Database of literature derived cellular measurements from the murine basal ganglia

Abstract

Quantitative measurements and descriptive statistics of different cellular elements in the brain are typically published in journal articles as text, tables, and example figures, and represent an important basis for the creation of biologically constrained computational models, design of intervention studies, and comparison of subject groups. Such data can be challenging to extract from publications and difficult to normalise and compare across studies, and few studies have so far attempted to integrate quantitative information available in journal articles. We here present a database of quantitative information about cellular parameters in the frequently studied murine basal ganglia. The database holds a curated and normalised selection of currently available data collected from the literature and public repositories, providing the most comprehensive collection of quantitative neuroanatomical data from the basal ganglia to date. The database is shared as a downloadable resource from the EBRAINS Knowledge Graph (https://kg.ebrains.eu), together with a workflow that allows interested researchers to update and expand the database with data from future reports.

Densities and numbers of calbindin and parvalbumin positive neurons across the rat and mouse brain

“…The considerable variability in neuron numbers across the literature ( Keller et al., 2018 ) and the challenges related to interpret the causes of such discrepancies (see, e.g. Bjerke et al., 2020a ) highlights the need for re-usable data and transparent analyses. Additional studies will be needed to accumulate quantitative evidence about normal inter-individual variability.…”

“…Others have focused on gathering measurements from the literature and calculating values for parameters that have yet to be tested experimentally ( Bezaire and Soltesz, 2013 ). However, there is growing awareness that numbers reported in the literature are prone to substantial variability across publications ( Bjerke et al., 2020a ; Keller et al., 2018 ). Quantitative studies of parvalbumin and calbindin neurons acquired across the brain are needed to elucidate their relative numbers and distributions within and across regions and species.…”

A graph-based approach for representing, integrating and analysing neuroscience data: the case of the murine basal ganglia

“…The data set's primary usage is for researchers to find and compare neuroanatomical information about the basal ganglia brain regions. In addition to the data set, (Bjerke et al , 2020) published a paper describing the data set development process and their findings.…”

“…The murine basal ganglia data set, created by Bjerke et al (2020), consists of quantitative neuroanatomical data about the healthy rat and mouse basal ganglia, collected from more than 200 research papers and data repositories. The data set contains three distinct information types: quantitations (counts), distributions and cell morphologies.…”

“…To this end, in this article, we show that a graph-based approach offers an effective mean for representing, analysing and accessing brain-related data by presenting an approach for organising brain-related data in a graph model enabling integration of various disparate data sources and improving the understanding and usability of data. The approach is exemplified in the case of a unique data set of quantitative neuroanatomical data about the murine basal ganglia (Bjerke et al , 2020) — a group of nuclei in the brain essential for processing information related to movement. Specifically, the murine basal ganglia data set is modelled as a graph, integrated with relevant data from third-party repositories, published through a Web-based user interface and API and analysed from exploratory and confirmatory perspectives using popular graph algorithms to extract new insights.…”