On a common circle: natural scenes and Gestalt rules

To understand how the human visual system analyzes images, it is essential to know the structure of the visual environment. In particular, natural images display consistent statistical properties that distinguish them from random luminance distributions. We have studied the geometric regularities of oriented elements (edges or line segments) present in an ensemble of visual scenes, asking how much information the presence of a segment in a particular location of the visual scene carries about the presence of a second segment at different relative positions and orientations. We observed strong long-range correlations in the distribution of oriented segments that extend over the whole visual field. We further show that a very simple geometric rule, cocircularity, predicts the arrangement of segments in natural scenes, and that different geometrical arrangements show relevant differences in their scaling properties. Our results show similarities to geometric features of previous physiological and psychophysical studies. We discuss the implications of these findings for theories of early vision.Comment: 3 figures, 2 large figures not include

Ambiguous figures and the content of experience

Representationalism is the position that the phenomenal character of an experience is either identical with, or supervenes on, the content of that experience. Many representationalists hold that the relevant content of experience is nonconceptual. I propose a counterexample to this form of representationalism that arises from the phenomenon of Gestalt switching, which occurs when viewing ambiguous figures. First, I argue that one does not need to appeal to the conceptual content of experience or to judgements to account for Gestalt switching. I then argue that experiences of certain ambiguous figures are problematic because they have different phenomenal characters but that no difference in the nonconceptual content of these experiences can be identified. I consider three solutions to this problem that have been proposed by both philosophers and psychologists and conclude that none can account for all the ambiguous figures that pose the problem. I conclude that the onus is on representationalists to specify the relevant difference in content or to abandon their position

Relations at Three Early Stages of Marriage as Reflected by the Use of Personal Pronouns

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/71573/1/j.1545-5300.1970.00069.x.pd

Formalized Conceptual Spaces with a Geometric Representation of Correlations

The highly influential framework of conceptual spaces provides a geometric way of representing knowledge. Instances are represented by points in a similarity space and concepts are represented by convex regions in this space. After pointing out a problem with the convexity requirement, we propose a formalization of conceptual spaces based on fuzzy star-shaped sets. Our formalization uses a parametric definition of concepts and extends the original framework by adding means to represent correlations between different domains in a geometric way. Moreover, we define various operations for our formalization, both for creating new concepts from old ones and for measuring relations between concepts. We present an illustrative toy-example and sketch a research project on concept formation that is based on both our formalization and its implementation.Comment: Published in the edited volume "Conceptual Spaces: Elaborations and Applications". arXiv admin note: text overlap with arXiv:1706.06366, arXiv:1707.02292, arXiv:1707.0516

Preferred Spatial Frequencies for Human Face Processing Are Associated with Optimal Class Discrimination in the Machine

Psychophysical studies suggest that humans preferentially use a narrow band of low spatial frequencies for face recognition. Here we asked whether artificial face recognition systems have an improved recognition performance at the same spatial frequencies as humans. To this end, we estimated recognition performance over a large database of face images by computing three discriminability measures: Fisher Linear Discriminant Analysis, Non-Parametric Discriminant Analysis, and Mutual Information. In order to address frequency dependence, discriminabilities were measured as a function of (filtered) image size. All three measures revealed a maximum at the same image sizes, where the spatial frequency content corresponds to the psychophysical found frequencies. Our results therefore support the notion that the critical band of spatial frequencies for face recognition in humans and machines follows from inherent properties of face images, and that the use of these frequencies is associated with optimal face recognition performance

Nonlinear Dynamics and Interpersonal Correlates of Verbal Turn-Taking Patterns in a Group Therapy Session

Interpersonal processes and dynamics are ubiquitous topics in psychotherapy, yet they are difficult to study and are theoretically fragmented across therapeutic subdisciplines. The current study tests an integrative model of interpersonal dynamics in small groups using nonlinear dynamical systems theory. The conversation of one group therapy session (with six adolescent sex offenders) is analyzed using orbital decomposition, which allows for the identification of patterns in categorical time series data. The results show evidence of selforganizing social patterns, based on formal measures of turbulence (Lyapunov dimension), information novelty (Shannon\u27s entropy), and complexity (fractal dimension). The degree of patterning in turn taking is significantly correlated with measurements of control, closeness, and conflict among group members. Clinical implications and directions for future research are discussed