General

We are applying biophysical and quantitative methods to the analysis of locomotion and sensory behavior in simple organisms. Our approach is to develop new instrumentation and techniques that allow us to measure and analyze behavioral responses at the motor output level. This systems-level approach will help us detail the molecular, cellular, and neuronal components involved in these pathways, and allows 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.

 

Measuring patterns of motion in C. elegans

We are developing a quantitative and principled analysis of motor behavior of C. elegans as it freely crawls on an agar plate. Behavioral data come from a custom built tracking microscope that allows us to capture and follow 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.

 

C. elegans sensorimotor analysis of thermotaxis

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 (within ~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 its thermosensory behavior, including the impulse response and isothermal sensorimotor program.

 

C. elegans thermal nociception

C. elegans responds to noxious mechanical, chemical and thermal stimuli with a stereotypical withdrawal or escape response. The thermal response in particular is interesting because it has been shown that C. elegans will react to laser heating with a response that is similar to nociception in higher organisms (Wittenburg, 1999). We have extended the Wittenburg study using a computer-controlled, semi-automated behavioral screen to show modulatory changes in the thermal pain response. In our assay, entire worms are locally heated with an IR laser as they crawl freely on an agar plate, and their motions are captured and measured by custom-written machine vision programs. This behavioral quantification gives us a finer description of the pain response than has been shown previously, and in particular, demonstrates that the pain response is complex and multi-faceted. For example, the crawling speed of the worm as it reacts to thermal pain is a measurement rich with features. This response to thermal pain can be deconstructed into separate components at different time scales (e.g. early latency, maximum speed, long-term enhanced speed). By observing changes in these features, we have shown that glutamate and neuropeptide mutants are defective in their pain response to different ranges of thermal intensity. Glutamate mutants are defective to low-power thermal stimuli (but not so low as to be thermosensation) and the neuropeptide mutants are defective to high-power thermal stimuli. The higher-resolution behavioral measurements have already proven to give a finer genetic dissection of the pain pathway. It is likely that we will be able to discover new genetic, neuronal, and network components involved in C. elegans pain transduction.

 

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) µ l-μ , for large l, 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.

 

E. coli thermotaxis

E. coli is also thermotactic---they will aggregate at a preferred temperature. These bacteria swim through fluids by controlling the rotation of helical flagellar motors that are randomly distributed on their body. We can monitor the motor behavior of single cells by tethering them to a glass coverslip via a single flagellar motor. By applying well-defined thermal stimuli we can measure the thermal responses of single bacteria in real time. Some of the questions about the thermosensory system we are asking: What is the thermotaxis strategy of E. coli? What can 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? What is the system's thermal sensitivity and does it approach physical limits?