Biological organisms perform many complex tasks with ease. Although we may have supercomputers that have reached the level of computing power beyond our imagination, some of the tasks we perform, such as pattern recognition and language undrstanding, are still beyond the reach of such supercomputers. Can quantum-mechanical models better account for such complex behavior in biological organisms? The rest of this chapter is devoted to this question. We propose a theoretical quantum brain model to explain human eye movement behavior, where the same collective response attribute of natural intelligence plays the key role. While simulating the quantum brain model, two very interesting phenomena are observed. First, as eye-sensor data is processed in a classical brain, a wave packet is triggered in the quantum brain. This wave packet moves like a particle. Secondly, when the eye tracks a fixed target, this wave packet moves not in a continuous but rather in a discrete mode. This result reminds one of the saccadic movements of the eye consisting of "jumps" and "rests". However, such a saccadic movement is intertwined with smooth-pursuit movements when the eye has to track a dynamic trajectory. In this sense, the proposed quantum brain concept is very successful in explaining the nature of eye movements that also accord with the experimental observations.
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