The long term objective of this research is to understand the biophysical mechanisms by which time-varying sensory stimuli are integrated in individual neurons. The immediate goal is to provide detailed biophysical explanations of how individual neurons multiply two inputs and how they implement invariance to certain stimulus attributes. Multiplication has been implicated in many neural computations, like the extraction of motion information from visual images, in both vertebrate and invertebrate nervous systems. Invariance is an attribute commonly found in higher order neurons that respond selectively to a stimulus feature independently of its context. Currently, there is little understanding of how these computations are accomplished by neurons. These issues will be investigated in the visual system of the locust, which possesses a neuron, the lobula giant movement detector (LGMD), that responds to objects looming on a collision course towards the animal. This neuron implements a multiplication operation between two distinct inputs impinging on its dendrites and exhibits responses that are invariant to many attributes of the looming object. Many features of the LGMD make it a favorable subject for biophysical studies.
The specific aims of the project are to characterize the properties of synaptic inputs onto the LGMD, including the role played by background synaptic activity in shaping its responses to looming stimuli. In addition, the basic properties of several active membrane conductances and their role in the integration of synaptic inputs within the dendritic tree of the cell will be studied. The spatio-temporal activation pattern of the LGMD's dendritic compartments during visual stimulation will also be assessed. These data will be used to build a model of the cell and its response to looming stimuli. The techniques employed will include stimulation of single facets on the compound eye of the locust - thus allowing to decompose complex visual stimuli in their elementary components - intracellular recordings, pharmacological manipulations, calcium imaging and compartmental modeling. The model and experimental data will be used to identify the biophysical mechanisms underlying multiplication and invariance in this neuron. Because very similar computations are found in vertebrate central nervous systems, this project is expected to advance the general understanding of how multiplication and invariance are implemented for neural information processing. Notably, multiplication and invariance have been shown to play an important role in visual perception and attention. Thus, characterizing the biophysical and cellular mechanisms of multiplication and invariance in this model system may also yield important insights in disorders involving perception and attention.

Public Health Relevance

This project will study in a model organism how two operations commonly found in the nervous system are implemented within single neurons: the multiplication of two independent input signals and the invariance of responses to specific properties of sensory stimuli. Both multiplication and invariance have been shown to play an important role in visual perception and attention. Thus, characterizing the biophysical and cellular mechanisms of multiplication and invariance may yield important insights in disorders involving perception and attention.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Research Project (R01)
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Sensorimotor Integration Study Section (SMI)
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Glanzman, Dennis L
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Baylor College of Medicine
Schools of Medicine
United States
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Wang, Hongxia; Dewell, Richard B; Zhu, Ying et al. (2018) Feedforward Inhibition Conveys Time-Varying Stimulus Information in a Collision Detection Circuit. Curr Biol 28:1509-1521.e3
Zhu, Ying; Dewell, Richard B; Wang, Hongxia et al. (2018) Pre-synaptic Muscarinic Excitation Enhances the Discrimination of Looming Stimuli in a Collision-Detection Neuron. Cell Rep 23:2365-2378
Dewell, Richard Burkett; Gabbiani, Fabrizio (2018) Biophysics of object segmentation in a collision-detecting neuron. Elife 7:
Haag, Juergen; Arenz, Alexander; Serbe, Etienne et al. (2016) Complementary mechanisms create direction selectivity in the fly. Elife 5:
Zhu, Ying; Gabbiani, Fabrizio (2016) Fine and distributed subcellular retinotopy of excitatory inputs to the dendritic tree of a collision-detecting neuron. J Neurophysiol 115:3101-12
Trousdale, James; Carroll, Samuel R; Gabbiani, Fabrizio et al. (2014) Near-optimal decoding of transient stimuli from coupled neuronal subpopulations. J Neurosci 34:12206-22
Chan, R W M; Gabbiani, F (2013) Collision-avoidance behaviors of minimally restrained flying locusts to looming stimuli. J Exp Biol 216:641-55
Jones, Peter W; Gabbiani, Fabrizio (2012) Logarithmic compression of sensory signals within the dendritic tree of a collision-sensitive neuron. J Neurosci 32:4923-34
Fotowat, Haleh; Harrison, Reid R; Gabbiani, Fabrizio (2011) Multiplexing of motor information in the discharge of a collision detecting neuron during escape behaviors. Neuron 69:147-58
Jones, Peter W; Gabbiani, Fabrizio (2010) Synchronized neural input shapes stimulus selectivity in a collision-detecting neuron. Curr Biol 20:2052-7

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