O fly, where art thou?

High speed visual insect swarm tracker (Hi-VISTA) used to identify the effects of confinement on individual insect flight

Individual insects flying in crowded assemblies perform complex aerial maneuvers by sensing and feeding back neighbor measurements to small changes in their wing motions. To understand the individual feedback rules that permit these fast, adaptive behaviors in group flight, both experimental preparations inducing crowded flight and high-speed tracking systems capable of tracking both body motions and more subtle wing motion changes for multiple insects in simultaneous flight are needed. This measurement capability extends tracking beyond the previous focus on individual insects to multiple insects. This paper describes an experimental preparation that induces crowded insect flight in more naturalistic conditions (a laboratory-outdoor transition tunnel) and directly compares the resulting flight performance to traditional flight enclosures. Measurements are made possible via the introduction of a multi-agent high speed insect tracker called Hi-VISTA, which provides a capability to track wing and body motions of multiple insects using high speed cameras (9000-12 500 fps). Processing steps consist of automatic background identification, data association, hull reconstruction, segmentation, and feature measurement. To improve the biological relevance of laboratory experiments and develop a platform for interaction studies, this paper applies the Hi-VISTA measurement system toApis melliferaforagers habituated to transit flights through the transparent transition environment. Binary statistical analysis (Welch's t-test, Cohen's d effect size) of 95 flight trajectories is presented, quantifying the differences between flights in an unobstructed environment and in a confined tunnel volume. The results indicate that body pitch angle, heading rate, flapping frequency, and vertical speed (heave) are each affected by confinement, and other flight variables show minor or statistically insignificant changes. These results form a baseline as swarm tracking and analysis begins to isolate the effects of neighbors from environmental enclosures, and improve the connection of high speed insect laboratory experiments to outdoor field experiments.

Estimating Orientation of Flying Fruit Flies

The recently growing interest in studying flight behaviours of fruit flies, Drosophila melanogaster, has highlighted the need for developing tools that acquire quantitative motion data. Despite recent advance of video tracking systems, acquiring a flying fly’s orientation remains a challenge for these tools. In this paper, we present a novel method for estimating individual flying fly’s orientation using image cues. Thanks to the line reconstruction algorithm in computer vision field, this work can thereby focus on the practical detail of implementation and evaluation of the orientation estimation algorithm. The orientation estimation algorithm can be incorporated into tracking algorithms. We rigorously evaluated the effectiveness and accuracy of the proposed algorithm by running experiments both on simulation data and on real-world data. This work complements methods for studying the fruit fly’s flight behaviours in a three-dimensional environment.

A Novel Method for Tracking Individuals of Fruit Fly Swarms Flying in a Laboratory Flight Arena

The growing interest in studying social behaviours of swarming fruit flies, Drosophila melanogaster, has heightened the need for developing tools that provide quantitative motion data. To achieve such a goal, multi-camera three-dimensional tracking technology is the key experimental gateway. We have developed a novel tracking system for tracking hundreds of fruit flies flying in a confined cubic flight arena. In addition to the proposed tracking algorithm, this work offers additional contributions in three aspects: body detection, orientation estimation, and data validation. To demonstrate the opportunities that the proposed system offers for generating high-throughput quantitative motion data, we conducted experiments on five experimental configurations. We also performed quantitative analysis on the kinematics and the spatial structure and the motion patterns of fruit fly swarms. We found that there exists an asymptotic distance between fruit flies in swarms as the population density increases. Further, we discovered the evidence for repulsive response when the distance between fruit flies approached the asymptotic distance. Overall, the proposed tracking system presents a powerful method for studying flight behaviours of fruit flies in a three-dimensional environment.

Markerless motion tracking of awake animals in positron emission tomography

Noninvasive functional imaging of awake, unrestrained small animals using motion-compensation removes the need for anesthetics and enables an animal's behavioral response to stimuli or administered drugs to be studied concurrently with imaging. While the feasibility of motion-compensated radiotracer imaging of awake rodents using marker-based optical motion tracking has been shown, markerless motion tracking would avoid the risk of marker detachment, streamline the experimental workflow, and potentially provide more accurate pose estimates over a greater range of motion. We have developed a stereoscopic tracking system which relies on native features on the head to estimate motion. Features are detected and matched across multiple camera views to accumulate a database of head landmarks and pose is estimated based on 3D-2D registration of the landmarks to features in each image. Pose estimates of a taxidermal rat head phantom undergoing realistic rat head motion via robot control had a root mean square error of 0.15 and 1.8 mm using markerless and marker-based motion tracking, respectively. Markerless motion tracking also led to an appreciable reduction in motion artifacts in motion-compensated positron emission tomography imaging of a live, unanesthetized rat. The results suggest that further improvements in live subjects are likely if nonrigid features are discriminated robustly and excluded from the pose estimation process.

The Drosophila visual system: From neural circuits to behavior

A compact genome and a tiny brain make Drosophila the prime model to understand the neural substrate of behavior. The neurogenetic efforts to reveal neural circuits underlying Drosophila vision started about half a century ago, and now the field is booming with sophisticated genetic tools, rich behavioral assays, and importantly, a greater number of scientists joining from different backgrounds. This review will briefly cover the structural anatomy of the Drosophila visual system, the animal’s visual behaviors, the genes involved in assembling these circuits, the new and powerful techniques, and the challenges ahead for ultimately identifying the general principles of biological computation in the brain.

 

A typical brain utilizes a great many compact neural circuits to collect and process information from the internal biological and external environmental worlds and generates motor commands for observable behaviors. The fruit fly Drosophila melanogaster, despite of its miniature body and tiny brain, can survive in almost any corner of the world.¹ It can find food, court mate, fight rival conspecific, avoid predators, and amazingly fly without crashing into trees. Drosophila vision and its underlying neuronal machinery has been a key research model for at least half century for neurogeneticists.² Given the efforts invested on the visual system, this animal model is likely to offer the first full understanding of how visual information is computed by a multi-cellular organism. Furthermore, research in Drosophila has revealed many genes that play crucial roles in the formation of functional brains across species. The architectural similarities between the visual systems of Drosophila and vertebrate at the molecular, cellular, and network levels suggest new principles discovered at the circuit level on the relationship between neurons and behavior in Drosophila shall also contribute greatly to our understanding of the general principles for how bigger brains work.³ I start with the anatomy of Drosophila visual system, which surprisingly still contains many uncharted areas.

Assessing senescence in Drosophila using video tracking

Senescence is associated with changes in gene expression, including the upregulation of stress response- and innate immune response-related genes. In addition, aging animals exhibit characteristic changes in movement behaviors including decreased gait speed and a deterioration in sleep/wake rhythms. Here, we describe methods for tracking Drosophila melanogaster movements in 3D with simultaneous quantification of fluorescent transgenic reporters. This approach allows for the assessment of correlations between behavior, aging, and gene expression as well as for the quantification of biomarkers of aging.

Three-dimensional tracking and behaviour monitoring of multiple fruit flies

The increasing interest in the investigation of social behaviours of a group of animals has heightened the need for developing tools that provide robust quantitative data. Drosophila melanogaster has emerged as an attractive model for behavioural analysis; however, there are still limited ways to monitor fly behaviour in a quantitative manner. To study social behaviour of a group of flies, acquiring the position of each individual over time is crucial. There are several studies that have tried to solve this problem and make this data acquisition automated. However, none of these studies has addressed the problem of keeping track of flies for a long period of time in three-dimensional space. Recently, we have developed an approach that enables us to detect and keep track of multiple flies in a three-dimensional arena for a long period of time, using multiple synchronized and calibrated cameras. After detecting flies in each view, correspondence between views is established using a novel approach we call the 'sequential Hungarian algorithm'. Subsequently, the three-dimensional positions of flies in space are reconstructed. We use the Hungarian algorithm and Kalman filter together for data association and tracking. We evaluated rigorously the system's performance for tracking and behaviour detection in multiple experiments, using from one to seven flies. Overall, this system presents a powerful new method for studying complex social interactions in a three-dimensional environment.

Automated quantification of locomotion, social interaction, and mate preference in Drosophila mutants

Automated tracking methods facilitate screening for and characterization of abnormal locomotion or more complex behaviors in Drosophila. We developed the Iowa Fly Locomotion and Interaction Tracker (IowaFLI Tracker), a MATLAB-based video analysis system, to identify and track multiple flies in a small arena. We report altered motor activity in the K(+) and Na(+) channel mutants, Hk(1) and para(ts1), which had previously been shown to display abnormal larval locomotion. Environmental factors influencing individual behavior, such as available "social space," were studied by using IowaFLI Tracker to simultaneously track multiple flies in the same arena. We found that crowding levels affect individual fly activity, with the total movement of individual flies attenuated around a particular density. This observation may have important implications in the design of activity chambers for studying particular kinds of social interactions. IowaFLI Tracker also directly quantifies social interactions by tracking the amount of time individuals are in proximity to one another-visualized as an "interactogram." This feature enables the development of a "target-preference" assay to study male courtship behavior where males are presented with a choice between two immobilized, decapitated females, and their locomotion and interactions quantified. We used this assay to study the chemosensory mutants olf D (para(olfD), sbl(2)) and Gr32a and their preferences towards virgin or mated females. Male olf D flies showed reduced courtship levels, with no clear preference towards either, whereas Gr32a males preferentially courted with virgin females over mated females in this assay. These initial results demonstrate that IowaFLI Tracker can be employed to explore motor coordination and social interaction phenomena in behavioral mutants of Drosophila.

Using GFP video to track 3D movement and conditional gene expression in free-moving flies

BACKGROUND

In vivo imaging and quantification of fluorescent reporter molecules is increasingly useful in biomedical research. For example, tracking animal movement in 3D with simultaneous quantification of fluorescent transgenic reporters allows for correlations between behavior, aging and gene expression. However implementation has been hindered in the past by the complexity of operating the systems.

RESULTS

We report significant technical improvements and user-friendly software (called FluoreScore) that enables tracking of 3D movement and the dynamics of gene expression in adult Drosophila, using two cameras and recorded GFP videos. Expression of a transgenic construct encoding eGFP was induced in free-moving adult flies using the Gene-Switch system and RU486 drug feeding. The time course of induction of eGFP expression was readily quantified from internal tissues including central nervous tissue.

CONCLUSIONS

FluoreScore should facilitate a variety of future studies involving quantification of movement behaviors and fluorescent molecules in free-moving animals.

Reconstructing the flight kinematics of swarming and mating in wild mosquitoes

We describe a novel tracking system for reconstructing three-dimensional tracks of individual mosquitoes in wild swarms and present the results of validating the system by filming swarms and mating events of the malaria mosquito Anopheles gambiae in Mali. The tracking system is designed to address noisy, low frame-rate (25 frames per second) video streams from a stereo camera system. Because flying A. gambiae move at 1-4 m s(-1), they appear as faded streaks in the images or sometimes do not appear at all. We provide an adaptive algorithm to search for missing streaks and a likelihood function that uses streak endpoints to extract velocity information. A modified multi-hypothesis tracker probabilistically addresses occlusions and a particle filter estimates the trajectories. The output of the tracking algorithm is a set of track segments with an average length of 0.6-1 s. The segments are verified and combined under human supervision to create individual tracks up to the duration of the video (90 s). We evaluate tracking performance using an established metric for multi-target tracking and validate the accuracy using independent stereo measurements of a single swarm. Three-dimensional reconstructions of A. gambiae swarming and mating events are presented.

A novel lenticular arena to quantify locomotor competence in walking fruit flies

Drosophila melanogaster has become an important invertebrate model organism in biological and medical research, for mutational and genetic analysis, and in toxicological screening. Many screening assays have been developed that assess the flies' mortality, reproduction, development, morphology, or behavioral competence. In this study, we describe a new assay for locomotor competence. It comprises a circular walking arena with a lenticular floor and a flat cover (the slope of the floor increases gradually from the center to the edge of the arena) plus automated fly tracking and statistical analysis. This simple modification of a flat arena presents a graduated physical challenge, with which we can assess fine gradations of motor ability, since a fly's time average radial distance from the arena center is a direct indicator of its climbing ability. The time averaged distribution of flies as a function of slope, activity levels, and walking speed, yields a fine grained picture of locomotory ability and motivation levels. We demonstrate the strengths and weaknesses of this assay (compared with a conventional tap-down test) by observing flies treated with a neurotoxin (BMAA) that acts as a glutamate agonist. The assay proves well suited to detect dose effects and progression effects with higher statistical power than the traditional tap-down, but it has a higher detection limit, making it less sensitive to treatment effects.

Application of a novel open-source program for measuring the effects of toxicants on the swimming behavior of large groups of unmarked fish

The aim of this study was to demonstrate a novel method for measuring the effects of toxicants on the behavior of groups of unmarked fish. Ctrax is an open source Python-based machine vision program that was originally designed to track fruit flies (Drosophila). The effects of the fish anaesthetic quinaldine sulfate on the behavior of groups of 10 unmarked Arabian killifish (Aphanias dispar) in a small arena were measured. Ctrax was able to identify and track the X-Y coordinates of the individual fish over 1 min recording periods. The data was analyzed using specifically written Matlab (The Mathworks™) toolboxes and the effects of quinaldine sulfate on absolute swimming velocity, forward swimming velocity, rate of change in orientation and distance to wall were calculated. Additionally the effects of quinaldine sulfate on path tortuosity were also measured. Ctrax has significant benefits over other available technologies for tracking the 2-dimensional coordinates of fish. In particular the software is open source and thus freely available, it is accurate, requires only simple easily available equipment and able to track potentially large groups of fish (possibly >50) while maintaining their individual identities.

The iFly tracking system for an automated locomotor and behavioural analysis of Drosophila melanogaster

The use of animal models in medical research provides insights into molecular and cellular mechanisms of human disease, and helps identify and test novel therapeutic strategies. Drosophila melanogaster--the common fruit fly--is one of the most well-established model organisms, as its study can be performed more readily and with far less expense than for other model animal systems, such as mice, fish, or primates. In the case of fruit flies, standard assays are based on the analysis of longevity and basic locomotor functions. Here we present the iFly tracking system, which enables to increase the amount of quantitative information that can be extracted from these studies, and to reduce significantly the duration and costs associated with them. The iFly system uses a single camera to simultaneously track the trajectories of up to 20 individual flies with about 100 μm spatial and 33 ms temporal resolution. The statistical analysis of fly movements recorded with such accuracy makes it possible to perform a rapid and fully automated quantitative analysis of locomotor changes in response to a range of different stimuli. We anticipate that the iFly method will reduce very considerably the costs and the duration of the testing of genetic and pharmacological interventions in Drosophila models, including an earlier detection of behavioural changes and a large increase in throughput compared to current longevity and locomotor assays.

Three-dimensional reconstruction of the fast-start swimming kinematics of densely schooling fish

Information transmission via non-verbal cues such as a fright response can be quantified in a fish school by reconstructing individual fish motion in three dimensions. In this paper, we describe an automated tracking framework to reconstruct the full-body trajectories of densely schooling fish using two-dimensional silhouettes in multiple cameras. We model the shape of each fish as a series of elliptical cross sections along a flexible midline. We estimate the size of each ellipse using an iterated extended Kalman filter. The shape model is used in a model-based tracking framework in which simulated annealing is applied at each step to estimate the midline. Results are presented for eight fish with occlusions. The tracking system is currently being used to investigate fast-start behaviour of schooling fish in response to looming stimuli.

Recording lifetime behavior and movement in an invertebrate model

Characterization of lifetime behavioral changes is essential for understanding aging and aging-related diseases. However, such studies are scarce partly due to the lack of efficient tools. Here we describe and provide proof of concept for a stereo vision system that classifies and sequentially records at an extremely fine scale six different behaviors (resting, micro-movement, walking, flying, feeding and drinking) and the within-cage (3D) location of individual tephritid fruit flies by time-of-day throughout their lives. Using flies fed on two different diets, full sugar-yeast and sugar-only diets, we report for the first time their behavioral changes throughout their lives at a high resolution. We have found that the daily activity peaks at the age of 15–20 days and then gradually declines with age for flies on both diets. However, the overall daily activity is higher for flies on sugar-only diet than those on the full diet. Flies on sugar-only diet show a stronger diurnal localization pattern with higher preference to staying on the top of the cage during the period of light-off when compared to flies on the full diet. Clustering analyses of age-specific behavior patterns reveal three distinct young, middle-aged and old clusters for flies on each of the two diets. The middle-aged groups for flies on sugar-only diet consist of much younger age groups when compared to flies on full diet. This technology provides research opportunities for using a behavioral informatics approach for understanding different ways in which behavior, movement, and aging in model organisms are mutually affecting.

Automated 3D trajectory measuring of large numbers of moving particles

Complex dynamics of natural particle systems, such as insect swarms, bird flocks, fish schools, has attracted great attention of scientists for years. Measuring 3D trajectory of each individual in a group is vital for quantitative study of their dynamic properties, yet such empirical data is rare mainly due to the challenges of maintaining the identities of large numbers of individuals with similar visual features and frequent occlusions. We here present an automatic and efficient algorithm to track 3D motion trajectories of large numbers of moving particles using two video cameras. Our method solves this problem by formulating it as three linear assignment problems (LAP). For each video sequence, the first LAP obtains 2D tracks of moving targets and is able to maintain target identities in the presence of occlusions; the second one matches the visually similar targets across two views via a novel technique named maximum epipolar co-motion length (MECL), which is not only able to effectively reduce matching ambiguity but also further diminish the influence of frequent occlusions; the last one links 3D track segments into complete trajectories via computing a globally optimal assignment based on temporal and kinematic cues. Experiment results on simulated particle swarms with various particle densities validated the accuracy and robustness of the proposed method. As real-world case, our method successfully acquired 3D flight paths of fruit fly (Drosophila melanogaster) group comprising hundreds of freely flying individuals.

Multi-camera real-time three-dimensional tracking of multiple flying animals

Automated tracking of animal movement allows analyses that would not otherwise be possible by providing great quantities of data. The additional capability of tracking in real time--with minimal latency--opens up the experimental possibility of manipulating sensory feedback, thus allowing detailed explorations of the neural basis for control of behaviour. Here, we describe a system capable of tracking the three-dimensional position and body orientation of animals such as flies and birds. The system operates with less than 40 ms latency and can track multiple animals simultaneously. To achieve these results, a multi-target tracking algorithm was developed based on the extended Kalman filter and the nearest neighbour standard filter data association algorithm. In one implementation, an 11-camera system is capable of tracking three flies simultaneously at 60 frames per second using a gigabit network of nine standard Intel Pentium 4 and Core 2 Duo computers. This manuscript presents the rationale and details of the algorithms employed and shows three implementations of the system. An experiment was performed using the tracking system to measure the effect of visual contrast on the flight speed of Drosophila melanogaster. At low contrasts, speed is more variable and faster on average than at high contrasts. Thus, the system is already a useful tool to study the neurobiology and behaviour of freely flying animals. If combined with other techniques, such as 'virtual reality'-type computer graphics or genetic manipulation, the tracking system would offer a powerful new way to investigate the biology of flying animals.

A new chamber for studying the behavior of Drosophila

Methods available for quickly and objectively quantifying the behavioral phenotypes of the fruit fly, Drosophila melanogaster, lag behind in sophistication the tools developed for manipulating their genotypes. We have developed a simple, easy-to-replicate, general-purpose experimental chamber for studying the ground-based behaviors of fruit flies. The major innovative feature of our design is that it restricts flies to a shallow volume of space, forcing all behavioral interactions to take place within a monolayer of individuals. The design lessens the frequency that flies occlude or obscure each other, limits the variability in their appearance, and promotes a greater number of flies to move throughout the center of the chamber, thereby increasing the frequency of their interactions. The new chamber design improves the quality of data collected by digital video and was conceived and designed to complement automated machine vision methodologies for studying behavior. Novel and improved methodologies for better quantifying the complex behavioral phenotypes of Drosophila will facilitate studies related to human disease and fundamental questions of behavioral neuroscience.

Hydrogen peroxide stimulates activity and alters behavior in Drosophila melanogaster

Circadian rhythms in animals are regulated at the level of individual cells and by systemic signaling to coordinate the activities of multiple tissues. The circadian pacemakers have several physiological outputs, including daily locomotor rhythms. Several redox-active compounds have been found to function in regulation of circadian rhythms in cells, however, how particular compounds might be involved in regulating specific animal behaviors remains largely unknown. Here the effects of hydrogen peroxide on Drosophila movement were analyzed using a recently developed three-dimensional real-time multiple fly tracking assay. Both hydrogen peroxide feeding and direct injection of hydrogen peroxide caused increased adult fly locomotor activity. Continuous treatment with hydrogen peroxide also suppressed daily locomotor rhythms. Conditional over-expression of the hydrogen peroxide-producing enzyme superoxide dismutase (SOD) also increased fly activity and altered the patterns of locomotor activity across days and weeks. The real-time fly tracking system allowed for detailed analysis of the effects of these manipulations on behavior. For example, both hydrogen peroxide feeding and SOD over-expression increased all fly motion parameters, however, hydrogen peroxide feeding caused relatively more erratic movement, whereas SOD over-expression produced relatively faster-moving flies. Taken together, the data demonstrate that hydrogen peroxide has dramatic effects on fly movement and daily locomotor rhythms, and implicate hydrogen peroxide in the normal control of these processes.

High-throughput ethomics in large groups of Drosophila

We present a camera-based method for automatically quantifying the individual and social behaviors of fruit flies, Drosophila melanogaster, interacting in a planar arena. Our system includes machine-vision algorithms that accurately track many individuals without swapping identities and classification algorithms that detect behaviors. The data may be represented as an ethogram that plots the time course of behaviors exhibited by each fly or as a vector that concisely captures the statistical properties of all behaviors displayed in a given period. We found that behavioral differences between individuals were consistent over time and were sufficient to accurately predict gender and genotype. In addition, we found that the relative positions of flies during social interactions vary according to gender, genotype and social environment. We expect that our software, which permits high-throughput screening, will complement existing molecular methods available in Drosophila, facilitating new investigations into the genetic and cellular basis of behavior.

Simultaneous tracking of movement and gene expression in multiple Drosophila melanogaster flies using GFP and DsRED fluorescent reporter transgenes

BACKGROUND

Fluorescent proteins such as GFP (Green Fluorescent Protein) and DsRED (Discosoma sp.Red Fluorescent Protein) are often used as reporter molecules for transgene expression in Drosophila and other species. We have recently reported methods that allow simultaneous tracking of animal movement and GFP expression in real time, however the assay was limited to single animals and a single transgene. Numerous studies would be facilitated by methods that allow for assay of multiple animals and multiple transgenes.

FINDINGS

Here we report an improved fly video tracking system that allows multiple transgenic flies to be tracked simultaneously using visible light, GFP fluorescence and DsRED fluorescence. The movement of multiple flies could be accurately tracked at real time rates, while simultaneously assaying the expression level of two different transgenes marked with GFP and DsRED. The individual flies could be accurately tracked and distinguished even during periods when transgene fluorescence was undetected. For example, characteristic patterns of hsp70 and hsp22 transgene induction could be simultaneously quantified and correlated with animal movement in aging flies, and as groups of flies died due to dessication/starvation.

CONCLUSION

The improved methods allow for more efficient assay of the correlation between gene expression, behavior, aging and mortality: multiple animals can be assayed with simultaneous quantification of multiple transgenes using GFP and DsRED fluorescence. These methods should allow for increased flexibility in experimental designs. For example, in the future it should be possible to use gene expression levels to predict remaining life span more accurately, and to quantify gene expression changes caused by interactions between animals in real time.

Simultaneous tracking of fly movement and gene expression using GFP

Background

Green Fluorescent Protein (GFP) is used extensively as a reporter for transgene expression in Drosophila and other organisms. However, GFP has not generally been used as a reporter for circadian patterns of gene expression, and it has not previously been possible to correlate patterns of reporter expression with 3D movement and behavior of transgenic animals.

Results

We present a video tracking system that allows tissue-specific GFP expression to be quantified and correlated with 3D animal movement in real time. eyeless/Pax6 reporter expression had a 12 hr period that correlated with fly activity levels.

hsp70 and hsp22 gene reporters were induced during fly aging in circadian patterns (24 hr and 18 hr periods, respectively), and spiked in the hours preceding and overlapping the death of the animal. The phase of hsp gene reporter expression relative to fly activity levels was different for each fly, and remained the same throughout the life span.

Conclusion

These experiments demonstrate that GFP can readily be used to assay longitudinally fly movement and tissue-specific patterns of gene expression. The hsp22-GFP and hsp70-GFP expression patterns were found to reflect accurately the endogenous gene expression patterns, including induction during aging and circadian periodicity. The combination of these new tracking methods with the hsp-GFP reporters revealed additional information, including a spike in hsp22 and hsp70 reporter expression preceding death, and an intriguing fly-to-fly variability in the phase of hsp70 and hsp22 reporter expression patterns. These methods allow specific temporal patterns of gene expression to be correlated with temporal patterns of animal activity, behavior and mortality.

Advances in age-old questions

Drosophila melanogaster is an ideal model organism for various types of aging studies. They are easy to maintain, relatively inexpensive, have short life cycles, provide large sample sizes, and can be genetically manipulated via various methods for testing. The 49(th) Annual Drosophila Research Conference, held in San Diego, CA (April 2-6, 2008), had over 30 poster presentations and eight platform talks devoted to physiology and aging, and seven presentations in a longevity and functional senescence workshop. The data presented via these avenues included life span manipulation, physiological related genes, candidate aging genes, gene expression, signaling, and using D. melanogaster as a model for age related disease, to name a few. This report provides highlights of some of the information presented in the poster, platform and workshop presentations.