Abstract
Some of the simpler invertebrates demonstrate robust and efficient features of sensory information processing, integration, and motor control. Development and analysis of computer models of the essential neural mechanisms leading to these capabilities elucidate design principles for flexible man-made remote sensing, vision, and control systems. The marine snail, Hermissenda crassicornis, is ideal for study and modeling of biological computing mechanisms because the connectivity of its visual and vestibular neuronal network has been determined in considerable detail. To extract principles of sensory integration, a computer model of the photoarray in a single Hermissenda eye is developed and analyzed. This model demonstrates 1) information processing capabilities observed in Hermissenda’s visual sensors, and 2) the importance of heterogeneity in the efficient and robust operation of biological networks.
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References
Alkon, D.L. 1987. Memory Traces in the Brain, Cambridge Press, Cambridge, MA.
Alkon, D.L., Fuortes, M.G.F. 1972. Responses of Photoreceptors in Hermissenda. J. Gen. Physiol, 60, 631–649.
Blackwell, K.T., Vogl T.P., Hyman S.D., Barbour G.S., Alkon D.L. 1992. A new approach to hand-written character recognition. Pattern Recog., 25, 655–666.
Detwiler P.B. 1976. Multiple Light-Evoked Conductance Changes in the Photoreceptor of Hermissenda crassicornis. J. Physiol, 256, 691–708.
Farley, J., W. Richards, and L. Grover. 1990. Associative Learning Changes Intrinsic to Hermissenda Type A Phtoreceptors. Behav.Neurosci, 104, 135–152.
Sakakibara, M., Alkon, D.L., Neary, J.T., Heldman, E., Gould, R. 1986. Inositol triphosphate regulation of photoreceptor membrane currents. Biophys. J., 50,797–803.
Stensaas, L.J., S.S. Stensaas, and O. Tmjillo-Cenoz. 1969. Same morphological Aspects of the Visual System of Hermissenda crassicornis. J. Ultrastruc. Res, 27, 510.
Werness S.A., Fay S.D., Blackwell K.T., Vogl T.P., Alkon D.L. 1992. Associative Learning in a Network Model of Hermissenda crassicornis. I. Theory. Biological Cybernetics, 68, 125–133.
Werness S.A., Fay S.D., Blackwell K.T., Vogl T.P., Alkon D.L. 1993. Associative Learning in a Network Model of Hermissenda crassicornis. II. Experiments. Biol. Cybern., 69, 19–23.
Wilson M.A., Bhalla U.S., Uhley J.D., Bower J.M. 1989. GENESIS: A System for Simulating Neural Networks. In Advances in Neural Information Processing Systems. D.S. Touretzky, ed., Morgan Kaufman. San Mateo, CA. pp. 485–492.
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© 1994 Springer Science+Business Media New York
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Werness, S.A., Fay, D., Blackwell, K.T., Vogl, T.P., Alkon, D.L. (1994). Computational Hermissenda Photoarray Model. In: Eeckman, F.H. (eds) Computation in Neurons and Neural Systems. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-2714-5_13
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DOI: https://doi.org/10.1007/978-1-4615-2714-5_13
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