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

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.Author Summary: Genetic analysis of learning in the black-bellied vinegar fly has revealed that a brain structure called the mushroom body is important to insect memory. The mushroom body contains three lobes with strikingly different shapes. A series of studies have concluded that the lobes have markedly different relevance to memory. For short-term memory, some studies have concluded that only a single lobe–the gamma lobe–is required. However, others have concluded that at least one of the other lobes is also involved. These studies used a data analysis method called ‘null hypothesis significance testing’ that may overemphasize differences between data. We examined whether estimation statistics, an alternative data analysis framework, could be used to verify or refute the lobular specialization hypothesis. Estimation statistics review methods were used to analyze published data on this topic. The estimation models indicate no evidence for lobular specialization, but instead show that neurons in all lobes contribute to short-term memory. These results verify a model in which learning is processed in a distributed manner across the mushroom body. These findings also demonstrate that estimation methods can be successfully harnessed for the analysis of complex experimental research data.