To explain how stimuli cause consciousness, we have to explain causality. We can't trace linear causal chains from receptors after the first cortical synapse, so we use circular causality to explain neural pattern formation by self-organizing dynamics. But an aspect of intentional action is causality, which we extrapolate to material objects in the world. Thus causality is a property of mind, not matter.

Recent interest in consciousness and the mind-brain problem has been fueled by technological advances in brain imaging and computer modeling in artificial intelligence: Can machines be conscious? The machine metaphor originated in Cartesian "reflections" and culminated in 19th century reflexology modeled on Newtonian optics. It replaced the Aquinian view of mind, which was focused on the emergence of intentionality within the body, with control of output by input through brain dynamics. The state variables for neural activity were identified successively with animal spirits, lan vital, electricity, energy, information, and, most recently, Heisenbergian potentia. The source of dynamic structure in brains was conceived to lie outside brains in genetic and environmental determinism. An alternative view has grown in the 20th century from roots in American Pragmatists, particularly John Dewey, and European philosophers, particularly Heidegger and Piaget, by which brains are intrinsically unstable and continually create themselves. This view has new support from neurobiological studies in properties of self-organizing nonlinear dynamic systems. Intentional behavior can only be understood in relation to the chaotic patterns of neural activity that produce it. The machine metaphor remains, but the machine is seen as selfdetermining. 1.

In a passive information processing system a stimulus input gives information, which is transduced by receptors into trains of impulses that signify the features of an object. The symbols are processed according to rules for learning and association and are then bound into a representation, which is stored, retrieved and matched with new incoming representations. In active systems perception begins with the emergence of a goal that is implemented by the search for information. The only input accepted is that which is consistent with the goal and anticipated as a consequence of the searching actions. The key component to be modeled in brains provides the dynamics that constructs goals and the adaptive actions by which they are achieved.