Fabrizio Gabbiani - US grants

DESCRIPTION (provided by applicant): 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.

Avoidance of collisions is critical to survival and the activity of sensory and motor neurons thought to be involved in visually-guided escape has been studied in several species. However, the mechanisms by which visual information processed in sensory areas leads to the preparation and execution of escape remains poorly understood. The current project addresses this question by studying escape of freely behaving locusts in response to simulated objects approaching on a collision course and by coupling these studies with electrophysiological recordings of neuronal activity both in restrained and freely moving animals. The locust will be studied because the neural pathways involved in generating escape behavior are well characterized and are accessible for neurophysiological investigation. The project will use a multi-disciplinary approach, combining behavior, neurophysiology and computer engineering to relate the generation of escape behaviors to the coding of visual stimuli in the activity of individual nerve cells. Gabbiani and his collaborators will first characterize how the timing of various stages of escape jumps elicited in locusts by the approach of an object on a collision course depends on the speed and size of the approaching object. Animals will be filmed with a high speed-video system as they jump from the simulated approach of objects, or looming stimuli. Next, in restrained animals, the electrical activity of neurons sensitive to looming, which relay information from sensory to motor centers in the locust central nervous system, will be examined in response to similar stimulus conditions. One individual neuron thought to be critical in this process, the descending contralateral motion detector (DCMD) neuron, will be studied in detail. In parallel to these neurophysiological studies, computer engineers on the project will develop a miniature digital wireless recording and transmission system able to be carried by the locust. This system will transmit up to eight channels of neuronal data from electrodes implanted in the insect's nervous system, including signals from the DCMD cell studied in the restrained locust. The small device will affixed to the back of locusts to monitor nervous activity in real time during escape jumps. In separate experiments, the muscular activity leading to the generation of jumps will be monitored as well. Taken together, this study will for the first time investigate quantitatively the relation between stimulus parameters, the activity of sensory neurons and the motor stages of a visually guided escape behavior in freely behaving animals, thus leading to an integrated understanding of the connection between its sensory and motor components. This project also has a broader imact beyond the research community. Dr. Gabbiani has worked, and will continue to work, closely with a high school science teacher in his laboratory to develop high school science curriculum modules on the neural control of behavior and the integration of computer engineering with biology. The project will also support the interdisciplinary training of several graduate students.

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).

All animals rely on the integration of sensory, postural and environmental information to generate complex motor behaviors such as swimming, playing tennis or flying. This collaborative project will study how the nervous system transforms information gathered by the senses into motor commands, based on the biomechanical properties of the muscles as well as the mechanical and environmental constraints imposed on the body by the outside world through the laws of physics. A favorable model system to study these complex aspects of behavior is the generation of collision avoidance maneuvers in flying insects, as much is known about their nervous system and the aerodynamic mechanisms underlying insect flight. The three groups that will collaborate on this project are based at Baylor College of Medicine, Rice University and the University of Arizona and will bring complementary expertise in neurophysiology, advanced computer modeling techniques, and aerodynamic engineering, respectively. This work will provide a comprehensive description of in-flight collision avoidance in response to visual threats and will thus contribute to an integrated understanding of the basis of complex sensory-motor transformations underlying behavior. The new insights that will be gathered over the course of the work could be applied to the design of real-time artificial vision systems and collision avoidance systems for various vehicles. Finally, this project will contribute to research education by allowing interested students to acquire interdisciplinary laboratory experience at the graduate as well as the undergraduate level, through various summer research programs. Students involved in the project at Baylor College of Medicine will learn how to record nervous activity from the brain of behaving animals and model its impact on behavior.

The brain regions devoted to the processing of sensory information are remarkable for their two-dimensional map-like (topographic) organization. Recent evidence suggests that this property can be maintained down to the subcellular level, in the form of topographically organized inputs onto the extended arborizations (dendrites) of single cells (neurons). The goal of this project is to identify the key principles underlying the processing of such topographic inputs in the dendrites of a prototypical neuron. The project focuses on a nerve cell that is most sensitive to objects approaching on a collision course with the animal and that is implicated in generating collision avoidance behaviors. The investigators use tools developed to study partial differential equations to determine the detailed dendritic distribution of the cell's ion channels. Next, techniques designed to reduce the complexity of mathematical models are used, as well as to simultaneously respect the topography of inputs, to extract a simplified representation of the neuron?s signal processing characteristics. This allows the investigators to characterize the role played by the neuron's dendrites in generating the responses of the neuron to objects approaching on a collision course. Particular focus is on understanding the invariance of responses to objects approaching from different directions.

The survival of all animals, including humans, critically depends on the neuronal processing of impending dangers. This project sheds light on how the brain accomplishes this feat in a particular model system ideally suited for this purpose. Mathematical tools are generated and are made available to other researchers to analyze neurons with similar properties in other contexts. Additionally, the project contributes to our basic understanding of brain function that may eventually lead to better cures for diseases affecting sensory perception. Finally, the results of this project could potentially find applications in the design of autonomous robots.

The goal of the proposal is to elucidate the neural computations carried out by the visual system to identify an impending threat and their use for the generation of collision avoidance behaviors. The proposal will develop advanced genetic, behavioral and imaging techniques to address these questions. The experimental data will be summarized in a biophysical model of the neural circuits generating collision avoidance behaviors that will be validated using the experimental data acquired during the project. The project will advance our understanding of how the visual system goes about reliably identifying a threat in the natural visual environment without reacting to irrelevant visual stimuli. The knowledge gained from the project is expected to allow the future design of efficient, neurally-inspired collision avoidance systems.

The proposed experiments will be carried out in the fruit fly Drosophila, a model system in which sophisticated genetics tools are available, including genetically encoded Ca2+ indicators and modifiers of neural activity that can be expressed in specific neural subpopulations. These tools, paired with the recent anatomical description of visual pathways at the electron microscopic level, offer the possibility of investigating how networks of neurons process information leading to visually guided escape behaviors at an unprecedented level of detail. In particular, these tools will allow (1) to carry out behavioral experiments where specific populations of neurons belonging to the visually-guided escape pathway are silenced; (2) to perform imaging experiments allowing to study the activation of the neurons belonging to the visually-guided escape pathway at all successive stages of the visual system and determine how/when the specificity for looming stimuli arises; (3) to apply localized stimuli and advanced microstimulation techniques allowing to isolate the contribution of individual photoreceptors to the processing of visual information related to looming stimuli in single neurons; (4) to develop genetic tools allowing to silence populations of neurons by using novel anion channel rhodopsins and allowing to sparsely label neurons of the pathway at two successive stages, either with an indicator of neuronal activity or with an optogenetic activator; (5) to test the functional connectivity at successive stages of the pathway using these tools in conjunction with three dimensional random access imaging; and (6) to model the neural computations carried out along the visually guided escape pathway.

Locusts are grasshoppers that can form enormous migrating swarms, once vividly recorded in ancient texts, but still occurring to this day and affecting the livelihood of one in ten people on Earth. Currently, multiple continents are experiencing locust plagues that threaten food security both locally and on a larger, potentially global, scale. What makes locusts particularly devastating is their ability to change their behavior depending on population density ? this is known as locust phase polyphenism. At low density, they are solitary and harmless grasshoppers, but at high density, they become gregarious and voracious pests that migrate. This plasticity, or variation, in behavior, appearance, and physiology is striking and how population density facilitates this change is still not fully understood. Studying the mechanism of this transformation holds the key to developing effective methods of control for this organism, ensuring food safety, and understanding how social/population pressures can fuel radical change in these animals. This undertaking will require comprehensive scientific integration across different biological disciplines to be accomplished. To address this challenge, a group of researchers has formed a cross-institutional, cross-disciplinary Biological Integration Institute ? the Behavioral Plasticity Research Institute (BPRI). Using cutting-edge technologies in research projects spanning from molecules to landscapes, the BPRI will greatly enhance our understanding of locust phase polyphenism and plasticity in other organisms. With a commitment to improving diversity, inclusion and equity, the institute will train the next generation of integrative biologists who can efficiently navigate across different disciplines. The institute will communicate groundbreaking research to the general public and the scientific community through video documentaries, symposia and workshops. The BPRI will partner with the Global Locust Initiative to translate the scientific advances to management for improving global food system sustainability.


Phenotypic plasticity ? the ability of a single genotype to produce different phenotypes in response to different environmental conditions ? is ubiquitous in nature and occurs across all scales of biological organization. To understand its mechanisms, maintenance, and evolution, complete biological integration is needed. Locust phase polyphenism represents one of the most striking examples of phenotypic plasticity. It also provides a powerful comparative system for understanding how gene expression patterns and epigenetic regulation are linked to shifts in behavior, physiology, and ecology that result in outbreaks, collective movement, and mass migration. The Behavioral Plasticity Research Institute (BPRI) will comprehensively dissect this phenomenon and use it as a model system to transform the study of phenotypic plasticity. Specifically, the BPRI will carry out ten integrative research activities, using three locust and three non-swarming grasshopper species with varying degrees of plasticity in the genus Schistocerca. The BPRI research will provide in-depth understanding of proximate mechanisms of locust phase polyphenism by generating high-quality reference genomes, complemented by tissue-specific and time-resolved transcriptomes and epigenomes, as well as CRISPR/Cas9 and reverse genetics tools to understand functional genetics. These mechanistic approaches will be integrated with organismal biology and ecology to investigate phase-associated nutritional physiology and ecological factors contributing to swarming under laboratory and field conditions. All research activities will be performed across species in a phylogeny-based comparative framework. The feedback among these activities will create synergies and lay the groundwork for the integrative study of phenotypic plasticity across model organisms from genomes to ecology and sustainability.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.