Consciousness modeling: a neural computing approach

A framework for consciousness is introduced based upon traditional artificial neural network models. This astral framework reflects explicit connections between two parts of brain: one global working memory and distributed modular cerebral networks related to specific brain functions. Accordingly, this framework is composed of two layers, physical mnemonic layer and abstract thinking layer, which cooperate together to accomplish information storage and cognition using algorithms of how these interactions contribute to consciousness: (1) the bottom-up-projection process whereby cerebral subsystems group distributed signals into coherent object patterns; (2) the top-down-attention process whereby global workspace selectively responses to highly impressive patterns; and (3) the horizontal resonant learning process whereby global workspace steadily adjusts its network to adapt to environmental changes. Using this framework, various sorts of human brain actions can be explained, leading to a general approach for analyzing brain functions.