Subjects have a rich history of decision making which would be expected to affect reasoning in new tasks. For example, averaging, a strategy that is effectively used in many decisions, may help explain the conjunction fallacy. Before resorting to accounts based on phylogeny, more parsimonious accounts in terms of ontogeny should be explored.

We discuss problematic theoretical and empirical issues and consider alternative explanations for Grodzinsky's hypotheses regarding receptive and expressive syntactic mechanisms in agrammatic aphasia. We also explore his claims pertaining to domain-specificity and neuroanatomical localization.

I begin with a characterization of neurolinguistic theories, trying to pinpoint some general properties that an account of brain/language relations should have. I then address specific criticisms made in the commentaries regarding the syntactic theory assumed in the target article, properties of the Trace Deletion Hypothesis (TDH) and the Tree-Pruning Hyothesis (TPH), other experimental results from aphasia, and findings from functional neuroimaging. Despite the criticism, the picture of the limited role of Broca's area remains unchanged.

Neuroanatomy and neurophysiology are insufficient to specify function. Modeling is essential to elucidate function, but psychophysics is also required. An example is the cognitive and sensorimotor branches of the visual system: anatomy shows direct cross talk between the branches. Psychophysics in normal humans shows links from cognitive to sensorimotor, but the reverse link is excluded by visual illusions affecting the cognitive system but not the sensorimotor system.

A proper evaluation of the biological significance of Pavlovian conditioning requires consideration of performance mechanisms. Domjan et al.'s definition of net benefit is simplistic, and their model promotes convergence in behaviour, ignoring the possibility of innovation.

The spatial time-frequency distribution matrix and associated Rényi entropy is proposed as the basis for a method that may be useful for estimating the significance of nonlocal neocortical interactions in the analysis of scalp EEG data. Implications of nonlocal interactions for source estimation are also considered.

Stanovich & West rely for many of their conclusions on correlations of reasoning tasks with SAT scores. The conclusions they draw are suspect because the SAT is not a particularly good measure of so-called g; g is not necessarily causal, SAT scores are no arbiter of what is true, and in any case it is not suprising that reasoning tests correlate with reasoning tests.

Not at all self-evident, the so-called isomorphisms between the phenomenology and physiology of dreams have been interpreted by Hobson et al. in an arbitrary manner to state that dreams are stimulated by chaotic brainstem stimulation (an assumption also adopted by Vertes & Eastman). I argue that this stimulation is not chaotic at all; nor does it occur in the absence of control from the cerebral cortex, which contributes complexity to brainstem activity as well as meaningful information worth consolidating in the brain during sleep.

[Hobson et al.; Vertes & Eastman]

The “problem” of dreaming in NREM sleep continues to challenge models that propose a causal relationship between REM mechanisms and the psychological features of dreaming. I suggest that, ultimately, efforts to identify correspondences among multiple levels of analysis will be more productive for dream theory than attempts to reduce dreaming to any one level of analysis.

[Hobson et al. ; Nielsen]

The distinction between abstract (rule-based) and contextual (intuitive) thinking is illustrated by studies of numeric versus linguistic expressions of probability. Verbal probabilities are believed to reflect intuitions that can be adaptive and occasionally normative (e.g., counteracting conjunction errors). Stanovich & West's interpretation of analytic thinking in terms of ability suggests a complementary ability perspective on intuitive thinking.

We applaud Domjan et al. for providing an elegant account of Pavlovian feed-forward mechanisms in social behavior that eschews the pitfall of purposivism. However, they seem to imply that they have provided a complete account without provision for operant conditioning. We argue that operant conditioning plays a central role in social behavior, giving examples from fish and infant behavior.

Current EEG research emphasizes gamma band coherence as a signature of functional integration, that is, the solution to the binding problem. We note that spatial patterns of coherent neural activity are also observed at other EEG frequencies. If these oscillations reflect Nunez's resonant modes, they offer a solution to the binding problem that emerges naturally from the architecture of cortical connections.

Neural organization raises, in an especially clear way, a major problem confronting contemporary cognitive science. The problem (the “big issue” of my title) is: What is the relation between the strategies used to solve basic problems of perception and action and those used to solve more abstract or “cognitive” problems? Is there a smooth, incremental route from what Arbib et al. call “instinctual schemas” to higher-level kinds of cognitive prowess? I argue that, despite some suggestive comments, Arbib et al. do not resolve this issue.

In the metaphor of behavioral momentum, the rate of a free operant in the presence of a discriminative stimulus is analogous to the velocity of a moving body, and resistance to change measures an aspect of behavior that is analogous to its inertial mass. An extension of the metaphor suggests that preference measures an analog to the gravitational mass of that body. The independent functions relating resistance to change and preference to the conditions of reinforcement may be construed as convergent measures of a single construct, analogous to physical mass, that represents the effects of a history of exposure to the signaled conditions of reinforcement and that unifies the traditionally separate notions of the strength of learning and the value of incentives. Research guided by the momentum metaphor encompasses the effects of reinforcement on response rate, resistance to change, and preference and has implications for clinical interventions, drug addiction, and self-control. In addition, its principles can be seen as a modern, quantitative version of Thorndike's (1911) Law of Effect, providing a new perspective on some of the challenges to his postulation of strengthening by reinforcement.

Violations and biases relative to normative principles of rationality tend to occur when the structure of task environments is novel or the decision goals are in conflict. The two blades of bounded rationality, the structure of task environments and the computational capacities of the actor, can sharpen the conceptual distinctions between the sources of the normative and descriptive gap.

This commentary focuses on the stimulus-reinforcer hypothesis of resistance to change. The overall context of reinforcement can account for resistance to extinction. There are ways to systematically test the hypothesis that Pavlovian contingencies account for the behavioral “mass” of discriminated operant behavior.

Domjan et al.'s model of how Pavlovian processes regulate social interaction can be extended to social learning, where an individual learns about the value of events, objects, or actions from information provided by another. The conditioned properties of a particular social partner, following from a history of interactions with that partner, can modulate the efficiency and specificity of social learning.

The biological theories of dreaming provide no explanation for the transduction from neuronal discharge to dreaming or waking consciousness. They cannot account for the variability in dream content between individuals or within individuals. Mind-brain isomorphism is poorly supported, as is dreaming's link to REM sleep. Biological theories of dreaming do not provide a function for dreaming nor a meaning for dreams. Evolutionary views of dreaming do not relate dream content to the current concerns of the dreamer and using the nightmare as the paradigm dream minimizes the impact of poor sleep on adaptations.

[Hobson et al.; Nielsen; Revonsuo; Solms]

Neural organization achieves its stated goal to “show how theory and experiment can supplement each other in an integrated, evolving account of structure, function, and dynamics” (p. ix), showing in a variety of contexts – from olfactory processing to spatial navigation, motor learning and more – how function may be realized in the neural tissue, with explanatory and predictive neural network models providing a cornerstone in this approach.

This commentary focuses on how bottom-up neocortical models can be developed into eigenfunction expansions of probability distributions appropriate to describe short-term memory in the context of scalp EEG. The mathematics of eigenfunctions are similar to the top-down eigenfunctions developed by Nunez, despite different physical manifestations. The bottom-up eigenfunctions are at the local mesocolumnar scale, whereas the top-down eigenfunctions are at the global regional scale. Our respective approaches have regions of substantial overlap, and future studies may expand top-down eigenfunctions into the bottom-up eigenfunctions, yielding a model of scalp EEG expressed in terms of columnar states of neocortical processing of attention and short-term memory.