Reference Hub1
A Neural Dynamic Model Based on Activation Diffusion and a Micro-Explanation for Cognitive Operations

A Neural Dynamic Model Based on Activation Diffusion and a Micro-Explanation for Cognitive Operations

Hui Wei
Copyright: © 2012 |Volume: 6 |Issue: 2 |Pages: 22
ISSN: 1557-3958|EISSN: 1557-3966|EISBN13: 9781466611184|DOI: 10.4018/jcini.2012040101
Cite Article Cite Article

MLA

Wei, Hui. "A Neural Dynamic Model Based on Activation Diffusion and a Micro-Explanation for Cognitive Operations." IJCINI vol.6, no.2 2012: pp.1-22. http://doi.org/10.4018/jcini.2012040101

APA

Wei, H. (2012). A Neural Dynamic Model Based on Activation Diffusion and a Micro-Explanation for Cognitive Operations. International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 6(2), 1-22. http://doi.org/10.4018/jcini.2012040101

Chicago

Wei, Hui. "A Neural Dynamic Model Based on Activation Diffusion and a Micro-Explanation for Cognitive Operations," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI) 6, no.2: 1-22. http://doi.org/10.4018/jcini.2012040101

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

The neural mechanism of memory has a very close relation with the problem of representation in artificial intelligence. In this paper a computational model was proposed to simulate the network of neurons in brain and how they process information. The model refers to morphological and electrophysiological characteristics of neural information processing, and is based on the assumption that neurons encode their firing sequence. The network structure, functions for neural encoding at different stages, the representation of stimuli in memory, and an algorithm to form a memory were presented. It also analyzed the stability and recall rate for learning and the capacity of memory. Because neural dynamic processes, one succeeding another, achieve a neuron-level and coherent form by which information is represented and processed, it may facilitate examination of various branches of Artificial Intelligence (AI), such as inference, problem solving, pattern recognition, natural language processing and learning. The processes of cognitive manipulation occurring in intelligent behavior have a consistent representation while all being modeled from the perspective of computational neuroscience. Thus, the dynamics of neurons make it possible to explain the inner mechanisms of different intelligent behaviors by a unified model of cognitive architecture at a micro-level.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.