Improve reporting practices for quantitative neuroscience data

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The brain is the most complex biological structure we know, and our imperfect understanding of its structure and function severely limits our options to manage and treat brain diseases. To unravel the architecture of brain systems and ultimately improve our understanding of brain function in health and disease, coordinated efforts are needed to acquire and synthesize information. Quantitative data about cellular elements of the brain are of particular interest to neuroscientists – from those attempting to understand how it is affected by different diseases, to those wishing to create computational models of normal brain function. However, simple questions like “how many cells are present in this brain area” are not trivial to answer. Although the body of research publications about the brain is steadily growing, lack of standardised reporting formats makes it difficult to find and compare different information elements.

To improve this situation, we created a database of quantitative information about cellular elements from the published literature. We focused on the regions of the rat and mouse basal ganglia, that are implicated in neurodegenerative diseases such as Parkinson’s and Huntington’s disease1,2. The entire database is openly shared through the EBRAINS infrastructure and is described in our recently published Data Descriptor in Nature: Scientific Data.

To represent all the information found in the literature in a unified way, it was necessary to standardise information about experiments and data described in publications. This was particularly challenging for anatomical regions, for which naming conventions are highly variable and documentation is often lacking3. We therefore established a workflow for translating all the anatomical terms found in the literature to standard terms found in brain reference atlases4–7 and stored metadata related to how the region was defined and the type of documentation provided. This will allow researchers to more easily assess whether estimates from several different studies can be compared.

The challenge of interpreting results reported in different publications was not exclusively due to lack of anatomical information. In many reports, the documentation of the analytic quantification procedures and antibodies used were sparse. Exploring and comparing the accumulated data, we found that reported numbers of cellular and subcellular elements are highly variable, difficult to compare, and seldom replicated across studies. Improved reporting practices are urgently needed to ensure that published information can have a value beyond the narrative of a specific publication.

With our shared database, we hope to have made the task of finding, extracting and comparing quantitative data easier for neuroscientists. Although we focused on certain regions and species in our study, we also show how other researchers can use the database to collect their data of interest. Thus, we believe that this dataset can be a valuable resource beyond the collected data. In addition, our effort sheds light on important weaknesses with current reporting practices that need to be addressed to improve our prospect of understanding the brain.

 

References:

  1. Obeso, J. et al. The basal ganglia in Parkinson’s disease: Current concepts and unexplained observations. Ann. Neurol. 64, S30–S46 (2009).
  2. Bunner, K. D. & Rebec, G. V. Corticostriatal dysfunction in Huntington’s disease: The basics. Front. Hum. Neurosci. 10, 317 (2016).
  3. Bjerke, I. et al. Navigating the murine brain: Toward best practices for determining and documenting neuroanatomical locations in experimental studies. Front. Neuroanat. 12, 82 (2018).
  4. Papp, E., Leergaard, T. T. B., Calabrese, E., Johnson, G. A. G. & Bjaalie, J. G. J. Waxholm Space atlas of the Sprague Dawley rat brain. Neuroimage 97, 374–386 (2014).
  5. Kjonigsen, L., Lillehaug, S., Bjaalie, J., Witter, M. & Leergaard, T. Waxholm Space atlas of the rat brain hippocampal region: Three-dimensional delineations based on magnetic resonance and diffusion tensor imaging. Neuroimage 108, 441–449 (2015).
  6. Osen, K., Imad, J., Wennberg, A., Papp, E. & Leergaard, T. Waxholm Space atlas of the rat brain auditory system: Three-dimensional delineations based on structural and diffusion tensor magnetic resonance imaging. Neuroimage 199, 38–56 (2019).
  7. Wang, Q. et al. The Allen Mouse Brain Common Coordinate Framework: A 3D reference atlas. Cell 181, 1–18 (2020).
Go to the profile of Ingvild Bjerke

Ingvild Bjerke

PhD student, University of Oslo

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