The term 'encephalization' expresses different ideas in different scientific disciplines. In comparative biology, it describes the difference between animals in the amount of neurons available beyond the average determined by allometric body design (e.g., Jerison, 1991; Schoenemann, 2004). Porpoises, for example, are said to be more encephalized than tenrecs because they are far above the regression line of log brain size plotted against log body size for all mammals, while tenrecs are far below. In paleoanthropology, encephalization designates the observed increase over evolutionary time in the absolute and relative size of the brain in hominids (e.g., McHenry, 1994; Bruner et al., 2003; Rightmire, 2004; Stedman et al., 2004). The brain of Homo erectus, at c. 1000 g, is thus considered to be more encephalized than the brain of Australopithecus, at c. 500 g. In neuroanatomy, encephalization describes the increased importance that higher brain structures play over lower ones in birds and mammals compared to other vertebrates and to invertebrates (Reiner et al., 2004). In this view, the average mammal brain is more encepha-lized than the average fish brain.
Despite their differences, all three usages share one common assumption: the information-processing advantage provided by extra neurons, increased size, and increased forebrain involvement should normally be the major evolutionary driving force behind encephalization. Extra neurons in the forebrain, whether they evolve in a hominid, a cuttlefish, a capuchin monkey, or a crow, should provide faster and/or more complex and/or a greater amount of information processing and information storage about changing environmental conditions. Natural selection can lead to efficient genetically biased responses to conditions that are stable over long periods of time. But when relationships between events change rapidly, neuronal storage allows animals to respond faster than information stored only in the genome. The main functional and evolutionary hypothesis on encephalization is thus that something about extra neurons, increased size, and increased forebrain involvement is associated with the speed, complexity, and amount of information processing in these structures.
It is useful to envision variation between animals in information-processing capacity as a cognitive continuum. A corvid, for example, seems to learn more items faster (Wilson et al., 1985) and with more complex processes (e.g., episodic memory, prospection; Emery and Clayton, 2004) than a columbiforme does. Its higher brain centers (the meso- and nidopallium) are eight times larger than that of a columbiforme of the equivalent body size (Rehkamper et al., 1991a; Boire, 1989). The whole brain of a corvid is more than 1.5 standard deviations above that of the average bird, while a columbiform brain is 1.5 standard deviations below. This kind of organ-function correlation is not very controversial when it involves wings and flight or beaks and feeding. When the correlation involves brains and cognition, however, this is often a different story. Critics plead that cognitive complexity is difficult to assess in a way that is generalism independent contrasts innovation specialized cognitive skills fair to all species (Macphail, 1982). They say that brains have many contradictory functions unlikely to lead to directional selection for an overall size increase (Shettleworth, 1998). Others claim that a correlation between morphology and function does not necessarily imply adaptation (Gould and Lewontin, 1979) and point out that adaptationist accounts of brain-cognition co-evolution in humans have often been politically tainted (Gould, 1981; see Human Cognitive Specializations).
Such qualms are legitimate and must be addressed, but they do not invalidate a critical empirical examination of brain-cognition questions. How is brain size variation distributed among taxa? Is the distribution continuous or patchy? Is it whole brain variation that we should be concerned with or variation in some specific structures? Is it relative rather than absolute size of neural structures that matters and if the former, relative to what? Can we reliably show that brain size variation is associated with variation in cognition? How did the variation evolve? What are the costs and benefits of larger versus smaller brains, and in what ecological contexts do these costs and benefits apply? These are the who, what, and why questions we will examine in this article.
Was this article helpful?