All cells and organisms make analog measurements of their environment and process these measurements to produce adaptive responses. We are interested in determining what computations are involved in this processing: i.e. what is the software and how is it implemented? i.e. what is the hardware? Our main approach is to develop novel instrumentation and methods to measure and analyze behavioural responses at the motor output level. This systems-level approach helps us detail the molecular, cellular, and neuronal components involved in these pathways, and also allow us to ask questions that span a number of traditional scientific boundaries such as sensory biology, systems neuroscience, theoretical neuroscience, and sensory ecology. Some of our projects are described below. [Last updated 2013]
Measuring patterns of motion in C. elegans
We have developed a quantitative and principled analysis of motor behavior of C. elegans as it freely crawls on an agar plate. Behavioural data come from a custom built tracking microscope that captures and follows the motions of single worms crawling on agar for long time periods. While previous work has described worm movements with ad hoc collections of metrics (e.g. oscillation frequency, center of mass, orientation, etc.), we extract the skeleton of the shape as a head-to-tail ordered array of tangent angles sampled along the curve to explore the full space of shapes, making no a priori assumptions about what aspects of shape are important. Using principal components analysis we show that the shape space is remarkably low dimensional, with four dimensions accounting for ~95% of the shape variance. Given this low dimensional description we can analyze the dynamics of movement as a time series for a small number of variables. Two dimensions exhibit a limit cycle oscillation, which corresponds to sinuous crawling movements. The displacements along the other two dimensions corresponds stereotyped movements such as turns, reversals, and omega turns.
Measuring and perturbing neurons in C. elegans
To study the neuronal correlates of behavior, we use a variety of techniques to measure and perturb the activity of C. elegans neurons. Neurons can be ablated (e.g. killed) using pulsed laser light from a dye laser or a Ti:Sapphire laser. Signals from neurons can be measured using fluorscence microscopy using genetically encoded calcium indicators like GCamP or Cameleon. Neurons can be activated directly using channelrhodopsin. Neurons can also be developmentally ablated or functionally silenced using a variety of genetic techniques. The goal here is to correlate these neuronal perturbations with our behavior measurements to understand how these behaviors are implemented at the neuronal level.
High-content phenotyping of sensorimotor behavior
C. elegans is a simple organism with only about 300 neurons, but it is capable of complex behavior. For example when a worm is faced with a noxious stimulus, it will undergo a series of stereotyped locomotion patterns to reflexively escape this stimulus. The initial response is typically a reversal, followed by a deep bending turn, ending with fast forward motion. How does the worm string together behavioral modules to provide a "complex" locomotion output to sensory inputs? What parameters can be controlled by the worm? What are the genetic and neuronal correlates to the behavior of these modules? To study this quantitatively we have developed a infrared laser assay that allows us to precisely stimuluate worms with a thermal noxious stimulus and quantify the behavioral output comprehensively using machine vision techniques. We find that many features of the locomotion behavior scale with the power of the stimulus such as the behavioral module duration, the speed, and latency. We also see a shift from a noisy, stochastic response, to a clean, deterministic response as the laser power shifts from low to high. This phenotyping is information rich, shows graduated changes, and can uncover modulatory changes in the behavior as a function of small genetic, neuronal, and environmental perturbations.
The nematode, C. elegans is thermotactic and prefers the temperature at which it was cultivated. When placed on agar plates in thermal gradients, worms will migrate toward their preferred temperature and near this temperature they will track isotherms with surprising accuracy (with 0.1C). The thermal preference of worms is plastic. If placed at a different temperature in the presence of food, worms will acquire a new thermal preference in about 4 hours. By applying defined thermal stimuli to single worms using an IR laser and then following the behavior of the worm in time with the worm tracker, we are studying various components of the thermosensory behavior of C. elegans, including the impulse response, isothermal behavior, and general computational strategy.
C. elegans foraging
What is the statistical foraging strategy of C. elegans? A common model to describe the foraging movements of organisms is the random walk, in which the duration and direction of the forward movement of the organism is chosen randomly. A variation on this strategy allows for taxis. For example, an organism can perform chemotaxis - biasing its motion along a chemical gradient towards an attractant or away from a repellant - by correlating the duration of forward movements with the changes in sensory input. In the absence of any such sensory stimuli, an important question is what statistical strategy will be the most efficient? Or more specifically, from what distribution should the organism choose the duration of its forward movements? It has been suggested that for randomly distributed targets it is more efficient to perform a Levy walk than a Brownian walk. A Levy walk is a random walk in which the run lengths have a power-law distribution( P(l)~l^(-μ) with 1 < μ < 3 ), and a Brownian walk is a random walk in which the run lengths have an normal distribution (μ > 3). More specifically it has been shown that for sparsely distributed targets, the optimal value of μ is 2. It is known that the turning frequency of C. elegans decreases as a function of time away from food. In order to quantify this behavior we are using the tracking microscope to measure trajectories of worms freely crawling on agar plates. We can show that C. elegans in the absence of food performs a Brownian walk initially (μ > 3) and shifts to a Levy walk (μ ~ 2) after a period of about 15 minutes. Through Monte Carlo simulations, we show that this behavior is in fact more efficient than either a Brownian walk or Levy walk alone. We also show that the statistical strategy is under genetic control. Dopamine receptor mutants, dop-2, show Brownian behavior at early and late times, while dop-3 mutants show Levy walk behavior at early and late times. We are continuing to explore how this statistical control of strategy is controlled through hormonal neurotransmitter systems of the worm.
C. elegans mechanobiology
Animals the size of C. elegans live their lives at low Reynolds number. In a world with no inertia, these micro-swimmers and crawlers experience forces which are governed by vastly different physics from what we feel at our scale. When crawling on wet surfaces, for example, surface tension significantly overpowers gravity. How hard must organisms work in order to overcome these forces, and how do forces exerted by the environment affect the movement strategy and behaviour? Does the organism adopt an optimal strategy, or is it limited by bending its own body? Additionally, how does C. elegans sense external forces? The neural connectome for the worm is mapped, but what is the receptive field and the dynamics of the neurons involved? We have developed a micropipette platform in collaboration with the Dalnoki-veress lab (McMaster University) that allows us to lightly hold freely-behaving subjects and either administer or measure micronewton forces. This platform allows us to probe the organism's responses to very light touch stimuli and to measure the viscous drag which must be overcome in crawling locomotion.
E. coli chemotaxis and thermotaxisIn addition to being a model organism for understanding chemosensation, E. coli is also thermotactic. Using a tethered cell assay where the bacterium is tethered to a glass coverslip by a single flagellar motor, we can measure the behavioral state of single bacteria in time. By applying well-defined thermal stimuli we can measure the thermal responses of single bacteria. What is the thermotaxis strategy of E. coli? What does the thermosensory system of E. coli tell us about the evolution of early thermal sensation? How does the this system remain robust across such a wide range of temperatures? We have developed a thermotaxis assay using PDMS devices in conjunction with the Groisman lab (UCSD) to perform experiments to ask these questions.