Ellengene H. Peterson, Ph.D.

     All vertebrates rely on the vestibular system to maintain balance and clear vision during normal behavior. Yet in spite of its central role in behavior, the vestibular system is one of our most poorly understood senses. At its most basic level, the vestibular system can be thought of as a pair of three-neuron arcs that link sensory receptors in the inner ear (hair cells in ampullae and otolith organs) with motor neurons that control neck and limb muscles or eye muscles. These three-neuron arcs provide simple but powerful experimental models for analyzing sensorimotor trans-formations and motor learning.

     Our experiments use an in vitro whole-brain preparation that includes the inner ear, brainstem, and neck musculature. This preparation allows us to study intact neurons and neural circuits that transform sensory signals into motor commands.   Current studies focus on two subjects. (1) We analyze the neuronal circuits that stabilize posture and gaze using experimental electron microscopy and light microscopy of anatomically and physiologically characterized neurons. (2) We use light and electron microscopy, computer models, and experimental tests of hair cell mechanics to understand how vestibular hair cells detect head movement.

Selected References:

• Fontilla, M.F. and E.H. Peterson (2000) Kinocilia heights on utricular hair cells. Hearing Research 145:8-16.

• Barrett, M.C., E.H.Peterson, and J.W. Grant (1999) Extrinsic Fabry-Perot Interferometer for measuring the stiffness of ciliary bundles on hair cells. IEEE Transactions in Biomedical Engineering 46: 331-339.

• E.H. Peterson (1998) Are there parallel channels in the vestibular nerve? News in Physiological Sciences 13: 194-201.

• Callister, R.J., E.H. Peterson, and A.M. Brichta (1999) Neuromuscular strategies underlying ballistic movements. Progress in Brain Research 123:233-243.

• E.H. Peterson, J. C. Cotton, and J.W. Grant (1996) Structural variation in ciliary bundles of posterior canal: Quantitative anatomy and computational analysis. Ann. N.Y. Acad. Sci. 781: 85-102.