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 thes 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 approaching on a collision course towards the animal and their two dimensional simulations on a video monitor, called looming stimuli. This neuron implements a multiplication operation between two distinct inputs impinging on its dendrites and exhibits responses that are invariant to many attributes of looming stimuli. 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 patter 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, two-photon confocal calcium imaging, optogenetics and anatomical reconstructions based on viral transfections, as well as compartmental modeling at various levels of abstraction. 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

Neural multiplication operations similar to those investigated in this project have been shown to play an important role in visual perception and attention. Thus, characterizing the biophysical and cellular mechanisms of multiplication in the model system that will be the focus of this work may also yield important insights into mental illnesses involving perception and attention.

Agency
National Institute of Health (NIH)
Type
Research Project (R01)
Project #
5R01MH065339-12
Application #
8685323
Study Section
Sensorimotor Integration Study Section (SMI)
Program Officer
Glanzman, Dennis L
Project Start
Project End
Budget Start
Budget End
Support Year
12
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Baylor College of Medicine
Department
Neurosciences
Type
Schools of Medicine
DUNS #
City
Houston
State
TX
Country
United States
Zip Code
77030
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
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
Fotowat, Haleh; Fayyazuddin, Amir; Bellen, Hugo J et al. (2009) A novel neuronal pathway for visually guided escape in Drosophila melanogaster. J Neurophysiol 102:875-85
Peron, Simon P; Jones, Peter W; Gabbiani, Fabrizio (2009) Precise subcellular input retinotopy and its computational consequences in an identified visual interneuron. Neuron 63:830-42
Peron, Simon Peter; Gabbiani, Fabrizio (2009) Role of spike-frequency adaptation in shaping neuronal response to dynamic stimuli. Biol Cybern 100:505-20
Peron, Simon; Gabbiani, Fabrizio (2009) Spike frequency adaptation mediates looming stimulus selectivity in a collision-detecting neuron. Nat Neurosci 12:318-26
Fotowat, Haleh; Gabbiani, Fabrizio (2007) Relationship between the phases of sensory and motor activity during a looming-evoked multistage escape behavior. J Neurosci 27:10047-59
Peron, Simon P; Krapp, Holger G; Gabbiani, Fabrizio (2007) Influence of electrotonic structure and synaptic mapping on the receptive field properties of a collision-detecting neuron. J Neurophysiol 97:159-77

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