Investigations of transcriptomic and neuroimaging data imply that the spatial patterning of the brain transcriptome follows broad spatial trends in the brain network architecture, which can be used to study the molecular mechanisms of functional connectivity. However, the sophisticated pre-processing and data fusion workflows involved in heteromodal data analysis often require the expertise of computer scientists. There is a need for tools that facilitate this process to enable research without the need for extensive programming knowledge. To address this problem, we present an extension to our spatial data mining application BrainTrawler with support for volumetric brain activity data (fMRI maps, cFOS imaging, etc.). By providing a web-based framework with co-registered transcriptomic and neuroimaging data in a 3D context, we enable researchers to explore gene-function relations in an integrated visual analytics workflow. Real-time spatial queries with arbitrary ROIs, activity thresholding and metadata filtering can be used to quickly find relevant activation patterns and to further query the extensive transcriptomic database of BrainTrawler. Dynamic visualizations for task- and treatment-group comparisons provide detailed insight into large functional study bodies and region profiles automatically relate visible activity patterns to the hierarchical organization of common brain atlases. By expanding the capabilities of BrainTrawler to include multimodal 3D brain activity data, we provide researchers with an extended toolset for gene-function comparisons.Figure: Screenshot series showing A) an example brain activity signal, B) the corresponding activity profile on the currently selected region hierarchy, C) a thresholding dialogue for ROI generation D) the resulting voxel-resolution ROI.