Feature Statistics Modulate the Activation of Meaning During Spoken Word Processing

Understanding spoken words involves a rapid mapping from speech to conceptual representations. One distributed feature‐based conceptual account assumes that the statistical characteristics of concepts’ features—the number of concepts they occur in (distinctiveness/sharedness) and likelihood of co‐occurrence (correlational strength)—determine conceptual activation. To test these claims, we investigated the role of distinctiveness/sharedness and correlational strength in speech‐to‐meaning mapping, using a lexical decision task and computational simulations. Responses were faster for concepts with higher sharedness, suggesting that shared features are facilitatory in tasks like lexical decision that require access to them. Correlational strength facilitated responses for slower participants, suggesting a time‐sensitive co‐occurrence‐driven settling mechanism. The computational simulation showed similar effects, with early effects of shared features and later effects of correlational strength. These results support a general‐to‐specific account of conceptual processing, whereby early activation of shared features is followed by the gradual emergence of a specific target representation.     

Conceptual Hierarchies in a Flat Attractor Network: Dynamics of Learning and Computations

The structure of people's conceptual knowledge of concrete nouns has traditionally been viewed as hierarchical ( Collins & Quillian, 1969 ). For example, superordinate concepts ( vegetable ) are assumed to reside at a higher level than basic-level concepts ( carrot ). A feature-based attractor network with a single layer of semantic features developed representations of both basic-level and superordinate concepts. No hierarchical structure was built into the network. In Experiment and Simulation 1, the graded structure of categories (typicality ratings) is accounted for by the flat attractor network. Experiment and Simulation 2 show that, as with basic-level concepts, such a network predicts feature verification latencies for superordinate concepts ( vegetable ). In Experiment and Simulation 3, counterintuitive results regarding the temporal dynamics of similarity in semantic priming are explained by the model. By treating both types of concepts the same in terms of representation, learning, and computations, the model provides new insights into semantic memory.     

From Complexity Concepts to Creative Applications

A complexity cosmography is introduced as construing a world that is self-organizing, dynamic, and emergent, and that comprises organic entities that too are self-organizing, dynamic, and emergent. Following critical reflection into the nature of utilising complexity in social inquiry, specific images, vocabularies and complexity-based methods and techniques as developed by the authors are introduced.     

Trust and Goodwill as Attractors: Reflecting on a Complexity-Informed Inquiry

This article discusses a complexity-informed review and evaluation project. Complexity-informed methods and techniques are used to fashion understanding of the relationships and processes implicated between the service agencies constituting the Youth Accommodation Interagency—Nepean (YAIN) and their Resource Worker, the influence of these relationships and processes on the achievement of desired and required goals, and the potential for replication of these relationships and processes elsewhere. The article concludes with critical reflection regarding what was learnt from utilizing complexity in this qualitative inquiry.     

Robustness to temporal constraint explains expertise in ball-over-net sports

The present study investigated motor expertise in interpersonal competitive ball-over-net sports in terms of a dynamical system with temporal input. In a theoretical framework, the behavior of the system is characterized by a fractal-like structure according to switching input, which changes uniquely according to the duration of input and internal parameter of the system. We investigated periodic movements, in which the player executed a forehand or backhand stroke repeatedly, and continuous switching movements, in which the player continuously switched between two movement patterns corresponding to hitting the ball under two ball directions and with six temporal constraint conditions during a table tennis rally. In the periodic movement, we observed two limit-cycle attractors corresponding to each direction in the phase space independent of temporal constraint or skill level. Conversely, in the continuous switching movement, a transition in trajectories between the two limit-cycle attractors was observed in the phase space, and this transition was characterized by a fractal-like structure. The fractal-like structure moved closer to the random structure as temporal constraint increased independent of skill level. However, the temporal constraint condition closest to the random structure was higher for the advanced players than for the novices, indicating that robustness to the temporal constraint was higher for the advanced players than for the novices. Our results suggest that motor expertise in interpersonal competitive ball-over-net sports is more robust to temporal constraints with various inputs.     

The emergence of personality: Dynamic foundations of individual variation

We conceptualize personality and individual variation from the perspective of dynamical systems. People’s thoughts, feelings, and predispositions for action are inherently dynamic, displaying constant change due to internal mechanisms and external forces, but over time the flow of thought and action converges on a narrow range of states—a fixed-point attractor—that provides cognitive, affective, and behavioral stability. An attractor for personal dynamics develops through two mechanisms: the synchronization of individuals’ internal states in social interaction, and the self-organization of thoughts and feelings with respect to a higher-order property (e.g., goal, self-concept). We present formal models of both processes and instantiate each in computer simulations. Discussion centers on the implications of interpersonal synchronization and self-organization dynamics for issues in personality psychology, including shared vs. non-shared environmental influences on personality development, the expression of personality in social interaction, personal stability vs. change, personal vs. situational causation, and the emergence of self-concept.     

Rating the similarity of simple perceptual stimuli: asymmetries induced by manipulating exposure frequency.

When judging the similarity of two stimuli, people's ratings often differ depending on the order in which the comparison is presented (A vs. B or B vs. A). Such directional asymmetries have typically been demonstrated using complex concepts that have a large number of semantic features and a standard explanation is that different sets of features are emphasized depending on the direction of the comparison. In this study, we show that directional asymmetries in the similarity of simple perceptual stimuli can be predictably manipulated merely by presenting each member of a pair with different frequency. Participants rated the similarity of color patches before and after performing an irrelevant training task in which a subset of colors was presented ten times more frequently than others. The similarity ratings after training were significantly more asymmetric than the ratings before training. We discuss the implications of these findings for models of similarity judgment and propose a computationally explicit explanation based on asymmetries in representational stability.     

Identification and integration of sensory modalities: Neural basis and relation to consciousness

A key question in studying consciousness is how neural operations in the brain can identify streams of sensory input as belonging to distinct modalities, which contributes to the representation of qualitatively different experiences. The basis for identification of modalities is proposed to be constituted by self-organized comparative operations across a network of unimodal and multimodal sensory areas. However, such network interactions alone cannot answer the question how sensory feature detectors collectively account for an integrated, yet phenomenally differentiated experiential content. This problem turns out to be different from, although related to, the binding problem. It is proposed that the neural correlate of an enriched, multimodal experience is constituted by the attractor state of a dynamic associative network. Within this network, unimodal and multimodal sensory maps continuously interact to influence each other’s attractor state, so that a feature change in one modality results in a fast re-coding of feature information in another modality. In this scheme, feature detection is coded by firing-rate, whereas firing phase codes relational aspects.