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.

THE mechanism by which general anesthetics prevent consciousness remains unknown largely because the mechanism by which brain physiology produces consciousness is unexplained. But the two mysteries seem

Artificial consciousness; Machine consciousness; Prosthetic artificial intelligence;

Brain systems operate on many levels of organization, each with its own scales of time and space. Dynamics is applicable to every level, from the atomic to the molecular, and from macromolecular organelles to the neurons into which they are incorporated. In turn the neurons form populations; they form systems, and so on to an embodied brain interacting intentionally with its environment. Each level is "macroscopic" to the one below it and "microscopic" to the one above it. Among the most difficult tasks are those of conceiving and describing the exchanges between levels, seeing that the scales of time and distance are incommensurate, and that causal inference is far more ambiguous between than within levels. That holds for the relation of action potentials from microelectrodes to whole brain activity seen with new techniques for brain imaging: fMRI and PET. A new recourse is to conceive, identify and model an intervening "mesoscopic" level, which is a local selforganizing neural population. Its characteristic activities consist of 'spontaneous' action potentials and EEG dendritic activity. Mesoscopic neurodynamics gives a clear understanding of self-organized chaotic patterns of neural activity in primary sensory areas when significant stimuli arrive. These patterns are created with each sniff, glance, or movement of the head and hands. They are triggered by sensory input, but they are not the result of information processing, and they are not representations of stimuli. They are manifestations of the way in which brains make and test hypotheses. The patterns show that brains do not take information into themselves. They formulate expectations as hypotheses and test them by taking action into the environment. They are not data-driven; they are hypothesisdriven, and all ...

Varela is well known in the systems sciences for his work on second-order cybernetics, biology of cognition and especially autopoietic theory. His concern during this period was to find an appropriate epistemological foundation for the self-reference inherent in life and mind. In his later years, Varela began to develop the so-called ‘enactive ’ approach to cognitive science, which sets itself apart from other sciences by promoting a careful consideration of concrete experiential insights. His final efforts were thus dedicated to finding a pragmatic phenomenological foundation for life and mind. It is argued that Varela’s experiential turn—from epistemology to phenomenology—can be seen as a natural progression that builds on many ideas that were already implicit in second-order cybernetics and biology of cognition. It is also suggested that the rigorous study of conscious experience may enable us to refine our theories and systemic concepts of life, mind and sociality. Copyright © 2011 John Wiley & Sons, Ltd.