Mirror neurons and imitation: a computationally guided review

Area of Science:

• Neuroscience
• Cognitive Science
• Computational Neuroscience

Background:

• Neurophysiology identifies individual mirror neurons in macaques, while brain imaging detects 'mirror systems' in humans.
• Conceptual models propose mirror neurons are crucial for action understanding, imitation, and language.
• However, only action understanding is well-established in monkeys, indicating functional differences.

Purpose of the Study:

• To differentiate between conceptual and computational models of mirror neuron function.
• To evaluate the strengths and weaknesses of existing computational models.
• To analyze specific models like Mirror Neuron System (MNS), Mental State Inference (MSI), and MOSAIC.

Main Methods:

• Meta-analysis of conceptual and computational models of mirror neuron function.
• Assessment of computational requirements for proposed mirror neuron functions.
• Comparison of model predictions with neurophysiological and brain imaging data.

Main Results:

• Conceptual models often neglect computational demands for functions like imitation.
• Some computational models incorrectly equate mirror neurons with imitation ability.
• A significant gap exists between conceptual understanding and computational modeling of mirror neurons.

Conclusions:

• Current models require refinement to accurately reflect mirror neuron/system capabilities.
• Further research is needed to bridge the gap between conceptual and computational approaches.
• Accurate modeling is essential for understanding complex cognitive functions attributed to mirror systems.