We compared the ability of three different contextual models of lexical semantic memory and of a simple associative model to predict the properties of semantic networks derived from word association norms. None of the semantic models were able to accurately predict all of the network properties. All three contextual models over-predicted clustering in the norms, whereas the associative model under-predicted clustering. Only a hybrid model that assumed that some of the responses were based on a contextual model and (...) others on an associative network successfully predicted all of the network properties and predicted a word's top five associates as well as or better than the better of the two constituent models. The results suggest that participants switch between a contextual representation and an associative network when generating free associations. We discuss the role that each of these representations may play in lexical semantic memory. Concordant with recent multicomponent theories of semantic memory, the associative network may encode coordinate relations between concepts, and contextual representations may be used to process information about more abstract concepts. (shrink)

This book argues that language is a network of concepts which in turn is part of the general cognitive network of the mind. It challenges the widely-held view that language is an innate mental module with its own special internal organization. It shows that language has the same internal organization as other areas of knowledge such as social relations and action schemas, and reveals the rich links between linguistic elements and contextual categories. Professor Hudson presents a new theory of how (...) we learn and use our knowledge of language. He puts this to work in a series of extended explorations of morphology, syntax, semantics, and sociolinguistics. Every step of his argument and exposition is illustrated with examples, including the kind mainstream theory finds it hard to analyse. He introduces the latest version of his influential theory of Word Grammar and shows how it can be used to explain the operations of language and as a key to understanding the associated operations of the mind. (shrink)

Indirect speech acts—responding “I forgot to wear my watch today” to someone who asked for the time—are ubiquitous in daily conversation, but are understudied in current neurobiological models of language. To comprehend an indirect speech act like this one, listeners must not only decode the lexical-semantic content of the utterance, but also make a pragmatic, bridging inference. This inference allows listeners to derive the speaker’s true, intended meaning—in the above dialog, for example, that the speaker cannot provide the time. In (...) the present work, we address this major gap by asking non-aphasic patients with behavioral variant frontotemporal dementia and brain-damaged controls with amnestic mild cognitive impairment to judge simple question-answer dialogs of the form: “Do you want some cake for dessert?” “I’m on a very strict diet right now,” and relate the results to structural and diffusion MRI. Accuracy and reaction time results demonstrate that subjects with bvFTD, but not MCI, are selectively impaired in indirect relative to direct speech act comprehension, due in part to their social and executive limitations, and performance is related to caregivers’ judgment of communication efficacy. MRI imaging associates the observed impairment in bvFTD to cortical thinning not only in traditional language-associated regions, but also in fronto-parietal regions implicated in social and executive cerebral networks. Finally, diffusion tensor imaging analyses implicate white matter tracts in both dorsal and ventral projection streams, including superior longitudinal fasciculus, frontal aslant, and uncinate fasciculus. These results have strong implications for updated neurobiological models of language, and emphasize a core, language-mediated social disorder in patients with bvFTD. (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)

This book offers an ideal first reader in ancient Greek. It presents a selection of extracts from a comprehensive range of Greek authors, from Homer to Plutarch, together with generous help with vocabulary and grammar. The passages have been chosen for their intrinsic interest and variety, and brief introductions set them in context. All but the commonest Greek words are glossed as they occur and a general vocabulary is included at the back. Although the book is designed to be used (...) by students who have only completed a beginner's course in Greek, students of all ages will find that it helps them to improve their ability and confidence in reading a wide range of prose and verse texts, while at the same time providing a fascinating and copiously illustrated introduction to the riches and variety of ancient Greek literature over a period of almost a thousand years. (shrink)

1. To list Pound’s triumphs of recognition in the realm of art, music, or literature is by itself no more enlightening than to catalog his oversights. Thus, for example, his instant and almost uncanny responsiveness to the work of Henri Gaudier-Brzeska is not more informative than his bizarre ranking of Francis Picabia’s paintings above those of Picasso or Matisse. Clearly it is essential to know, with as much specificity as possible, exactly what Pound said about a particular work of art (...) or literature and, equally important, given the frequent shifts of emphasis and interest throughout his long career, just when these opinions were first formulated. Like every reader of the The Cantos, I am conscious of the enormous service rendered by Pound scholars whose research is giving us a more complete inventory of the poet’s various statements and positions, and it would be foolish to take my point here as a derogation of such efforts. But a list, no matter how complete, is not an argument, and an inventory, no matter how scrupulously assembled, is not an explanation; a recurrent problem in Pound studies is that too often the compoilation of discrete items of information is seen as a sufficient answer to problems of interpretation and understanding. In other words, I think it essential that discussions of pound and the Visual Arts move beyond the quagmire resulting from still another frain-storm of “factual atoms” chronicling his various passions and dislikes.2. Far from implying, however, that we must therefore simply accept Pound’s brilliant discoveries and pass over his “howling blunders,” my position would emphasize the need to take his ideas seriously enough to confront them, to test them against the material to which they are a response and for which they often seek to provide an explanatory account. There are times, as I have argued in an analogous context, when it is less demeaning to give a man credit for his worst errors than to remove from him the capacity to err.3. What we require, I believe, is less a catalog of all of Pound’s specific statements about various artists, with each utterance assigned a positive or negative prefix depending upon our own personal and currently sanctioned hierarchy of values, than a careful study of the place of those statements in the logic and texture of Pound’s own work. The attempt to focus attention on The Cantos’ network of artistic references—its invocation of masterpieces and privileged moments of cultural achievement—will yield only trivial results unless the inner dynamic linking Pound’s various exampla and the actual role these play in the poem’s argument become clearer in the process. Michael André Bernstein, associate professor of English and comparative literature at the University of California, Berkeley, is the author of The Tale of the Tribe: Ezra Pound and the Modern Verse Epic and Prima della Rivoluzione , a volume of verse. He is currently completing a study of the Abject Hero and literary genealogy. His previous contribution to. (shrink)

The meaning of most words in language depends on their context. Understanding how the human brain extracts contextualized meaning, and identifying where in the brain this takes place, remain important scientific challenges. But technological and computational advances in neuroscience and artificial intelligence now provide unprecedented opportunities to study the human brain in action as language is read and understood. Recent contextualized language models seem to be able to capture homonymic meaning variation (“bat”, in a baseball vs. a vampire context), as (...) well as more nuanced differences of meaning—for example, polysemous words such as “book”, which can be interpreted in distinct but related senses (“explain a book”, information, vs. “open a book”, object) whose differences are fine‐grained. We study these subtle differences in lexical meaning along the concrete/abstract dimension, as they are triggered by verb‐noun semantic composition. We analyze functional magnetic resonance imaging (fMRI) activations elicited by Italian verb phrases containing nouns whose interpretation is affected by the verb to different degrees. By using a contextualized language model and human concreteness ratings, we shed light on where in the brain such fine‐grained meaning variation takes place and how it is coded. Our results show that phrase concreteness judgments and the contextualized model can predict BOLD activation associated with semantic composition within the language network. Importantly, representations derived from a complex, nonlinear composition process consistently outperform simpler composition approaches. This is compatible with a holistic view of semantic composition in the brain, where semantic representations are modified by the process of composition itself. When looking at individual brain areas, we find that encoding performance is statistically significant, although with differing patterns of results, suggesting differential involvement, in the posterior superior temporal sulcus, inferior frontal gyrus and anterior temporal lobe, and in motor areas previously associated with processing of concreteness/abstractness. (shrink)

We present statistical analyses of the large‐scale structure of 3 types of semantic networks: word associations, WordNet, and Roget's Thesaurus. We show that they have a small‐world structure, characterized by sparse connectivity, short average path lengths between words, and strong local clustering. In addition, the distributions of the number of connections follow power laws that indicate a scale‐free pattern of connectivity, with most nodes having relatively few connections joined together through a small number of hubs with many connections. (...) These regularities have also been found in certain other complex natural networks, such as the World Wide Web, but they are not consistent with many conventional models of semantic organization, based on inheritance hierarchies, arbitrarily structured networks, or high‐dimensional vector spaces. We propose that these structures reflect the mechanisms by which semantic networks grow. We describe a simple model for semantic growth, in which each new word or concept is connected to an existing network by differentiating the connectivity pattern of an existing node. This model generates appropriate small‐world statistics and power‐law connectivity distributions, and it also suggests one possible mechanistic basis for the effects of learning history variables (age of acquisition, usage frequency) on behavioral performance in semantic processing tasks. (shrink)

People construe reality by using words as basic units of meaningful categorization. The present theory-driven study applied the method of a free association task to explore how people express the concepts of the world and the self in words. The respondents were asked to recall any five words relating with the word world. Afterwards they were asked to recall any five words relating with the word self. The method of free association provided the respondents with absolute freedom to (...) choose any words they wanted. Such free recall task is suggested as being a relatively direct approach to the respondents’ self- and world-related conceptual categories, without enormous rational processing. The results provide us, first, with associative ranges for constructs of the world and the self, where some associative dimensions are defined by semantic polarities in the meanings of peripheral categories (e.g., Nature vs. Culture). Second, our analysis showed that some groups of verbal categories that were associated with the words world and self are central, while others are peripheral with respect to the central position. Third, the analysis of category networks revealed that some categories play the role of a transmitter, mediating the pathway between other categories in the network. (shrink)

We present statistical analyses of the large‐scale structure of 3 types of semantic networks: word associations, WordNet, and Roget's Thesaurus. We show that they have a small‐world structure, characterized by sparse connectivity, short average path lengths between words, and strong local clustering. In addition, the distributions of the number of connections follow power laws that indicate a scale‐free pattern of connectivity, with most nodes having relatively few connections joined together through a small number of hubs with many connections. (...) These regularities have also been found in certain other complex natural networks, such as the World Wide Web, but they are not consistent with many conventional models of semantic organization, based on inheritance hierarchies, arbitrarily structured networks, or high‐dimensional vector spaces. We propose that these structures reflect the mechanisms by which semantic networks grow. We describe a simple model for semantic growth, in which each new word or concept is connected to an existing network by differentiating the connectivity pattern of an existing node. This model generates appropriate small‐world statistics and power‐law connectivity distributions, and it also suggests one possible mechanistic basis for the effects of learning history variables (age of acquisition, usage frequency) on behavioral performance in semantic processing tasks. (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)

Words become associated following repeated co-occurrence episodes. This process might be further determined by the semantic characteristics of the words. The present study focused on how semantic and episodic factors interact in incidental formation of word associations. First, we found that human participants associate semantically related words more easily than unrelated words; this advantage increased linearly with repeated co-occurrence. Second, we developed a computational model, SEMANT, suggesting a possible mechanism for this semantic-episodic interaction. In SEMANT, episodic associations are (...) implemented through lateral connections between nodes in a pre-existent self-organized map of word semantics. These connections are strengthened at each instance of concomitant activation, proportionally with the amount of the overlapping activity waves of activated nodes. In computer simulations SEMANT replicated the dynamics of associative learning in humans and led to testable predictions concerning normal associative learning as well as impaired learning in a diffuse semantic system like that characteristic of schizophrenia. (shrink)

We present statistical analyses of the large‐scale structure of 3 types of semantic networks: word associations, WordNet, and Roget's Thesaurus. We show that they have a small‐world structure, characterized by sparse connectivity, short average path lengths between words, and strong local clustering. In addition, the distributions of the number of connections follow power laws that indicate a scale‐free pattern of connectivity, with most nodes having relatively few connections joined together through a small number of hubs with many connections. (...) These regularities have also been found in certain other complex natural networks, such as the World Wide Web, but they are not consistent with many conventional models of semantic organization, based on inheritance hierarchies, arbitrarily structured networks, or high‐dimensional vector spaces. We propose that these structures reflect the mechanisms by which semantic networks grow. We describe a simple model for semantic growth, in which each new word or concept is connected to an existing network by differentiating the connectivity pattern of an existing node. This model generates appropriate small‐world statistics and power‐law connectivity distributions, and it also suggests one possible mechanistic basis for the effects of learning history variables (age of acquisition, usage frequency) on behavioral performance in semantic processing tasks. (shrink)

This paper critically examines the claim that parallel distributed processing (PDP) networks are autonomous learning systems. A PDP model of a simple distributed associative memory is considered. It is shown that the 'generic' PDP architecture cannot implement the computations required by this memory system without the aid of external control. In other words, the model is not autonomous. Two specific problems are highlighted: (i) simultaneous learning and recall are not permitted to occur as would be required of an autonomous (...) system; (ii) connections between processing units cannot simultaneously represent current and previous network activation as would be required if learning is to occur. Similar problems exist for more sophisticated networks constructed from the generic PDP architecture. We argue that this is because these models are not adequately constrained by the properties of the functional architecture assumed by PDP modelers. It is also argued that without such constraints, PDP researchers cannot claim to have developed an architecture radically different from that proposed by the Classical approach in cognitive science. (shrink)

Usage-based linguists and psychologists have produced a large body of empirical results suggesting that linguistic structure is derived from language use. However, while researchers agree that these results characterize grammar as an emergent phenomenon, there is no consensus among usage-based scholars as to how the various results can be explained and integrated into an explicit theory or model. Building on network theory, the current paper outlines a structured network approach to the study of grammar in which the core concepts of (...) syntax are analyzed by a set of relations that specify associations between different aspects of a speaker’s linguistic knowledge. These associations are shaped by domain-general processes that can give rise to new structures and meanings in language acquisition and language change. Combining research from linguistics and psychology, the paper proposes specific network analyses for the following phenomena: argument structure, word classes, constituent structure, constructions and construction families, and grammatical categories such as voice, case and number. The article builds on data and analyses presented inDiessel but approaches the topic from a different perspective. (shrink)

Sibley et al. (2008) report a recurrent neural network model designed to learn wordform representations suitable for written and spoken word identification. The authors claim that their sequence encoder network overcomes a key limitation associated with models that code letters by position (e.g., CAT might be coded as C‐in‐position‐1, A‐in‐position‐2, T‐in‐position‐3). The problem with coding letters by position (slot‐coding) is that it is difficult to generalize knowledge across positions; for example, the overlap between CAT and TOMCAT is lost. (...) Although we agree this is a critical problem with many slot‐coding schemes, we question whether the sequence encoder model addresses this limitation, and we highlight another deficiency of the model. We conclude that alternative theories are more promising. (shrink)

Lexical ambiguity can be syntactic if it involves more than one grammatical category for a single word, or semantic if more than one meaning can be associated with a word. In this article we discuss the application of a Bayesian‐network model in the resolution of lexical ambiguities of both types. The network we propose comprises a parsing subnetwork, which can be constructed automatically for any context‐free grammar, and a subnetwork for semantic analysis, which, in the spirit of (...) Fillmore's (1968) case grammars, seeks to fulfill the required cases of all candidates for verb of the sentence. Solving for the highest joint probability of the variables conditioned upon the evidences to the network yields the most likely candidate with its meaning, along with its cases and respective meanings. This is achieved by fixing the values of all evidence nodes concurrently, and then performing a stochastic simulation in which the remaining nodes are updated probabilistically with a high degree of parallelism. The process of disambiguation is directed neither by the syntax nor the semantics, but rather by the interrelation between the two subnetworks. The use of a Bayesian‐network model allows us to express this interrelation between the two subnetworks and among their constituents in a rather direct and rigorous way that, in connection with the convergence properties of the stochastic simulation, reveals a very robust model. (shrink)

A fundamental claim associated with parallel distributed processing theories of cognition is that knowledge is coded in a distributed manner in mind and brain. This approach rejects the claim that knowledge is coded in a localist fashion, with words, objects, and simple concepts, that is, coded with their own dedicated representations. One of the putative advantages of this approach is that the theories are biologically plausible. Indeed, advocates of the PDP approach often highlight the close parallels between distributed representations (...) learned in connectionist models and neural coding in brain and often dismiss localist theories as biologically implausible. The author reviews a range a data that strongly challenge this claim and shows that localist models provide a better account of single-cell recording studies. The author also contrast local and alternative distributed coding schemes and argues that common rejection of grandmother cell theories in neuroscience is due to a misunderstanding about how localist models behave. The author concludes that the localist representations embedded in theories of perception and cognition are consistent with neuroscience; biology only calls into question the distributed representations often learned in PDP models. (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)

One of the main limitations of natural language‐based approaches to meaning is that they do not incorporate multimodal representations the way humans do. In this study, we evaluate how well different kinds of models account for people's representations of both concrete and abstract concepts. The models we compare include unimodal distributional linguistic models as well as multimodal models which combine linguistic with perceptual or affective information. There are two types of linguistic models: those based on text corpora and those derived (...) from word association data. We present two new studies and a reanalysis of a series of previous studies. The studies demonstrate that both visual and affective multimodal models better capture behavior that reflects human representations than unimodal linguistic models. The size of the multimodal advantage depends on the nature of semantic representations involved, and it is especially pronounced for basic‐level concepts that belong to the same superordinate category. Additional visual and affective features improve the accuracy of linguistic models based on text corpora more than those based on word associations; this suggests systematic qualitative differences between what information is encoded in natural language versus what information is reflected in word associations. Altogether, our work presents new evidence that multimodal information is important for capturing both abstract and concrete words and that fully representing word meaning requires more than purely linguistic information. Implications for both embodied and distributional views of semantic representation are discussed. (shrink)

Semantic priming has been a focus of research in the cognitive sciences for more than 30 years and is commonly used as a tool for investigating other aspects of perception and cognition, such as word recognition, language comprehension, and knowledge representations. Semantic Priming: Perspectives from Memory and Word Recognition examines empirical and theoretical advancements in the understanding of semantic priming, providing a succinct, in-depth review of this important phenomenon, framed in terms of models of memory and models of (...) word recognition. The first section examines models of semantic priming, including spreading activation models, the verification model, compound-cue models, distributed network models, and multistage activation models (e.g. interactive-activation model). The second section examines issues and findings that have played an especially important role in testing models of priming and includes chapters on the following topics: methodological issues (e.g. counterbalancing of materials, choice of priming baselines); automatic vs. strategic priming; associative vs. "pure" semantic priming; mediated priming; long-term semantic priming; backward priming; unconscious priming; the prime-task effect; list context effects; effects of word frequency, stimulus quality, and stimulus repetition; and the cognitive neuroscience of semantic priming. The book closes with a summary and a discussion of promising new research directions. The volume will be of interest to a wide range of researchers and students in the cognitive sciences and neurosciences. (shrink)

Background: Although performance on the category fluency test is influenced by many cognitive functions, item-level scoring methods of CFT performance might be a promising way to capture aspects of semantic memory that are less influenced by intervenient abilities. One such approach is based on the calculation of correlation coefficients that quantify the association between item-level features and the serial order with which words are recalled.Methods: We explored the neural underpinnings of 10 of these correlational indices in a sample of 40 (...) healthy adults who completed a classic 1-min CFT and an MRI protocol inclusive of T1-weighted and resting-state fMRI sequences for the evaluation of the default-mode network. Two sets of linear models were defined to test the association between neural maps and each correlational index: a first set in which major demographic and clinical descriptors were controlled for and a second set in which, additionally, all other 9 correlational indices were regressed out.Results: In the analysis of the DMN, ‘SRO-frequency’, ‘SRO-dominance’ and ‘SRO-body-object interaction’ correlational indices were all negatively associated with the anterior portion of the right temporoparietal junction. The ‘SRO-frequency’ correlational index was also negatively associated with the right dorsal anterior cingulate and the ‘SRO-dominance’ correlational index with the right lateral prefrontal cortex. From the second set of models, the ‘SRO-typicality’ correlational index was positively associated with the left entorhinal cortex. No association was found in relation to grey matter maps.Conclusion: The ability to retrieve more difficult words during CFT performance as measured by the correlational indices between SRO and item-level descriptors is associated with DMN expression in regions deputed to attentional reorienting and processing of salience of infrequent stimuli and dominance status. Of all item-level features, typicality appears to be that most closely linked with entorhinal functioning and may thus play a relevant role in assessing its value in testing procedures for early detection of subtle cognitive difficulties in people with suspected Alzheimer’s degeneration. Although exploratory, these findings warrant further investigations in larger cohorts. (shrink)

The automated parsing of 130,213 news articles about the 2012 US presidential elections produces a network formed by the key political actors and issues, which were linked by relations of support and opposition. The nodes are formed by noun phrases and links by verbs, directly expressing the action of one node upon the other. This network is studied by applying insights from several theories and techniques, and by combining existing tools in an innovative way, including: graph partitioning, centrality, assortativity, hierarchy (...) and structural balance. The analysis yields various patterns. First, we observe that the fundamental split between the Republican and Democrat camps can be easily detected by network partitioning, which provides a strong validation check of the approach adopted, as well as a sound way to assign actors and topics to one of the two camps. Second, we identify the most central nodes of the political camps. We also learnt that Clinton played a more central role than Biden in the Democrat camp; the overall campaign was much focused on economy and rights; the Republican Party is the most divisive subject in the campaign, and is portrayed more negatively than the Democrats; and, overall, the media reported positive statements more frequently for the Democrats than the Republicans. This is the first study in which political positions are automatically extracted and derived from a very large corpus of online news, generating a network that goes well beyond traditional word-association networks by means of richer linguistic analysis of texts. (shrink)

The purpose of this study is to determine the psychological meaning of coauthorship for a group of scientists, based on the assumption that the meaning of a concept is related to experience on “how a person behaves in a situation, depending on what the situation signifies to him”. The semantic meaning provides for an interpretation of action in beliefs, goals and intentions, following the idea that semantic meaning is a basis for inferring intentions to perform action. We used the Natural (...) Semantic Networks Method. We interviewed 162 scientists in the physical and natural sciences. Results show a cluster of the semantic meaning of coauthorship in which collaboration, teamwork, work, common interest, discussion and others, are retrieved from memory and represented as a natural semantic network of the concept of coauthorship. Collaboration and teamwork are the two concepts that have the highest semantic value and this holds true for various disciplines although teamwork is the most elicited word associated to coauthorship. We propose a model in which coauthorship represents the result of the experience, attitudes and behavior of a group process concerning collaboration and teamwork in science. (shrink)

It is well-established that toddlers can correctly select a novel referent from an ambiguous array in response to a novel label. There is also a growing consensus that robust word learning requires repeated label-object encounters. However, the effect of the context in which a novel object is encountered is less well-understood. We present two embodied neural network replications of recent empirical tasks, which demonstrated that the context in which a target object is encountered is fundamental to referent selection and (...) word learning. Our model offers an explicit account of the bottom-up associative and embodied mechanisms which could support children’s early word learning and emphasises the importance of viewing behaviour as the interaction of learning at multiple timescales. (shrink)

ObjectivesSeveral studies have examined the effects of repetitive transcranial magnetic stimulation (rTMS) on associative memory (AM) but findings were inconsistent. Here, we aimed to test whether twice-daily rTMS could significantly improve AM.MethodsIn this single-blind, sham-controlled experiment, 40 participants were randomized to receive twice-daily sham or real rTMS sessions for five consecutive days (a total of 16,000 pulses). The stimulation target in left inferior parietal lobule (IPL) exhibiting peak functional connectivity to the left hippocampus was individually defined for each participant. Participants (...) completed both a picture-cued word association task and Stroop test at baseline and 1 day after the final real or sham rTMS session. Effects of twice-daily rTMS on AM and Stroop test performance were compared using two-way repeated measures analysis of variance with main factors Group (real vs. sham) and Time (baseline vs. post-rTMS).ResultsThere was a significant Group × Time interaction effect. AM score was significantly enhanced in the twice-daily real group after rTMS, but this difference could not survive the post hoc analysis after multiple comparison correction. Further, AM improvement in the twice-daily real group was not superior to a previously reported once-daily rTMS group receiving 8,000 pulses. Then, we combined the twice- and once-daily real groups, and found a significant Group × Time interaction effect. Post hoc analysis indicated that the AM score was significantly enhanced in the real group after multiple comparisons correction.ConclusionOur prospective experiment did not show significant rTMS effect on AM, but this effect may become significant if more participants could be recruited as revealed by our retrospective analysis. (shrink)

This paper investigated the part played by collaborative practices in chaneling the work of prominent biochemists into the development of molecular biology. The RNA collaborative network that emerged in the 1960s in France encompassed a continuum of activities that linked laboratories to policy-making centers. New institutional frameworks such as the DGRST committees were instrumental in establishing new patterns of funding, and in offering arenas for multidisciplinary debates and boundary assessment. It should be stressed however, that although this collaborative network was (...) based on centralized initiatives aimed at developing molecular biology as a new biological specialty, it operated above all as a nexus of practices. The main argument of this paper is that the central allocation of funds and resources, exemplified by the DGRST operation, actually enhanced the creation of a self-conscious community of biochemists turned molecular biologists by virtue of an increased circulation of tools, skills, and results that took place within the RNA network and a few analogous systems of exchange.Having hands on “things” viewed as identical for all practical purposes was a potent factor in changing the experimental systems and their meanings. Limited but shared means of doing helped to reduce uncertainties, change representations, and turn contingent decisions into meaningful choices. The collaborative enterprises then resulted in personal contacts and the transfer of skills and materials, which gradually incorporated the biochemical tools into systems producing facts relevant to molecular biology as defined by its early practitioners. In that sense, networking was a regulatory process that stabilized new research objects and acculturated French biochemists.The mere existence of such a collaborative network also changed the scale of the disciplining process. Collaborations may have been started for contingent motives, but multiple exchanges resulted in the emergence of a new collective, and amplified small displacements. Collaborations, however, worked both ways, and the RNA network may be viewed as an efficient “trading-post.” An unexpected outcome of the development of a conversion zone is the fact that, by the late 1960s, the former biochemists dominated the “new” world of molecular biology — both in terms of research habits, since interests in structural studies dominated the field, and in terms of institutional initiatives such as the creation of laboratories and institutes for molecular biology.As an example of the cognitive displacements achieved by the network, I have focused here on the stabilization of “messenger RNA” as a new biological entity. This process illustrates the role of “boundary objects” and other mediating innovations in the development of disciplinary structures. Students of science trained in the symbolic interactionism tradition have proposed that “boundary objects” enhance the multiple interactions between heterogeneous social worlds: they are robust enough to enhance unity, but plastic enough to be manipulated in different social and cultural contexts.81 Within the emerging network, messenger RNA was a weakly structured “genetic information carrier” in common use, but it could, at the same time, be a strongly structured “macromolecular structure” adapted to practical and local uses. Consequently, messenger RNA favored the association of groups of heterogeneous scientists with backgrounds and interests in medical biochemistry, genetics, physical chemistry, organic chemistry, and so forth. This contrast between general and local uses was also instrumental in integrating the manipulation of things and the negotiation of aims. In contrast to transfer RNAs, which in the French context remained objects for chemical (and mainly structural) studies, messenger RNA became a key component of the new culture of “genetic information”. Messenger RNA was a loose theoretical entity described as a “genetic information carrier” in the policy-making documents, while operational but tacit and more conflicting definitions prevailed at the bench. In other words, messenger RNA was not only a classical “boundary object” but also a “flag object,” which tightened the collaborative network by mediating between the DGRST offices and the laboratories. (shrink)

Récurrente sous différentes formes dans le domaine de la lexicométrie, l’analyse cooccurrentielle vise à dévoiler les attractions lexicales qui opèrent dans un texte en restituant un état intermédiaire entre la séquence textuelle et l’inventaire lexical, état qui doit combiner l’explicitation syntagmatique de l’une avec la hiérarchisation statistique de l’autre. Pour dépasser les résultats des méthodes de cooccurrence classiques et identifier des systèmes cooccurrentiels plus complexes à l’oeuvre dans le texte, il s’avère nécessaire de substituer à l’approche analytique des associations lexicales (...) une vue synthétique de ces attractions prééminentes en contexte. (shrink)

Existing behavioral, neuropsychological and functional neuroimaging data suggest that at least two major cognitive strategies are used for new word learning: fast mapping via context-dependent inference and explicit encoding via direct instruction. However, these distinctions remain debated at both behavioral and neurophysiological levels, not least due to confounds related to diverging experimental settings. Furthermore, the neural dynamics underpinning these two putative processes remain poorly understood. To tackle this, we designed a paradigm presenting 20 new spoken words in association with (...) pictures in either FM or EE settings, closely matched for auditory and visual features and overall task demands. We tested word acquisition using a range of behavioral measures as well as passive event-related potential responses, an established measure of word memory trace activation, and compared brain activity elicited by novel FM and EE words before and after the learning session. Behavioral data obtained in free recall, recognition and semantic word-picture matching tasks indicated successful acquisition of new words after just 10 exposures. Crucially, we found no behavioral evidence of different acquisition outcomes between FM and EE learning. ERP data, which exhibited the main response peaks at ~170, 250, and 520 ms, also indicated successful learning, with statistically different responses between novel and familiar words present only before, but not after the training, suggesting rapid formation of new neural memory circuits matching in activation those for previously known words. Furthermore, already at the earliest peak, we found different topographic distributions for the two learning types, with left-lateralized FM dynamics, suggestive of core language system involvement, and more diffuse activity for EE items, possibly suggesting the role of attention/executive control network. A similar effect also manifested later, at ~520 ms. Our data suggest that while both EE and FM learning can be successful for rapid word acquisition at the behavioral level, the diverging electrophysiological patterns suggest a dissociation between the neural systems underpinning these learning strategies. (shrink)

Current empirical work suggests that early social experiences could have a substantial impact on the areas of the brain responsible for representation of the body. In this context, one aspect of functioning that may be particularly susceptible to social experiences is interoception. Interoceptive functioning has been linked to several areas of the brain which show protracted post-natal development, thus leaving a substantial window of opportunity for environmental input to impact the development of the interoceptive network. We first introduce a biopsychosocial (...) model of interoceptive development. In our proposed model of interoceptive development, attachment related processes are purported to affect the development of interoception by influencing the growth of neural architecture and by modifying functioning of the HPA axis. Further, the idea that patterns of caretaking affect children’s development of interoception is presented. This model explains both normatively developing interoception and accounts for instances in which dysfunctional attachment related processes can lead to either a hypersensitivity or a blunted awareness of bodily cues. Second, we report findings from two existing datasets showing significant relationships between attachment related processes and interoception. In the first study, looking at a sample of healthy young adults (n = 132, 66 males), we assessed self-reported interoceptive awareness and attachment style. We found relationships between aspects of interoception and attachment style such that avoidant individuals reported lower interoceptive functioning across several dimensions (r’s (130) = -.20 to -.26, p’s<.05). More anxious individuals, on the other hand, reported heightened interoceptive across several dimensions (r’s(130)=.18 to.43, p’s <.05). In the second study, we examined the congruence between a person’s self-reported negative emotion and a measure of sympathetic nervous system arousal (SCL). The congruence score was positively associated with parental rejection of negative emotion. These results suggest that parenting style, as reported by the mother, are associated with a child’s ability to coordinate their self-reported emotional and physiological responding across a series of independent assessments, r(108)= -.24, p<.05. In other words, the more maternal reported parental rejection of child negative emotions, the less congruent a child’s self and physiological reports of distress. (shrink)

The negative impact of adverse experiences in childhood on neurodevelopment is well documented. Less attention however has been given to the impact of variations in “normative” parenting behaviors. The influence of these parenting behaviors is likely to be marked during periods of rapid brain reorganization, such as late childhood. The aim of the current study was to investigate associations between normative parenting behaviors and the development of structural brain networks across late childhood. Data were collected from a longitudinal sample (...) of 114 mother-child dyads, recruited from low socioeconomic areas of Melbourne, Australia. At the first assessment parenting behaviors were coded from two lab-based interaction tasks and structural magnetic resonance imaging scans of the children were performed. At the second assessment, approximately 18 months later MRI scans were repeated. Cortical thickness was extracted from T1-weighted images using FreeSurfer. Structural covariance networks were constructed from partial correlations of CT estimates between brain regions and estimates of network efficiency and modularity were obtained for each time point. The change in these network measures, from Time 1 to Time 2, was also calculated. At Time 2, less positive maternal affective behavior was associated with higher modularity, while negative maternal affective behavior was not related. No support was found for an association between local or global efficacy and maternal affective behaviors at Time 2. Similarly, no support was demonstrated for associations between maternal affective behaviors and change in network efficiency and modularity, from Time 1 to Time 2. These results indicate that normative variations in parenting may influence the development of structural brain networks in late childhood and extend current knowledge about environmental influences on structural connectivity in a developmental context. (shrink)

Ideas from random graph theory are used to give an heuristic argument that associative memory structure depends discontinuously on pattern recognition ability. This argument suggests that there may be a certain minimal size for intelligent systems.

When we humans receive uncertain information, we interpret it properly, so we can expand the conversation, and take the proper actions. This is possible because we have “common sense” concerning the basic word concept, which is built up from long time experience storing knowledge of our language. Of the common sense we use in our every day lives we think that there are; common sense concerning quantity such as size, weight, speed, time, or place; common sense concerning sense or (...) feeling such as hot, beautiful, or loud; and moreover common sense concerning emotion such as happy or sad. In order to make computers closer to human beings, we think that the construction of a “Common Sense Judgment System” which deals with these kinds of common sense is necessary. When aiming to realize this “Common Sense Judgment System” and trying to make a computer have the same common sense knowledge and judgment ability as human beings, a very important factor is the handling of unknown words. Judgment concerning words which were given to the computer as knowledge before hand, it can refer to that knowledge, and the process will have no problem at all. But when an unknown word, which is not registered as knowledge, is inputted, how to process that word is a very difficult problem. In this paper, by using a concept base, which is made from several electric dictionaries; the degree of association, which is done based on the concept base; neural network, putting the closeness of meaning in consideration, we propose a method of unknown word processing, which connects an inputted unknown word to a representing word that is registered in the judgment knowledge base, and we will verify its effectiveness by experiment applied to the emotional judgment subsystem. (shrink)

Récurrente sous différentes formes dans le domaine de la lexicométrie, l’analyse cooccurrentielle vise à dévoiler les attractions lexicales qui opèrent dans un texte en restituant un état intermédiaire entre la séquence textuelle et l’inventaire lexical, état qui doit combiner l’explicitation syntagmatique de l’une avec la hiérarchisation statistique de l’autre. Pour dépasser les résultats des méthodes de cooccurrence classiques et identifier des systèmes cooccurrentiels plus complexes à l’oeuvre dans le texte, il s’avère nécessaire de substituer à l’approche analytique des associations lexicales (...) une vue synthétique de ces attractions prééminentes en contexte. (shrink)

Merker's insightful broad review fertilely recasts the mind/brain issue, but the phenomenological appeals require additional considerations of behavioral and neural flexibility. Motor equivalences and perceptual constancies may be cortical contributions to a “robotic” tectal orientation mechanism. Intermediate “third layers” of associative neural networks, each with a few diffusely summing convergence-divergence modules, may be the economical expedient by which evolution has extended the limited unity-in-diversity of sensorimotor coordination to perception, action, thinking, and memory. (Published Online May 1 2007).

Scientific study of dreams requires the most objective methods to reliably analyze dream content. In this context, artificial intelligence should prove useful for an automatic and non subjective scoring technique. Past research has utilized word search and emotional affiliation methods, to model and automatically match human judges’ scoring of dream report’s negative emotional tone. The current study added word associations to improve the model’s accuracy. Word associations were established using words’ frequency of co-occurrence with their defining words (...) as found in a dictionary and an encyclopedia. It was hypothesized that this addition would facilitate the machine learning model and improve its predictability beyond those of previous models. With a sample of 458 dreams, this model demonstrated an improvement in accuracy from 59% to 63% on the negative emotional tone scale, and for the first time reached an accuracy of 77% on the positive scale. (shrink)

This is an excerpt from a report that highlights and explores five questions which arose from the workshop on perceptual learning and perceptual recognition at the University of Toronto, Mississauga on May 10th and 11th, 2012. This excerpt explores the question: What are the origins of multimodal associations?

Public companies in the US stock market must annually report their activities and financial performances to the SEC by filing the so-called 10-K form. Recent studies have demonstrated that changes in the textual content of the corporate annual filing can convey strong signals of companies’ future returns. In this study, we combine natural language processing techniques and network science to introduce a novel 10-K-based network, named Lazy Network, that leverages year-on-year changes in companies’ 10-Ks detected using a neural network embedding (...) model. The Lazy Network aims to capture textual changes derived from financial or economic changes on the equity market. Leveraging the Lazy Network, we present a novel investment strategy that attempts to select the least disrupted and stable companies by capturing the peripheries of the Lazy Network. We show that this strategy earns statistically significant risk-adjusted excess returns. Specifically, the proposed portfolios yield up to 95 basis points in monthly five-factor alphas, outperforming similar strategies in the literature. (shrink)

Background: Alexithymia is a personality trait which is characterized by an inability to identify and describe conscious emotions of oneself and others.Aim: The present study aimed to determine whether various measures of mental health, interoception, psychological flexibility, and self-as-context, predicted through linear associations alexithymia as an outcome. This also included relevant mediators and non-linear predictors identified for particular sub-groups of participants through cluster analyses of an Artificial Neural Network output.Methodology: Two hundred and thirty participants completed an online survey which included (...) the following questionnaires: Toronto alexithymia scale; Acceptance and Action Questionnaire 2 ; Positive and Negative Affect Scale, Depression, Anxiety, and Stress Scale 21 ; Multidimensional Assessment of Interoceptive Awareness ; and the Self-as-Context scale. A stepwise backwards linear regression and mediation analysis were performed, as well as a cluster analysis of the non-linear ANN upper hidden layer output.Results: Higher levels of alexithymia were associated with increased psychological inflexibility, lower positive affect scores, and lower interoception for the subscales of “not distracting” and “attention regulation.” SAC mediated the relation between emotional regulation and total alexithymia. The ANNs accounted for more of the variance than the linear regressions, and were able to identify complex and varied patterns within the participant subgroupings.Conclusion: The findings were discussed within the context of developing a SAC processed-based therapeutic model for alexithymia, where it is suggested that alexithymia is a complex and multi-faceted condition, which requires a similarly complex, and process-based approach to accurately diagnose and treat this condition. (shrink)

Creative association is inherent and essential to creativity and insight. Here we utilised a Chinese compound Remote Associates Task (cRAT) to identify the potential impact of word order (i.e., solution position hereinafter) and word frequency on creative association across two behavioural experiments. Experiment 1 identified the effects of (a) word order and word frequency on cRAT-induced association without considering the specific strategies used during solving such problems and (b) their interaction not only on performance in solving (...) the cRAT, including solution time and accuracy, but also on difficulty rating. Following a coarse-to-fine approach, Experiment 2 examined the effect of both factors on creative association determined according to each participant’s trial-by-trial reports regarding insight solution strategies. Main effects of word order and word frequency, and a two-way interaction, were found on the accuracy and self-rated difficulty. These findings shed light on creative association, multiply-constrained problem solving and constructing compounds. (shrink)

Do properties of a word's features influence the order of its acquisition in early word learning? Combining the principles of mutual exclusivity and shape bias, the present work takes a network analysis approach to understanding how feature distinctiveness predicts the order of early word learning. Distance networks were built from nouns with edge lengths computed using various distance measures. Feature distinctiveness was computed as a distance measure, showing how far an object in a network is from (...) other objects based on shared and non-shared features. Feature distinctiveness predicted order of acquisition across all measures: Words that were further away from other words in the network space were learned earlier. The best distance measures were based only on non-shared features and did not include shared features. This indicates that shared features may play less of a role in early word learning than non-shared features. In addition, the strongest effects were found for visual form and surface features. Cluster analysis further revealed that this effect is a localized effect in the object feature space, where objects' distances from their cluster centroid were inversely correlated with their age of acquisition. Together, these results suggest a role for feature distinctiveness in early word learning. (shrink)