Nuances of knowing: Brain potentials reveal implicit effects of domain knowledge on word processing in the absence of sentence-level knowledge

In previous work investigating the relationship between domain knowledge (of the fictional world of Harry Potter) and sentence comprehension, domain knowledge had a greater impact on electrical brain potentials to words which completed sentences about fictional "facts" participants reported they did not know compared to facts they did. This suggests that individuals use domain knowledge continuously to activate relevant/related concepts as they process sentences, even with only partial knowledge. As that study relied on subjective reports, it may have resulted in response bias related to an individual's overall domain knowledge. In the present study, we therefore asked participants with varying degrees of domain knowledge to complete sentences describing fictional "facts" as an objective measure of sentence-level knowledge. We then recorded EEG as the same individuals (re-)read the same sentences, including their appropriate final words, and sorted these according to their objective knowledge scores. Replicating and extending Troyer et al., domain knowledge immediately facilitated access to meaning for unknown words; greater domain knowledge was associated with reduced N400 amplitudes for unknown words. These findings constitute novel evidence for graded preactivation of conceptual knowledge (e.g., at the level of semantic features and/or relations) in the absence of lexical prediction. Knowledge also influenced post-N400 memory/integration processes for these same unknown words; greater domain knowledge was associated with enhanced late positive components (LPCs), suggesting that deeper encoding during language processing may be engendered when knowledgeable individuals encounter an apparent gap in their knowledge.

Feats: A database of semantic features for early produced noun concepts

Semantic feature production norms have several desirable characteristics that have supported models of representation and processing in adults. However, several key challenges have limited the use of semantic feature norms in studies of early language acquisition. First, existing norms provide uneven and inconsistent coverage of early-acquired concepts that are typically produced and assessed in children under the age of three, which is a time of tremendous growth of early vocabulary skills. Second, it is difficult to assess the degree to which young children may be familiar with normed features derived from these adult-generated datasets. Third, it has been difficult to adopt standard methods to generate semantic network models of early noun learning. Here, we introduce Feats-a tool that was designed to make headway on these challenges by providing a database, the Language Learning and Meaning Acquisition (LLaMA) lab Noun Norms that extends a widely used set of feature norms McRae et al. Behavior Research Methods 37, 547-559, (2005) to include full coverage of noun concepts on a commonly used early vocabulary assessment. Feats includes several tools to facilitate exploration of features comprising early-acquired nouns, assess the developmental appropriateness of individual features using toddler-accessibility norms, and extract semantic network statistics for individual vocabulary profiles. We provide a tutorial overview of Feats. We additionally validate our approach by presenting an analysis of an overlapping set of concepts collected across prior and new data collection methods. Furthermore, using network graph analyses, we show that the extended set of norms provides novel, reliable results given their enhanced coverage.

Perirhinal cortex automatically tracks multiple types of familiarity regardless of task-relevance

Perirhinal cortex (PrC) has long been implicated in familiarity assessment for objects and corresponding concepts. However, extant studies have focused mainly on changes in familiarity induced by recent exposure in laboratory settings. There is an increasing appreciation of other types of familiarity signals, in particular graded familiarity accumulated throughout one's lifetime. In prior work (Duke et al., 2017, Cortex, 89, 61-70), PrC has been shown to track lifetime familiarity ratings when participants make related judgements. A theoretically important characteristic of familiarity is its proposed automaticity. Support for automaticity comes from a documented impact of recent stimulus exposure on behavioral performance, and on PrC signals, under conditions in which this exposure is not task relevant. In the current fMRI study, we tested whether PrC also tracks lifetime familiarity of object concepts automatically, and whether this type of familiarity influences behavior even when it is not task relevant. During scanning, neurotypical participants (N = 30, age range 18-40, 7 males) provided animacy judgements about concrete object concepts presented at differing frequencies in an initial study phase. In a subsequent test phase, they made graded judgements of recent or lifetime familiarity. Behavioral performance showed sensitivity to lifetime familiarity even when it was not relevant for the task at hand. Across five sets of fMRI analyses, we found that PrC consistently tracked recent and lifetime familiarity of object concepts regardless of the task at hand. Critically, while several other temporal-lobe regions also showed isolated familiarity effects, none of them tracked familiarity with the same consistency. These findings demonstrate that PrC automatically tracks multiple types of familiarity. They support models that assign a broad role in the representation of information about object concepts to this structure.

Investigating the Extent to which Distributional Semantic Models Capture a Broad Range of Semantic Relations

Distributional semantic models (DSMs) are a primary method for distilling semantic information from corpora. However, a key question remains: What types of semantic relations among words do DSMs detect? Prior work typically has addressed this question using limited human data that are restricted to semantic similarity and/or general semantic relatedness. We tested eight DSMs that are popular in current cognitive and psycholinguistic research (positive pointwise mutual information; global vectors; and three variations each of Skip-gram and continuous bag of words (CBOW) using word, context, and mean embeddings) on a theoretically motivated, rich set of semantic relations involving words from multiple syntactic classes and spanning the abstract-concrete continuum (19 sets of ratings). We found that, overall, the DSMs are best at capturing overall semantic similarity and also can capture verb-noun thematic role relations and noun-noun event-based relations that play important roles in sentence comprehension. Interestingly, Skip-gram and CBOW performed the best in terms of capturing similarity, whereas GloVe dominated the thematic role and event-based relations. We discuss the theoretical and practical implications of our results, make recommendations for users of these models, and demonstrate significant differences in model performance on event-based relations.

Predictive language comprehension in Parkinson's disease

Verb and action knowledge deficits are reported in persons with Parkinson's disease (PD), even in the absence of dementia or mild cognitive impairment. However, the impact of these deficits on combinatorial semantic processing is less well understood. Following on previous verb and action knowledge findings, we tested the hypothesis that PD impairs the ability to integrate event-based thematic fit information during online sentence processing. Specifically, we anticipated persons with PD with age-typical cognitive abilities would perform more poorly than healthy controls during a visual world paradigm task requiring participants to predict a target object constrained by the thematic fit of the agent-verb combination. Twenty-four PD and 24 healthy age-matched participants completed comprehensive neuropsychological assessments. We recorded participants' eye movements as they heard predictive sentences (The fisherman rocks the boat) alongside target, agent-related, verb-related, and unrelated images. We tested effects of group (PD/control) on gaze using growth curve models. There were no significant differences between PD and control participants, suggesting that PD participants successfully and rapidly use combinatory thematic fit information to predict upcoming language. Baseline sentences with no predictive information (e.g., Look at the drum) confirmed that groups showed equivalent sentence processing and eye movement patterns. Additionally, we conducted an exploratory analysis contrasting PD and controls' performance on low-motion-content versus high-motion-content verbs. This analysis revealed fewer predictive fixations in high-motion sentences only for healthy older adults. PD participants may adapt to their disease by relying on spared, non-action-simulation-based language processing mechanisms, although this conclusion is speculative, as the analyses of high- vs. low-motion items was highly limited by the study design. These findings provide novel evidence that individuals with PD match healthy adults in their ability to use verb meaning to predict upcoming nouns despite previous findings of verb semantic impairment in PD across a variety of tasks.

Knowledge of the temporal structure of events in relation to autistic traits and social ability

Event knowledge, a person's understanding of patterns of activities in the world, is crucial for everyday social interactions. Social communication differences are prominent in autism, which may be related to atypical event knowledge, such as atypical knowledge of the sequences of activities that comprise the temporal structure of events. Previous research has found that autistic individuals have atypical event knowledge, but research in this area is minimal, particularly regarding autistic individuals' knowledge of the temporal structure of events. Furthermore, no studies have investigated the link between event knowledge and autistic traits in a non-clinical sample. We investigated relationships between event knowledge and autistic traits in individuals from the general population with varying degrees of autistic traits. We predicted that atypical ordering of event activities is related to autistic traits, particularly social communication abilities, but not other clinical traits. In Study 1, atypical ordering of event activities correlated with social ability, but not with most measures of repetitive behaviours and restricted interests. In Study 2, the typicality of activity ordering varied by participants' social ability and the social nature of the events. Relationships were not found between event activity ordering and other clinical traits. These findings suggest a relationship between autistic traits, specifically social abilities, and knowledge of the temporal structure of events in a general population sample.

Can you touch the N400? The interactive effects of body-object interaction and task demands on N400 amplitudes and decision latencies

The effects of semantic richness on N400 amplitudes remain unclear. Some studies have reported semantic richness evoking greater N400s, whereas others have reported the opposite effect. Moreover, N400 effects of some semantic richness variables, such as body-object interaction (BOI), have yet to be demonstrated. BOI quantifies the degree to which a word's referent is easy to interact with; words such as bicycle are high-BOI whereas words such as butterfly are low-BOI. We examined BOI effects on N400 amplitudes and decision latencies in two semantic tasks. We found that in a touchable/untouchable task, low-BOI words (e.g., butterfly) evoked greater N400s than high-BOI words (e.g., bicycle), but there was no difference in decision latencies. Conversely, in a concrete/abstract task, high and low-BOI words evoked similar N400s, but decision latencies were shorter for high-BOI than for low-BOI words. Our results show that semantic richness upstream and downstream effects are dissociable and task dependent.

Thematic and other semantic relations central to abstract (and concrete) concepts

In this article, we discuss multiple types of meaningful (semantic) relations underlying abstract (as compared to concrete) concepts. We adopt the viewpoint that words act as cues to meaning (Elman in Ment Lexicon 6(1):1-34, 2011; Lupyan and Lewis in Lang Cogn Neurosci 34(10):1319-1337, 2019), which is dependent on the dynamic contents of a comprehender's mental model of the situation. This view foregrounds the importance of both linguistic and real-world context as individuals make sense of words, flexibly access relevant knowledge, and understand described events and situations. We discuss theories of, and experimental work on, abstract concepts through the lens of the importance of thematic and other semantic relations. We then tie these findings to the sentence processing literature in which such meaningful relations within sentential contexts are often experimentally manipulated. In this literature, some specific classes/types of abstract words have been studied, although not comprehensively, and with limited connection to the literature on knowledge underlying abstract concepts reviewed herein. We conclude by arguing that the ways in which humans understand relatively more abstract concepts, in particular, can be informed by the careful study of words presented not in isolation, but rather in situational and linguistic contexts, and as a function of individual differences in knowledge, goals, and beliefs.

Late positive complex in event-related potentials tracks memory signals when they are decision relevant

The Late Positive Complex (LPC) is an Event-Related Potential (ERP) consistently observed in recognition-memory paradigms. In the present study, we investigated whether the LPC tracks the strength of multiple types of memory signals, and whether it does so in a decision dependent manner. For this purpose, we employed judgements of cumulative lifetime exposure to object concepts, and judgements of cumulative recent exposure (i.e., frequency judgements) in a study-test paradigm. A comparison of ERP signatures in relation to degree of prior exposure across the two memory tasks and the study phase revealed that the LPC tracks both types of memory signals, but only when they are relevant to the decision at hand. Another ERP component previously implicated in recognition memory, the FN400, showed a distinct pattern of activity across conditions that differed from the LPC; it tracked only recent exposure in a decision-dependent manner. Another similar ERP component typically linked to conceptual processing in past work, the N400, was sensitive to degree of recent and lifetime exposure, but it did not track them in a decision dependent manner. Finally, source localization analyses pointed to a potential source of the LPC in left ventral lateral parietal cortex, which also showed the decision-dependent effect. The current findings highlight the role of decision making in ERP markers of prior exposure in tasks other than those typically used in studies of recognition memory, and provides an initial link between the LPC and the previously suggested role of ventral lateral parietal cortex in memory judgements.

Universal Features in Phonological Neighbor Networks

Human speech perception involves transforming a countinuous acoustic signal into discrete linguistically meaningful units (phonemes) while simultaneously causing a listener to activate words that are similar to the spoken utterance and to each other. The Neighborhood Activation Model posits that phonological neighbors (two forms [words] that differ by one phoneme) compete significantly for recognition as a spoken word is heard. This definition of phonological similarity can be extended to an entire corpus of forms to produce a phonological neighbor network (PNN). We study PNNs for five languages: English, Spanish, French, Dutch, and German. Consistent with previous work, we find that the PNNs share a consistent set of topological features. Using an approach that generates random lexicons with increasing levels of phonological realism, we show that even random forms with minimal relationship to any real language, combined with only the empirical distribution of language-specific phonological form lengths, are sufficient to produce the topological properties observed in the real language PNNs. The resulting pseudo-PNNs are insensitive to the level of lingustic realism in the random lexicons but quite sensitive to the shape of the form length distribution. We therefore conclude that “universal” features seen across multiple languages are really string universals, not language universals, and arise primarily due to limitations in the kinds of networks generated by the one-step neighbor definition. Taken together, our results indicate that caution is warranted when linking the dynamics of human spoken word recognition to the topological properties of PNNs, and that the investigation of alternative similarity metrics for phonological forms should be a priority.

Abstract Concepts and Pictures of Real-World Situations Activate One Another

concepts typically are defined in terms of lacking physical or perceptual referents. We argue instead that they are not devoid of perceptual information because knowledge of real-world situations is an important component of learning and using many abstract concepts. Although the relationship between perceptual information and abstract concepts is less straightforward than for concrete concepts, situation-based perceptual knowledge is part of many abstract concepts. In Experiment 1, participants made lexical decisions to abstract words that were preceded by related and unrelated pictures of situations. For example, share was preceded by a picture of two girls sharing a cob of corn. When pictures were presented for 500 ms, latencies did not differ. However, when pictures were presented for 1,000 ms, decision latencies were significantly shorter for abstract words preceded by related versus unrelated pictures. Because the abstract concepts corresponded to the pictured situation as a whole, rather than a single concrete object or entity, the necessary relational processing takes time. In Experiment 2, on each trial, an abstract word was presented for 250 ms, immediately followed by a picture. Participants indicated whether or not the picture showed a normal situation. Decision latencies were significantly shorter for pictures preceded by related versus unrelated abstract words. Our experiments provide evidence that knowledge of events and situations is important for learning and using at least some types of abstract concepts. That is, abstract concepts are grounded in situations, but in a more complex manner than for concrete concepts. Although people's understanding of abstract concepts certainly includes knowledge gained from language describing situations and events for which those concepts are relevant, sensory and motor information experienced during real-life events is important as well.

Complement Coercion: The Joint Effects of Type and Typicality

Complement coercion (begin a book →reading) involves a type clash between an event-selecting verb and an entity-denoting object, triggering a covert event (reading). Two main factors involved in complement coercion have been investigated: the semantic type of the object (event vs. entity), and the typicality of the covert event (the author began a book →writing). In previous research, reading times have been measured at the object. However, the influence of the typicality of the subject–object combination on processing an aspectual verb such as begin has not been studied. Using a self-paced reading study, we manipulated semantic type and subject–object typicality, exploiting German word order to measure reading times at the aspectual verb. These variables interacted at the target verb. We conclude that both type and typicality probabilistically guide expectations about upcoming input. These results are compatible with an expectation-based view of complement coercion and language comprehension more generally in which there is rapid interaction between what is typically viewed as linguistic knowledge, and what is typically viewed as domain general knowledge about how the world works.

Perirhinal cortex tracks degree of recent as well as cumulative lifetime experience with object concepts

Evidence from numerous sources indicates that recognition of the prior occurrence of objects requires computations of perirhinal cortex (PrC) in the medial temporal lobe (MTL). Extant research has primarily probed recognition memory based on item exposure in a recent experimental study episode. Outside the laboratory, however, familiarity for objects typically accrues gradually with learning across many different episodic contexts, which can be distributed over a lifetime of experience. It is currently unknown whether PrC also tracks this cumulative lifetime experience with object concepts. To address this issue, we conducted a functional magnetic resonance imaging (fMRI) experiment in healthy individuals in which we compared judgments of the perceived lifetime familiarity with object concepts, a task that has previously been employed in many normative studies on concept knowledge, with frequency judgments for recent laboratory exposure in a study phase. Guided by neurophysiological data showing that neurons in primate PrC signal prior object exposure at multiple time scales, we predicted that PrC responses would track perceived prior experience in both types of judgments. Left PrC and a number of cortical regions that are often co-activated as part of the default-mode network showed an increase in Blood-Oxygen-Level Dependent (BOLD) response in relation to increases in the perceived cumulative lifetime familiarity of object concepts. These regions included the left hippocampus, left mid-lateral temporal cortex, as well as anterior and posterior cortical midline structures. Critically, left PrC was found to be the only region that showed this response in combination with the typically observed decrease in signal for perceived recent exposure in the experimental study phase. These findings provide, to our knowledge, the first evidence that ties signals in human PrC to variations in cumulative lifetime experience with object concepts. They offer a new link between the role of PrC in recognition memory and its broader role in conceptual processing.

The reliability of the N400 in single subjects: implications for patients with disorders of consciousness

Functional neuroimaging assessments of residual cognitive capacities, including those that support language, can improve diagnostic and prognostic accuracy in patients with disorders of consciousness. Due to the portability and relative inexpensiveness of electroencephalography, the N400 event-related potential component has been proposed as a clinically valid means to identify preserved linguistic function in non-communicative patients. Across three experiments, we show that changes in both stimuli and task demands significantly influence the probability of detecting statistically significant N400 effects - that is, the difference in N400 amplitudes caused by the experimental manipulation. In terms of task demands, passively heard linguistic stimuli were significantly less likely to elicit N400 effects than task-relevant stimuli. Due to the inability of the majority of patients with disorders of consciousness to follow task commands, the insensitivity of passive listening would impede the identification of residual language abilities even when such abilities exist. In terms of stimuli, passively heard normatively associated word pairs produced the highest detection rate of N400 effects (50% of the participants), compared with semantically-similar word pairs (0%) and high-cloze sentences (17%). This result is consistent with a prediction error account of N400 magnitude, with highly predictable targets leading to smaller N400 waves, and therefore larger N400 effects. Overall, our data indicate that non-repeating normatively associated word pairs provide the highest probability of detecting single-subject N400s during passive listening, and may thereby provide a clinically viable means of assessing residual linguistic function. We also show that more liberal analyses may further increase the detection-rate, but at the potential cost of increased false alarms.

Computational Grounded Cognition: a new alliance between grounded cognition and computational modeling

Grounded theories assume that there is no central module for cognition. According to this view, all cognitive phenomena, including those considered the province of amodal cognition such as reasoning, numeric, and language processing, are ultimately grounded in (and emerge from) a variety of bodily, affective, perceptual, and motor processes. The development and expression of cognition is constrained by the embodiment of cognitive agents and various contextual factors (physical and social) in which they are immersed. The grounded framework has received numerous empirical confirmations. Still, there are very few explicit computational models that implement grounding in sensory, motor and affective processes as intrinsic to cognition, and demonstrate that grounded theories can mechanistically implement higher cognitive abilities. We propose a new alliance between grounded cognition and computational modeling toward a novel multidisciplinary enterprise: Computational Grounded Cognition. We clarify the defining features of this novel approach and emphasize the importance of using the methodology of Cognitive Robotics, which permits simultaneous consideration of multiple aspects of grounding, embodiment, and situatedness, showing how they constrain the development and expression of cognition.

Integrating words that refer to typical sequences of events

The organisation and processing of event concepts in semantic memory is an important issue in language processing and memory research. The present study tested whether pairs of words denoting events that can plausibly occur in sequence (marinate-grill) generate expectancies for a target that denotes a subsequently occurring event (chew). In Experiment 1, two events that tend to occur sequentially primed the third. In Experiment 2, the individual primes (i.e., marinate and grill separately) did not prime their related event targets. Experiments 1 and 2 used a lexical-decision task on the target. Therefore, information from both primes must be integrated to sufficiently activate knowledge of the subsequently occurring target. This is the first study to demonstrate priming among words denoting sequentially occurring events. In Experiment 3, a relatedness decision task, processing of these event triplets was facilitated when the first two event words were presented in a temporally correct order compared with when their order was reversed. These findings are not predicted by spreading activation theory and cannot be simulated by corpus-based models that do not include order-sensitive measures. We interpret the results as evidence for the role of situation models and the use of world knowledge during online language comprehension, even in the absence of sentential contexts.

Generalized event knowledge activation during online sentence comprehension

Recent research has demonstrated that knowledge of real-world eventsplays an important role inguiding online language comprehension. The present study addresses the scope of event knowledge activation during the course of comprehension, specifically investigating whether activation is limited to those knowledge elements that align with the local linguistic context.The present study addresses this issue by analyzing event-related brain potentials (ERPs) recorded as participants read brief scenariosdescribing typical real-world events. Experiment 1 demonstratesthat a contextually anomalous word elicits a reduced N400 if it is generally related to the described event, even when controlling for the degree of association of this word with individual words in the preceding context and with the expected continuation. Experiment 2 shows that this effect disappears when the discourse context is removed.These findings demonstrate that during the course of incremental comprehension, comprehenders activate general knowledge about the described event, even at points at which this knowledge would constitute an anomalous continuation of the linguistic stream. Generalized event knowledge activationcontributes to mental representations of described events, is immediately available to influence language processing, and likely drives linguistic expectancy generation.

False recall in the Deese-Roediger-McDermott paradigm: The roles of gist and associative strength

Theories of false memories, particularly in the Deese-Roediger-McDermott (DRM) paradigm, focus on word association strength and gist. Backward associative strength (BAS) is a strong predictor of false recall in this paradigm. However, other than being defined as a measure of association between studied list words and falsely recalled nonpresented critical words, there is little understanding of this variable. In Experiment 1, we used a knowledge-type taxonomy to classify the semantic relations in DRM stimuli. These knowledge types predicted false-recall probability, as well as BAS itself, with the most important being situation features, synonyms, and taxonomic relations. In three subsequent experiments, we demonstrated that lists composed solely of situation features can elicit a gist and produce false memories, particularly when monitoring processes are made more difficult. Our results identify the semantic factors that underlie BAS and suggest how considering semantic relations leads to a better understanding of gist formation.

Event-based plausibility immediately influences on-line language comprehension

In some theories of sentence comprehension, linguistically relevant lexical knowledge, such as selectional restrictions, is privileged in terms of the time-course of its access and influence. We examined whether event knowledge computed by combining multiple concepts can rapidly influence language understanding even in the absence of selectional restriction violations. Specifically, we investigated whether instruments can combine with actions to influence comprehension of ensuing patients of (as in Rayner, Warren, Juhuasz, & Liversedge, 2004; Warren & McConnell, 2007). Instrument-verb-patient triplets were created in a norming study designed to tap directly into event knowledge. In self-paced reading (Experiment 1), participants were faster to read patient nouns, such as hair, when they were typical of the instrument-action pair (Donna used the shampoo to wash vs. the hose to wash). Experiment 2 showed that these results were not due to direct instrument-patient relations. Experiment 3 replicated Experiment 1 using eyetracking, with effects of event typicality observed in first fixation and gaze durations on the patient noun. This research demonstrates that conceptual event-based expectations are computed and used rapidly and dynamically during on-line language comprehension. We discuss relationships among plausibility and predictability, as well as their implications. We conclude that selectional restrictions may be best considered as event-based conceptual knowledge rather than lexical-grammatical knowledge.

The mechanics of embodiment: a dialog on embodiment and computational modeling

Embodied theories are increasingly challenging traditional views of cognition by arguing that conceptual representations that constitute our knowledge are grounded in sensory and motor experiences, and processed at this sensorimotor level, rather than being represented and processed abstractly in an amodal conceptual system. Given the established empirical foundation, and the relatively underspecified theories to date, many researchers are extremely interested in embodied cognition but are clamoring for more mechanistic implementations. What is needed at this stage is a push toward explicit computational models that implement sensorimotor grounding as intrinsic to cognitive processes. In this article, six authors from varying backgrounds and approaches address issues concerning the construction of embodied computational models, and illustrate what they view as the critical current and next steps toward mechanistic theories of embodiment. The first part has the form of a dialog between two fictional characters: Ernest, the "experimenter," and Mary, the "computational modeler." The dialog consists of an interactive sequence of questions, requests for clarification, challenges, and (tentative) answers, and touches the most important aspects of grounded theories that should inform computational modeling and, conversely, the impact that computational modeling could have on embodied theories. The second part of the article discusses the most important open challenges for embodied computational modeling.

Effects of event knowledge in processing verbal arguments

This research tests whether comprehenders use their knowledge of typical events in real time to process verbal arguments. In self-paced reading and event-related brain potential (ERP) experiments, we used materials in which the likelihood of a specific patient noun (brakes or spelling) depended on the combination of an agent and verb (mechanic checked vs. journalist checked). Reading times were shorter at the word directly following the patient for the congruent than the incongruent items. Differential N400s were found earlier, immediately at the patient. Norming studies ruled out any account of these results based on direct relations between the agent and patient. Thus, comprehenders dynamically combine information about real-world events based on intrasentential agents and verbs, and this combination then rapidly influences online sentence interpretation.

People Use their Knowledge of Common Events to Understand Language, and Do So as Quickly as Possible

People possess a great deal of knowledge about how the world works, and it is undoubtedly true that adults use this knowledge when understanding and producing language. However, psycholinguistic theories differ regarding whether this extra-linguistic pragmatic knowledge can be activated and used immediately, or only after a delay. The authors present research that investigates whether people immediately use their generalized knowledge of common events when understanding language. This research demonstrates that (i) individual isolated words immediately activate event-based knowledge; (ii) combinations of words in sentences immediately constrain people's event-based expectations for concepts that are upcoming in language; (iii) syntax modulates people's expectations for ensuing concepts; and (iv) event-based knowledge can produce expectations for ensuing syntactic structures. It is concluded that theories of sentence comprehension must allow for the rapid dynamic interplay among these sources of information.

Semantic richness and the activation of concepts in semantic memory: evidence from event-related potentials

Semantic richness refers to the amount of semantic information associated with a concept. Reaction-time (RT) studies have shown that words referring to rich concepts elicit faster responses than those referring to impoverished ones, suggesting that richer concepts are activated more quickly. In a recent functional neuroimaging study, richer concepts evoked less neural activity, which was interpreted as faster activation. The interpretations of these findings appear to conflict with event-related potential (ERP) studies showing no evidence that speed of concept activation is influenced by typical semantic variables. Resolution of this apparent contradiction is important because the interpretation of 40 years of semantic-memory RT studies depends on whether factors such as semantic richness influence the duration of initial concept activation or later decision and response processes. Consistent with previous studies of the effects of semantic factors on ERP, the present study shows that richness influences the magnitude, but not the latency, of the P2 and N400 ERP components (which are early relative to behavioral responses), suggesting that effects of richness on RT reflect temporal effects on downstream decision or response mechanisms rather than on upstream concept activation.

Activating event knowledge

An increasing number of results in sentence and discourse processing demonstrate that comprehension relies on rich pragmatic knowledge about real-world events, and that incoming words incrementally activate such knowledge. If so, then even outside of any larger context, nouns should activate knowledge of the generalized events that they denote or typically play a role in. We used short stimulus onset asynchrony priming to demonstrate that (1) event nouns prime people (sale-shopper) and objects (trip-luggage) commonly found at those events; (2) location nouns prime people/animals (hospital-doctor) and objects (barn-hay) commonly found at those locations; and (3) instrument nouns prime things on which those instruments are commonly used (key-door), but not the types of people who tend to use them (hose-gardener). The priming effects are not due to normative word association. On our account, facilitation results from event knowledge relating primes and targets. This has much in common with computational models like LSA or BEAGLE in which one word primes another if they frequently occur in similar contexts. LSA predicts priming for all six experiments, whereas BEAGLE correctly predicted that priming should not occur for the instrument-people relation but should occur for the other five. We conclude that event-based relations are encoded in semantic memory and computed as part of word meaning, and have a strong influence on language comprehension.

The wind chilled the spectators, but the wine just chilled: Sense, structure, and sentence comprehension

Anticipation plays a role in language comprehension. In this article, we explore the extent to which verb sense influences expectations about upcoming structure. We focus on change of state verbs like shatter, which have different senses that are expressed in either transitive or intransitive structures, depending on the sense that is used. In two experiments we influence the interpretation of verb sense by manipulating the thematic fit of the grammatical subject as cause or affected entity for the verb, and test whether readers' expectations for a transitive or intransitive structure change as a result. This sense-biasing context influenced reading times in the post-verbal regions. Reading times for transitive sentences were faster following good-cause than good theme subjects, but the opposite pattern was found for intransitive sentences. We conclude that readers use sense-contingent subcategorization preferences during on-line comprehension.

Outcome after combined pulmonary endarterectomy and mitral valve replacement

Concomitant pulmonary endarterectomy and cardiac surgery has rarely been described in the literature. We report a 30-year-old patient who underwent pulmonary endarterectomy and concomitant mitral valve replacement associated with closure of a patent foramen ovale.

Conceptual Hierarchies in a Flat Attractor Network: Dynamics of Learning and Computations

The structure of people's conceptual knowledge of concrete nouns has traditionally been viewed as hierarchical (Collins & Quillian, 1969). For example, superordinate concepts (vegetable) are assumed to reside at a higher level than basic-level concepts (carrot). A feature-based attractor network with a single layer of semantic features developed representations of both basic-level and superordinate concepts. No hierarchical structure was built into the network. In Experiment and Simulation 1, the graded structure of categories (typicality ratings) is accounted for by the flat attractor-network. Experiment and Simulation 2 show that, as with basic-level concepts, such a network predicts feature verification latencies for superordinate concepts (vegetable ). In Experiment and Simulation 3, counterintuitive results regarding the temporal dynamics of similarity in semantic priming are explained by the model. By treating both types of concepts the same in terms of representation, learning, and computations, the model provides new insights into semantic memory.

Shared Features Dominate Semantic Richness Effects for Concrete Concepts

When asked to list semantic features for concrete concepts, participants list many features for some concepts and few for others. Concepts with many semantic features are processed faster in lexical and semantic decision tasks (Pexman, Holyk, & Monfils, 2003; Pexman, Lupker, & Hino, 2002). Using both lexical and concreteness decision tasks, we provided further insight into these number-of-features (NoF) effects. We began by replicating the effect using a larger and better controlled set of items. We then investigated the relationship between NoF and feature distinctiveness and found that features shared by numerous concrete concepts such as facilitate decisions to a greater extent than do distinctive features such as . Finally, we showed that NoF effects are carried by shared visual form and surface, encyclopedic, tactile, and taste knowledge. We propose a decision-making account of these results, rather than one based on the computation of word meaning.

Synthesis and cannabinoid activity of 1-substituted-indole-3-oxadiazole derivatives: Novel agonists for the CB1 receptor

An exploratory chemical effort has been undertaken to develop a novel series of compounds as selective CB(1) agonists. It is hoped that compounds of this type will have clinical utility in pain control, and cerebral ischaemia following stroke or traumatic head injury. We report here medicinal chemistry studies directed towards the investigation of a series of 1-substituted-indole-3-oxadiazoles as potential CB(1) agonists.