Multi-camera Realtime 3D 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 realtime - with minimal latency - opens up the experimental possibility of manipulating sensory feedback, thus allowing detailed explorations of the neural basis for control of behavior. Here we describe a new system capable of tracking the position and body orientation of animals such as flies and birds. The system operates with less than 40 msec 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 Neighbor Standard Filter data association algorithm. In one implementation, an eleven 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 behavior 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.Comment: pdfTeX using libpoppler 3.141592-1.40.3-2.2 (Web2C 7.5.6), 18 pages with 9 figure

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

Successional Change in Phosphorus Stoichiometry Explains the Inverse Relationship between Herbivory and Lupin Density on Mount St. Helens

The average nitrogen-to-phosphorus ratio (N?P) of insect herbivores is less than that of leaves, suggesting that P may mediate plant-insect interactions more often than appreciated. We investigated whether succession-related heterogeneity in N and P stoichiometry influences herbivore performance on N-fixing lupin (Lupinus lepidus) colonizing primary successional volcanic surfaces, where the abundances of several specialist lepidopteran herbivores are inversely related to lupin density and are known to alter lupin colonization dynamics. We examined larval performance in response to leaf nutritional characteristics using gelechiid and pyralid leaf-tiers, and a noctuid leaf-cutter.Apple JL, Wink M, Wills SE, Bishop JG (2009) Successional Change in Phosphorus Stoichiometry Explains the Inverse Relationship between Herbivory and Lupin Density on Mount St. Helens. PLoS ONE 4(11): e7807. doi:10.1371/journal.pone.000780

N-3 polyunsaturated fatty acid and neuroinflammation in aging and Alzheimer's disease

The innate immune system of the brain is mainly composed of microglial cells, which play a key role in the maintenance of synapses and the protection of neurons against noxious agents or lesions owing to their phagocytic activity. In the healthy brain, microglia are highly motile and strongly interact with neurons either by physical contact, induction of oxidative stress or through specific mediators, such as chemokines and cytokines. In response to inflammatory insult however, microglial cells get activated and produce inflammatory cytokines. The action of cytokines on specific receptors expressed in the brain triggers the development of sickness behavior and altered cognitive and emotional processes. The effects are acute and reversible as normal behavior is restored once the synthesis of inflammatory brain cytokines returns to baseline after a few hours. However, in pathological situations, these cytokines may reach toxic levels and have irreversible consequences such as neuronal death, as observed in neurodegenerative disorders such as Alzheimer’s disease. Omega-3 (n-3) polyunsaturated fatty acids (PUFAs) are essential nutrients and fundamental components of neuronal and glial cell membranes. They accumulate in the brain during the perinatal period in a dietary supply-dependent fashion. Their brain levels may diminish with age, but can be increased by diets enriched in n-3 PUFAs. Changes in the immune profile have been associated with n-3 PUFAs intake in humans and animal models. Therefore, the increasing exposure of the population to diets low in n-3 PUFAs could contribute to the deleterious effects of the chronic activation of microglia in the brain

Biologically motivated visual control of attitude and altitude in translatory flight

Flying insects use highly efficient visual strategies for stabilizing their motion in three-dimensional space. We present a flight control model that uses a combination of biologically inspired, visual feedforward mechanisms for stabilizing attitude (i.e. pitch and roll angles) and altitude during translatory motion. The attitude sensor exploits the position invariant vertical intensity gradient that exists in most natural open environments to orient the upper surface of a flying agent towards the region of maximum brightness (dorsal light response). Altitude is controlled using distance information contained in the frontoventral translatory optic flow (motion parallax). Our results from open-loop computer simulations show that the signals produced by these mechanisms robustly indicate the direction of deviation from a certain attitude angle or ground distance. We argue that in a closed control loop, these qualitative signals can be sufficient for flight stabilization. We present closed-loop trajectories of a simulated agent equipped with both mechanisms, flying over a textured, uneven surface. The agent shows robust flight behavior with six degrees of freedom.