Abstract
This paper examines the notion of quantum neural computing in the context of several new directions in neural network research. In particular, we consider new neuron and network models that lead to rapid training, chaotic dynamics in neuron assemblies, models of attention and awareness, cytoskeletal microtubule information processing, and quantum models. Recent discoveries in neuroscience that cannot be placed in the reductionist models of biological information processing are examined. We consider some characteristics of a quantum neural computer. We show that information is not a locally additive variable in a quantum computation; this property may be used to examine the nature of biological information structures.
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