Open and closed loops: A computational approach to attention and consciousness

Area of Science:

• Cognitive Science
• Computational Neuroscience
• Developmental Psychology

Background:

• Recent research suggests attention and consciousness may be independent.
• Investigating their interaction is challenging due to the complex nature of these cognitive functions.
• Existing models often lack a comprehensive framework integrating both constructs.

Purpose of the Study:

• To present a novel computational framework for conceptualizing attention and consciousness.
• To model these functions as distinct but interacting large-scale processes.
• To incorporate a developmental perspective, highlighting the role of learning.

Main Methods:

• Development of a biologically inspired computational architecture.
• Conceptualization of attention and consciousness as functionally and structurally differentiated processes.
• Modeling the full stimulus-to-response arc.

Main Results:

• The proposed architecture assumes general independence of attention and consciousness.
• It posits strong interactive pathways between these two cognitive functions.
• The framework accommodates the gradual development of attention and consciousness through learning.

Conclusions:

• Attention and consciousness, while fundamentally independent, exhibit significant interaction.
• A computational, biologically inspired approach offers a viable framework for studying these constructs.
• The developmental trajectory, driven by learning, is crucial for understanding their emergence.