The laboratory is interested in computational aspects of sensory information processing from the single cell to the network level. The mechanisms underlying information processing by neurons and neuronal networks are currently the subject of intense investigations. In visual sensory systems, significant progress has been made in understanding the circuitry and the response dynamics underlying the receptive field properties of visual neurons. Our understanding of the cellular and dendritic mechanisms that could contribute to the processing of sensory information in single neurons has also been greatly increased. However, still very little is known about how the biophysical properties of single neurons are actually used to implement specific computations. Two types of neuronal computations thought to be fundamental to the processing of information within the nervous system are the multiplication of independent signals and invariance of neuronal responses.

We are studying collision avoidance in the visual system of the locust as a model to investigate these questions. The locust optic lobes possess an identified neuron, the lobula giant motion detector neuron (LGMD), which responds vigorously to objects approaching on a collision course with the animal (looming stimuli). The firing rate of the LGMD peaks when an approaching object approximately reaches a constant angular threshold size on the retina, suggesting that angular threshold might be the variable used to trigger escape and collision avoidance behaviors. The time-course of the firing rate of this neuron in response to looming stimuli is best described by multiplying two inputs impinging on the dendrites of the LGMD. One input is excitatory and sensitive to motion while the other input is inhibitory and sensitive to size. Current evidence suggests that this multiplication is in part implemented within the dendritic tree of the neuron. Furthermore, the response of the LGMD is invariant to a wide range of loooming stimulus parameters, including the contrast, the texture, the angle of approach and the particular shape of the approaching object. Because the LGMD can be reliably identified from animal to animal and recorded intracellularly for extended periods of time, it offers an ideal model to investigate the biophysical mechanisms underlying these computations.

Additionally, we are interested in investigating the behavioral basis of collision avoidance behaviors in other species, including the vinegar fly Drosophila melanogaster and the laboratory mouse.