Abstract: We give a brief account on the existing strategies in quantum-mechanical approaching the problem of consciousness. To a list of distinguished approaches we add the next plausible notion: when treated quantummechanically, consciousness should be modeled as an open quantum system. This notion is tightly connected to the von Neumann's "collapse " ("wave packet reduction"). Here we strongly emphasize that the problem of the "collapse " cannot be resolved within the quantum mechanics of open quantum systems (or: decoherence theory). Some clues in this regard are briefly outlined.

Abstract The universal Turing machine is an anticipatory theory of computability by any digital or quantum machine. However the Church-Turing hypothesis only gives weak anticipation. The construction of the quantum computer (unlike classical computing) requires theory with strong anticipation. Category theory provides the necessary coordinate-free mathematical language which is both constructive and non-local to subsume the various interpretations of quantum theory in one pullback/pushout Dolittle diagram. This diagram can be used to test and classify physical devices and proposed algorithms for weak or strong anticipation. Quantum Information Science is more than a merger of Church-Turing and quantum theories. It has constructively to bridge the non-local chasm between the weak anticipation of mathematics and the strong anticipation of physics.

An integrated model of conscious image processing in human cortex is proposed based on the Holonomic Brain Theory by Karl Pribram and related models. After optimal delineation of the neural and quantum ingredients, the model combines the predominantly (sub)neuronal image processing and the essentially quantum-based repetitive act of becoming-conscious of the resulting phenomenal image. The model optimally incorporates contemporary limited knowledge starting from a systematic search for fit between existing computational models, and between available experimental data, and between data and models. Since we are not yet able to tackle qualitative conscious experience directly, processes for making an image (or result of image processing, respectively) conscious are discussed. A quantum implementation of holography-like processing of images in the striate cortex (V1) is proposed using a computational model called quantum associative network. The input to the quantum net could be the Gabor wavelets, together with their coefficients, which are infomax-constrained spectral and sparse neural codes produced in the convolutional