BrainKnowledge: A Human Brain Function Mapping Knowledge-Base System

Abstract

Associating fMRI image datasets with the available literature is crucial for the analysis and interpretation of fMRI data. Here, we present a human brain function mapping knowledge-base system (BrainKnowledge) that associates fMRI data analysis and literature search functions. BrainKnowledge not only contains indexed literature, but also provides the ability to compare experimental data with those derived from the literature. BrainKnowledge provides three major functions: (1) to search for brain activation models by selecting a particular brain function; (2) to query functions by brain structure; (3) to compare the fMRI data with data extracted from the literature. All these functions are based on our literature extraction and mining module developed earlier (Hsiao, Chen, Chen. Journal of Biomedical Informatics 42, 912-922, 2009), which automatically downloads and extracts information from a vast amount of fMRI literature and generates co-occurrence models and brain association patterns to illustrate the relevance of brain structures and functions. BrainKnowledge currently provides three co-occurrence models: (1) a structure-to-function co-occurrence model; (2) a function-to-structure co-occurrence model; and (3) a brain structure co-occurrence model. Each model has been generated from over 15,000 extracted Medline abstracts. In this study, we illustrate the capabilities of BrainKnowledge and provide an application example with the studies of affect. BrainKnowledge, which combines fMRI experimental results with Medline abstracts, may be of great assistance to scientists not only by freeing up resources and valuable time, but also by providing a powerful tool that collects and organizes over ten thousand abstracts into readily usable and relevant sources of information for researchers.

A Web-Based Atlas Combining MRI and Histology of the Squirrel Monkey Brain

“…However, these are printed atlases and, unlike digital atlases, do not facilitate spatial normalization of new image information for quantitative comparisons of brains across subjects, time, or differing experimental conditions. In other species, atlases based on magnetic resonance imaging (MRI) have become valuable tools to reference the anatomy of the brain (Hsiao et al 2011; Sunkin et al 2013; Ding et al 2017; Woodward et al 2018; Frey et al 2011; Toga et al 1989) (http://observatory.brain-map.org/visualcoding, https://brainknowledge.mricloud.org/map%3Fmapname=wholebrain, http://www.thehumanbrain.info/brain/brain_navigator.php) Recently, we have introduced the first MRI atlas of the squirrel monkey brain to facilitate three-dimensional (3D) anatomical localization or segmentation, and to enable comparisons of experimental data across different subjects (K. G. Schilling et al 2017).…”