Neural Computation
Forward models for physiological motor control
Neural Networks - 1996 Special issue: four major hypotheses in neuroscience
Memory and learning of sequential patterns by nonmonotone neural networks
Neural Networks - 1996 Special issue: four major hypotheses in neuroscience
Multiple paired forward and inverse models for motor control
Neural Networks - Special issue on neural control and robotics: biology and technology
The mirror system, imitation, and the evolution of language
Imitation in animals and artifacts
Imitation in animals and artifacts
Neural Networks - 2004 Special issue: New developments in self-organizing systems
MOSAIC Model for Sensorimotor Learning and Control
Neural Computation
Adaptive mixtures of local experts
Neural Computation
The evolution of imitation and mirror neurons in adaptive agents
Cognitive Systems Research
Neural Networks - 2006 Special issue: The brain mechanisms of imitation learning
Emergence of Mirror Neurons in a Model of Gaze Following
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
PRESENCE: A Human-Inspired Architecture for Speech-Based Human-Machine Interaction
IEEE Transactions on Computers
Social Interaction in Robotic Agents Emulating the Mirror Neuron Function
IWINAC '07 Proceedings of the 2nd international work-conference on Nature Inspired Problem-Solving Methods in Knowledge Engineering: Interplay Between Natural and Artificial Computation, Part II
Neural Model for the Visual Recognition of Goal-Directed Movements
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part II
Proceedings of the 3rd International Conference on Bio-Inspired Models of Network, Information and Computing Sytems
End or means-the "what" and "how" of observed intentional actions
Journal of Cognitive Neuroscience
An Adaptive Agent Model for Emotion Reading by Mirroring Body States and Hebbian Learning
PRIMA '09 Proceedings of the 12th International Conference on Principles of Practice in Multi-Agent Systems
Automatic selection of task spaces for imitation learning
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
A novel motor function training assisted system for upper limbs rehabilitation
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Emulation and behavior understanding through shared values
Robotics and Autonomous Systems
Learning new motion primitives in the mirror neuron system: a self-organising computational model
SAB'10 Proceedings of the 11th international conference on Simulation of adaptive behavior: from animals to animats
Emotion recognition from EEG using higher order crossings
IEEE Transactions on Information Technology in Biomedicine - Special section on affective and pervasive computing for healthcare
Considerations for a neuroscience-inspired approach to the design of artificial intelligent systems
AGI'11 Proceedings of the 4th international conference on Artificial general intelligence
Active learning of visual descriptors for grasping using non-parametric smoothed beta distributions
Robotics and Autonomous Systems
Motor simulation via coupled internal models using sequential Monte Carlo
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Object-object interaction affordance learning
Robotics and Autonomous Systems
| Hi-index | 0.01 |
Neurophysiology reveals the properties of individual mirror neurons in the macaque while brain imaging reveals the presence of 'mirror systems' (not individual neurons) in the human. Current conceptual models attribute high level functions such as action understanding, imitation, and language to mirror neurons. However, only the first of these three functions is well-developed in monkeys. We thus distinguish current opinions (conceptual models) on mirror neuron function from more detailed computational models. We assess the strengths and weaknesses of current computational models in addressing the data and speculations on mirror neurons (macaque) and mirror systems (human). In particular, our mirror neuron system (MNS), mental state inference (MSI) and modular selection and identification for control (MOSAIC) models are analyzed in more detail. Conceptual models often overlook the computational requirements for posited functions, while too many computational models adopt the erroneous hypothesis that mirror neurons are interchangeable with imitation ability. Our meta-analysis underlines the gap between conceptual and computational models and points out the research effort required from both sides to reduce this gap.