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Published on Jan 18, 2008
Google Tech Talks January, 10 2008
Syllabus and Recommended Literature
This tech talk series explores the enormous opportunities afforded by the emerging field of quantum computing. The exploitation of quantum phenomena not only offers tremendous speed-ups for important algorithms but may also prove key to achieving genuine synthetic intelligence. We argue that understanding higher brain function requires references to quantum mechanics as well. These talks look at the topic of quantum computing from mathematical, engineering and neurobiological perspectives, and we attempt to present the material so that the base concepts can be understood by listeners with no background in quantum physics.
In this third talk we review the history of the theory that quantum effects are essential to understanding brain function. We look at the theory of Penrose and Hameroff and its refutation by the decoherence calculations of Tegmark. Our experiments with pattern recognition using a quantum computer teach new lessons on which type of problems the brain may solve by quantum processes and how the data flow might look. Specifically, we conjecture that computations that are not time-critical and which require the solution of a global optimization problem are good candidates for brain processes facilitated by quantum phenomena. We then study situations in which coherence could be maintained to be of behavioral relevance as well as recent findings that show the relevance of coherence in basic biological processes such as photo synthesis and enzyme function. We advance a speculative theory that mental states induced by tryptamines might come about by enhancing the propensity of the brain to relegate certain computations to quantum annealing. We argue that by virtue of being a physical substrate the brain exists in a global superposition with the environment and participates in information exchange via fundamental physical interactions. This regime becomes relevant in situations in which neural dynamics is less driven by sensory input or behavioral affordances. Studying multiple corpora of reports describing experiences mediated by the psychoactive brew ayahuasca, we argue that our model outperforms a more mainstream neurobiological explanation based on neural assemblies.