The contents of our conscious mind can seem unpredictable, whimsical, and free from external control. When instructed to attend to a stimulus in a work setting, for example, one might find oneself thinking about household chores. Conscious content thus appears different in nature from reflex action. Under the appropriate conditions, reflexes occur predictably, reliably, and via external control. Despite these intuitions, theorists have proposed that, under certain conditions, conscious content resembles reflexes and arises reliably via external control. We introduce the (...) Reflexive Imagery Task, a paradigm in which, as a function of external control, conscious content is triggered reliably and unintentionally: When instructed to not subvocalize the name of a stimulus object, participants reliably failed to suppress the set-related imagery. This stimulus-elicited content is considered ‘high-level’ content and, in terms of stages of processing, occurs late in the processing stream. We discuss the implications of this paradigm for consciousness research. (shrink)

Theories of sentence production that involve a convergence of activation from conceptual‐semantic and syntactic‐sequential units inspired a connectionist model that was trained to produce simple sentences. The model used a learning algorithm that resulted in a sharing of responsibility (or “division of labor”) between syntactic and semantic inputs for lexical activation according to their predictive power. Semantically rich, or “heavy”, verbs in the model came to rely on semantic cues more than on syntactic cues, whereas semantically impoverished, or “light”, verbs (...) relied more on syntactic cues. When the syntactic and semantic inputs were lesioned, the model exhibited patterns of production characteristic of agrammatic and anomic aphasic patients, respectively. Anomic models tended to lose the ability to retrieve heavy verbs, whereas agrammatic models were more impaired in retrieving light verbs. These results obtained in both sentence production and single‐word naming simulations. Moreover, simulated agrammatic lexical retrieval was more impaired overall in sentences than in single‐word tasks, in agreement with the literature. The results provide a demonstration of the division‐of‐labor principle, as well as general support for the claim that connectionist learning principles can contribute to the understanding of non‐transparent neuropsychological dissociations. (shrink)

This Special Issue on Connectionist Models of Human Language Processing provides an opportunity for an appraisal both of specific connectionist models and of the status and utility of connectionist models of language in general. This introduction provides the background for the papers in the Special Issue. The development of connectionist models of language is traced, from their intellectual origins, to the state of current research. Key themes that arise throughout different areas of connectionist psycholinguistics are highlighted, and recent developments in (...) speech processing, morphology, sentence processing, language production, and reading are described. We argue that connectionist psycholinguistics has already had a significant impact on the psychology of language, and that connectionist models are likely to have an important influence on future research. (shrink)

Our target article proposed that language production and comprehension are interwoven, with speakers making predictions of their own utterances and comprehenders making predictions of other people's utterances at different linguistic levels. Here, we respond to comments about such issues as cognitive architecture and its neural basis, learning and development, monitoring, the nature of forward models, communicative intentions, and dialogue.

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)

Topics in Cognitive Science, Volume 14, Issue 2, Page 295-310, April 2022.

Currently, production and comprehension are regarded as quite distinct in accounts of language processing. In rejecting this dichotomy, we instead assert that producing and understanding are interwoven, and that this interweaving is what enables people to predict themselves and each other. We start by noting that production and comprehension are forms of action and action perception. We then consider the evidence for interweaving in action, action perception, and joint action, and explain such evidence in terms of prediction. Specifically, we assume (...) that actors construct forward models of their actions before they execute those actions, and that perceivers of others' actions covertly imitate those actions, then construct forward models of those actions. We use these accounts of action, action perception, and joint action to develop accounts of production, comprehension, and interactive language. Importantly, they incorporate well-defined levels of linguistic representation. We show how speakers and comprehenders use covert imitation and forward modeling to make predictions at these levels of representation, how they interweave production and comprehension processes, and how they use these predictions to monitor the upcoming utterances. We show how these accounts explain a range of behavioral and neuroscientific data on language processing and discuss some of the implications of our proposal. (shrink)

Models of both speech perception and speech production typically postulate a processing level that involves some form of phonological processing. There is disagreement, however, on the question of whether there are separate phonological systems for speech input versus speech output. We review a range of neuroscientific data that indicate that input and output phonological systems partially overlap. An important anatomical site of overlap appears to be the left posterior superior temporal gyrus. We then present the results of a new event‐related (...) functional magnetic resonance imaging (fMRI) experiment in which participants were asked to listen to and then (covertly) produce speech. In each participant, we found two regions in the left posterior superior temporal gyrus that responded both to the perception and production components of the task, suggesting that there is overlap in the neural systems that participate in phonological aspects of speech perception and speech production. The implications for neural models of verbal working memory are also discussed in connection with our findings. (shrink)

Difficulty retrieving information (e.g., words) from memory is prevalent in neurogenic communication disorders (e.g., aphasia and dementia). Theoretical modeling of retrieval failures often relies on clinical data, despite methodological limitations (e.g., locus of retrieval failure, heterogeneity of individuals, and progression of disorder/disease). Techniques from network science are naturally capable of handling these limitations. This paper reviews recent work using a multiplex lexical network to account for word retrieval failures and highlights how network science can address the limitations of clinical data. (...) Critically, any model we employ could impact clinical practice and patient lives, harkening the need for theoretically well-informed network models. (shrink)

Theories of language production have long been expressed as connectionist models. We outline the issues and challenges that must be addressed by connectionist models of lexical access and grammatical encoding, and review three recent models. The models illustrate the value of an interactive activation approach to lexical access in production, the need for sequential output in both phonological and grammatical encoding, and the potential for accounting for structural effects on errors and structural priming from learning.

While the idea that thinking is a form of silent self-talk goes back at least to Plato, it is not immediately clear how to state this thesis precisely. The aim of the paper is to spell out the notion that we think in language by recourse to recent work on inner speech. To that end, inner speech and overt speech are briefly compared. I then propose that inner speaking be defined as a mental episode that substantially engages the speech production (...) system; the underlying model of speech production is sketched. Next, the cognitive role of inner speaking is explored, especially its role in thinking and reasoning. The question of whether it is a way of making thoughts accessible (to whomever) or whether it is a means of thinking itself is raised. I argue that there are two reasons for assuming that, occasionally, we think in language. More specifically, I will claim that some instances of thinking are instances of inner speaking as they exploit certain properties of natural language, and that some instances of inner speaking are instances of thinking as they play a decisive role in paradigmatic cases of thinking that result from internalizing and re-using certain social-linguistic practices. Finally, the Language-of-Thought hypothesis as an alternative account is critically discussed. (shrink)

Investigating instances where lexical selection fails can lead to deeper insights into the cognitive machinery and architecture supporting successful word retrieval and speech production. In this paper, we used a multiplex lexical network approach that combines semantic and phonological similarities among words to model the structure of the mental lexicon. Network measures at different levels of analysis (degree, network distance, and closeness centrality) were used to investigate the influence of network structure on picture naming accuracy and errors by people with (...) Anomic, Broca's, Conduction, and Wernicke's aphasia. Our results reveal that word retrieval is influenced by the multiplex lexical network structure in at least two ways—(a) the accuracy of production and error type on incorrect productions were influenced by the degree and closeness centrality of the target word, and (b) error type also varied in terms of network distance between the target word and produced error word. Taken together, the analyses demonstrate that network science techniques, particularly the use of the multiplex lexical network to simultaneously represent semantic and phonological relationships among words, reveal how the structure of the mental lexicon influences language processes beyond traditionally examined psycholinguistic variables. We propose a framework for how the multiplex lexical network approach allows for understanding the influence of mental lexicon structure on word retrieval processes, with an eye toward a better understanding of the nature of clinical impairments, like aphasia. (shrink)

Computational modeling and eye-tracking were used to investigate how phonological and semantic information interact to influence the time course of spoken word recognition. We extended our recent models to account for new evidence that competition among phonological neighbors influences activation of semantically related concepts during spoken word recognition . The model made a novel prediction: Semantic input modulates the effect of phonological neighbors on target word processing, producing an approximately inverted-U-shaped pattern with a high phonological density advantage at an intermediate (...) level of semantic input—in contrast to the typical disadvantage for high phonological density words in spoken word recognition. This prediction was confirmed with a new analysis of the Apfelbaum et al. data and in a visual world paradigm experiment with preview duration serving as a manipulation of strength of semantic input. These results are consistent with our previous claim that strongly active neighbors produce net inhibitory effects and weakly active neighbors produce net facilitative effects. (shrink)

In a seminal 1977 article, Rumelhart argued that perception required the simultaneous use of multiple sources of information, allowing perceivers to optimally interpret sensory information at many levels of representation in real time as information arrives. Building on Rumelhart's arguments, we present the Interactive Activation hypothesis—the idea that the mechanism used in perception and comprehension to achieve these feats exploits an interactive activation process implemented through the bidirectional propagation of activation among simple processing units. We then examine the interactive activation (...) model of letter and word perception and the TRACE model of speech perception, as early attempts to explore this hypothesis, and review the experimental evidence relevant to their assumptions and predictions. We consider how well these models address the computational challenge posed by the problem of perception, and we consider how consistent they are with evidence from behavioral experiments. We examine empirical and theoretical controversies surrounding the idea of interactive processing, including a controversy that swirls around the relationship between interactive computation and optimal Bayesian inference. Some of the implementation details of early versions of interactive activation models caused deviation from optimality and from aspects of human performance data. More recent versions of these models, however, overcome these deficiencies. Among these is a model called the multinomial interactive activation model, which explicitly links interactive activation and Bayesian computations. We also review evidence from neurophysiological and neuroimaging studies supporting the view that interactive processing is a characteristic of the perceptual processing machinery in the brain. In sum, we argue that a computational analysis, as well as behavioral and neuroscience evidence, all support the Interactive Activation hypothesis. The evidence suggests that contemporary versions of models based on the idea of interactive activation continue to provide a basis for efforts to achieve a fuller understanding of the process of perception. (shrink)

The ability to combine words into novel sentences has been used to argue that humans have symbolic language production abilities. Critiques of connectionist models of language often center on the inability of these models to generalize symbolically (Fodor & Pylyshyn, 1988; Marcus, 1998). To address these issues, a connectionist model of sentence production was developed. The model had variables (role‐concept bindings) that were inspired by spatial representations (Landau & Jackendoff, 1993). In order to take advantage of these variables, a novel (...) dual‐pathway architecture with event semantics is proposed and shown to be better at symbolic generalization than several variants. This architecture has one pathway for mapping message content to words and a separate pathway that enforces sequencing constraints. Analysis of the model's hidden units demonstrated that the model learned different types of information in each pathway, and that the model's compositional behavior arose from the combination of these two pathways. The model's ability to balance symbolic and statistical behavior in syntax acquisition and to model aphasic double dissociations provided independent support for the dual‐pathway architecture. (shrink)

Individuals with agrammatic Broca's aphasia experience difficulty when processing reversible non-canonical sentences. Different accounts have been proposed to explain this phenomenon. The Trace Deletion account attributes this deficit to an impairment in syntactic representations, whereas others propose that the underlying structural representations are unimpaired, but sentence comprehension is affected by processing deficits, such as slow lexical activation, reduction in memory resources, slowed processing and/or intermittent deficiency, among others. We test the claims of two processing accounts, slowed processing and intermittent deficiency, (...) and two versions of the Trace Deletion Hypothesis, in a computational framework for sentence processing implemented in ACT-R. The assumption of slowed processing is operationalized as slow procedural memory, so that each processing action is performed slower than normal, and intermittent deficiency as extra noise in the procedural memory, so that the parsing steps are more noisy than normal. We operationalize the TDH as an absence of trace information in the parse tree. To test the predictions of the models implementing these theories, we use the data from a German sentence—picture matching study reported in Hanne, Sekerina, Vasishth, Burchert, and De Bleser. The data consist of offline and online measures. From among the models considered, the model assuming that both slowed processing and intermittent deficiency are present emerges as the best model of sentence processing difficulty in aphasia. The modeling of individual differences suggests that, if we assume that patients have both slowed processing and intermittent deficiency, they have them in differing degrees. (shrink)

I address the problem of the distinction between semantic and conceptual representations from general considerations about how to distinguish a representational kind. I consider three different ways of telling representational kinds apart – in terms of structure, processing and content – and I examine if semantic representations may constitute a distinct kind with respect to each of them. I argue that the best options for semantic representation to be regarded as a distinct representational kind with respect to each of the (...) three criteria conflict with each other, since it appears respectively as an atomic representation, as a sort of procedural rule or as a structured complex. (shrink)

This article illustrates the main theoretical and practical problem of the study of the anagram in poetry, the still unknown entity of the anagrammatic combination, which requires specific software in order to perform a structural analysis of the text. This difficulty explains the failure of Saussure’s original hypotheses and the gradual decline, following the rediscovery of his work, of the interest of researchers in this subject. However, some poems (by Blake, Moore, Mallarmé, Valéry, Apollinaire, and Leopardi) illustrate the enormous potential (...) of the anagram for the structural analysis of poetic texts: the study of formal structure, of semantic-thematic nuclei and of metaphor, together with the main criteria for examining, with some simplification, the anagrammatic combination. An explanation is also offered for anagrammatic and grammatical-syntactic cooperation, involving the current theory of the lemma. At the time of the generation of a poetic text, the anagram acts as an associative intermediary between the combinatory matrix of the signifieds and the combinatory matrix of the signifiers, producing a lexical selection that gives anagrammatic coherence to the text. This associative intermediary enables us to understand the particular recursive function of semiosis in poetry that is given a distinct unity by the anagram. (shrink)

Background To produce and understand words, humans access the mental lexicon. From a functional perspective, the long-term memory component of the mental lexicon is comprised of three levels: the concept level, the lemma level, and the phonological level. At each level, different kinds of word information are stored. Semantic as well as phonological cues can help to facilitate word access during a naming task, especially when neural dysfunctions are present. The processing corresponding to word access occurs in specific parts of (...) working memory. Neural models for simulating speech processing help to uncover the complex relationships that exist between neural dysfunctions and corresponding behavioral patterns. Methods The Neural Engineering Framework (NEF) and the Semantic Pointer Architecture (SPA) are used to develop a quantitative neural model of the mental lexicon and its access during speech processing. By simulating a picture-naming task (WWT 6-10), the influence of cues is investigated by introducing neural dysfunctions within the neural model at different levels of the mental lexicon. Results First, the neural model is able to simulate the test behavior for normal children that exhibit no lexical dysfunction. Second, the model shows worse results in test performance as larger degrees of dysfunction are introduced. Third, if the severity of dysfunction is not too high, phonological and semantic cues are observed to lead to an increase in the number of correctly named words. Phonological cues are observed to be more effective than semantic cues. Conclusion Our simulation results are in line with human experimental data. Specifically, phonological cues seem not only to activate phonologically similar items within the phonological level. Moreover, phonological cues support higher-level processing during access of the mental lexicon. Thus, the neural model introduced in this paper offers a promising approach to modeling the mental lexicon, and to incorporating the mental lexicon into a complex model of language processing. (shrink)

El pensamiento es incorporado por la articulación de los dos algoritmos: la estructura interna para conocer y la realidad, externa, a ser reconocida. La realidad interna está dada desde la estructura de la lengua, la cual más adelante dará lugar a un formato lógica-matemática. La realidad externa, que es también antropológica, está mediada por las áreas somatosensoriales cerebrales, que protológicamente acercan a lo distinto del humano. La filosofía y la ciencia tienen la tarea de acercarse a estas realidades para enhebrarlas, (...) de lo cual resulta un conocimiento general y una ciencia epistemológicamente bien fundada, puesto que hay una estructura ontológica y lógica que les da razón. Desde este fundamento no resultan bien libradas ni el empirismo ni es racionalismo y se abre una ventana para una metafísica menos unilateral y más rigurosa. (shrink)

Interactive theories of lexical retrieval in language production assume that activation cascades from earlier to later processing levels, and feeds back in the reverse direction. This commentary invites Pickering & Garrod (P&G) to consider whether cascading and feedback can be seen as a form of forwarding modeling within a hierarchical production system.