Automated analysis of courtship suppression learning and memory in Drosophila melanogaster

Abstract

Study of the fruit fly, Drosophila melanogaster, has yielded important insights into the underlying molecular mechanisms of learning and memory. Courtship conditioning is a well-established behavioral assay used to study Drosophila learning and memory. Here, we describe the development of software to analyze courtship suppression assay data that correctly identifies normal or abnormal learning and memory traits of individual flies. Development of this automated analysis software will significantly enhance our ability to use this assay in large-scale genetic screens and disease modeling. The software increases the consistency, objectivity, and types of data generated.

Keywords: automated behavior analysis; clustering; courtship suppression; feature detection; learning; memory; video processing.

Figure 2. Software is capable of measuring successful learning with successful memory in Drosophila courtship suppression. (A) denotes learning ability during the first 10 min and last 10 min of the courtship suppression assay training phase. Grey bars indicate courtship index (CI) as computed by the software program and subsequently subjected to arcsin square root transformation. White bars indicate CI as computed manually as previously described, and subsequently subjected to arcsin square root transformation. Note significant learning is measured by both methods. n = 36. (B) denotes memory ability of trained flies compared with sham trained flies. Grey bars indicate CI as computed by the software program and subsequently subjected to arcsin square root transformation. White bars indicate CI as computed manually, as previously described, and subsequently subjected to arcsin square root transformation. Note successful memory in both cases. n = 30. Error bars represent ± SEM. *p < 0.05.

Figure 3. Software is capable of measuring successful learning with unsuccessful memory in Drosophila courtship suppression. Grey bars indicate courtship index (CI) as computed by the software program and subsequently subjected to arcsin square root transformation in each panel. White bars indicate CI as computed manually in each panel, as previously described, and subsequently subjected to arcsin square root transformation. (A) denotes learning ability during the first 10 min and last 10 min of the courtship suppression assay training phase. Note significant learning is measured by both methods. n = 25. (B) denotes memory ability of trained flies compared with sham trained flies. Note unsuccessful memory in both cases. n = 25. Error bars represent ± SEM. *p < 0.05.

Figure 4. Software is capable of detecting both successful and unsuccessful learning and memory without prior human intervention. Flies are computationally clustered into two groups using geometric feature vectors automatically derived from videos. The two groups in each case are as follows: (A) Flies with successful memory; (B) flies with no memory; (C) flies with successful learning; and (D) flies with no learning. Grey bars indicate CI as computed by the software program and subsequently subjected to arcsin square root transformation for each group. White bars indicate CI as computed manually for each group, and subsequently subjected to arcsin square root transformation. (A) denotes memory ability of trained flies compared with sham trained flies. This group exhibits successful memory in both cases. n = 29. (B) denotes memory ability of trained flies compared with sham trained flies. This group exhibits unsuccessful memory in both cases. n = 28. (C) denotes learning ability during the first 10 min and last 10 min of the courtship suppression assay training phase. This group exhibits significant learning in both cases. n = 31. (D) denotes learning ability during the first 10 min and last 10 min of the courtship suppression assay training phase. This group exhibits unsuccessful learning in both cases. n = 26. Error bars represent ± SEM. *p < 0.05.

Figure 1. Schematic of video capture and assessment. (A) Representative image from a courtship video used for analysis in this study. Two individual frames are shown. (B) Representative binary image produced by background subtraction and filtering. (C) Representative image for male/female identification and tracking.