Associate Professor - Department of Neuroscience Adjunct Associate Professor - Department of Computational and Applied Mathematics, Rice University Ph.D., Swiss Institute of Technology, Zuerich, 1992 One Baylor Plaza Baylor College of Medicine Houston TX, 77030 Telephone: 713-798-1849 - Fax: 713-798-3946 Email: gabbiani@bcm.edu Web:glab.bcm.tmc.edu

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.

Our current and future research plans include the characterization of the response properties of afferent neurons presynaptic to the LGMD. We are also developing systems that will allow us to stimulate a large number of single inputs to the LGMD in arbitrary sequence. Paired with intracellular recordings and calcium imaging in vivo, this allows us to explore properties of the micro-circuitry presynaptic to the LGMD neuron and the integration of synaptic inputs within this neuron. Finally, we are performing behavioral experiments and simultaneous extracellular recordings to investigate the role of these computations in behavior, such as jumping and collision avoidance in flight.

top

Peron SP, Jones PW, Gabbiani F. Precise Subcellular Input Retinotopy and Its Computational Consequences in an Identified Visual Interneuron. Neuron (2009) 63:830-842.

Peron S, Gabbiani F. Spike frequency adaptation mediates looming stimulus selectivity in a collision-detecting neuron. Nat Neurosci (2009) 12: 318-326.

Peron SP, Krapp HG, Gabbiani F. Influence of electrotonic structure and synaptic mapping on the receptive field properties of a collision-detecting neuron. J Neurophysiol (2007) 97, 159-177

Fotowat H, Gabbiani F. Relationship between the phases of sensory and motor activity during a looming-evoked multistage escape behavior. J Neurosci. 2007 Sep 12;27(37):10047-59.

Gabbiani F and Krapp HG. Spike-frequency adaptation and intrinsic properties of an identified, looming-sensitive neuron. J Neurophysiol. (2006) 96, 2951-2962

Krahe R, Gabbiani F. Burst firing in sensory systems. Nat Rev Neurosci. 2004 5:13-23.

Gabbiani F, Krapp HG, Koch C, Laurent G. Multiplicative computation in a visual neuron sensitive to looming. Nature. 2002 420:320-4.

Gabbiani F, Mo C, Laurent G. Invariance of angular threshold computation in a wide-field looming-sensitive neuron. J Neurosci. 2001 21:314-29.

Gabbiani F, Krapp HG, Laurent G. Computation of object approach by a wide-field, motion-sensitive neuron. J Neurosci. 1999 19:1122-41.

Gabbiani F, Koch C. Coding of time-varying signals in spike trains of integrate-and-fire neurons with random threshold. Neural Comput 1996 8:44-66.

top

1993 Roche Research Fellowship in Neurosciences

1997-2000 Sloan Research Fellowship in Theoretical Neurosciences

2001-2003 Alfred P. Sloan Research Fellow

2006 Summer Research Fellowship, Marine Biological Laboratory, Woods Hole, MA

top

Our laboratory works on the mechanisms by which single neurons, the elementary building blocks of the brain, process sensory information. We focus on understanding collision avoidance in the the locust, a system ideally suited for this purpose. Locusts possess identified neurons that are specialized in processing visual information related to collision avoidance (picture) and that can be recorded over long periods of time and reliably found across animals. This allows for a detailed characterization of their biophysical properties and an investigation of their role in generating escape behaviors.

top