What is Consciousness?

Table of Contents The problem of consciousness Microtubules Pan-experiential philosophy meets modern physics Quantum computing and consciousness Roger Penrose's 'objective reduction' Are proteins qubits? Microtubule quantum automata - the 'Orch OR' model Orch OR, cognition and free will Consciousness and evolution Conclusions Acknowledgements/References

1. The Problem of Consciousness

Conventional explanations portray consciousness as an emergent property of classical computer-like activities in the brain's neural networks. The prevailing views among scientists in this camp are that 1) patterns of neural network activities correlate with mental states, 2) synchronous network oscillations in thalamus and cerebral cortex temporally bind information, and 3) consciousness emerges as a novel property of computational complexity among neurons.

However, these approaches appear to fall short in fully explaining certain enigmatic features of consciousness, such as:

• The nature of subjective experience, or 'qualia'- our 'inner life' (Chalmers' "hard problem");
• Binding of spatially distributed brain activities into unitary objects in vision, and a coherent sense of self, or 'oneness';
• Transition from pre-conscious processes to consciousness itself;
• Non-computability, or the notion that consciousness involves a factor which is neither random, nor algorithmic, and that consciousness cannot be simulated (Penrose, 1989, 1994, 1997);
• Free will; and,
• Subjective time flow.

Brain imaging technologies demonstrate anatomical location of activities which appear to correlate with consciousness, but which may not be directly responsible for consciousness.

Figure 1. PET scan image of brain showing visual and auditory recognition (from S Petersen, Neuroimaging Laboratory, Washington University, St. Louis. Also see J.A. Hobson "Consciousness," Scientific American Library, 1999, p. 65).

Figure 2. Electrophysiological correlates of consciousness.

How do neural firings lead to thoughts and feelings? The conventional (a.k.a. functionalist, reductionist, materialist, physicalist, computationalist) approach argues that neurons and their chemical synapses are the fundamental units of information in the brain, and that conscious experience emerges when a critical level of complexity is reached in the brain's neural networks.

The basic idea is that the mind is a computer functioning in the brain (brain = mind = computer). However in fitting the brain to a computational view, such explanations omit incompatible neurophysiological details:

• Widespread apparent randomness at all levels of neural processes (is it really noise, or underlying levels of complexity?);
• Glial cells (which account for some 80% of brain);
• Dendritic-dendritic processing;
• Electrotonic gap junctions;
• Cytoplasmic/cytoskeletal activities; and,
• Living state (the brain is alive!)

A further difficulty is the absence of testable hypotheses in emergence theory. No threshold or rationale is specified; rather, consciousness "just happens".

Finally, the complexity of individual neurons and synapses is not accounted for in such arguments. Since many formsof motile single-celled organisms lacking neurons or synapses are able to swim, find food, learn, and multiply through the use of their internal cytoskeleton, can they be considered more advanced than neurons?

Figure 3. Single cell paramecium can swim and avoid obstacles using its cytoskeleton.

Are neurons merely simple switches?

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