Vitroid - a robot with link between living neuronal network in vitro and robot body (original) (raw)

A robust pattern of neuronal response to outer phenomena in "Vitroid", the hybrid neuro-robot

2008

Rat hippocampal neurons reorganized a complex networks on microelectrodes array dish. The living neuronal network can distinguish patterns of action potentials evoked by different inputs, suggesting that a cultured neuronal network can represent particular states as symbols. A neuro-robot-hybrid system with living neuronal network and miniature moving robot was developed. We use a Khepera II robot for interfacing with a living neuronal network and the outer world and succeeded in performing collision avoidance behavior with premised control rule sets. Using self-tuning fuzzy reasoning, we associated a distinct spatial pattern of electrical activity with a particular phenomenon in the outside of the culture dish. The particular relationship between network activity and outer phenomenon was performed by control rules of electrical stimulation to the neuronal network, responding to outer phenomenon, while a spatio -temporal patterns of neuronal activity were linked to output devices by...

Vitroid – the robot system with an interface between a living neuronal network and outer world

International Journal of Mechatronics and Manufacturing Systems, 2011

We have developed a neuro-robot-hybrid system using a living neuronal network and a miniature moving robot. The living network of rat hippocampal neurons can distinguish patterns of action potentials evoked by different inputs, suggesting that a cultured neuronal network can represent particular states as symbols. We used a Khepera II robot and a robot made using a LEGO mindstorm NXT kit to interface with a living neuronal network and the outer world. We call the system 'vitroid'. Vitroid has living neurons, a robot body, and direct coupling controllers to interface the neurons with the robot. Vitroid was able to perform obstacle avoidance behaviour with premised control rule sets.

Neurorobot Vitroid — A living test model for embodiment brain research

One of effective approaches to problems of conventional artificial intelligence is "embodied cognitive science". To realize an embodiment of a cultured living neuronal circuit, we provided cultured neurons with a body of a miniature-moving robot. The aim of this neuro-robot system is preparing a testing environment of the suitable relationship between activity of living neuronal network (LNN) and phenomena in outside world. We call our neuro-robot system as ”Vitroid", meaning a system as a kind of a “test tube” for cognitive agent made by living component. We have investigated whether the Vitroid with various algorithms for linking neurons and outer world can be embedded a certain a priori behavior, and elucidated the modification of network dynamics induced by robot behaviors. We have developed Vitroid with simplified fuzzy reasoning, and a weighted averaging of selected electrode activity. Both algorithms for linking induced the decrease of standard deviation of the...

Interaction and Intelligence in Living Neuronal Networks Connected to Moving Robot

2006

The temporal patterns of spontaneous action potentials are analyzed, using the multi-site recording system for extracellular potentials of neurons and the living neuronal networks cultured on a 2-dimensional electrode arrays. We carried out the system integration for Khepera II robot and living neuronal network. We call the system as "biomodeling system". Our goal is reconstruction of the neuronal network, which can process "thinking" in the dissociated culture system.

Interaction and intelligence in living neuronal networks interfaced with moving robot

2006

Neurons form complex networks and it seems that the living neuronal network can perform certain type of information processing. We are interested in intelligence autonomously formed in vitro. The most important features of the two-dimensional culture neural network are that it is a system in which the information processing is autonomously carries out. We reported previously that the functional connections were dynamically modified by synaptic potentiation and the process may be required for reorganization of the functional group of neurons. Such neuron assemblies are critical for information processing in brain. Certain types of feedback stimulation caused suppression of spontaneous network electrical activities and drastic re-organization of functional connections between neurons, when these activities are initially almost synchronized. The result suggests that neurons in dissociated culture autonomously re-organized their functional neuronal networks interacted with their environment. The spatio-temporal pattern of activity in the networks may be a reflection of their external environment. We also interfaced the cultured neuronal network with moving robot. The planar microelectrodes can be used for detecting neuronal electrical signals from the living neuronal network cultured on a 2-dimensional electrode array. The speed of actuators of moving robot was determined by these detected signals. Our goal is reconstruction of the neural network, which can process "thinking" in the dissociated culture system.

Controlling a Mobile Robot with a Biological Brain

Defence Science Journal, 2010

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 robotthereby 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.

Biomodeling System - Interaction Between Living Neuronal Networks and the Outer World

2007

Rat hippocampal neurons reorganized into complex networks in a culture dish with 64 planar microelectrodes and the electrical activity of neurons were recorded from individual sites. Multi-site recording system for extracellular action potentials was used for recording the activity of living neuronal networks and for applying input from the outer world to the network. The living neuronal network was able to distinguish among patterns of evoked action potentials based on different input, suggesting that the living neuronal network can express several pattern independently, meaning that it has fundamental mechanisms for intelligent information processing. We are developing a "biomodeling system," in which a living neuronal network is connected to a moving robot with premised control rules corresponding to a genetically provided interface of neuronal networks to peripheral systems. Premised rules are described in fuzzy logic and the robot can generate instinctive behavior, avoiding collision. Sensor input from the robot body was sent to a neuronal network, and the robot moved based on commands from the living neuronal network. This is a good modeling system to analyze interaction between biological information processing and electrical devices.

Robot-Embodied Neuronal Networks as an Interactive Model of Learning

The open neurology journal, 2017

The reductionist approach of neuronal cell culture has been useful for analyses of synaptic signaling. Murine cortical neurons in culture spontaneously form an ex vivo network capable of transmitting complex signals, and have been useful for analyses of several fundamental aspects of neuronal development hitherto difficult to clarify in situ. However, these networks lack the ability to receive and respond to sensory input from the environment as do neurons in vivo. Establishment of these networks in culture chambers containing multi-electrode arrays allows recording of synaptic activity as well as stimulation. This article describes the embodiment of ex vivo neuronal networks neurons in a closed-loop cybernetic system, consisting of digitized video signals as sensory input and a robot arm as motor output. In this system, the neuronal network essentially functions as a simple central nervous system. This embodied network displays the ability to track a target in a naturalistic enviro...

Development of artificial cognitive systems based on models of the brain of living organisms

Russian Journal of Genetics: Applied Research, 2015

Despite the continuous growth of our knowledge of the functioning of nervous systems and sophisticated features of the neuroanatomy and neurophysiology of various animal species, the basic mech anisms that provide for such properties as the ability to learn, use memory, recognize patterns, and learn about the world are poorly understood. In this paper, we present an overview of artificial devices that model the brain and solve such cognitive tasks as navigation, pattern recognition, routing, and target site finding. We discuss both hybrid systems (hybrots), in which living neural networks control an artificial body, and systems in which such an artificial body is controlled by computer programs based on different models of the brain and its regions (animats). Two basic types of hybrid systems are considered: those in which the robot is connected to the brain of a living body, such as a rat, and those in which information is received from neurons taken from the body or neurons cultured on a microelectrode array detecting their electrical potentials. Among the com putational approaches that simulate nervous systems of living organisms, we can mark out the Darwin family of devices based on the theory of neuronal group selection (TNGS). In addition, we consider papers in which animats solve navigation tasks using different models of the rat hippocampus, based on such modeling meth ods as cognitive graph, view cells, place cells, and experience cells. The approaches under consideration pro vide researchers with new tools to analyze basic principles of neuron interaction between each other and with the outside world, the principles that provide higher brain functions.

Hybrots: Hybrids of Living Neurons and Robots for Studying Neural Computation

2004

We are developing new tools to study the computational properties of living neuronal networks. We are especially interested in the collective, emergent properties at the mesoscopic scale (Freeman 2000) of thousands of brain cells working together to learn, process information, and to control behavior. We grow dissociated monolayer mammalian cortical cultures on multi-electrode arrays. We created the electronics and software necessary for a real-time feedback loop that allows the neurons to trigger their own stimulation. A key part of this loop is a system for re-embodying the in vitro network. We use the neural activity to control either simulated animals (animats) or robots. By using networks of a few thousand neurons and glia, we have tremendous access to the cells, not feasible in vivo. This allows physical and pharmacological manipulation, and continuous imaging at the millisecond and micron scales, to determine the cell-and network-level morphological correlates of learning and memory. We also model the cultured network in software; This helps direct our experiments, which then improves the model. By combining small networks of real brain cells, computer simulations, and robotics into new hybrid neural microsystems (which we call Hybrots), we hope to determine which neural properties are essential for the kinds of collective dynamics that might be used in artificially intelligent systems. BIS1-4 3 of 6 4 Copyright © #### by ASME