Measuring Chinese character recognition ability is essential in research on character learning among learners of Chinese as a second language. Three methods are typically used to evaluate character recognition competence by investigating the following properties of a given character: pronunciation, meaning, and pronunciation and meaning. However, no study has explored the similar or dissimilar outcomes that these three measurements might yield. The current study examined this issue by testing 162 CSL learners with various L1 backgrounds and Chinese proficiency levels. Participants' (...) performance in character recognition measured using a phonological method, a semantic method, and a PS method was compared, which led to two major findings. In terms of similarity, participants' performance in character recognition and the influence of L1 background and Chinese proficiency level on character recognition was similar across the three methods. As for differences, the semantic method could yield a character recognition test with better quality than the other two methods, and the three methods yielded different best fitting models and showed different predictions for Chinese proficiency across different L1 groups. Theoretical and practical implications of these findings are proposed. (shrink)

A large literature suggests that the organization of words in semantic memory, reflecting meaningful relations among words and the concepts to which they refer, supports many cognitive processes, including memory encoding and retrieval, word learning, and inferential reasoning. The co‐activation of related items has been proposed as a mechanism by which semantic knowledge influences cognition, and contemporary accounts of semantic knowledge propose that this co‐activation is graded—that it depends on how strongly related the items are in semantic memory. Prior research (...) with adults yielded evidence supporting this prediction; however, there is currently no evidence of graded co‐activation early in development. This study provides the first evidence that in children the co‐activation of related items depends on their relational strength in semantic memory. Participants (N = 84, age range: 3–9 years) were asked to identify a target (e.g., bone) amid distractors. Children's responses were slowed down by the presence of a related distractor (e.g., puppy) relative to unrelated distractors (e.g., flower)—suggesting that children co‐activated related items upon hearing the name of the target. Importantly, the degree of this co‐activation was predicted by the strength of the target–distractor relation, such that distractors more strongly related to the targets slowed down children to a larger extent. These findings have important implications for understanding how organized semantic knowledge affects other cognitive processes across development. (shrink)

A naturalistic scheme of primitive conceptual representations is proposed using the statistical measure of mutual information. It is argued that a concept represents, not the class of objects that caused its tokening, but the class of objects that is most likely to have caused it (had it been tokened), as specified by the statistical measure of mutual information. This solves the problem of misrepresentation which plagues causal accounts, by taking the representation relation to be determined via ordinal relationships between conditional (...) probabilities. The scheme can deal with statistical biases and does not rely on arbitrary criteria. Implications for the theory of meaning and semantic content are addressed. (shrink)

The DRM paradigm produces robust false memories of non-presented critical words. After studying a thematic word list participants falsely remember the critical item “sleep.” We report two false memory experiments. Study One introduces a novel use of the lexical decision task to prime critical words. Participants see two letter-strings and make timed responses indicating whether they are both words. The word pairs Night-Bed and Dream-Thweeb both prime “sleep” but only one pair contains two words. Our primary purpose is to introduce (...) this new methodology via two pilot experiments. The results, considered preliminary, are promising as they indicate that participants were as likely to recognize critical words and presented words just as when studying thematic lists. Study Two actually employs the standard DRM lists so that semantic priming is in play there as well. The second study, however, uses functional near-infrared spectroscopy to measure activity in the prefrontal cortex during a DRM task which includes a deception phase where participants intentionally lie about critical lures. False and true memories occurred at high levels and activated many of the same brain regions but, compared to true memories, cortical activity was higher for false memories and lies. Accuracy findings are accompanied by confidence and reaction time results. Both investigations suggest that it is difficult to distinguish accurate from inaccurate memories. We explain results in terms of activation-monitoring theory and Fuzzy Trace Theory. We provide real world implications and suggest extending the present research to varying age groups and special populations. A nagging question has not been satisfactorily answered: Could neural pathways exist that signal the presence of false memories and lies? Answering this question will require imaging experiments that focus on regions of distinction such as the anterior prefrontal cortex. (shrink)

This paper introduces a special issue of Cognitive Science initiated on the 25th anniversary of the publication of Parallel Distributed Processing (PDP), a two-volume work that introduced the use of neural network models as vehicles for understanding cognition. The collection surveys the core commitments of the PDP framework, the key issues the framework has addressed, and the debates the framework has spawned, and presents viewpoints on the current status of these issues. The articles focus on both historical roots and contemporary (...) developments in learning, optimality theory, perception, memory, language, conceptual knowledge, cognitive control, and consciousness. Here we consider the approach more generally, reviewing the original motivations, the resulting framework, and the central tenets of the underlying theory. We then evaluate the impact of PDP both on the field at large and within specific subdomains of cognitive science and consider the current role of PDP models within the broader landscape of contemporary theoretical frameworks in cognitive science. Looking to the future, we consider the implications for cognitive science of the recent success of machine learning systems called “deep networks”—systems that build on key ideas presented in the PDP volumes. (shrink)

The Influence of Emotional and Non-emotional Concepts Activation on Information Processing and Unintentional Memorizing The aim of the work is to compare mechanisms of semantic and emotional processing and memory. Targets were primed by category name. The congruency of prime and target was manipulated. The reaction time of lexical decisions and the effects of unintentional memorizing of word targets were measured. Activation of semantic and emotional nodes leads to faster processing of related concepts: congruent targets are processed faster than incongruent. (...) Processing congruent primed emotional concepts depends on their modality: anger and joy words are processed faster than sadness. Thus, congruently primed activating emotional concepts are processed differently from congruently primed deactivating concepts. The effectiveness of unintentional memory of emotional and non-emotional concepts is based on different mechanisms: congruently primed emotional words are better remembered than incongruently primed. The results are discussed in the framework of spreading activation theory and theory of emotional memory. (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)