Integrating the Automatic and the Controlled: Strategies in Semantic Priming in an Attractor Network With Latching Dynamics

Semantic priming has long been recognized to reflect, along with automatic semantic mechanisms, the contribution of controlled strategies. However, previous theories of controlled priming were mostly qualitative, lacking common grounds with modern mathematical models of automatic priming based on neural networks. Recently, we introduced a novel attractor network model of automatic semantic priming with latching dynamics. Here, we extend this work to show how the same model can also account for important findings regarding controlled processes. Assuming the rate of semantic transitions in the network can be adapted using simple reinforcement learning, we show how basic findings attributed to controlled processes in priming can be achieved, including their dependency on stimulus onset asynchrony and relatedness proportion and their unique effect on associative, category‐exemplar, mediated and backward prime‐target relations. We discuss how our mechanism relates to the classic expectancy theory and how it can be further extended in future developments of the model.     

A Network Perspective on the Processes of Empowered Organizations

Organizational empowerment is a multi-faceted concept that involves processes occurring both within and between organizations that facilitate achievement of their goals. This paper takes a closer look at three interorganizational processes that lead to empowered organizations: building alliances, getting the word out, and capturing others’ attention. These processes are located within the broader nomological network of empowerment and organizational empowerment, and are linked to particular patterns of interorganizational relationships that facilitate organizations’ ability to engage in them. A new network-based measure, γ-centrality, is introduced to capture the particular network structure associated with each process to be assessed. It is demonstrated first in a hypothetical organizational network, then applied to take a closer look at organizational empowerment in the context of a coordinating council composed of human service agencies. The paper concludes with a discussion of the implications of relationships between these processes, and the potential for unintended consequences in the empowerment of organizations.     

Rethinking parafoveal processing in reading: Serial-attention models can explain semantic preview benefit and N+2 preview effects

During reading, some information about the word to the right of fixation in the parafovea is typically acquired prior to that word being fixated. Although some degree parafoveal processing is uncontroversial, its precise nature and extent are unclear. For example, can it advance up to the level of semantic processing? Additionally, can it extend across more than two spatially adjacent words? Affirmative answers to either of these questions would seemingly be problematic for serial-attention models of eye-movement control in reading, which maintain that attention is allocated to only one word at a time (see Reichle, 2011). However, in this paper we report simulation results using one such model, E-Z Reader (Reichle, Pollatsek, Fisher, & Rayner, 1998), to examine the two preceding questions. These results suggest the existence of both semantic preview and N+2 preview effects, indicating that they are not incompatible with serial-attention models. We discuss the implications of these findings for models of eye-movement control in reading and provide a new theoretical framework for conceptualizing parafoveal processing during reading and its influence on eye movement behaviour.     

The network of conscientiousness

According to the network perspective, the coalescence of several personality characteristics into major personality dimensions results from a pattern of complex interactions that can be modeled as a network. We focused on one personality dimension, conscientiousness, and on its main facets. We administered a large battery of questionnaires to two samples (N = 210 and N = 230) and analyzed them by means of network analysis. The results showed that some elements of the network, such as general self-control and orientation toward the future, characterized all facets. These “shared” elements could be responsible for the facets to clump into one major dimension. Other elements of the network uniquely characterized different facets. These “unique” elements could underlie the main differences among conscientiousness facets.     

Generalisation of fear and avoidance along a semantic continuum

Directly conditioned fear and avoidance readily generalises to dissimilar but conceptually related stimuli. Here, for the first time, we examined the conceptual/semantic generalisation of both fear and avoidance using real words (synonyms). Participants were first exposed to a differential fear conditioning procedure in which one word (e.g., “broth”; CS+) was followed with brief electric shock [unconditioned stimulus (US)] and another was not (e.g., “assist”; CS–). Next, an instrumental conditioning phase taught avoidance in the presence the CS+ but not the CS–. During generalisation testing, synonyms of the CS+ (e.g., “soup”; GCS+) and CS– (e.g., “help”; GCS–) were presented in the absence of shock. Conditioned fear and avoidance, measured via skin conductance responses, behavioural avoidance and US expectancy ratings, generalised to the semantically related, but not to the semantically unrelated, synonyms. Findings have implications for how natural language categories and concepts mediate the expansion of fear and avoidance repertoires in clinical contexts.     

An adaptive temporal-causal network model to analyse extinction of communication over time

The persistence of information communicated between humans is difficult to measure as it is affected by many features. This paper presents an approach to computationally model the cognitive processes of information sharing to describe persistence or extinction of communication in Twitter over time. The adaptive mental network model explains, for example, how an individual can experience information overflow on a topic, and how this affects the sharing of information. Parameter tuning by Simulated Annealing is used to identify characteristics of the network model that fit to empirical data from Twitter. The data collected is related to the independentism in Catalunya, Spain, which is considered a global issue with repercussion in Europe.     

On the dynamics and adaptivity of mental processes: Relating adaptive dynamical systems and self-modeling network models by mathematical analysis

In this paper, it is addressed by mathematical analysis how network-oriented modeling relates to the dynamical systems perspective on mental processes. It has been mathematically proven that any dynamical system can be modeled as a temporal-causal network model and that any adaptive dynamical system (of any order) can be modeled by a self-modeling network (of the same order).     

Global and Local Feature Distinctiveness Effects in Language Acquisition

Various aspects of semantic features drive early vocabulary development, but less is known about how the global and local structure of the overall semantic feature space influences language acquisition. A feature network of English words was constructed from a large database of adult feature production norms such that edges in the network represented feature distances between words (i.e., Manhattan distances of probability distributions of features elicited for each pair of words). A word's global feature distinctiveness is measured with respect to all other words in the network and a word's local feature distinctiveness is measured relative to words in sub-networks derived from clustering analyses. This paper investigates how feature distinctiveness of individual words at local and global scales of the network influences language acquisition. Regression analyses indicate that global feature distinctiveness was associated with earlier age of acquisition ratings, and was a stronger predictor of age of acquisition than local feature distinctiveness. These results suggest that the global structure of the semantic feature network could play an important role in language acquisition, whereby globally distinctive concepts help to structure vocabulary development over the lifespan.     

Does Semantics Need Normativity? Comments on Allan Gibbard,Meaning and Normativity

In the book Gibbard proposes, first, that statements about meaning are normative statements and, second, that they can be given an expressivist treatment, along the lines of Gibbard’s preferred metaethics. In my paper, I examine the first step: The claim that meaning statements are to be construed as being normative, as involving ‘oughts’. Gibbard distinguishes two versions of the normativity of meaning thesis – a weak version, according to which every means implies an ought, and a strong version, according to which for every means, there is an ought that implies it. I argue that neither thesis withstands scrutiny. The weak thesis depends on assumptions about the notion of semantic correctness that the anti-normativist rejects, and the strong thesis does not solve the problems Gibbard wants it to solve: the problems of indeterminacy and meaning skepticism. I conclude that semantics does not need normativity.