Neurorobotics
Encyclopedia
Neurorobotics, a combined study of neuroscience
, robotics
, and artificial intelligence
(AI), is the science and technology of embodied autonomous neural systems. Neural systems include brain-inspired algorithms (e.g. connectionist networks), computational models of biological neural networks (e.g. artificial spiking neural network
s, large-scale simulations of neural microcircuits) and actual biological systems (e.g. in vivo and in vitro neural nets). Such neural systems can be embodied in machines with mechanic or any other forms of physical actuation. This includes robot
s, prosthetic
or wearable systems but at also, at smaller scale, micro-machines and, at the larger scales, furniture and infrastructures.
Neurorobotics is that branch of neuroscience with robotics, which deals with the study and application of science and technology of embodied autonomous neural systems like brain-inspired algorithms. At its core, neurorobotics is based on the idea that the brain is embodied and the body is embedded in the environment. Therefore, most neurorobots are required to function in the real world, as opposed to a simulated environment.
and control systems, and have proved their merit in developing controllers for robots. Locomotion
is modeled by a number of neurologically inspired theories on the action of motor systems. Locomotion control has been mimicked using models or central pattern generators, clumps of neurons capable of driving repetitive behavior, to make four-legged walking robots. Other groups have expanded the idea of combining rudimentary control systems into a hierarchical set of simple autonomous systems. These systems can formulate complex movements from a combination of these rudimentary subsets. This theory of motor action is based on the organization of cortical column
s, which progressively integrate from simple sensory input into a complex afferent signals, or from complex motor programs to simple controls for each muscle fiber in efferent signals, forming a similar hierarchical structure.
Another method for motor control uses learned error correction and predictive controls to form a sort of simulated muscle memory. In this model, awkward, random, and error-prone movements are corrected for using error feedback to produce smooth and accurate movements over time. The controller learns to create the correct control signal by predicting the error. Using these ideas, robots have been designed which can learn to produce adaptive arm movements or to avoid obstacles in a course.
systems. Many studies currently examine the memory system of rats, particularly the rat hippocampus
, dealing with place cells, which fire for a specific location that has been learned. Systems modeled after the rat hippocampus are generally able to learn mental maps
of the environment, including recognizing landmarks and associating behaviors with them, allowing them to predict the upcoming obstacles and landmarks.
Another study has produced a robot based on the proposed learning paradigm of barn owls for orientation and localization based on primarily auditory, but also visual stumuli. The hypothesized method involves synaptic plasticity and neuromodulation
, a mostly chemical effect in which reward neurotransmitters such as dopamine or seratonin affect the firing sensitivity of a neuron to be sharper. The robot used in the study adequately matched the behavior of barn owls. Furthermore, the close interaction between motor output and auditory feedback proved to be vital in the learning process, supporting active sensing theories that are involved in many of the learning models.
Neurorobots in these studies are presented with simple mazes or patterns to learn. Some of the problems presented to the neurorobot include recognition of symbols, colors, or other patterns and execute simple actions based on the pattern. In the case of the barn owl simulation, the robot had to determine its location and direction to navigate in its environment.
(MEA), which is capable of both recording the neural activity and stimulating the tissue. In some cases, the MEA is connected to a computer which presents a simulated environment to the brain tissue and translates brain activity into actions in the simulation, as well as providing sensory feedback. The ability to record neural activity gives researchers a window into a brain, albeit simple, which they can use to learn about a number of the same issues neurorobots are used for.
An area of concern with the biological robots is ethics. Many questions are raised about how to treat such experiments. Seemingly the most important question is that of consciousness and whether or not the rat brain experiences it. This discussion boils down to the many theories of what consciousness is.
See Hybrot
, consciousness
.
With subject of neuroscience growing as it has, numerous neural treatments have emerged, from pharmaceuticals to neural rehabilitation. Progress is dependent on an intricate understanding of the brain and how exactly it functions. It is very difficult to study the brain, especially in humans due to the danger associated with cranial surgeries. Therefore, the use of technology to fill the void of testable subjects is vital. Neurorobots accomplish exactly this, improving the range of tests and experiments that can be performed in the study of neural processes.
Neuroscience
Neuroscience is the scientific study of the nervous system. Traditionally, neuroscience has been seen as a branch of biology. However, it is currently an interdisciplinary science that collaborates with other fields such as chemistry, computer science, engineering, linguistics, mathematics,...
, robotics
Robotics
Robotics is the branch of technology that deals with the design, construction, operation, structural disposition, manufacture and application of robots...
, and artificial intelligence
Artificial intelligence
Artificial intelligence is the intelligence of machines and the branch of computer science that aims to create it. AI textbooks define the field as "the study and design of intelligent agents" where an intelligent agent is a system that perceives its environment and takes actions that maximize its...
(AI), is the science and technology of embodied autonomous neural systems. Neural systems include brain-inspired algorithms (e.g. connectionist networks), computational models of biological neural networks (e.g. artificial spiking neural network
Spiking neural network
Spiking neural networks fall into the third generation of neural network models, increasing the level of realism in a neural simulation. In addition to neuronal and synaptic state, SNNs also incorporate the concept of time into their operating model...
s, large-scale simulations of neural microcircuits) and actual biological systems (e.g. in vivo and in vitro neural nets). Such neural systems can be embodied in machines with mechanic or any other forms of physical actuation. This includes robot
Robot
A robot is a mechanical or virtual intelligent agent that can perform tasks automatically or with guidance, typically by remote control. In practice a robot is usually an electro-mechanical machine that is guided by computer and electronic programming. Robots can be autonomous, semi-autonomous or...
s, prosthetic
Prosthesis
In medicine, a prosthesis, prosthetic, or prosthetic limb is an artificial device extension that replaces a missing body part. It is part of the field of biomechatronics, the science of using mechanical devices with human muscle, skeleton, and nervous systems to assist or enhance motor control...
or wearable systems but at also, at smaller scale, micro-machines and, at the larger scales, furniture and infrastructures.
Neurorobotics is that branch of neuroscience with robotics, which deals with the study and application of science and technology of embodied autonomous neural systems like brain-inspired algorithms. At its core, neurorobotics is based on the idea that the brain is embodied and the body is embedded in the environment. Therefore, most neurorobots are required to function in the real world, as opposed to a simulated environment.
Introduction
Neurorobotics represents the two-front approach to the study of intelligence. Neuroscience attempts to discern what intelligence consists of and how it works by investigating intelligent biological systems, while the study of artificial intelligence attempts to recreate intelligence through non-biological, or atificial means. Neurorobotics is the boundary between the two, where biologically inspired theories are tested in a grounded environment, with a physical implementation of said model. The successes and failures of a neurorobot and the model it is built from can provide evidence to refute or support that theory, and give insight for future study.Major classes of neurorobotic models
Neurorobots can be divided into various major classes based on the robot's purpose. Each class is designed to implement a specific mechanism of interest for study. The three common types of neurorobots are those used to study motor control, memory, and action selection.Locomotion and motor control
Neurorobots are often used to study motor feedbackFeedback
Feedback describes the situation when output from an event or phenomenon in the past will influence an occurrence or occurrences of the same Feedback describes the situation when output from (or information about the result of) an event or phenomenon in the past will influence an occurrence or...
and control systems, and have proved their merit in developing controllers for robots. Locomotion
Animal locomotion
Animal locomotion, which is the act of self-propulsion by an animal, has many manifestations, including running, swimming, jumping and flying. Animals move for a variety of reasons, such as to find food, a mate, or a suitable microhabitat, and to escape predators...
is modeled by a number of neurologically inspired theories on the action of motor systems. Locomotion control has been mimicked using models or central pattern generators, clumps of neurons capable of driving repetitive behavior, to make four-legged walking robots. Other groups have expanded the idea of combining rudimentary control systems into a hierarchical set of simple autonomous systems. These systems can formulate complex movements from a combination of these rudimentary subsets. This theory of motor action is based on the organization of cortical column
Cortical column
A cortical column, also called hypercolumn or sometimes cortical module, is a group of neurons in the brain cortex which can be successively penetrated by a probe inserted perpendicularly to the cortical surface, and which have nearly identical receptive fields...
s, which progressively integrate from simple sensory input into a complex afferent signals, or from complex motor programs to simple controls for each muscle fiber in efferent signals, forming a similar hierarchical structure.
Another method for motor control uses learned error correction and predictive controls to form a sort of simulated muscle memory. In this model, awkward, random, and error-prone movements are corrected for using error feedback to produce smooth and accurate movements over time. The controller learns to create the correct control signal by predicting the error. Using these ideas, robots have been designed which can learn to produce adaptive arm movements or to avoid obstacles in a course.
Learning and memory systems
Robots designed to test theories of animal memoryMemory
In psychology, memory is an organism's ability to store, retain, and recall information and experiences. Traditional studies of memory began in the fields of philosophy, including techniques of artificially enhancing memory....
systems. Many studies currently examine the memory system of rats, particularly the rat hippocampus
Hippocampus
The hippocampus is a major component of the brains of humans and other vertebrates. It belongs to the limbic system and plays important roles in the consolidation of information from short-term memory to long-term memory and spatial navigation. Humans and other mammals have two hippocampi, one in...
, dealing with place cells, which fire for a specific location that has been learned. Systems modeled after the rat hippocampus are generally able to learn mental maps
Cognitive map
Cognitive maps are a type of mental processing composed of a series of psychological transformations by which an individual can acquire, code, store, recall, and decode information about the relative locations and attributes of phenomena in their everyday or metaphorical spatial environment.The...
of the environment, including recognizing landmarks and associating behaviors with them, allowing them to predict the upcoming obstacles and landmarks.
Another study has produced a robot based on the proposed learning paradigm of barn owls for orientation and localization based on primarily auditory, but also visual stumuli. The hypothesized method involves synaptic plasticity and neuromodulation
Neuromodulation
In Neuromodulation several classes of neurotransmitters regulate diverse populations of central nervous system neurons...
, a mostly chemical effect in which reward neurotransmitters such as dopamine or seratonin affect the firing sensitivity of a neuron to be sharper. The robot used in the study adequately matched the behavior of barn owls. Furthermore, the close interaction between motor output and auditory feedback proved to be vital in the learning process, supporting active sensing theories that are involved in many of the learning models.
Neurorobots in these studies are presented with simple mazes or patterns to learn. Some of the problems presented to the neurorobot include recognition of symbols, colors, or other patterns and execute simple actions based on the pattern. In the case of the barn owl simulation, the robot had to determine its location and direction to navigate in its environment.
Action selection and value systems
Action selection studies deal with negative or positive weighting to an action and its outcome. Neurorobots can and have been used to study *simple* ethical interactions, such as the classical thought experiment where there are more people than a life raft can hold, and someone must leave the boat to save the rest. However, more neurorobots used in the study of action selection contend with much simpler persuasions such as self preservation or perpetuation of the population of robots in the study. These neurorobots are modeled after the neuromodulation of synapses to encourage circuits with positive results. In biological systems, neurotransmitters such as dopamine or acetylcholine positively reinforce neural signals that are beneficial. One study of such interaction involved the robot Darwin VII, which used visual, auditory, and a simulated taste input to "eat" conductive metal blocks. The arbitrarily chosen good blocks had a striped pattern on them while the bad blocks had a circular shape on them. The taste sense was simulated by conductivity of the blocks. The robot had positive and negative feedbacks to the taste based on its level of conductivity. The researchers observed the robot to see how it learned its action selection behaviors based on the inputs it had. Other studies have used herds of small robots which feed on batteries strewn about the room, and communicate its findings to other robots.Biological robots
These are not officially a neurorobot in that they are not neurologically inspired AI systems, but actual neuron tissue wired to a robot. This employs the use of cultured neural networks to study brain development or neural interactions. These typically consist of a neural culture raised on a multielectrode arrayMultielectrode array
Multielectrode arrays or microelectrode arrays are devices that contain multiple plates or shanks through which neural signals are obtained or delivered, essentially serving as neural interfaces that connect neurons to electronic circuitry...
(MEA), which is capable of both recording the neural activity and stimulating the tissue. In some cases, the MEA is connected to a computer which presents a simulated environment to the brain tissue and translates brain activity into actions in the simulation, as well as providing sensory feedback. The ability to record neural activity gives researchers a window into a brain, albeit simple, which they can use to learn about a number of the same issues neurorobots are used for.
An area of concern with the biological robots is ethics. Many questions are raised about how to treat such experiments. Seemingly the most important question is that of consciousness and whether or not the rat brain experiences it. This discussion boils down to the many theories of what consciousness is.
See Hybrot
Hybrot
A hybrot is a cybernetic organism in the form of a robot controlled by a computer consisting of both electronic and biological elements. The biological elements are typically rat neurons connected to a computer chip....
, consciousness
Consciousness
Consciousness is a term that refers to the relationship between the mind and the world with which it interacts. It has been defined as: subjectivity, awareness, the ability to experience or to feel, wakefulness, having a sense of selfhood, and the executive control system of the mind...
.
Implications for neuroscience
Neuroscientists benefit from neurorobotics because it provides a blank slate to test various possible methods of brain function in a controlled and testable environment. Furthermore, while the robots are more simplified versions of the systems they emulate, they are more specific, allowing more direct testing of the issue at hand. They also have the benefit of being accessible at all times, while it is much more difficult to monitor even large portions of a brain while the animal is active, let alone individual neurons.With subject of neuroscience growing as it has, numerous neural treatments have emerged, from pharmaceuticals to neural rehabilitation. Progress is dependent on an intricate understanding of the brain and how exactly it functions. It is very difficult to study the brain, especially in humans due to the danger associated with cranial surgeries. Therefore, the use of technology to fill the void of testable subjects is vital. Neurorobots accomplish exactly this, improving the range of tests and experiments that can be performed in the study of neural processes.
External links
- Neurorobotics on Scholarpedia (Jeff Krichmar (2008), Scholarpedia, 3(3):1365)
- A lab that focuses on neurorobotics at Northwestern University.
- Frontiers in Neurorobotics.
- Neurorobotics: an experimental science of embodiment by Frederic Kaplan
- Neurorobotics Lab, Control Systems Lab, National Technical University of Athens (Prof. Kostas J. Kyriakopoulos)