A Neurologically Inspired Network Model for Graziano's Attention Schema Theory for Consciousness

This paper describes a network-oriented model based on the neuroscientist Graziano’s Attention Schema Theory for consciousness. This theory describes an attention schema as an internal model of the attention process supporting the control of attention, similar to how our mind uses a body schema as an internal model of the body to control its movements. The Attention Schema Theory comes with a number of testable predictions. After designing a neurologically inspired temporalcausal network model for the Attention schema Theory, a few simulations were conducted to verify some of these predictions. One prediction is that a noticeable attention control deficit occurs when using attention without awareness. Another is that a noticeable attention control deficit occurs when using only bottom-up influence (from the sensory representations) without any top-down influence (for example, from goal or control states). The presented model is illustrated by a scenario where a hunter imagines (using internal simulation) a prey which he wants to attend to and catch, but shortly after he or she imagines a predator which he then wants to attend to and avoid. The outcomes of the simulations support the predictions that were made.