Whether Mirror and Conceptual Neurons are Myths? Sparse vs. Distributed Neuronal Representations

Area of Science:

• Neuroscience
• Cognitive Science
• Artificial Intelligence

Background:

• Existing models like multi-layer neural networks, mirror neurons, and gnostic neurons inadequately explain higher mental functions.
• Natural minds exhibit complex functions observable from both third-person and first-person perspectives.

Purpose of the Study:

• To develop an operative model explaining how knowledge in the mind creates conscious sensations.
• To elucidate the neural representations of perceptions, sensory impressions, and environmental models.
• To understand the mechanisms behind complex cognitive functions like speech.

Main Methods:

• Integrating concepts of chemical trace preservation and hierarchical postsynaptic associations.
• Analyzing the detection of structural similarities between remembered patterns and new perceptions.
• Incorporating principles of information processing, representational competition, and stimulating factors.

Main Results:

• Proposed a unified framework combining existing neural concepts with new ones to explain complex mental functions.
• Outlined methods for detecting pattern similarities and associations in neural representations.
• Explained the role of representational competition in cognitive processes.

Conclusions:

• A new model effectively explains complex mental functions, including speech production and recognition.
• Parallel physical process modeling of neural networks can lead to physical models of conscious, intelligent minds.
• This approach offers a pathway to understanding and creating artificial general intelligence.