We consider the issue of the reorganization of the structure or activity, in response to a stimulus, in more detail. We will motivate the reader in terms of visual inputs but the discussion is valid for other types of inputs as well. We sketch the following process: the overall architecture of the nested system is determined by the external or internal stimulus, this represents the determination of the connections at the highest hierarchi­cal levels and progresses down in a recursive manner.

[The] superorganism is a self-organizing system incorporating two very distinct pathways of communication. One mode is via localized individual worker inter­actions with low connectedness, and the other one via volatile or semiochemical pheromones with high connectedness. If we examine the communication modes at the functional level, we see that the pheromones reach the entire superorgan­ism, more or less: a global message with a global reaction (for example, the queen pheromones simultaneously and continuously signal to every worker in the colony that it is queenright). An index of average system connectedness (ASC) has been defined as For a fully connected network the index is 1. Another fundamental communication within the superorganism is the one that defines its constitution. This is a much slower process which can be seen, for example, when a queen ant founds her colony. The queen governs the process of caste morphogenesis (Brian, 1983; Holldobler and Wilson, 1994). Within the new colony, the queen, having just mated with her suitors and received more than 200 million sperm, shakes off her wings and digs a little nest in the ground, where she now is in a race with time to produce her worker offspring. She raises her first brood of workers by converting her body fat and muscles into energy. She must create a perfectly balanced work force that is the smallest possible in size, yet capable of successful foraging, so that the workers can bring food to her before she starves to death. The queen produces the workers of the correct size for her initial survival and later, after the colony has started going, she produces a complement of workers of different sizes as well as soldier ants in order to have the right organization for the survival of the colony. When researchers have removed members of a specific caste from an ongoing colony, the queen compensates for this deficit by producing more members of that caste. The communication process behind this remarkable control is not known. The communication mechanisms of the ant or the honeybee superorganisms may be supposed to have analogs in the brain.

Self-Organization by Association

Now we consider the question of the learning by association by the neural hardware. We assume here that such structures are realized as feedforward networks. Self-organization by association may also be viewed as learning. As shown in the eyes wander in the process of perception; they jump, then come to rest momentarily which produces a dot on the record. This process skips areas with little details. These eye movements suggest that there in no fixing of any particular pattern in perception. It appears then that schemes such as backpropagation, where the synaptic weights are adjusted upon considerable training, are not realistic. We would expect that, to be biologically plausible, learning by association should be instantaneous. Such a method might be relevant in the learning of organization. This is based on a new architecture that depends on the nature of the data. It was shown that this approach is much faster than backpropagation and provides good generalization. This approach, which is an example of prescriptive learning, trains the network by isolating the corner in the n-dimensional cube of the inputs represented by the input vector being learnt. Several algorithms to train the new feedforward network were presented. These algorithms were of three kinds. In the first of these (CC1) the weights were obtained upon the use of the perceptron algorithm. In the second (CC2), the weights were obtained by inspection from the data, but this did not provide generalization. In the third (CC3), the weights obtained by the second method were modified in a variety of ways that amounted to randomization and which now provided generalization. During such randomization some of the learnt patterns could be misclassified; further checking and adjustment of the weights was, therefore, necessitated. Various comparisons were reported in (Raina, 1994; Madineni, 1994). The comparisons showed that the new technique could be 200 times faster than the fastest version of the backpropagation algorithm with excellent generalization performance. This technique's generalization might not be as good as when further adjustments are made, but the loss in performance could, in certain situations, be more than compensated by the advantage accruing from the instantaneous training which makes it possible to have as large a network as one pleases.

   Conclusions

We have reviewed different kinds of evidence in favor of an underlying quantum basis to brain behavior: response to single photons by the vision system, the unity of the awareness process, and the fact that the process of self-organization is best seen as triggering a re­duction of the wavefunction corresponding to the thought process. The self-organizational signals are a response to a combination of the inner and the external sensory signals. If biological processing is distinct from classical computing then it is easy to see why machines are unable to do certain kind of holistic processing that is easily done by animals. We sug­gest that biological organization may be supposed to be a quantum macrostructure that is constantly interacting with the environment and reorganizing. This reorganization may parallel perception representing a reduction into an eigenstructure. In several writings, Neils Bohr stressed how the principle of complementarity must include life. Although complementarity as a philosophy is not much in vogue these days due to the ascendancy of the computer metaphor, it is the only consistent interpretive approach to quantum mechanics. Schrodinger's cat paradox shows how indeterminacy is associated with macroscopic systems if they are interacting with quantum systems. Life cannot exist without light; from this perspective alone we are compelled to consider quantum models. An implication of this reasoning is the rejection of the materialist position that considers the identity of the neural and thought processes. A complete description of the individual must be in an suitable dimensional space which includes thoughts and concepts. The structure of system may be described in terms of a binary sequence. One can then speak of complementary variables relating the structure and the environment. Such a reformulation of quantum mechanics may allow it to include living organisms. Brain processes may also be seen in terms of two kinds of communications: one faster and the other slower. This is illustrated by the example of superorganisms where we have localized individual worker interaction with low connectedness and a faster communication using semiochemical pheromones. A specific signaling that regulates organization could provide important clues to the development of the quantum mechanics of living systems. A quantum theoretical basis to life provides resolution to several thorny questions al­though it raises other fresh problems. The most pleasing feature is that it acknowledges the reality of "effort," and "intention," "free will," which have no place in materialist or causal schemes. Neither can we consider consciousness as an epiphenomenon. If consciousness has independent existence then it is a universal function and a brain is to be considered as simply the hardware that reduces this function. We have considered the most basic behavior in our description of the three languages of the brain. At higher levels of description we must speak of other languages.