Nicholas Baker

Physiological and psychophysical evidence suggests that the visual system represents object outlines using prominent curvature features, particularly regions of extreme curvature (convex maxima and concave minima). These curvature extrema often coincide with points of high informational content (“surprisal”), but this relationship is only correlational. It remains unclear whether the visual system explicitly encodes curvature extrema or instead prioritizes the most informative contour locations. To address this, we conducted two shape-matching experiments comparing the roles of curvature extrema and surprisal in shape representation. Observers performed match-to-sample tasks in which smooth reference shapes were matched to simplified polygonal versions created by connecting subsets of contour points corresponding to (i) curvature maxima, (ii) curvature maxima and minima, or (iii) points of highest surprisal. Stimuli included artificial shapes composed of compound radial frequency patterns and natural shapes (animal outlines), the latter allowing us to dissociate curvature and information by restricting sampled points. Performance was higher for natural than artificial shapes (95% vs. ∼86%). Shapes defined by a small number of high-surprisal points matched performance in baseline and curvature maxima and minima conditions, but exceeded performance for curvature maxima alone (∼90% vs. ∼65%). In a second experiment, we contrasted surprisal with curvature maxima and minima conditions while varying the number of sampled points (4–32). Performance increased with point number, approaching ∼90%. Critically, under strong simplification (4–6 points), surprisal-based shapes yielded higher accuracy than curvature-based shapes. These findings suggest that shape representation emphasizes features with high informational content rather than curvature extrema per se.

The aim of this chapter is to provide a primer on structured mental representations and their place in philosophical and scientific theorizing. We discuss four questions: 1. What does it mean to say that a psychological representation is structured? 2. Why does a representation’s structure matter? 3. What are examples of possible representational structures? 4. How can such representational structures be discovered empirically? We encourage several pluralist perspectives concerning structured mental representation. The first is pluralism about which mental capacities make use of structured representations. Structured representations are not exclusive to evolutionarily and cognitively advanced faculties of language, thought, and reasoning; they underwrite a wide variety of mental capacities. The second perspective is pluralism about the neural underpinnings of representational structures. There are many ways a structured representation might be realized in populations of cells. The third perspective concerns pluralism about types of representational structure. Structured representations are not restricted to sentences and formulas; they can take a wide variety of forms.

The Wnt family of developmental regulators were named after the Drosophila segmentation gene wingless and the murine proto‐oncogene int‐1. Homology between these two genes connected oncogenesis to cell‐cell signals in development. I review how wingless was initially characterized, and cloned, as part of the quest to identify developmental cell‐to‐cell signals, based on predictions of the Positional Information Model, and on the properties of homeotic and segmentation gene mutants. The requirements and cell‐nonautonomy of wingless in patterning multiple embryonic and adult structures solidified its status as a candidate signaling molecule. The physical location of wingless mutations and transcription unit defined the gene and its developmental transcription pattern. When the Drosophila homolog of int‐1 was then isolated, and predicted to encode a secreted proto‐oncogene homolog, it's identity to the wingless gene confirmed that a developmental cell‐cell signal had been identified and connected cancer to development.

Much progress has been made recently towards uncovering the mechanisms that control the size to which organisms and their organs grow, and identifying some of the genes responsible. Size control, however, is only half of the equation. In growing to the right size, tissues must also grow to the right shape. A recent paper1 suggests that a hitherto overlooked cellular behaviour governs the size and shape of a growing tissue, and issues a challenge to developmental biologists to identify the molecular mechanisms involved. BioEssays 25:5–8, 2003. © 2002 Wiley Periodicals, Inc.