Stephen L. Holtz, B.S. - US grants

7. Project Summary / Abstract Peripheral sensory systems collect information about the environment, and they also extract information about specific behaviorally-relevant stimulus features. The task of mechanosensory peripheral neurons is to encode and extract information about the mechanical forces acting on the body. We do not fully understand the mechanisms or coding principles underlying peripheral mechanosensory codes. In this project, I will study a tractable experimental model for this problem ? namely, the largest mechanosensory organ in Drosophila, Johston?s Organ. Johnston?s organ encodes antennal rotations driven by touch, wind, self-motion, and sound. Thus, this organ has somatosensory, vestibular, and auditory functions. It contains ~500 neurons (Johnston?s Organ Neurons or JONs) which are responsible for decomposing the antenna?s rotational movements into a neural code. The broad goal of this study is to determine how these 500 neurons work together as an ensemble to encode specific features of antennal motion. In order to measure JON spiking activity during antennal stimulation, we have developed several innovative techniques. Specifically, we will use a combination of electrophysiology (to obtain single-spike resolution), and genetically encoded voltage indicators (to obtain single-cell resolution). Because Drosophila nervous systems are highly stereotyped, and because we have a large set of transgenic lines targeting different JON subsets, we will be able to assemble a picture of the entire coding ensemble by sequentially sampling many cells, and by tagging these cells using genetic markers and anatomical landmarks. Ultimately, this project will yield generalizable mathematical models describing JON tuning profiles. These models will concisely describe the coding properties of the JON ensemble. They will also allow us to generate new testable hypotheses about the mechanisms that specify JON mechanical tuning, as well as new conceptual insights into the specializations and constraints that characterize mechnosensory codes in general. These insights into mechanosensory coding will have many practical applications. For example, work on the insect mechanosensory system has produced improvements in artificial hearing aids. Moreover, basic research into neural coding has fueled innovations in artificial proprioceptive devices and vestibular devices.