Anderson's compelling case for neural reuse is well motivated by empirical results and evolutionary considerations and dovetails nicely with the “descent with modification” perspective put forward by our lab (Marcus Reference Marcus2006; Marcus & Rabagliati Reference Marcus and Rabagliati2006). An important additional line of support comes from the study of human individual differences.

In an entirely modular brain, one might predict that individual differences in specific cognitive domains would be largely separate and uncorrelated, but the opposite is in fact true: An extensive literature has shown that performance on separate cognitive tasks tends to be correlated within individuals. This “positive manifold,” first noted by Spearman (Reference Spearman1904), is arguably one of the most replicated findings in all of psychology (e.g., Deary et al. Reference Deary, Spinath and Bates2006). At first glance, such correlations might appear to be a statistical by-product of the fact that any individual cognitive task draws on multiple underlying processes. However, even when the impurity of individual tasks is taken into account, using more sophisticated structural equation models that form latent cognitive constructs (representing a cognitive ability, such as short-term memory, by the shared variance among performance on diverse tasks with different specific task demands), clear correlations between cognitive capacities within individuals remain. Positive manifold is not an artifact, but a fact of human cognitive life. (Our point here is reminiscent of Anderson's observation that patterns of co-activation in fMRI remain even after subtraction, and are therefore not attributable solely to mechanistic impurities at the task level.)

These correlations between cognitive domains have now been shown in hundreds of separate data sets, and at many levels, ranging from parts of standardized tests such as SAT math and SAT verbal, to broad ability domains such as memory and spatial visualization (see Carroll Reference Carroll1993), to more specific links such as susceptibility to memory interference and sentence processing (Rabaglia & Marcus, in preparation). Recently, it has been pointed out that “the existence of g creates a complicated situation for neuroscience” (Deary et al. Reference Deary, Penke and Johnson2010). Adequate theories of brain organization and functioning will have to be consistent with the robust finding of positive manifold, and Anderson's theory of neural reuse is one of the few that is. Strictly modular theories would not predict such between-domain correlations, and nor would theories that are driven purely by experience (since experience is likely to differ heavily between domains).

At the same time, the concept of neural reuse (or decent with modification) may help to shed some light on the interpretation of positive manifold itself. Despite being noted for more than 100 years, there is not yet a consensus on how to explain the phenomenon. Spearman's view was that positive manifold reflected the operation of a general intelligence factor, referred to as “g.” Since then, proposed causes range from biological factors such as overall mental speed (Jensen Reference Jensen1998) or myelination (Chiang et al. Reference Chiang, Barysheva, Shattuck, Lee, Madsen, Avedissian, Klunder, Toga, McMahon, de Zubicaray, Wright, Srivastava, Balov and Thompson2009), to some special rudimentary cognitive ability influencing the operation of others, such as the optimal allocation of resources or a limited central memory capacity (e.g., Kyllonen & Christal Reference Kyllonen and Christal1990); but each of these individually only accounts for (at most) a portion of the variance. If neural reuse characterizes brain functioning for most of human cognition, overlap in the neural substrates recruited by separate cognitive capacities could, in fact, be another factor contributing to positive manifold. One finding that could lend support to this notion is the fact that Ravens Progressive Matrices – arguably the gold standard for tapping into “g” – is an abstract reasoning task, and, as Anderson points out, reasoning tasks are among the most widely distributed in terms of neural areas of activation. Indeed, the most heavily “g-loaded” tasks, or, in other words, the tasks that seem most related to what a range of cognitive abilities tend to share, are usually those involving frontal-lobe type abilities (see, for example, Jung & Haier Reference Jung and Haier2007) – the very same abilities that are presumably latest-evolving and thus perhaps most characterized by reuse.