Controlling a mobile robot with a biological brain

The intelligent controlling mechanism of a typical mobile robot is usually a computer system. Some recent research is ongoing in which biological neurons are being cultured and trained to act as the brain of an interactive real world robot–thereby either completely replacing, or operating in a cooperative fashion with, a computer system. Studying such hybrid systems can provide distinct insights into the operation of biological neural structures, and therefore, such research has immediate medical implications as well as enormous potential in robotics. The main aim of the research is to assess the computational and learning capacity of dissociated cultured neuronal networks. A hybrid system incorporating closed-loop control of a mobile robot by a dissociated culture of neurons has been created. The system is flexible and allows for closed-loop operation, either with hardware robot or its software simulation. The paper provides an overview of the problem area, gives an idea of the breadth of present ongoing research, establises a new system architecture and, as an example, reports on the results of conducted experiments with real-life robots. Defence Science Journal, 2010, 60(1), pp.5-14 , DOI:http://dx.doi.org/10.14429/dsj.60.11

[1]  M S Lewicki,et al.  A review of methods for spike sorting: the detection and classification of neural action potentials. , 1998, Network.

[2]  Paul Marks.  Rat-brained robots take their first steps , 2008 .

[3]  Steve M. Potter,et al.  Precisely timed spatiotemporal patterns of neural activity in dissociated cortical cultures , 2007, Neuroscience.

[4]  Michela Chiappalone,et al.  Computational analysis in vitro: dynamics and plasticity of a neuro-robotic system , 2005, Journal of neural engineering.

[5]  Larry Bull,et al.  Initial results from the use of learning classifier systems to control in vitro neuronal networks , 2007, GECCO '07.

[6]  Kevin Warwick,et al.  Emergent Behaviour in Autonomous Robots , 2004 .

[7]  G Shahaf,et al.  Learning in Networks of Cortical Neurons , 2001, The Journal of Neuroscience.

[8]  Yan Wu,et al.  Multisite two-photon imaging of neurons on multielectrode arrays , 2001, SPIE BiOS.

[9]  Shennan A. Weiss,et al.  Rat navigation guided by remote control , 2002 .

[10]  Slawomir J. Nasuto,et al.  Robust methodology for the study of cultured neuronal networks On MEAs , 2008 .

[11]  Steve M. Potter,et al.  Multi-site two-photon imaging of neurons on multi-electrode arrays , 2001 .

[12]  Sergio Martinoia,et al.  Coding and decoding of information in a bi-directional neural interface , 2005, Neurocomputing.

[13]  J. Pine.  Recording action potentials from cultured neurons with extracellular microcircuit electrodes , 1980, Journal of Neuroscience Methods.

[14]  Steve M. Potter,et al.  A new approach to neural cell culture for long-term studies , 2001, Journal of Neuroscience Methods.

[15]  M. Igarashi,et al.  Decreased synaptic density in aged brains and its prevention by rearing under enriched environment as revealed by synaptophysin contents , 1994, Journal of neuroscience research.

[16]  Guenter W. Gross,et al.  DYNAMICS OF BURST PATTERNS GENERATED BY MONOLAYER NETWORKS IN CULTURE , 1993 .

[17]  H. Robinson,et al.  Spontaneous periodic synchronized bursting during formation of mature patterns of connections in cortical cultures , 1996, Neuroscience Letters.

[18]  Daniel A. Wagenaar,et al.  The Neurally Controlled Animat: Biological Brains Acting with Simulated Bodies , 2001, Auton. Robots.

[19]  Isao Shimoyama,et al.  Locomotion control of a bio-robotic system via electric stimulation , 1997, Proceedings of the 1997 IEEE/RSJ International Conference on Intelligent Robot and Systems. Innovative Robotics for Real-World Applications. IROS '97.

[20]  Steve M. Potter,et al.  Removing Some 'A' from AI: Embodied Cultured Networks , 2003, Embodied Artificial Intelligence.

[21]  Kevin Warwick,et al.  Museum robots: multi-robot systems for public exhibition , 2004 .

[22]  T.B. DeMarse,et al.  MeaBench: A toolset for multi-electrode data acquisition and on-line analysis , 2005, Conference Proceedings. 2nd International IEEE EMBS Conference on Neural Engineering, 2005..

[23]  Sergio Martinoia,et al.  Connecting Neurons to a Mobile Robot: An In Vitro Bidirectional Neural Interface , 2007, Comput. Intell. Neurosci..

[24]  Ferdinando A. Mussa-Ivaldi,et al.  Connecting Brains to Robots: An Artificial Body for Studying the Computational Properties of Neural Tissues , 2000, Artificial Life.

[25]  Michael E. Hasselmo,et al.  Acetylcholine and Learning in a Cortical Associative Memory , 1993, Neural Computation.

[26]  T.B. DeMarse,et al.  Adaptive flight control with living neuronal networks on microelectrode arrays , 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..

[27]  G. Loeb,et al.  A miniature microelectrode array to monitor the bioelectric activity of cultured cells. , 1972, Experimental cell research.

[28]  Luca Berdondini,et al.  Network Dynamics and Synchronous Activity in cultured Cortical Neurons , 2007, Int. J. Neural Syst..

[29]  A. Habets,et al.  Development in the absence of spontaneous bioelectric activity results in increased stereotyped burst firing in cultures of dissociated cerebral cortex , 2004, Experimental Brain Research.

[30]  G. Gross.  Simultaneous Single Unit Recording in vitro with a Photoetched Laser Deinsulated Gold Multimicroelectrode Surface , 1979, IEEE Transactions on Biomedical Engineering.

[31]  Miguel A. L. Nicolelis,et al.  Real-time control of a robot arm using simultaneously recorded neurons in the motor cortex , 1999, Nature Neuroscience.