Our studies of naturally occurring human dialogue have led to the recognition of a class of regularities which characterize impoltant aspects of communication. People appear to interact according to established patterns which span several turns in a dialogue and which recur frequently. These patterns appear to be organized around the goals which the dialogue serves for each participant. Many things which are said later in a dialogue can only be interpreted as pursuit of these goals, established by earlier dialogue.These patterns (...) have been represented b) a set of knowledge structures called Dialogue‐Games, capturing shared, conventional knowledge that people have about communication and how it can be used to achieve goals. A Dialogue‐Game has Parameters, which represent those elements that vary across instances of a particular pattern‐the particular dialogue participants and the content topic. The states of the world which must be in effect for a particular Dialogue‐Game to be employed successfully are represented by Specifications of these Parameters. Finally, the expected sequence of intermediate states that occur during instances of a particular conventional pattern are represented by the Components of the corresponding Dialogue‐Game.Representations for several Dialogue‐Games are presented here, based on our analyses of different kinds of naturally occurring dialogue. A process model is discussed, showing Dialogue‐Game identification, pursuit, and termination as part of the comprehension of dialogue utterances. This Dialogue‐Game model captures some of the important functional aspects of language, especially indirect uses to achieve implicit communication. (shrink)

Preparing words in speech production is normally a fast and accurate process. We generate them two or three per second in fluent conversation; and overtly naming a clear picture of an object can easily be initiated within 600 msec after picture onset. The underlying process, however, is exceedingly complex. The theory reviewed in this target article analyzes this process as staged and feedforward. After a first stage of conceptual preparation, word generation proceeds through lexical selection, morphological and phonological encoding, phonetic (...) encoding, and articulation itself. In addition, the speaker exerts some degree of output control, by monitoring of self-produced internal and overt speech. The core of the theory, ranging from lexical selection to the initiation of phonetic encoding, is captured in a computational model, called WEAVER++. Both the theory and the computational model have been developed in interaction with reaction time experiments, particularly in picture naming or related word production paradigms, with the aim of accounting for the real-time processing in normal word production. A comprehensive review of theory, model, and experiments is presented. The model can handle some of the main observations in the domain of speech errors (the major empirical domain for most other theories of lexical access), and the theory opens new ways of approaching the cerebral organization of speech production by way of high-temporal-resolution imaging. (shrink)

Localist models of spreading activation (SA) and models assuming distributed representations offer very different takes on semantic priming, a widely investigated paradigm in word recognition and semantic memory research. In this study, we implemented SA in an attractor neural network model with distributed representations and created a unified framework for the two approaches. Our models assume a synaptic depression mechanism leading to autonomous transitions between encoded memory patterns (latching dynamics), which account for the major characteristics of automatic semantic priming in (...) humans. Using computer simulations, we demonstrated how findings that challenged attractor‐based networks in the past, such as mediated and asymmetric priming, are a natural consequence of our present model’s dynamics. Puzzling results regarding backward priming were also given a straightforward explanation. In addition, the current model addresses some of the differences between semantic and associative relatedness and explains how these differences interact with stimulus onset asynchrony in priming experiments. (shrink)

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. (shrink)

Results from three field network studies show that depending on individuals’ network positions (central or peripheral), experts and novices have varying ethical predispositions (EP). In particular, central experts (vs. peripheral experts) have higher EP, while novices in the same positions (vs. peripheral novices) have lower EP. Results demonstrate individuals’ relational-interdependent self-construal mediates these relationships. Importantly, this research suggests that the interaction between network and individual difference variables uniquely affect individuals’ ethical predisposition. Given the lack of research focus on the impact (...) of structural positions on EP, this article demonstrates the importance of combining network and individual variables to investigate individuals’ EP. (shrink)

Both scientists and children make important structural discoveries, yet their computational underpinnings are not well understood. Structure discovery has previously been formalized as probabilistic inference about the right structural form—where form could be a tree, ring, chain, grid, etc.. Although this approach can learn intuitive organizations, including a tree for animals and a ring for the color circle, it assumes a strong inductive bias that considers only these particular forms, and each form is explicitly provided as initial knowledge. Here we (...) introduce a new computational model of how organizing structure can be discovered, utilizing a broad hypothesis space with a preference for sparse connectivity. Given that the inductive bias is more general, the model's initial knowledge shows little qualitative resemblance to some of the discoveries it supports. As a consequence, the model can also learn complex structures for domains that lack intuitive description, as well as predict human property induction judgments without explicit structural forms. By allowing form to emerge from sparsity, our approach clarifies how both the richness and flexibility of human conceptual organization can coexist. (shrink)

Considerable work during the past two decades has focused on modeling the structure of semantic memory, although the performance of these models in complex and unconstrained semantic tasks remains relatively understudied. We introduce a two‐player cooperative word game, Connector (based on the boardgame Codenames), and investigate whether similarity metrics derived from two large databases of human free association norms, the University of South Florida norms and the Small World of Words norms, and two distributional semantic models based on large language (...) corpora (word2vec and GloVe) predict performance in this game. Participant dyads were presented with 20‐item word boards with word pairs of varying relatedness. The speaker received a word pair from the board (e.g., exam‐algebra) and generated a one‐word semantic clue (e.g., math), which was used by the guesser to identify the word pair on the board across three attempts. Response times to generate the clue, as well as accuracy and latencies for the guessed word pair, were strongly predicted by the cosine similarity between word pairs and clues in random walk‐based associative models, and to a lesser degree by the distributional models, suggesting that conceptual representations activated during free association were better able to capture search and retrieval processes in the game. Further, the speaker adjusted subsequent clues based on the first attempt by the guesser, who in turn benefited from the adjustment in clues, suggesting a cooperative influence in the game that was effectively captured by both associative and distributional models. These results indicate that both associative and distributional models can capture relatively unconstrained search processes in a cooperative game setting, and Connector is particularly suited to examine communication and semantic search processes. (shrink)

Topics in Cognitive Science, Volume 14, Issue 1, Page 54-77, January 2022.

Two experiments investigated subliminal semantic and form priming in a word-completion task. Visual gap-words with a dominant and a subordinate solution were preceded by form-related or by semantically related words, which were briefly presented and sandwich-masked. Priming of the subordinate solution was assessed in Experiment 1, relative to a neutral condition. Both solutions were primed in Experiment 2. In the absence of conscious prime recognition, both semantic and form primes reliably increased the probability with which the primed solution was given. (...) With our variant of fragment-completion, response priming can be ruled out as explanation. Moreover, effects were already present at first presentation, excluding an interpretation in terms of partial awareness due to massive repetition. The data demonstrate automatic activation at both form and semantic levels in the absence of conscious awareness. (shrink)

The lexical–semantic organization of the mental lexicon is bound to change across the lifespan. Nevertheless, the effects of lexical–semantic factors on word processing are usually based on studies enrolling young adult cohorts. The current study aims to investigate to what extent age‐specific semantic organization predicts performance in referential word production over the lifespan, from school‐age children to older adults. In Study 1, we conducted a free semantic association task with participants from six age‐groups (ranging from 10 to 80 years old) (...) to compute measures that capture age‐specific properties of the mental lexicon across the lifespan. These measures relate to lifespan changes in the Available Richness of the mental lexicon and in the lexical–semantic Network Prototypicality of concrete words. In Study 2, we used the collected data to predict performance in a picture‐naming task on a new group of participants within the same age‐groups as for Study 1. The results show that age‐specific semantic Available Richness and Network Prototypicality affect word production speed while the semantic variables collected only in young adults do not. A richer and more prototypical semantic network across subjects from a given age‐group is associated with faster word production speed. The current results indicate that age‐specific semantic organization is crucial to predict lexical–semantic behaviors across the lifespan. Similarly, these results also provide cues to the understanding of the lexical–semantic properties of the mental lexicon and to lexical selection in referential tasks. (shrink)

Language and culture endow humans with access to conceptual information that far exceeds any which could be accessed by a non-human animal. Yet, it is possible that, even without language or specific experiences, non-human animals represent and infer some aspects of similarity relations between objects in the same way as humans. Here, we show that monkeys’ discrimination sensitivity when identifying images of animals is predicted by established measures of semantic similarity derived from human conceptual judgments. We used metrics from computer (...) vision and computational neuroscience to show that monkeys’ and humans’ performance cannot be explained by low-level visual similarity alone. The results demonstrate that at least some of the underlying structure of object representations in humans is shared with non-human primates, at an abstract level that extends beyond low-level visual similarity. Because the monkeys had no experience with the objects we tested, the results suggest that monkeys and humans share a primitive representation of object similarity that is independent of formal knowledge and cultural experience, and likely derived from common evolutionary constraints on object representation. (shrink)

Measures and theories of information abound, but there are few formalised methods for treating the contextuality that can manifest in different information systems. Quantum theory provides one possible formalism for treating information in context. This paper introduces a quantum inspired model of the human mental lexicon. This model is currently being experimentally investigated and we present a preliminary set of pilot data suggesting that concept combinations can indeed behave non-separably.

According to Mednick’s (1962) theory of individual differences in creativity, creative individuals appear to have a richer and more flexible associative network than less creative individuals. Thus, creative individuals are characterized by “flat” (broader associations) instead of “steep” (few, common associations) associational hierarchies. To study these differences, we implement a novel computational approach to the study of semantic networks, through the analysis of free associations. The core notion of our method is that concepts in the network are related to each (...) other by their association correlations - overlap of similar associative responses (“association clouds”). We began by collecting a large sample of participants who underwent several creativity measurements and used a decision tree approach to divide the sample into low and high creative groups. Next, each group underwent a free association generation paradigm which allowed us to construct and analyze the semantic networks of both groups. Comparison of the semantic memory networks of persons with low creative ability and persons with high creative ability revealed differences between the two networks. The semantic memory network of persons with low creative ability seems to be more rigid, compared to the network of persons with high creative ability, in the sense that it is more spread out and breaks apart into more sub-parts. We discuss how our findings are in accord and extend Mednick’s (1962) theory and the feasibility of using network science paradigms to investigate high level cognition. (shrink)

Recently, priming effects of unconscious stimuli that were never presented as targets have been taken as evidence for the processing of the stimuli’s semantic categories. The present study explored the necessary conditions for a transfer of priming to novel primes. Stimuli were digits and letters which were presented in various viewer-related orientations . The transfer of priming to novel stimulus orientations and identities was remarkably limited: in Experiment 1, in which all conscious targets stood upright, no transfer to unconscious primes (...) in a non-target orientation was found. Experiment 2, in which primes were presented without masks, ruled out the possibility that primes were presented too short to allow congruency effects. In Experiments 3 and 4, in which all targets were presented upside down, priming transferred to upright stimuli with target identities but neither to horizontal stimuli nor to stimuli with novel identities. We suggest that whether a transfer of priming to unpracticed stimuli occurs or not depends on observers’ expectations of specific stimulus exemplars. (shrink)

People believe that the effects of unecological behaviors may be compensated for by engaging in alternative conservation activities. The problem is, however, that those who hold such beliefs are less likely to engage in real behaviors. Understanding the structure of compensatory beliefs could potentially minimize this negative effect. In a pair of studies we explored two aspects that appear key for compensatory beliefs 1) the similarity and 2) the relative difficulty of behaviors. We found that people spontaneously proposed compensatory behaviors (...) which belonged to the same pro-ecological domain as the corresponding initial behaviors. However, participants in the quantitative study agreed more often that they should compensate for one behavior with another when both behaviors belonged to the same cognitive category and simultaneously the compensatory behavior was relatively less demanding than the initial one. (shrink)