Optimality of a Sensory Receptor Array

Montana State University, Bozeman MT

Investigators

Abstract

An implicit hypothesis underlying much recent research in neuroscience and neuroethology is that sensory systems have evolved, through natural selection, toward optimal functional performance and/or energetic efficiency. However, it has proven extremely difficult to derive precise definitions for functional optimality and efficiency, and even more difficult to determine the nature and relative importance of different factors that might be constraining this process of optimization. A multidisciplinary group of researchers lead by Dr. Gedeon will develop a theoretical framework for defining and assessing optimality of one specific sensory system and are also carrying out experiments to assess its optimality and efficiency. The system they are studying is the cercal sensory system of the cricket, Acheta domesticus. This system functions as a low-frequency, near-field extension of the animal's auditory system, and mediates the detection, localization and identification of signals generated by predators, mates and competitors. The sense organ for this system consists of a pair of antenna-like 'cerci' at the rear of the cricket's body, each of which is covered with approximately 1000 mechanosensory hairs. Each of these hairs is attached to a single nerve cell. The group's working hypothesis is that the biomechanical and neurophysiological characteristics of these receptor organs are optimized for the sensory processing operations they mediate. The researchers will determine the extent and nature of optimization in the array of mechanosensory hairs and receptors, and will also identify specific constraints under which the optimization has taken place. For example, they will determine whether the physical structures of the hairs are matched to behaviorally relevant air-current signals and also determine if the global configuration of the ensemble of hairs on the two cerci reflects optimization with respect to sensitivity, robustness to noise, and/or to the detection of specific types of signals having particular behavioral importance, such as those from predators. They will also characterize constraints on optimization related to biomechanics, resource utilization, and efficiency of subsequent processing operations. These aims are being achieved through a combination of mathematical analysis, computer simulation, quantitative morphometric analysis of the sensory structures, and neurophysiological experiments. Graduate students in Mathematics and Neuroscience will be involved in the project, and an interdisciplinary graduate-level course is being developed that focuses on optimality in neural systems. Further, in collaboration with the American Indian Research Opportunities program at Montana State University, Native American students at the undergraduate and pre-college levels will carry out many of the experiments and associated data analysis.