Articles: biological-evolution.
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Kin selection theory predicts that altruistic behaviors, those that decrease the fitness of the individual performing the behavior but increase the fitness of the recipient, can increase in frequency if the individuals interacting are closely related. Several studies have shown that inbreeding therefore generally increases the effectiveness of kin selection when fitnesses are linear, additive functions of the number of altruists in the family, although with extreme forms of altruism, inbreeding can actually retard the evolution of altruism. These models assume that a constant proportion of the population mates at random and a constant proportion practices some form of inbreeding. ⋯ This association subsequently results in indirect selection on the inbreeding locus. However, the dynamics of this model go beyond a simple "hitch-hiking" effect, because high levels of altruism lead to increased inbreeding, and high degrees of inbreeding accelerate the rate of change of the altruistic allele in the entire population. Thus, the dynamics of this model are similar to those of "runaway" sexual selection, with gene frequency change at the two loci interactively causing rapid evolutionary change.
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Previous articles (3-6) have presented two experimental methods--the Dynamic Behavioral Stage Analysis Method (DBSAM) and the Micro-sleep and Micro-wakefulness Processing Method (MMP)--as investigational approaches oriented in the direction of developing a theoretical concept. MMP employs a simplified method that uses duration of sleep and wakefulness (ti) as the parameter to alter the time units and reverse diagnose sleep and wakefulness as wakefulness and sleep, respectively. ⋯ This paper discusses the conceptual background necessary to understand the correlation between sleep, wakefulness, and consciousness, using model data. It also hypothesizes that conscious activity level, generated by sleep and wakefulness vectors, acts as an address specifier of information that is input and output within the brain.