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Maugard M, Doux C, Bonvento G. A new statistical method to analyze Morris Water Maze data using Dirichlet distribution. F1000Res. 2019;8:1601doi: 10.12688/f1000research.20072.1.
Maugard, M., Doux, C., & Bonvento, G. (2019). A new statistical method to analyze Morris Water Maze data using Dirichlet distribution. F1000Research, 81601. https://doi.org/10.12688/f1000research.20072.1
Maugard, Marianne, et al. "A new statistical method to analyze Morris Water Maze data using Dirichlet distribution." F1000Research vol. 8 (2019): 1601. doi: https://doi.org/10.12688/f1000research.20072.1
Maugard M, Doux C, Bonvento G. A new statistical method to analyze Morris Water Maze data using Dirichlet distribution. F1000Res. 2019 Sep 06;8:1601. doi: 10.12688/f1000research.20072.1. eCollection 2019. PMID: 31723422; PMCID: PMC6833991.
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F1000Res. 2019 Sep 06;8:1601. doi: 10.12688/f1000research.20072.1. eCollection 2019.

A new statistical method to analyze Morris Water Maze data using Dirichlet distribution.

F1000Research

Marianne Maugard, Cyrille Doux, Gilles Bonvento

Affiliations

  1. Commissariat à l'Energie Atomique et aux Energies Alternatives, Département de la Recherche Fondamentale, Institut de Biologie François Jacob, Fontenay-aux-Roses, 92260, France.
  2. Neurodegenerative Disease Laboratory, Centre National de la Recherche Scientifique, Université Paris-Sud, Université Paris-Saclay, Fontenay-aux-Roses, 92260, France.
  3. AstroParticule et Cosmologie, Université Paris Diderot, Paris, 75205, France.
  4. Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA, 19104, USA.

PMID: 31723422 PMCID: PMC6833991 DOI: 10.12688/f1000research.20072.1

Abstract

The Morris Water Maze (MWM) is a behavioral test widely used in the field of neuroscience to evaluate spatial learning memory of rodents. However, the interpretation of results is often impaired by the common use of statistical tests based on independence and normal distributions that do not reflect basic properties of the test data, such as the constant-sum constraint. In this work, we propose to analyze MWM data with the Dirichlet distribution, which describes constant-sum data with minimal hypotheses, and we introduce a statistical test based on uniformity (equal amount of time spent in each quadrant of the maze) that evaluates memory impairments. We demonstrate that this test better represents MWM data and show its efficiency on simulated as well as

Copyright: © 2019 Maugard M et al.

Keywords: Dirichlet distribution; Morris Water Maze; Statistical analysis

Conflict of interest statement

No competing interests were disclosed.

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