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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.

Robot-Embodied Neuronal Networks as an Interactive Model of Learning

“…Many studies have resorted to artificial networks, which provide an environment that can readily and precisely be manipulated, but retain the limitation that they are not comprised of actual neurons. Previous studies have utilized similar ex vivo networks to operate a small model vehicle within a closed environment and observed network firing patterns in response to physical barriers [25,26]. The current system expands upon this "reactive" earlier embodiment of neuronal networks in our system monitored active tracking of a target versus passive response.…”

“…However, networks established from dissociated neurons as used herein can be maintained for several months (and longer under optimal conditions) [25]. Networks generated herein have no architectural restrictions during axonogenesis, which therefore fosters nearest-neighbor connections.…”

“…A more robust and "real-world" approach towards activity and responsiveness of ex vivo neuronal networks has been to interface them with robotics [25,26]. Herein, we provided ex vivo neuronal networks with sensory input using a digital video camera, and converting resultant network signaling to impulses capable of operating a robotic arm.…”

Survey and evaluation of neural computation models for bio-integrated systems

“…These systems, called Bio-Integrated Systems (BISs), have started to raise the attention of researchers from diverse disciplines such as robotics [4,5] and communication networks [6][7][8]. An interesting step toward BISs consists in interfacing neural networks with nonbiological system controllers by culturing neurons on an electrode grid surface, such as a MicroElectrode Array (MEA) that is capable to both stimulate neurons and record their firing patterns [9]. Example of state-of-the-art achievements with regard to interfacing the living cultures with nonbiological systems would be the closed-loop stimulus-response system developed by Potter et al [10], the robot with a biological brain developed by Warwick et al [4] as well as the Lego Mindstorm robot created by Shahaf et al [11] in which data produced by ultrasonic sensors, i.e.…”

Natural Signal Classification by Neural Cliques and Phase-Locked Attractors

“…Recently, T. Natschläger, W. However, by this simplification and by emphasizing that cortical networks, rather than individual neurons, should be viewed as basic computational units, the LSM computational framework suggests a radically different paradigm for neural computation. Moreover, the LSM framework enables the application of real cortical networks in real-world tasks by embodiment of cortical neural culture in artificial environments [5].…”