Ross M D, Chimento T, Doshay D, Cheng R
National Aeronautics and Space Administration, Ames Research Center, Moffett Field, California 94035.
Ann N Y Acad Sci. 1992 May 22;656:75-91. doi: 10.1111/j.1749-6632.1992.tb25201.x.
The macular neuroepithelium is morphologically organized as a weighted neural network for parallel distributed processing of information. The network is continuous across the striola, where some type II hair cells synapse with calyces containing type I cells with tufts of opposite directional polarities. Whether other hair cell to calyx appositions that lack synapses interact because of intercellular potassium accumulation remains an open question. A functionally important inference of macular organization is that just as arrays of hair cells communicate an entire piece of information to a nerve fiber, so do macular subarrays of nerve fibers (not single units) carry the whole coded message to the brain stem. Moreover, the size of the network subarray can expand or become more limited depending upon the strength and/or duration of the input. It is the functioning of the network and its subarrays that must be understood if we are to learn how maculas carry out their work and adapt to new environments. Simulations of functioning maculas, or subparts, based on precise morphology and known physiology are useful tools to gain insights into macular information processing. The current simulations of afferent collateral electrical activity are a prelude to development of a 3-D model. The simulations demonstrate a relationship between geometry and function, with the diameter of the stem apparently being a major determinant of electrical activity transmitted to the base in the case of collaterals with short stems. Thus, while changes in synaptic number and/or size may be an important adaptive mechanism in an altered g environment, changes in diameter of the stem is another means of altering outflow. Research on the effects of microgravity should be extremely useful in examining the validity of this and other concepts of neural adaptation, since maculas are biological linear accelerometers ideally suited to the task. Maculas are also extremely interesting to study in detail because of the richness of connectivities and submicroscopic organization they present. Many of their features are common with more complex parts of the brain. It seems possible that knowledge of the three-dimensional geometric relationships operative in a functioning macula will contribute much to the understanding of the dynamics underlying more complex behavior. Computerized approaches greatly facilitate this task and provide an objective method of analysis. It is likely that, in the end, simple rules will be found to govern optimal neural architectural organization, even at higher cognitive levels. The architecture only appears complex because we do not yet grasp its meaning.(ABSTRACT TRUNCATED AT 400 WORDS)