify the roots of psychiatric diseases. In the field of bioinformatics, such an annotation analysis, gene functional enrichment analysis has already been employed to systematically dissect large ‘interesting’ gene lists from the high-throughput studies, and furthermore identify the most relevant biological processes (Huang et al. Enrichment or depletion of a GO category within a class of genes: which test? Neuroimaging analysis generates results in clusters of voxels/brain regions or in functional connectivity (FC) links between pairs of voxels or brain areas with correlated activity. For the Hippocampus, 17 out of 217 functional terms, including ‘memory’, ‘episodic memory’, ‘navigation’, ‘recall’, ‘learning task’ etc. Select one of the options below to target your search: Literature citations; Taxonomy; Keywords; Subcellular locations; Cross-referenced databases; Human diseases Then, for each background AHBA sample, we map it to one of the given clusters/regions, that which has the largest number of overlapping voxels with this AHBA sample. However, our toolbox can provide candidate genes for further mediation analysis if behavior, neuroimaging and genetic data are available at the individual level. In developing the functional and genetic annotation methods, we took into account factors that might affect the results. Secondly, it should be noted that we do not analyze the directed relationship between behavior-brain imaging-genetics in BAT, as the mediation analysis can only be performed using data at the individual level. In addition to traditional brain atlases, we also applied BAT to the recent HCP Brain Atlas (Glasser et al., 2016). These genes were significantly enriched in biological terms such as ‘brain development’ and ‘neurogenesis’. Oxford University Press is a department of the University of Oxford. During the past decades, hundreds of gene functional enrichment analysis tools have been developed and employed by tens of thousands of high-throughput studies, providing valuable insights into the underlying biological meaning of the gene analysis results. 3D Bounding Box Annotation Tool (3D-BAT) Point cloud and Image Labeling. The first one is the most efficient and is suitable for all forms of cluster/regions. genes expressed in this brain region or cluster or clusters more than in the rest of the brain) (P < 0.05, Bonferroni corrected). Our open source, web-based 3D BAT incorporates several smart features to improve usability and efficiency. Disturbed sleep is frequently encountered in patients with schizophrenia and is an important part of its pathophysiology (Cohrs, 2008). We found that these two similarity matrices corresponded significantly, as described next. The functional annotation analysis of BAT is based on the 217 selected functional terms for Neurosynth, which does not involve all the functional terms associated with all brain areas. An advantage of BAT is that the MATLAB source code is provided with the toolbox, allowing users to understand what is being computed, and to enable users to develop further enhancements. Finally, of all the identified functional terms, ‘sleep’ was the most significant (P < 1e−4). Moreover, in BAT the significance levels can be set by users to levels that make the results reliable. Meanwhile, the Allen Human Brain Atlas (AHBA) was constructed and provided a comprehensive ‘all genes-all structure’ profile of the human brain (Shen et al., 2012). (F) BAT can perform genetic annotation analysis for the user-provided neuroimaging results and identify the most correlated genetic correlates. A resting-state brain-wide association analysis was performed on multiple sites (with a total of 789 participants including 360 patients) (Li et al., 2017), and the results were integrated by meta-analysis. Bat coronavirus HKU5 (BtCoV) (BtCoV/HKU5/2004) Status. The 180 cortical areas in the parcellation are distinguished by multi-modal data including anatomical measurements, task-related functional magnetic resonance imaging of seven tasks and resting-state FC in a subject cohort of 210 healthy young adults. Further, the significance of the network’s MCAR is assessed using non-parametric permutation tests. It also includes light 3-wheel vehicles, often with a light plastic roof and open on the sides, that tend to be common in Asia (rickshaws). All these results confirm that our genetic annotation results based on the regional expression profiles are not significantly affected by the ROI size. This was an important advance, but did not address the genetic features underlying the 180 cortical areas, nor in detail the functions of each of the cortical areas (Yeo and Eickhoff, 2016). To illustrate how BAT can help to gain insight into the biological meaning of neuroimaging results, we performed a functional and genetic annotation analysis for the clusters obtained in a BWAS of FC for autism (Cheng et al., 2015), in which a statistical map is obtained by meta-analysis (with the Liptak–Stouffer Z-score approach) that integrates BWAS results from 16 imaging sites (418 patients and 509 controls). So please back up (download) your annotated scenes (~every 10 min). Further efforts could involve integrating activation maps from all available meta-analysis databases [such as Brainmap (Fox and Lancaster, 2002)], reliable brain network parcellations obtained from large-scale neuroimaging datasets or meta-analysis [e.g. BAT can perform functional and genetic annotation for many neuroimaging results, either in 3D-volume space or 2D-surface space, in the form of clusters/regions or FCs (see Fig.1 for details). (A) Left Hippocampus: 17 functional terms, including memory-related ones such as ‘memory’, ‘recognition memory’ and ‘Semantic memory’, were found to be significantly associated with the left hippocampus. However, a huge gap still exists in using these data to interpret neuroimaging results. The functional and genetic annotations provided by BAT provide a valuable complement to these widely used atlases. For genes, 4839 genes were found to be over-expressed including BDNF. sedans, hatch-backs, wagons, vans, mini-vans, SUVs, jeeps and pickup trucks (a pickup truck is a light duty truck with an enclosed cab and an open or closed cargo area; a pickup truck can be intended primarily for hauling cargo or for personal use). H.W. Gene enrichment analysis shows that these genes are enriched in memory and learning related GO biological processes such as ‘Learning’, ‘Memory’ and ‘Long term potentiation’. Next, we summarize the results for a newly discovered cortical area, the MI, which is part of the insular cortex. is supported by the National Science Foundation of China [number 61573107], the Special Funds for Major State Basic Research Projects of China [number 2015CB856003], the Shanghai Natural Science Foundation [number 17ZR1444200] and the National Basic Research Program of China (Precision Psychiatry Program) [number 2016YFC0906402]. The co-activation network was obtained by calculating the correlation coefficient between the ACRs (of all 217 terms or tasks) for each pair of brain regions in a given atlas, and the gene co-expression was obtained by calculating the correlation between the gene expression profile for each pair of brain regions in the same atlas. If there is a rider and/or passenger, include them in the box. However, it differs significantly from our approach in the following aspects: (i) the goal of ‘Neurosynth-Gene’ is to map individual cognitive phenomena to molecular processes, while the goal of BAT is to provide functional and genetic annotations for extensive neuroimaging results not necessarily confined to cognitive processes, e.g. Using BAT, we performed functional and genetic annotation analysis for several widely known brain atlases, including the Brodmann (Brodmann, 1909), AAL2 (Rolls et al., 2015), the new HCP atlas (Glasser et al., 2016), Power 264 (Power et al., 2011) and Craddock 200 (Craddock et al., 2012), as detailed in Supplementary Table S3. This is not provided by ‘Neurosynth-Gene’. To illustrate the information that BAT makes available for the 180 cortical areas in the HCP Brain Atlas, we describe the results for two selected areas: one is the hippocampus, and the other is a cortical area newly identified with the HCP Brain Atlas, the ‘Middle Insular Area’ (MI). the region had at least one significant functional annotation by permutation test, P < 0.05) with those summarized in Wikipedia (wiki) (, to validate our approach. First, selection bias caused by limitations in the data sources might introduced potential false positive results. After determining the voxel selection approach, BAT runs the permutation multiple times (the number of permutations can be defined by the user), to get a null distribution of the ACR for each term. In addition, several other terms related to cognitive processes were also found to be significantly enriched, including ‘attention’ and ‘memory’, detailed in Supplementary Table S8. A total of 83 functional terms were found to be significantly related to the clusters, including ‘Autism’ and several autism-related symptoms such as ‘autobiographical memory’, ‘communication’, ‘self-referential’, ‘theory of mind’ and so on. a single AAL2 region), a cluster/region consisting of multiple connected components (e.g. Firstly, in the genetic analysis, in order to confirm that the size of the ROI does not significantly affect our genetic annotation results, we use 3, 6 and 9 mm spheres to define the ABHA samples and performed the genetic annotation analysis for regions in the AAL2 atlas. Annotation systems. is supported in part by the Key Research and Development Plan of Shandong Province [number 2017CXGC1503 and 2018GSF118228]. These genes were significantly enriched in biological terms such as ‘brain development’ (P = 1.31e−5, BHFDR corrected), and ‘neurogenesis’ (P = 2.43e−5, BHFDR corrected), which are known to underlie the pathology of schizophrenia. However, the results obtained in neuroimaging analysis, usually in the forms of clusters of voxels/brain regions or functional connectivities/networks, often remain hard to explain. A user-friendly MATLAB GUI and 3D visual interface are also provided for users’ convenience. For full access to this pdf, sign in to an existing account, or purchase an annual subscription. We performed BAT on the 89 FCs that were significantly increased in chronic schizophrenia compared to controls. We then randomly select the same number of regions as those in the FC list from the whole-brain atlas being used. Since each study usually has a small sample size and the results may be under powered and have a high false discovery rate (Yarkoni, 2009; Yarkoni et al., 2010), explanations based on these results may not be very reliable. Inspired by gene enrichment analysis, we developed the BAT toolbox, which employs brain voxel-level functional and genetic knowledge to help systemically explore the region-level neuroimaging results (i.e.