Automated monitoring and analysis of social behavior in Drosophila

Abstract

We introduce a method based on machine vision for automatically measuring aggression and courtship in Drosophila melanogaster. The genetic and neural circuit bases of these innate social behaviors are poorly understood. High-throughput behavioral screening in this genetically tractable model organism is a potentially powerful approach, but it is currently very laborious. Our system monitors interacting pairs of flies, and computes their location, orientation and wing posture. These features are used for detecting behaviors exhibited during aggression and courtship. Among these, wing threat, lunging and tussling are specific to aggression; circling, wing extension (courtship “song”) and copulation are specific to courtship; locomotion and chasing are common to both. Ethograms may be constructed automatically from these measurements, saving considerable time and effort. This technology should enable large-scale screens for genes and neural circuits controlling courtship and aggression.

Automated image-based tracking and its application in ecology

“…Historically, direct observation by trained biologists was used to quantify behavior [6,7]. However, the extent and resolution to which direct observations can be made is highly constrained [8] and the number of individuals that can be observed simultaneously is small. In addition, an exact record of events is not preserved, only the biologist's subjective account of them.…”

“…Research in this last category usually focuses on a small number of individuals, because identifying the detailed pose required for automated behavioral analysis is difficult in larger groups. Tracking over short durations (minutes) has aided in our understanding of the genetic basis of social behavior, such as aggression or courtship [8,85], where the high throughput that automation allows provides enhanced power for uncovering patterns in behavioral data [27]. Research over longer times can uncover complex temporal linkages between social behaviors [8,28], and experiments over the order of weeks provide unique insight into the social and behavioral development of individuals in intraspecific groups [31,53,54].…”

“…In nature, however, interactions between species often involve individuals that differ greatly in size and shape [30) (Movie S13 in the supplementary material online). Although such differences can be useful for distinguishing individuals [8,20), many tracking systems rely on know ledge about the typical shape of individuals to aid in the segmentation and analysis of images [27,28,31). Even if shape issues are overcome, it remains a difficult task for computer vision algorithms to separate small animals from the body and appendages of larger animals.…”

“…The position and pose of organisms with stiff and simple shaped bodies can be computed by fitting a shape contour to the image of the organism [8,27) (Figure 10 …”

“…These issues can be readily overcome with standard photogrammetric techniques (91) shows the angular density of predators around a representative focal prey, with high predation density behind the prey revealing that piscivorous predators tend to attack from behind their prey [4] , and panel (H) shows a reconstruction of the visual field of an individual fish embedded in the center of a large school, which provides novel insight into information flows within animal groups [26] . Behavioral information can also reveal the temporal linkage between complex behaviors, such as (1), the transitional behavioral graph for social interactions in Drosophila [8]. See…”