Estimating Information Processing in a Memory System: The Utility of Meta-analytic Methods for Genetics.

• Main Authors: Tugce Yildizoglu, Jan-Marek Weislogel, Farhan Mohammad, Edwin S-Y Chan, Pryseley N Assam, Adam Claridge-Chang
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2015-12-01
• Series: PLoS Genetics
• Online Access: http://europepmc.org/articles/PMC4672901?pdf=render
• ISSN: 1553-7390; 1553-7404

Genetic studies in Drosophila reveal that olfactory memory relies on a brain structure called the mushroom body. The mainstream view is that each of the three lobes of the mushroom body play specialized roles in short-term aversive olfactory memory, but a number of studies have made divergent conclusions based on their varying experimental findings. Like many fields, neurogenetics uses null hypothesis significance testing for data analysis. Critics of significance testing claim that this method promotes discrepancies by using arbitrary thresholds (α) to apply reject/accept dichotomies to continuous data, which is not reflective of the biological reality of quantitative phenotypes. We explored using estimation statistics, an alternative data analysis framework, to examine published fly short-term memory data. Systematic review was used to identify behavioral experiments examining the physiological basis of olfactory memory and meta-analytic approaches were applied to assess the role of lobular specialization. Multivariate meta-regression models revealed that short-term memory lobular specialization is not supported by the data; it identified the cellular extent of a transgenic driver as the major predictor of its effect on short-term memory. These findings demonstrate that effect sizes, meta-analysis, meta-regression, hierarchical models and estimation methods in general can be successfully harnessed to identify knowledge gaps, synthesize divergent results, accommodate heterogeneous experimental design and quantify genetic mechanisms.