Fundamental to spatial knowledge in all species are the representations underlying object recognition, object search, and navigation through space. But what sets humans apart from other species is our ability to express spatial experience through language. This target article explores the language of objects and places, asking what geometric properties are preserved in the representations underlying object nouns and spatial prepositions in English. Evidence from these two aspects of language suggests there are significant differences in the geometric richness with which objects and places are encoded. When an object is named (i.e., with count nouns), detailed geometric properties – principally the object's shape (axes, solid and hollow volumes, surfaces, and parts) – are represented. In contrast, when an object plays the role of either “figure” (located object) or “ground” (reference object) in a locational expression, only very coarse geometric object properties are represented, primarily the main axes. In addition, the spatial functions encoded by spatial prepositions tend to be nonmetric and relatively coarse, for example, “containment,” “contact,” “relative distance,” and “relative direction.” These properties are representative of other languages as well. The striking differences in the way language encodes objects versus places lead us to suggest two explanations: First, there is a tendency for languages to level out geometric detail from both object and place representations. Second, a nonlinguistic disparity between the representations of “what” and “where” underlies how language represents objects and places. The language of objects and places converges with and enriches our understanding of corresponding spatial representations.

The way people come to report private stimulation (e.g., feeling states) arising within their own bodies is not well understood. Although the Darwinian assumption of biological continuity has been the basis of extensive animal modeling for many human biological and behavioral phenomena, few have attempted to model human communication based on private stimulation. This target article discusses such an animal model using concepts and methods derived from the study of discriminative stimulus effects of drugs and recent research on interanimal communication. We discuss how humans acquire the capacity to identify and report private stimulation and we analyze intra- and interspecies differences in neurochemical mechanisms for transducing interoceptive stimuli, enzymatic and other metabolic factors, learning ability, and discrimination learning histories and their relation to psychiatric and developmental disabilities.

Human agents draw a variety of inferences effortlessly, spontaneously, and with remarkable efficiency – as though these inferences were a reflexive response of their cognitive apparatus. Furthermore, these inferences are drawn with reference to a large body of background knowledge. This remarkable human ability seems paradoxical given the complexity of reasoning reported by researchers in artificial intelligence. It also poses a challenge for cognitive science and computational neuroscience: How can a system of simple and slow neuronlike elements represent a large body of systemic knowledge and perform a range of inferences with such speed? We describe a computational model that takes a step toward addressing the cognitive science challenge and resolving the artificial intelligence paradox. We show how a connectionist network can encode millions of facts and rules involving n-ary predicates and variables and perform a class of inferences in a few hundred milliseconds. Efficient reasoning requires the rapid representation and propagation of dynamic bindings. Our model (which we refer to as SHRUTI) achieves this by representing (1) dynamic bindings as the synchronous firing of appropriate nodes, (2) rules as interconnection patterns that direct the propagation of rhythmic activity, and (3) long-term facts as temporal pattern-matching subnetworks. The model is consistent with recent neurophysiological evidence that synchronous activity occurs in the brain and may play a representational role in neural information processing. The model also makes specific psychologically significant predictions about the nature of reflexive reasoning. It identifies constraints on the form of rules that may participate in such reasoning and relates the capacity of the working memory underlying reflexive reasoning to biological parameters such as the lowest frequency at which nodes can sustain synchronous oscillations and the coarseness of synchronization.

As adults we believe that our knowledge of our own psychological states is substantially different from our knowledge of the psychological states of others: First-person knowledge comes directly from experience, but third-person knowledge involves inference. Developmental evidence suggests otherwise. Many 3-year-old children are consistently wrong in reporting some of their own immediately past psychological states and show similar difficulties reporting the psychological states of others. At about age 4 there is an important developmental shift to a representational model of the mind. This affects children's understanding of their own minds as well as the minds of others. Our sense that our perception of our own minds is direct may be analogous to many cases where expertise provides an illusion of direct perception. These empirical findings have important implications for debates about the foundations of cognitive science.

Folk psychology, the naive understanding of mental state concepts, requires a model of how people ascribe mental states to themselves. Competent speakers associate a distinctive memory representation (a category representation, CR) with each mentalistic word in their lexicon. A decision to ascribe such a word to oneself depends on matching to the CR an instance representation (IR) of one's current state. As in visual object recognition, evidence about a CR's content includes the IRs that are or are not available to trigger a match. This poses serious problems for functionalism, the theory-of-mind approach to the meaning of mental terms. A simple functionalist model is inadequate because (1) the relational and subjunctive (what would have happened) information it requires concerning target states is not generally available and (2) it could lead to combinatorial explosion. A modified functionalist model can appeal to qualitative (phenomenological) properties, but the earlier problems still reappear. Qualitative properties are important for sensations, propositional attitudes, and their contents, providing a model that need not refer to functional (causal-relational) properties at all. The introspectionist character of the proposed model does not imply that ascribing mental states to oneself is infallible or complete; nor is the model refuted by empirical research on introspective reports. Empirical research on “theory of mind” does not support any strict version of functionalism but only an understanding of mentalistic words that may depend on phenomenological or experiential qualities.

Common folks “have” emotions and talk to others; and sometimes they make “their” emotions the topic of such talk. The emotions seem to be “theirs,” since they can be conceived of as private states (or events); and they can be topicalized, because we seem to be able to attribute or lend a conventionalized public form (such as a linguistic label or name) to some inner (and therefore nonpublic) state or event. This is the way much of our folk-talk and folk-thinking about emotions, the expression thereof, the role of language in these expressions, and communication in general are organized. However, as we have shown (Bamberg & Lindenberger 1984), such talk serves the purpose of communicating effectively and reaching mutual understanding.