The additional data, perspectives, questions, and criticisms contributed by the commentaries strengthen our view that local cortical processors coordinate their activity with the context in which it occurs using contextual fields and synchronized population codes. We therefore predict that whereas the specialization of function has been the keynote of this century the coordination of function will be the keynote of the next.

It is worthwhile to search for forms of coding, processing, and learning common to various cortical regions and cognitive functions. Local cortical processors may coordinate their activity by maximizing the transmission of information coherently related to the context in which it occurs, thus forming synchronized population codes. This coordination involves contextual field (CF) connections that link processors within and between cortical regions. The effects of CF connections are distinguished from those mediating receptive field (RF) input; it is shown how CFs (...) can guide both learning and processing without becoming confused with the transmission of RF information. Simulations explore the capabilities of networks built from local processors with both RF and CF connections. Physiological evidence for synchronization, CFs, and plasticity of the RF and CF connections is described. Coordination via CFs is related to perceptual grouping, the effects of context on contrast sensitivity, amblyopia, implicit influences of color in achromotopsia, object and word perception, and the discovery of distal environmental variables and their interactions through self-organization. Cortical computation could thus involve the flexible evaluation of relations between input signals by locally specialized but adaptive processors whose activity is dynamically associated and coordinated within and between regions through specialized contextual connections. Key Words: cell assemblies; cerebral cortex; context; coordination; dynamic binding; epistemology; functional specialization; learning; neural coding; neural computation; neuropsychology; object recognition; perception; reading; self-organization; synaptic plasticity; synchronization. (shrink)

Although Barresi & Moore could have grounded their framework more explicitly in existing models, they offer a provocative testbed for the assumptions of symbolic interactionism and further thinking about self-regulation, especially in autistics.

Barresi & Moore provide an impressive account of how the coordination of first and third person information about the self and other could produce an account of intentional relations. They are less explicit as to how the child comes to understand the basic epistemic relation between experience and knowledge, that is, how informational access causes belief. We suggest one route.

This paper argues that humans possess unique cognitive abilities due to the presence of a functional system that exists in the human brain that is absent in the non-human brain. This system, the frontal feedback system, was born in the hominin brain when the great phylogenetic expansion of the prefrontal cortex relative to posterior sensory regions surpassed a critical threshold. Surpassing that threshold effectively reversed the preferred direction of information flow in the highest association regions of the neocortex, producing the (...) frontal feedback system. This reversal was from the caudo-rostral bias characteristic of non-human, or pre-human, brain dynamics to a rostro-caudal bias characteristic of modern human brain dynamics. The frontal feedback system works through frontal motor routines, or action schemes, manipulating the release and reconstruction of stored sensory memories in posterior sensory areas. As an obligatory feature of frontal feedback, a central character, or self, emerges within this cortical network that manifests itself as agent in these reconstructions as well as in the experience of sensory perceptions. Dynamical-systems modeling of cortical interactions is combined in the paper with recent neuroimaging studies of “resting-state” brain activity to bridge the gap between microscopic and macroscopic levels of cortical behavior. This synthesis is used to support the proposal of an information flow reversal occurring in the hominin brain and also to explain how such a reversal generates the wide variety of cognitive and experiential phenomena that many consider to be uniquely human. (shrink)

The intentionality schema is an abstraction that relates phylogenetic and ontogenetic sequences of social understanding, but it also obscures the differences between humans and other primates. In particular, it ignores human social developmental and communicative history and the important roles that language plays in human understanding of others' intentional states.

The intentional schema may not be sufficiently characterized to make questions about its role in individual and species development intelligible. The idea of metarepresentation may perhaps give it enough content. The importance of metarepresentation itself, however, can be called into question.

The “intentional schema” seems identical to or dependent upon kinesthetic–visual matching, both of which account for similar empirical findings. The intentional schema, however, fails to account for variability in children's understanding of false belief and differences in children's understanding of self and other in pretense.

In the first section of the article, we examine some recent criticisms of the connectionist enterprise: first, that connectionist models are fundamentally behaviorist in nature (and, therefore, non-cognitive), and second that connectionist models are fundamentally associationist in nature (and, therefore, cognitively weak). We argue that, for a limited class of connectionist models (feed-forward, pattern-associator models), the first criticism is unavoidable. With respect to the second criticism, we propose that connectionist modelsare fundamentally associationist but that this is appropriate for building models (...) of human cognition. However, we do accept the point that there are cognitive capacities for which any purely associative model cannot provide a satisfactory account. The implication that we draw from is this is not that associationist models and mechanisms should be scrapped, but rather that they should be enhanced.In the next section of the article, we identify a set of connectionist approaches which are characterized by “active symbols” — recurrent circuits which are the basis of knowledge representation. We claim that such approaches avoid criticisms of behaviorism and are, in principle, capable of supporting full cognition. In the final section of the article, we speculate at some length about what we believe would be the characteristics of a fully realized active symbol system. This includes both potential problems and possible solutions (for example, mechanisms needed to control activity in a complex recurrent network) as well as the promise of such systems (in particular, the emergence of knowledge structures which would constitute genuine internal models). (shrink)

Barresi & Moore provide a welcome focus on children's abilities to integrate first and third person information about intentional relations but they pay insufficient attention to the origins of children's understanding of the nature of subjective orientations vis-à-vis a shared world and the potential significance of such understanding as a source (rather than an outcome) of domain-general information-processing capacities.

Immediate imitation is likely to be a major, direct input to Barresi & Moore's level 2 competence, but deferred imitation is unlikely to play a key role in the transition to level 3, because (1) the attribution of first person knowledge is neither a necessary cause nor an obvious consequence of deferred imitation, and (2) deferred imitation does not correlate phylogenetically with capacities that more plausibly either yield or reflect a concept of intentional agency.