Although there is empirical evidence of neural filling-in, this does not necessarily entail “isomorphic” theory. Most cortical neurons do not respond to a uniform surface and are instead sensitive to surface size and quality. I propose that a population of such neurons encodes the presence of a surface. This scheme is different from either the “cognitive” or “isomorphic” theories.

Although cognitive psychology is still dominated by computational theories, there is an emerging emphasis on dynamical aspects of cognition. Examples are provided supporting the increased use of dynamically inspired models by psychologists. Despite measurement and model verification problems in the direct use of dynamical system theoretic technology, van Gelder's general approach to cognition is recommended.

Another objection to the dynamical hypothesis is explored. To resolve it completely, one must focus more directly on an area not emphasized in van Gelder's discussion: the contributions of dynamical systems theory to understanding how cognition is neutrally implemented.

It is argued that feature creation may not only depend on categorical distinctions that are made during category learning, but also on the choice set during subsequent categorization.

Chow attacks statistical power analysis on theoretical grounds. I argue that if significance testing is defensible, so is power analysis. A number of Chow's criticisms seem to suggest that power analysts are confused about certain fundamental issues. I claim that few power analysts make the mistakes Chow describes. Finally, I address Chow's claim that power analysis is irrelevant to NHSTP because it deals with a different issue.

The filling-in process proposed as a cover up for the existence of the blind spot has some conceptual similarities to blindsight. The perceptual operation of a hypothetical mechanism responsible for filling in represents a logical paradox. The apparent indeterminacy of the percept in the optic-disc region can be tested experimentally by viewing the grating test pattern below.

A number of commentators agree that the evidence reviewed in the target article supports a previously unrecognized role for ovarian hormones in feminization of the brain. Others question this view, suggesting that the traditional model of sexual differentiation already accounts for ovarian influence. This position is supported by various reinterpretations of the data presented (e.g., ovarian effects are secondary to the presence/absence of androgen, ovarian effects are smaller than testicular effects, ovarian effects are not organizational). We discuss these issues, and reiterate our position that evidence of neurobehavioral ovarian effects is incompatible with the currently accepted model of sexual differentiation. Other points regarding species generalizations, the direct versus indirect action of estrogen, and nonhormonal mechanisms of sexual differentiation are also discussed. Finally, we address the controversial issue of using ratio scores in the assessment of the human corpus callosum (where CC scores are divided by an index of brain size). Future applications to human research are also discussed.

Representation of similarities is not sufficient for most visual tasks. The proposed framework collapses useful dimensions such as position and pose for the sake of naming the object. Collapsing these dimensions leaves no representation of the object itself, but only an internal name that cannot be meaningfully manipulated.

Mazur & Booth fail to consider the conceptual complexities of dominance; it is unlikely that there is a motive to dominate in animals. Also, the lack of empirical evidence for a causal link between testosterone and dominance is obscured by the narrative reviewing procedure, which is prone to bias.

Cognitive theories based on a fixed feature set suffer from frame and symbol grounding problems. Flexible features and other empirically acquired constraints (e.g., analog-to-analog mappings) provide a framework for letting extrinsic relations influence symbol manipulation. By offering a biologically plausible basis for feature learning, nonorthogonal multiresolution analysis and dimensionality reduction, informed by functional constraints, may contribute to a solution to the symbol grounding problem.

Edelman suggests that any shape is encoded by an excitation vector with components corresponding to excitations of corresponding neuronal modules. This results in discrimination of stimuli in a shape space of low dimensionality. Similar vector encoding is present in color vision. Red-green, blue-yellow, bright and dark neurons are modules that represent a number of different color stimuli in color space of low dimensionality. Vector encoding allows effective computation of color differences and color similarities. Such a neuronal vector-encoding approach has also been applied to the perception of visual movement, line orientation, and stereopsis.

The Gestalt principle of isomorphism reveals the primacy of subjective experience as a valid source of evidence for the information encoded neurophysiologically. This theory invalidates the abstractionist view that the neurophysiological representation can be of lower dimensionality than the percept to which it gives rise.

What van Gelder calls the dynamical hypothesis is only a special case of what we here dub the general dynamical hypothesis. His terminology makes it easy to overlook important alternative dynamical approaches in cognitive science. Connectionist models typically conform to the general dynamical hypothesis, but not to van Gelder's.

We take up two issues discussed by Chow: the claim by critics of hypothesis testing that the null hypothesis (H0) is always false, and the claim that reporting effect sizes is more appropriate than relying on statistical significance. Concerning the former, we agree with Chow's sentiment despite noting serious shortcomings in his discussion. Concerning the latter, we agree with Chow that effect size need not translate into scientific relevance, and furthermore reiterate that with small samples effect size measures cannot substitute for significance.

Cognitive systems are wilder than today's dynamical systems theory can handle. Cognitive systems might be tamed in principle, but the very notion of a dynamical system will change in the process.

Representationalism emerges unscathed from Pessoa et al.'s attack. They fail to undermine a key reason for its influence: it has the theoretical resources to explain many illusory visual experiences such as illusory contours and features. Furthermore, in attempting to undermine representationalism, the authors seem to erect an unduly inflated distinction between neural accounts of perception and personal-level accounts of perception.

The usefulness of effect-size differs in utilitarian experiments from its use in theory corroborations. Chow introduces the question of the relationship of effect-size to practical validity and the role of the assessment of “importance” in this. This review develops this question and suggests the actuarial table as a replacement for effect-size in practical decision-making.

In men, high levels of endogenous testosterone (T) seem to encourage behavior intended to dominate – to enhance one's status over – other people. Sometimes dominant behavior is aggressive, its apparent intent being to inflict harm on another person, but often dominance is expressed nonaggressively. Sometimes dominant behavior takes the form of antisocial behavior, including rebellion against authority and law breaking. Measurement of T at a single point in time, presumably indicative of a man's basal T level, predicts many of these dominant or antisocial behaviors. T not only affects behavior but also responds to it. The act of competing for dominant status affects male T levels in two ways. First, T rises in the face of a challenge, as if it were an anticipatory response to impending competition. Second, after the competition, T rises in winners and declines in losers. Thus, there is a reciprocity between T and dominance behavior, each affecting the other. We contrast a reciprocal model, in which T level is variable, acting as both a cause and effect of behavior, with a basal model, in which T level is assumed to be a persistent trait that influences behavior. An unusual data set on Air Force veterans, in which data were collected four times over a decade, enables us to compare the basal and reciprocal models as explanations for the relationship between T and divorce. We discuss sociological implications of these models.

The neural basis of the Chorus model has been cast in terms of the visual alphabet theory, but the neural evidence can also be interpreted as supporting a theory of higher level representation in which neurons are responsive to complex 3D stimuli. These neurons, functioning as a population, could also form the basis of a representation such as envisaged by the Chorus model.

Schyns, Goldstone & Thibaut oppose the notion of fixed feature analysis, suggesting the possibility of flexible feature creation in object recognition and categorisation. Such proposals cannot be assessed until clear definitions of the objects in question and their decompositions are formulated. Flexibility may come from the decompositions of objects rather than from feature creation.