Abstract
The brain is perhaps the most advanced and robust computation system known. We are creating a method to study how information is processed and encoded in living cultured neuronal networks by interfacing them to a computer-generated animal, the Neurally-Controlled Animat, within a virtual world. Cortical neurons from rats are dissociated and cultured on a surface containing a grid of electrodes (multi-electrode arrays, or MEAs) capable of both recording and stimulating neural activity. Distributed patterns of neural activity are used to control the behavior of the Animat in a simulated environment. The computer acts as its sensory system providing electrical feedback to the network about the Animat's movement within its environment. Changes in the Animat's behavior due to interaction with its surroundings are studied in concert with the biological processes (e.g., neural plasticity) that produced those changes, to understand how information is processed and encoded within a living neural network. Thus, we have created a hybrid real-time processing engine and control system that consists of living, electronic, and simulated components. Eventually this approach may be applied to controlling robotic devices, or lead to better real-time silicon-based information processing and control algorithms that are fault tolerant and can repair themselves.
Similar content being viewed by others
References
Bi, G.Q. and Poo, M.M. 1999. Distributed synaptic modification in neural networks induced by patterned stimulation. Letters to Nature, 401:792–796.
Chapin, J.K., Moxon, K.A., Markowitz, R.S., and Nicolelis, M.A.L. 1999. Real-time control of a robot arm using simultaneously recorded neurons in the motor cortex. Nature Neuroscience, 2:664–670.
Georgopoulos, A.P., Schwartz, A.B., and Kettner, R.E. 1986. Neuronal population coding of movement direction. Science, 233:1416–1419.
Gross, G.W. 1979. Simultaneous single unit recording in vitro with a photoetched laser deinsulated gold multimicroelectrode surface. IEEE Transactions on Biomedical Engineering, 26:273–279.
Gross, G.W., Rhoades, B.K., and Kowalski, J.K. 1993. Dynamics of burst patterns generated by monolayer networks in culture. Neurobionics: An Interdisciplinary Approach to Substitute Impaired Functions of the Human Nervous System, H.W. Bothe, M. Samii, and R. Eckmiller (Eds.), Amsterdam: North-Holland, pp. 89–121.
Jimbo, Y., Tateno, T., and Robinson, H.P.C. 1999. Simultaneous induction of pathway-specific potentiation and depression in networks of cortical neurons. Biophysical Journal, 76:670–678.
Kamioka, H., Maeda, E., Jimbo, Y., Robinson, H.P.C., and Kawana, A. 1996. Spontaneous periodic synchronized bursting during the formation of mature patterns of connections in cortical neurons. Neuroscience Letters, 206:109–112.
Nicolelis, M.A.L., Ghazanfar, A.A., Stambaugh, C.R., Oliveira, L.M.O., Laubach, M., Chapin, J.K., Nelson, R.J., and Kaas, J.H. 1998. Simultaneous encoding of tactile information by three primate cortical areas. Nature Neuroscience, 1:621–630.
Pine, J. 1980. Recording action potentials from cultured neurons with extracellular microcircuit electrodes. Journal of Neuroscience Methods, 2:19–31.
Potter, S.M. 2000. Two-photon microscopy for 4D imaging of living neurons. In Imaging Neurons: A Laboratory Manual, R. Yuste, F. Lanni, and A. Konnerth (Eds.), CSHL Press: Cold Spring Harbor, pp. 20.1–20.16.A.
Potter, S.M. 2001. Distributed processing in cultured neuronal networks. In Progress in Brain Research: Advances in Neural Population Coding, Nicolelis, M.A.L (Ed.), Vol. 130, Amsterdam: Elsevier, pp. 49–62.
Potter, S.M. and DeMarse, T.B. 2001. A new approach to neural cell culture for long-term studies. J. Neurosci. Methods, 110:17–24.
Potter, S.M., Lukina, N., Longmuir, K.J., and Wu, Y. 2001. Multisite two-photon imaging of neurons on multi-electrode arrays. In SPIE Proceedings, 4262:104–110.
Potter, S.M., Mart, A.N., and Pine, J. 1997. High-speed CCD movie camera with random pixel selection, for neurobiology research. In SPIE Proceedings, 2869:243–253.
Tateno, T. and Jimbo, Y. 1999. Activity-dependent enhancement in the reliability of correlated spike timings in cultured cortical neurons. Biological Cybernetics, 80:45–55.
Thomas, C.A., Springer, P.A., Loeb, G.E., Berwald-Netter, Y., and Okun, L.M. 1972. A miniature microelectrode array to monitor the bioelectric activity of cultured cells. Exp. Cell Res., 74:61–66.
Watanabe, S., Jimbo, Y., Kamioka, H., Kirino, Y., and Kawana, A. 1996. Development of low magnesium-induced spontaneous synchronized bursting and GABAergic modulation in cultured rat neocortical neurons. Neuroscience Letters, 210:41–44.
Wessberg, J., Stambaugh, C.R., Kralik, J.D., Beck, P.D., Laubach, M., Chapin, J.K., Kim, J., Biggs, J., Srinivasan, M.A., and Nicolelis, M.A.L. 2000. Real-time prediction of hand trajectory by ensembles of cortical neurons in primates. Nature, 408:361–365.
Wilson, S.W. 1985. Knowledge growth in an artificial animal. In Proceedings of the First International Conference on Genetic Algorithms and their Applications, Grefenstette (Ed.), Lawrence Erlbaum Associates: Hillsdale, NJ. pp. 16–23.
Wilson, S.W. 1987. Classifier systems and the animat problem. Machine Learning, 2:199–228.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
DeMarse, T.B., Wagenaar, D.A., Blau, A.W. et al. The Neurally Controlled Animat: Biological Brains Acting with Simulated Bodies. Autonomous Robots 11, 305–310 (2001). https://doi.org/10.1023/A:1012407611130
Issue Date:
DOI: https://doi.org/10.1023/A:1012407611130