Arbib, Érdi, and Szentágothai's book should be a required reading for any serious student of the brain. The scope and the accessibility of its presentation of the neurobiological data (especially the functional anatomy of select parts of the central nervous system) more than make up for the peculiarities of the theoretical stance it adopts.

Several suggestions are made for revision of Strategic Pluralism Theory (SPT). One revision requires recognition of the impact of individual differences in cognitive and behavioral competence on optimal mating strategy. In addition, SPT may need to incorporate certain self-regulatory processes such as the impact of widespread valuation of mates with one trait on their availability.

Women's preference for symmetrical men need not have evolved as part of a good gene sexual selection (GGSS) reproductive strategy employed during recent human evolutionary history. It may be a remnant of the reproductive strategy of a perhaps promiscuous species which existed prior to the divergence of the human line from that of the bonobo and chimp.

Human males are more polygamously inclined than females. However, there is substantial within-sex variation in polygamous inclinations and practices. This is acknowledged by Gangestad & Simpson but we pose the question: Is the target article's “strategic pluralism” pluralistic enough? In addition, we argue that the hypothesis that the female orgasm is an adaptation for post-copulatory female choice between rival ejaculates demands more research.

Localist networks are symbolic models, because their nodes refer to extra-mental objects and events. Hence, localist networks can be combined with symbolic computations to form hybrid models. Such models are already familiar and they are likely to represent the dominant type of cognitive model in the next few decades.

I argue that the rôle for the cerebellar cortex is in the generation of sensory predictions, not motor sequences. This proposal may explain the allometric relationship described in Braitenberg et al.'s target article. I also point out that the parallel beam organisation may have a nontemporal basis.

Different sciences approach the brain-behaviour system at various levels, but often apparently share terminology. “Function” is used both ontogenetically and phylogenetically. Within the ontogeny it has various meanings; the one adopted by Arbib et al. is that of mainstream cognitive psychology. This usage is relatively imprecise, and the psychologists who are sceptical about the ability of cognitive psychology to predict behavioural outcomes may have the same reservations about Arbib et al.'s cognitive neuroscience.

Plamondon's kinematic theory is very powerful from a descriptive point of view. Unfortunately, the fact that it neglects some fundamental features of the motor system, such as nonlinear inertial torque interactions or joint redundancies, limits its explanatory power and biological validity. As a consequence, the data presented by Plamondon & Alimi should be analyzed and interpreted with caution. There appears to be a gap between the observations reported by the authors and some of the conclusions they draw.

An impressive review of brain neurophysiology provides the basis for modelling the dynamics of transmission in neural circuits, using appropriate nonlinear mathematics. The coverage is unbalanced, however: the parallel dynamics at the level of behaviour and sensory-cognitive processes are sparsely addressed, so the final chapter fails to indicate the complexity and subtlety of relevant modern work.

The commentators have raised some interesting issues but none question the viability of a localist approach to connectionist modelling. Once localist models are properly defined they can be seen to exhibit many properties relevant to the modelling of both psychological and brain function. They can be used to implement exemplar models, prototype models and models of sequence memory and they form a foundation upon which symbolic models can be constructed. Localist models are insensitive to interference and have learning rules that are biologically plausible. They have more explanatory value than their distributed counterparts and they relate transparently to a number of classic mathematical models of behaviour.

Saunders & van Brakel's analysis of the phenomenal categorization and subsequent experimental research in unique hues fails to include contemporary methodological improvements. Alternative strategies are offered from the author's research that rely less on language and world knowledge and provide strong evidence for the general theoretical constructs of elemental hue, nonbasic, and basic color terms.

This commentary cites several findings of neuromuscular research that are consistent with aspects of Plamondon's kinematic theory. In addition, we point out certain biomechanical properties of the limb that influence the requirements for the production of accurate movement, and might thus compromise the global applicability of any law governing speed/accuracy trade-offs.

Multidimensional scaling of subjective color differences has shown that color stimuli are located on a hypersphere in four-dimensional space. The semantic space of color names is isomorphic with perceptual color space. A spherical four-dimensional space revealed in monkeys and fish suggests the primacy of common neuronal basis.

Neural organization attempts to thwart, at least in part, modern neuroscientists' tendency to focus reductionistically on ever smaller microsystems. But although emphasizing higher levels of systems organization, the authors end up enforcing reductionisms of their own, principally the reduction of their domain to the study of invariable normal functioning, without explicit modeling of the deviations that constitute disease states or aging. This reductionism seriously weakens the authors' claims about the truth of their quantitative models.

Page has done connectionist researchers a valuable service in this target article. He points out that connectionist models using localized representations often work as well or better than models using distributed representations. I point out that models using distributed representations are difficult to understand and often lack parsimony and plausibility. In conclusion, I give an example – the case of the missing fundamental in music – that can easily be explained by a model using localist representations but can be explained only with great difficulty and implausibility by a model using distributed representations.

Neural organization has many facets; multiple descriptive levels and multiple analytical strategies coexist. Although most neuroscientists agree that a multidisciplinary, multistrategic approach is necessary to understand neural organization, diverse individual approaches make it difficult to find the optimal mixture and priority list.

The physics of color and the psychology of color naming are not isomorphic. Physically, the spectrum is continuous with regard to wavelength – one point in the spectrum differs from another only by the amount of wavelength difference. Psychologically, hue is categorical – colors change qualitatively from one wavelength region to another. The psychological characterization of hue that characterizes color vision hasbeen revealed in a series of modern psychophysical studies with human adults and infants and with various infrahuman species, including vertebrates and invertebrates. These biopsychological data supplant an older psycholinguistic and anthropological literature that posited that language and culture alone influence perceptual processes; language and culture may modify color naming beyond basic categorizations.

The tidal-wave theory is inspired by the particular morphology of the cerebellar cortex. It elegantly attributes function to the anisotropy of the cerebellar wiring and the geometry of Purkinje cell dendrites. In this commentary, physiological considerations are used to elaborate temporal and spatial constraints of the tidal-wave theory. It is shown, first, that limitations of temporal precision in the cortical inputs to the mammalian cerebellum delimit the spatial resolution of an input sequence (i.e., the minimal distance along the parallel fibers which can detect sequential input) to the range of a millimeter at best. Second, temporal characteristics of Purkinje cell postsynaptic potentials are argued to predict a distance of at least several millimeters along the parallel fiber beam in order to generate a sequence in the cerebellar output. It is concluded that the implementation of tidal waves as a general principle of cerebellar function is questionable as there exist cerebelli too small to match these constraints.

Saunders & van Brakel argue, inter alia, that there is “little evidence” for the claim that there are four unique hues (red, green, blue, and yellow), and that there are two corresponding opponent processes. We argue that this is quite mistaken.

The sequence-in/sequence-out cerebellar machinery is considered from the computational point of view. We outline a learning framework which discriminates short-term from long-term learning and is able to explain single-trial adaptation to unexpected loads.