Semantic form as interface

The term interface had a remarkable career over the past several decades, motivated largely by its use in computer science. Although the concept of a "surface common to two areas" (Oxford Advanced Learner's Dictionary, 1980) is intuitively clear enough, the range of its application is not very sharp and well defined, a "common surface" is open to a wide range of interpretations

On staying grounded and avoiding Quixotic dead ends

The 15 articles in this special issue on The Representation of Concepts illustrate the rich variety of theoretical positions and supporting research that characterize the area. Although much agreement exists among contributors, much disagreement exists as well, especially about the roles of grounding and abstraction in conceptual processing. I first review theoretical approaches raised in these articles that I believe are Quixotic dead ends, namely, approaches that are principled and inspired but likely to fail. In the process, I review various theories of amodal symbols, their distortions of grounded theories, and fallacies in the evidence used to support them. Incorporating further contributions across articles, I then sketch a theoretical approach that I believe is likely to be successful, which includes grounding, abstraction, flexibility, explaining classic conceptual phenomena, and making contact with real-world situations. This account further proposes that (1) a key element of grounding is neural reuse, (2) abstraction takes the forms of multimodal compression, distilled abstraction, and distributed linguistic representation (but not amodal symbols), and (3) flexible context-dependent representations are a hallmark of conceptual processing

Semantic memory redux: an experimental test of hierarchical category representation

Four experiments investigated the classic issue in semantic memory of whether people organize categorical information in hierarchies and use inference to retrieve information from them, as proposed by Collins & Quillian (1969). Past evidence has focused on RT to confirm sentences such as “All birds are animals” or “Canaries breathe.” However, confounding variables such as familiarity and associations between the terms have led to contradictory results. Our experiments avoided such problems by teaching subjects novel materials. Experiment 1 tested an implicit hierarchical structure in the features of a set of studied objects (e.g., all brown objects were large). Experiment 2 taught subjects nested categories of artificial bugs. In Experiment 3, subjects learned a tree structure of novel category hierarchies. In all three, the results differed from the predictions of the hierarchical inference model. In Experiment 4, subjects learned a hierarchy by means of paired associates of novel category names. Here we finally found the RT signature of hierarchical inference. We conclude that it is possible to store information in a hierarchy and retrieve it via inference, but it is difficult and avoided whenever possible. The results are more consistent with feature comparison models than hierarchical models of semantic memory

On the assimilation of instructions : stimulus-response associations are implemented but not stimulus-task associations

The assimilation of instructions consists of two stages. First, a task model is formed on the basis of instructions. Second, this model is implemented, resulting in highly accessible representations, which enable reflexive behavior that guides the application of instructions. Research frequently demonstrated that instructions can lead to automatic response activation, which indicates that stimulus-response associations can be implemented on the basis of a task model. However, instructions not only indicate how to respond (stimulus-response mappings) but also when (i.e., the conditions under which mappings apply). Accordingly, we tested whether instruction implementation leads both to the activation of stimulus-response associations and of associations between stimuli and the context or task in which the instructed stimulus-response mappings are relevant (i.e., stimulus-task associations). In four experiments, we measured if implementing newly instructed stimulus-response mappings also leads to bivalence costs (i.e., shorter latencies when a stimulus can only occur in one task compared to when it can occur in two tasks), which indicate the presence of stimulus-task associations. We consistently observed automatic response activation on the basis of instructions, but no bivalence costs. A discrepancy thus exists between information conveyed in an instructed task model and the elements of that task model that are implemented. We propose that future research on automatic effects of instructions should broaden its scope and focus both on the formation of an instructed task model and its subsequent implementation

Techniques for augmenting the visualisation of dynamic raster surfaces

Despite their aesthetic appeal and condensed nature, dynamic raster surface representations such as a temporal series of a landform and an attribute series of a socio-economic attribute of an area, are often criticised for the lack of an effective information delivery and interactivity.In this work, we readdress some of the earlier raised reasons for these limitations -information-laden quality of surface datasets, lack of spatial and temporal continuity in the original data, and a limited scope for a real-time interactivity. We demonstrate with examples that the use of four techniques namely the re-expression of the surfaces as a framework of morphometric features, spatial generalisation, morphing, graphic lag and brushing can augment the visualisation of dynamic raster surfaces in temporal and attribute series

Word contexts enhance the neural representation of individual letters in early visual cortex

Visual context facilitates perception, but how this is neurally implemented remains unclear. One example of contextual facilitation is found in reading, where letters are more easily identified when embedded in a word. Bottom-up models explain this word advantage as a post-perceptual decision bias, while top-down models propose that word contexts enhance perception itself. Here, we arbitrate between these accounts by presenting words and nonwords and probing the representational fidelity of individual letters using functional magnetic resonance imaging. In line with top-down models, we find that word contexts enhance letter representations in early visual cortex. Moreover, we observe increased coupling between letter information in visual cortex and brain activity in key areas of the reading network, suggesting these areas may be the source of the enhancement. Our results provide evidence for top-down representational enhancement in word recognition, demonstrating that word contexts can modulate perceptual processing already at the earliest visual regions