Understanding how the collective activity of neurons gives rise to behavior is one of the great challenges for biology in this century. This task is especially daunting because it is difficult both to quantify behavior precisely and to monitor the activity of neurons relevant to a particular behavior. To help meet this challenge, we develop new instruments and techniques for behavioral analysis and neural recording, and apply them to the model organism with the simplest and best-characterized nervous system, Caenorhabditis elegans. We hope that this will allow us to develop key insights into the control of behavior by neural circuits and reveal the genes required for the function of these circuits. It is our expectation that these lessons can then be applied to larger organisms, where the technical challenges are greater.
We currently focus on two areas that are essential for a detailed quantitative understanding of the relationship between neuronal activity and behavior in C. elegans.
Advanced Volumetric Microscopy
Adult C. elegans have only 302 neurons, half of which are located in the animal's head. To relate behavior to neural activity, we must monitor the activity of these neurons. We are developing hardware and software that allow us to rapidly construct three-dimensional movies of the worm's head. By using fluorescent probes that indicate neuronal activity, we can simultaneously monitor and quantify the activity of a large number of neurons. Due to the small size of the organism and short exposure times, the primary technical challenge lies in capturing enough photons from the sample to obtain an accurate report of neuronal activity. We hope to utilize advanced optical techniques developed by the labs of Eric Betzig, Mats Gustafsson, and Charles Shank (all now at Janelia Farm Research Campus) as they become available. Presently, we illuminate the worm's brain with a thin sheet of light that spares all but the in-focus portion of the sample from strong illumination, and sweep this sheet through the worm's head while imaging with fast and sensitive cameras.
When the imaging system is complete, we should be able to monitor at least a couple of dozen neurons simultaneously. At that point, we can begin to ask questions about the neural basis of worm behavior and hope to find comprehensive answers. For instance, when a worm is exposed to food, what are the responses of all of its sensory neurons? This question could be directly answered by recording the activity of all the sensory neurons; the importance of each activity pattern for food-seeking behavior could then be probed by altering the activity of the neurons one at a time. This style of experiment should allow us to build up a comprehensive picture of neural activity in the worm, from which we hope to uncover computational principles used by small neural circuits.
Population-wide Behavioral Quantification
The behavior of individual worms can be quantified by computer tracking systems that follow individual animals as they move and behave. Behavior is often variable, however, so it is necessary to collect statistics from a population of dozens of individuals to gain an accurate picture of behavior. We therefore have built a tracking system that simultaneously monitors dozens of worms and automatically analyzes their behavior. Because this method is so much faster than the standard semiautomated single-worm analysis methods, we are able to screen thousands of lines of potentially mutant worms for abnormal behavior. Initially, in collaboration with Catharine Rankin (University of British Columbia), we are identifying genes specifically involved in habituating to and recovering from repeated taps. This simple mode of learning—decreasing a response to a repeated (yet nonhazardous) stimulus—is widespread throughout nervous systems of all animals, so we expect to find new genes that play important roles in the molecular mechanisms of learning.
