The semantic richness of abstract concepts

AC-PLT: An algorithm for computer-assisted coding of semantic property listing data

In this paper, we present a novel algorithm that uses machine learning and natural language processing techniques to facilitate the coding of feature listing data. Feature listing is a method in which participants are asked to provide a list of features that are typically true of a given concept or word. This method is commonly used in research studies to gain insights into people's understanding of various concepts. The standard procedure for extracting meaning from feature listings is to manually code the data, which can be time-consuming and prone to errors, leading to reliability concerns. Our algorithm aims at addressing these challenges by automatically assigning human-created codes to feature listing data that achieve a quantitatively good agreement with human coders. Our preliminary results suggest that our algorithm has the potential to improve the efficiency and accuracy of content analysis of feature listing data. Additionally, this tool is an important step toward developing a fully automated coding algorithm, which we are currently preliminarily devising.

Describing and understanding the time course of the property listing task

To study linguistically coded concepts, researchers often resort to the Property Listing Task (PLT). In a PLT, participants are asked to list properties that describe a concept (e.g., for DOG, subjects may list "is a pet", "has four legs", etc.). When PLT data is collected for many concepts, researchers obtain Conceptual Properties Norms (CPNs), which are used to study semantic content and as a source of control variables. Though the PLT and CPNs are widely used across psychology, only recently a model that describes the listing course of a PLT has been developed and validated. That original model describes the listing course using order of production of properties. Here we go a step beyond and validate the model using response times (RT), i.e., the time from cue onset to property listing. Our results show that RT data exhibits the same regularities observed in the previous model, but now we can also analyze the time course, i.e., dynamics of the PLT. As such, the RT validated model may be applied to study several similar memory retrieval tasks, such as the Free Listing Task, Verbal Fluidity Task, and to research related cognitive processes. To illustrate those kinds of analyses, we present a brief example of the difference in PLT's dynamics between listing properties for abstract versus concrete concepts, which shows that the model may be fruitfully applied to study concepts.

Using agreement probability to study differences in types of concepts and conceptualizers

Agreement probability p(a) is a homogeneity measure of lists of properties produced by participants in a Property Listing Task (PLT) for a concept. Agreement probability's mathematical properties allow a rich analysis of property-based descriptions. To illustrate, we use p(a) to delve into the differences between concrete and abstract concepts in sighted and blind populations. Results show that concrete concepts are more homogeneous within sighted and blind groups than abstract ones (i.e., exhibit a higher p(a) than abstract ones) and that concrete concepts in the blind group are less homogeneous than in the sighted sample. This supports the idea that listed properties for concrete concepts should be more similar across subjects due to the influence of visual/perceptual information on the learning process. In contrast, abstract concepts are learned based mainly on social and linguistic information, which exhibit more variability among people, thus, making the listed properties more dissimilar across subjects. Relative to abstract concepts, the difference in p(a) between sighted and blind is not statistically significant. Though this is a null result, and should be considered with care, it is expected because abstract concepts should be learned by paying attention to the same social and linguistic input in both, blind and sighted, and thus, there is no reason to expect that the respective lists of properties should differ. Finally, we used p(a) to classify concrete and abstract concepts with a good level of certainty. All these analyses suggest that p(a) can be fruitfully used to study data obtained in a PLT.

Consensus Paper: Current Perspectives on Abstract Concepts and Future Research Directions

concepts are relevant to a wide range of disciplines, including cognitive science, linguistics, psychology, cognitive, social, and affective neuroscience, and philosophy. This consensus paper synthesizes the work and views of researchers in the field, discussing current perspectives on theoretical and methodological issues, and recommendations for future research. In this paper, we urge researchers to go beyond the traditional abstract-concrete dichotomy and consider the multiple dimensions that characterize concepts (e.g., sensorimotor experience, social interaction, conceptual metaphor), as well as the mediating influence of linguistic and cultural context on conceptual representations. We also promote the use of interactive methods to investigate both the comprehension and production of abstract concepts, while also focusing on individual differences in conceptual representations. Overall, we argue that abstract concepts should be studied in a more nuanced way that takes into account their complexity and diversity, which should permit us a fuller, more holistic understanding of abstract cognition.

Grounded Cognition, Linguistic Relativity, and Abstract Concepts

Kemmerer's paper convincingly claims that the grounded cognition model (GCM) entails linguistic relativity. Here, we underline that tackling linguistic relativity and cultural differences is vital for GCM. First, it allows GCM to focus more on flexible rather than stable aspects of cognition. Second, it highlights the centrality of linguistic experience for human cognition. While GCM-inspired research underscored the similarity between linguistic and nonlinguistic concepts, it is now paramount to understand when and how language(s) influence knowledge. To this aim, we argue that linguistic variation might be particularly relevant for more abstract concepts-which are more debatable and open to revisions.

Concepts require flexible grounding

Research on semantic memory has a problem. On the one hand, a robust body of evidence implicates sensorimotor regions in conceptual processing. On the other hand, a different body of evidence implicates a modality independent semantic system. The standard solution to this tension is to posit a hub-and-spoke system with modality independent hubs and modality specific spokes. In this paper, I argue in support of an alternative view of grounding which remains committed to neural reenactment but emphasizes the multimodal and multilevel nature of the semantic system. This view is built upon the recognition that abstraction is a design feature of concepts. Semantic memory employs hierarchically structured representations to capture different degrees of abstraction. Grounding does not work the way that many embodied approaches have assumed.

Abstract concepts and emotion: cross-linguistic evidence and arguments against affective embodiment

How are abstract concepts such as 'freedom' and 'democracy' represented in the mind? One prominent proposal suggests that abstract concepts are grounded in emotion. Supporting this 'affective embodiment' account, abstract concepts are rated to be more strongly positive or more strongly negative than concrete concepts. This paper demonstrates that this finding generalizes across languages by synthesizing rating data from Cantonese, Mandarin Chinese, Croatian, Dutch, French, German, Indonesian, Italian, Polish and Spanish. However, a deeper look at the same data suggests that the idea of emotional grounding only characterizes a small subset of abstract concepts. Moreover, when the concreteness/abstractness dimension is not operationalized using concreteness ratings, it is actually found that concrete concepts are rated as more emotional than abstract ones. Altogether, these results suggest limitations to the idea that emotion is an important factor in the grounding of abstract concepts. This article is part of the theme issue 'Concepts in interaction: social engagement and inner experiences'.

CPNCoverageAnalysis: An R package for parameter estimation in conceptual properties norming studies

In conceptual properties norming studies (CPNs), participants list properties that describe a set of concepts. From CPNs, many different parameters are calculated, such as semantic richness. A generally overlooked issue is that those values are only point estimates of the true unknown population parameters. In the present work, we present an R package that allows us to treat those values as population parameter estimates. Relatedly, a general practice in CPNs is using an equal number of participants who list properties for each concept (i.e., standardizing sample size). As we illustrate through examples, this procedure has negative effects on data's statistical analyses. Here, we argue that a better method is to standardize coverage (i.e., the proportion of sampled properties to the total number of properties that describe a concept), such that a similar coverage is achieved across concepts. When standardizing coverage rather than sample size, it is more likely that the set of concepts in a CPN all exhibit a similar representativeness. Moreover, by computing coverage the researcher can decide whether the CPN reached a sufficiently high coverage, so that its results might be generalizable to other studies. The R package we make available in the current work allows one to compute coverage and to estimate the necessary number of participants to reach a target coverage. We show this sampling procedure by using the R package on real and simulated CPN data.

Effects of social experience on abstract concepts in semantic priming

Humans can understand thousands of abstract words, even when they do not have clearly perceivable referents. Recent views highlight an important role of social experience in grounding of abstract concepts and sub-kinds of abstract concepts, but empirical work in this area is still in its early stages. In the present study, a picture-word semantic priming paradigm was employed to investigate the contribution effect of social experience that is provided by real-life pictures to social abstract (SA, e.g., friendship, betrayal) concepts and emotional abstract (EA, e.g., happiness, anger) concepts. Using a lexical decision task, we examined responses to picture-SA word pairs (Experiment 1) and picture-EA word pairs (Experiment 2) in social/emotional semantically related and unrelated conditions. All pairs shared either positive or negative valence. The results showed quicker responses to positive SA and EA words that were preceded by related vs. unrelated prime pictures. Specifically, positive SA words were facilitated by the corresponding social scene pictures, whereas positive EA words were facilitated by pictures depict the corresponding facial expressions and gestures. However, such facilitatory effect was not observed in negative picture-SA/EA word conditions. This pattern of results suggests that a facilitatory effect of social experience on abstract concepts varies with different sub-kinds of abstract concepts, that seems to be limited to positive SA concepts. Overall, our findings confirm the crucial role of social experience for abstract concepts and further suggest that not all abstract concepts can benefit from social experience, at least in the semantic priming.

Investigating the influence of semantic factors on word retrieval: Reservations, results and recommendations

There is consensus that word retrieval starts with activation of semantic representations. However, in adults without language impairment, relatively little attention has been paid to the effects of the semantic attributes of to-be-retrieved words. This paper, therefore, addresses the question of which item-inherent semantic factors influence word retrieval. Specifically, it reviews the literature on a selection of these factors: imageability, concreteness, number of semantic features, typicality, intercorrelational density, featural distinctiveness, concept distinctiveness, animacy, semantic neighbourhood density, semantic similarity, operativity, valence, and arousal. It highlights several methodological challenges in this field, and has a focus on the insights from studies with people with aphasia where the effects of these variables are more prevalent. The paper concludes that further research simultaneously examining the effects of different semantic factors that are likely to affect lexical co-activation, and the interaction of these variables, would be fruitful, as would suitably scaled computational modelling of these effects in unimpaired language processing and in language impairment. Such research would enable the refinement of theories of semantic processing and word production, and potentially have implications for diagnosis and treatment of semantic and lexical impairments.

Distributional Measures of Semantic Abstraction

This article provides an in-depth study of distributional measures for distinguishing between degrees of semantic abstraction. Abstraction is considered a “central construct in cognitive science” and a “process of information reduction that allows for efficient storage and retrieval of central knowledge”. Relying on the distributional hypothesis, computational studies have successfully exploited measures of contextual co-occurrence and neighbourhood density to distinguish between conceptual semantic categorisations. So far, these studies have modeled semantic abstraction across lexical-semantic tasks such as ambiguity; diachronic meaning changes; abstractness vs. concreteness; and hypernymy. Yet, the distributional approaches target different conceptual types of semantic relatedness, and as to our knowledge not much attention has been paid to apply, compare or analyse the computational abstraction measures across conceptual tasks. The current article suggests a novel perspective that exploits variants of distributional measures to investigate semantic abstraction in English in terms of the abstract–concrete dichotomy (e.g., glory–banana) and in terms of the generality–specificity distinction (e.g., animal–fish), in order to compare the strengths and weaknesses of the measures regarding categorisations of abstraction, and to determine and investigate conceptual differences. In a series of experiments we identify reliable distributional measures for both instantiations of lexical-semantic abstraction and reach a precision higher than 0.7, but the measures clearly differ for the abstract–concrete vs. abstract–specific distinctions and for nouns vs. verbs. Overall, we identify two groups of measures, (i) frequency and word entropy when distinguishing between more and less abstract words in terms of the generality–specificity distinction, and (ii) neighbourhood density variants (especially target–context diversity) when distinguishing between more and less abstract words in terms of the abstract–concrete dichotomy. We conclude that more general words are used more often and are less surprising than more specific words, and that abstract words establish themselves empirically in semantically more diverse contexts than concrete words. Finally, our experiments once more point out that distributional models of conceptual categorisations need to take word classes and ambiguity into account: results for nouns vs. verbs differ in many respects, and ambiguity hinders fine-tuning empirical observations.

Language Processing Differences Between Blind and Sighted Individuals and the Abstract Versus Concrete Concept Difference

In the property listing task (PLT), participants are asked to list properties for a concept (e.g., for the concept dog, "barks," and "is a pet" may be produced). In conceptual property norming (CPNs) studies, participants are asked to list properties for large sets of concepts. Here, we use a mathematical model of the property listing process to explore two longstanding issues: characterizing the difference between concrete and abstract concepts, and characterizing semantic knowledge in the blind versus sighted population. When we apply our mathematical model to a large CPN reporting properties listed by sighted and blind participants, the model uncovers significant differences between concrete and abstract concepts. Though we also find that blind individuals show many of the same processing differences between abstract and concrete concepts found in sighted individuals, our model shows that those differences are noticeably less pronounced than in sighted individuals. We discuss our results vis-a-vis theories attempting to characterize abstract concepts.

Abstract concepts in interaction: the need of others when guessing abstract concepts smooths dyadic motor interactions

concepts (ACs, e.g. 'justice') are more complex compared with concrete concepts (CCs) (e.g. 'table'). Indeed, they do not possess a single object as a referent, they assemble quite heterogeneous members and they are more detached from exteroceptive and more grounded in interoceptive experience. Recent views have hypothesized that interpersonal communication is particularly crucial to acquire and use ACs. The current study investigates the reliance of ACs/CCs representation on interpersonal behaviour. We asked participants to perform a motor interaction task with two avatars who embodied two real confederates. Before and after the motor interaction task, the two confederates provided participants with hints in a concept guessing task associated with visual stimuli: one helped in guessing ACs and the other, CCs. A control study we performed both with the materials employed in the main experiment and with other materials, confirmed that associating verbal concepts with visual images was more difficult with ACs than with CCs. Consistently, the results of the main experiment showed that participants asked for more hints with ACs than CCs and were more synchronous when interacting with the avatar corresponding to the AC's confederate. The results highlight an important role of sociality in grounding ACs.

Intangible features extraction in the processing of abstract concepts: Evidence from picture-word priming

Over the last decade, hypotheses ranging from linguistic symbol processing to embodiment have been formulated to account for the content and mechanisms responsible for the representation of abstract concepts. Results of recent studies have suggested that abstract concepts, just like concrete ones, can benefit from knowledge of real-world situational context, but that they can also be processed based on abstract pictures devoid of such situational features. This paper presents two semantic priming experiments to explore such mechanisms further. The first experiment replicates Kuipers, Jones, and Thierry (2018) in a cross-linguistic setting which shows that abstract concepts can be processed from abstract pictures devoid of tangible features. In the second experiment, we studied extraction mechanisms that come into play when participants are presented with abstract and concrete pictures that provide situational information to illustrate target abstract concepts. We expected this facilitatory effect to be limited to concrete picture primes. Our data analysed with both Bayesian and Frequentist tests showed however that even when presented with tangible situational information, the extraction of features still occurred for abstract pictures. We discuss the implications of this with respect to future avenues for studying the processing of abstract concepts.

Semantic similarity and associated abstractness norms for 630 French word pairs

The representation of abstract concepts remains a challenge, justifying the need for further experimental investigation. To that end, we introduce a normative database for 630 semantically similar French word pairs and associated levels of abstractness for 1260 isolated words based on data from 900 subjects. The semantic similarity and abstractness norms were obtained in two studies using 7-point scales. The database is organised according to word-pair semantic similarity, abstractness, and associated lexical variables such as word length (in number of letters), word frequency, and other lexical variables to allow for matching of experimental material. The associated variables were obtained by cross-referencing our database with other known psycholinguistic databases including Lexique (New et al., 2004), the French Lexicon Project (Ferrand et al., 2010), Wordlex (Gimenes & New, 2016), and MEGALEX (Ferrand et al., 2018). We introduced sufficient diversity to allow researchers to select pairs with varying levels of semantic similarity and abstractness. In addition, it is possible to use these data as continuous or discrete variables. The full data are available in the supplementary materials as well as on OSF ( https://osf.io/qsd4v/ ).

Overusing the pacifier during infancy sets a footprint on abstract words processing

Perturbations to the speech articulators induced by frequently using an interfering object during infancy (i.e., pacifier) might shape children's language experience and the building of conceptual representations. Seventy-one typically developing third graders performed a semantic categorization task with abstract, concrete and emotional words. Children who used the pacifier for a more extended period were slower than the others. Moreover, overusing the pacifier increased response time of abstract words, whereas emotional and (above all) concrete words were less affected. Results support the view that abstract words are grounded both in perception-action and in linguistic experience.

Heterogenous abstract concepts: is "ponder" different from "dissolve"?

words have usually been treated as a homogenous group, with limited investigation of the influence of different underlying representational systems for these words. In the present study we examined lexical-semantic processing of abstract verbs, separating them into mental state, emotional state and nonembodied state types. We used a syntactic classification task and a memory task to investigate behavioural differences amongst the abstract verb types. Semantic richness effects of each of the verbs' associates were then investigated to determine the relationship of linguistic associations to semantic processing response times for abstract verbs. We found a modest effect of abstract verb type, with mental state abstract verbs processed more quickly than nonembodied abstract verbs in the syntactic classification task; however, this effect was task dependent. We also found that memory was less accurate for the mental state abstract verbs. The semantic richness analysis of abstract verb associates revealed (1) that the concreteness of an abstract verb's associates has a positive relationship to the verb's response time and (2) a negative relationship between response time and age of acquisition for associates of nonembodied verbs. The results provide support for the proposal that abstract concepts engage complex representations in modal and linguistic systems.

How to carry out conceptual properties norming studies as parameter estimation studies: Lessons from ecology

Conceptual properties norming studies (CPNs) ask participants to produce properties that describe concepts. From that data, different metrics may be computed (e.g., semantic richness, similarity measures), which are then used in studying concepts and as a source of carefully controlled stimuli for experimentation. Notwithstanding those metrics' demonstrated usefulness, researchers have customarily overlooked that they are only point estimates of the true unknown population values, and therefore, only rough approximations. Thus, though research based on CPN data may produce reliable results, those results are likely to be general and coarse-grained. In contrast, we suggest viewing CPNs as parameter estimation procedures, where researchers obtain only estimates of the unknown population parameters. Thus, more specific and fine-grained analyses must consider those parameters' variability. To this end, we introduce a probabilistic model from the field of ecology. Its related statistical expressions can be applied to compute estimates of CPNs' parameters and their corresponding variances. Furthermore, those expressions can be used to guide the sampling process. The traditional practice in CPN studies is to use the same number of participants across concepts, intuitively believing that practice will render the computed metrics comparable across concepts and CPNs. In contrast, the current work shows why an equal number of participants per concept is generally not desirable. Using CPN data, we show how to use the equations and discuss how they may allow more reasonable analyses and comparisons of parameter values among different concepts in a CPN, and across different CPNs.

Estimating the prevalence and diversity of words in written language

Recently, a new crowd-sourced language metric has been introduced, entitled word prevalence, which estimates the proportion of the population that knows a given word. This measure has been shown to account for unique variance in large sets of lexical performance. This article aims to build on the work of Brysbaert et al. and Keuleers et al. by introducing new corpus-based metrics that estimate how likely a word is to be an active member of the natural language environment, and hence known by a larger subset of the general population. This metric is derived from an analysis of a newly collected corpus of over 25,000 fiction and non-fiction books and will be shown that it is capable of accounting for significantly more variance than past corpus-based measures.

Feature distinctiveness effects in language acquisition and lexical processing: Insights from megastudies

Semantic features are central to many influential theories of word meaning and semantic memory, but new methods of quantifying the information embedded in feature production norms are needed to advance our understanding of semantic processing and language acquisition. This paper capitalized on databases of semantic feature production norms and age-of-acquisition ratings, and megastudies including the English Lexicon Project and the Calgary Semantic Decision Project, to examine the influence of feature distinctiveness on language acquisition, visual lexical decision, and semantic decision. A feature network of English words was constructed such that edges in the network represented feature distance, or dissimilarity, between words (i.e., Jaccard and Manhattan distances of probability distributions of features elicited for each pair of words), enabling us to quantify the relative feature distinctiveness of individual words relative to other words in the network. Words with greater feature distinctiveness tended to be acquired earlier. Regression analyses of megastudy data revealed that Manhattan feature distinctiveness inhibited performance on the visual lexical decision task, facilitated semantic decision performance for concrete concepts, and inhibited semantic decision performance for abstract concepts. These results demonstrate the importance of considering the structural properties of words embedded in a semantic feature space in order to increase our understanding of semantic processing and language acquisition.

A practical primer on processing semantic property norm data

Semantic property listing tasks require participants to generate short propositions (e.g., [Formula: see text], [Formula: see text]) for a specific concept (e.g., DOG). This task is the cornerstone of the creation of semantic property norms which are essential for modeling, stimuli creation, and understanding similarity between concepts. Despite the wide applicability of semantic property norms for a large variety of concepts across different groups of people, the methodological aspects of the property listing task have received less attention, even though the procedure and processing of the data can substantially affect the nature and quality of the measures derived from them. The goal of this paper is to provide a practical primer on how to collect and process semantic property norms. We will discuss the key methods to elicit semantic properties and compare different methods to derive meaningful representations from them. This will cover the role of instructions and test context, property preprocessing (e.g., lemmatization), property weighting, and relationship encoding using ontologies. With these choices in mind, we propose and demonstrate a processing pipeline that transparently documents these steps, resulting in improved comparability across different studies. The impact of these choices will be demonstrated using intrinsic (e.g., reliability, number of properties) and extrinsic measures (e.g., categorization, semantic similarity, lexical processing). This practical primer will offer potential solutions to several long-standing problems and allow researchers to develop new property listing norms overcoming the constraints of previous studies.

Mapping semantic space: property norms and semantic richness

In semantic property listing tasks, participants list many features for some concepts and fewer for others. This variability in number of features (NoF) has been used in previous research as a measure of a concept's semantic richness, and such studies have shown that in lexical-semantic tasks responses tend to be facilitated for words with high NoF compared to those for words with low NoF, even when many other relevant factors are controlled (Pexman et al. in Psychon Bull Rev 9:542-549, 2002; Mem Cogn 31:842-855, 2003; Psychon Bull Rev 15:161-167, 2008; Goh et al. in Front Psychol, 2016. https://doi.org/10.3389/fpsyg.2016.00976 ). Furthermore, shared features (i.e., features that are shared by multiple words) appear to facilitate responses in lexical-semantic tasks to a greater degree than distinctive features (Devereux et al. in Cogn Sci 40:325-350, 2016; Grondin et al. in J Mem Lang 60:1-19, 2009). This previous work was limited, however, to relatively small sets of words, typically those extracted from the McRae norms (McRae et al. in Behav Res Methods 37(4):547-559, 2005). New property listing norms provide the opportunity to extract NoF values for many more items (Buchanan et al. in Behav Res Methods 51:1849-1863, 2019). The purpose of the present study was to test whether NoF effects generalize to this larger item set, and to explore how NoF is related to other measures of semantic richness, including subjective ratings of concreteness, imageability, body-object interaction, sensory experience, valence, arousal, and age of acquisition, as well as more objective measures like semantic diversity, number of associates, and lexical centrality. Using the new Buchanan norms, we found significant NoF effects in lexical decision (is it a word or a nonword?) and semantic decision (is it concrete or abstract?) tasks. We also found significant effects of words' number of shared (less distinctive) features in each task. Further, factor analyses of all semantic richness measures showed a distinct factor structure, suggesting that there are clusters of semantic richness dimensions that seem to correspond to more embodied semantic dimensions and more distributional semantic dimensions. Results are interpreted as evidence that semantic representation is multimodal and multidimensional, and provide new insights about the structure of semantic space.

Close yet independent: Dissociation of social from valence and abstract semantic dimensions in the left anterior temporal lobe

The anterior temporal lobe (ATL) is engaged in various types of semantic dimensions. One consistently reported dimension is social information, with abstract words describing social behaviors inducing stronger activations in the ATL than nonsocial words. One potential factor that has been systematically confounded in this finding is emotional valence, given that abstract social words tend to be associated with emotional feelings. We investigated which factors drove the ATL sensitivity using a 2 (social/nonsocial) × 2 (valenced/neutral) factorial design in an fMRI study with relatively high spatial resolutions. We found that sociality and valence were processed in different ATL regions without significant interactions: The social effect was found in the left anterior superior temporal sulcus (aSTS), whereas the valence effect activated small clusters in the bilateral temporal poles (TP). In the left ATL, the social- and valence-related clusters were distinct from another superior ATL area that exhibited a general "abstractness" effect with little modulation of sociality or valence. These subregions exhibited distinct whole-brain functional connectivity patterns during the resting state, with the social cluster functionally connected to the default mode network, the valence cluster connected to the adjacent temporal regions and amygdala, and the abstractness cluster connected to a distributed network including a set of language-related regions. These results of activation profiles and connectivity patterns together indicate that the way in which the left ATL supports semantic processing is highly fine-grained, with the neural substrate for social semantic effects dissociated from those for emotional valence and abstractness.

More than a scaffold: Language is a neuroenhancement

What role does language play in our thoughts? A longstanding proposal that has gained traction among supporters of embodied or grounded cognition suggests that it serves as a cognitive scaffold. This idea turns on the fact that language-with its ability to capture statistical regularities, leverage culturally acquired information, and engage grounded metaphors-is an effective and readily available support for our thinking. In this essay, I argue that language should be viewed as more than this; it should be viewed as a neuroenhancement. The neurologically realized language system is an important subcomponent of a flexible, multimodal, and multilevel conceptual system. It is not merely a source for information about the world but also a computational add-on that extends our conceptual reach. This approach provides a compelling explanation of the course of development, our facility with abstract concepts, and even the scope of language-specific influences on cognition.

Learning abstract words and concepts: insights from developmental language disorder

Some explanations of abstract word learning suggest that these words are learnt primarily from the linguistic input, using statistical co-occurrences of words in language, whereas concrete words can also rely on non-linguistic, experiential information. According to this hypothesis, we expect that, if the learner is not able to fully exploit the information in the linguistic input, abstract words should be affected more than concrete ones. Embodied approaches instead argue that both abstract and concrete words can rely on experiential information and, therefore, there might not be any linguistic primacy. Here, we test the role of linguistic input in the development of abstract knowledge with children with developmental language disorder (DLD) and typically developing children aged 8-13. We show that DLD children, who by definition have impoverished language, do not show a disproportionate impairment for abstract words in lexical decision and definition tasks. These results indicate that linguistic information does not have a primary role in the learning of abstract concepts and words; rather, it would play a significant role in semantic development across all domains of knowledge.This article is part of the theme issue 'Varieties of abstract concepts: development, use and representation in the brain'.

The multifaceted abstract brain

concepts play a central role in human behaviour and constitute a critical component of the human conceptual system. Here, we investigate the neural basis of four types of abstract concepts, examining their similarities and differences through neuroimaging meta-analyses. We examine numerical and emotional concepts, and two higher-order abstract processes, morality judgements and theory of mind. Three main findings emerge. First, representation of abstract concepts is more widespread than is often assumed. Second, representations of different types of abstract concepts differ in important respects. Each of the domains examined here was associated with some unique areas. Third, some areas were commonly activated across domains and included inferior parietal, posterior cingulate and medial prefrontal cortex. We interpret these regions in terms of their role in episodic recall, event representation and social-emotional processing. We suggest that different types of abstract concepts can be represented and grounded through differing contributions from event-based, interoceptive, introspective and sensory-motor representations. The results underscore the richness and diversity of abstract concepts, argue against single-mechanism accounts for representation of all types of abstract concepts and suggest mechanisms for their direct and indirect grounding.This article is part of the theme issue 'Varieties of abstract concepts: development, use and representation in the brain'.

Language as a disruptive technology: abstract concepts, embodiment and the flexible mind

A growing body of evidence suggests that cognition is embodied and grounded. Abstract concepts, though, remain a significant theoretical challenge. A number of researchers have proposed that language makes an important contribution to our capacity to acquire and employ concepts, particularly abstract ones. In this essay, I critically examine this suggestion and ultimately defend a version of it. I argue that a successful account of how language augments cognition should emphasize its symbolic properties and incorporate a view of embodiment that recognizes the flexible, multimodal and task-related nature of action, emotion and perception systems. On this view, language is an ontogenetically disruptive cognitive technology that expands our conceptual reach.This article is part of the theme issue 'Varieties of abstract concepts: development, use and representation in the brain'.

Communicating abstract meaning: concepts revealed in words and gestures

words refer to concepts that cannot be directly experienced through our senses (e.g. truth, morality). How we ground the meanings of abstract words is one of the deepest problems in cognitive science today. We investigated this question in an experiment in which 62 participants were asked to communicate the meanings of words (20 abstract nouns, e.g. impulse; 10 concrete nouns, e.g. insect) to a partner without using the words themselves (the taboo task). We analysed the speech and associated gestures that participants used to communicate the meaning of each word in the taboo task. Analysis of verbal and gestural data yielded a number of insights. When communicating about the meanings of abstract words, participants' speech referenced more people and introspections. In contrast, the meanings of concrete words were communicated by referencing more objects and entities. Gesture results showed that when participants spoke about abstract word meanings their speech was accompanied by more metaphorical and beat gestures, and speech about concrete word meanings was accompanied by more iconic gestures. Taken together, the results suggest that abstract meanings are best captured by a model that allows dynamic access to multiple representation systems.This article is part of the theme issue 'Varieties of abstract concepts: development, use and representation in the brain'.

Sociality to Reach Objects and to Catch Meaning

Sociality influences both concrete and abstract concepts acquisition and representation, but in different ways. Here we propose that sociality is crucial during the acquisition of abstract concepts but less for concrete concepts, that have a bounded perceptual referent and can be learned more autonomously. For the acquisition of abstract concepts, instead, the human relation would be pivotal in order to master complex meanings. Once acquired, concrete words can act as tools, able to modify our sensorimotor representation of the surrounding environment. Indeed, pronouncing a word the referent of which is distant from us we implicitly assume that, thanks to the contribution of others, the object becomes reachable; this would expand our perception of the near bodily space. Abstract concepts would modify our sensorimotor representation of the space only in the earlier phases of their acquisition, specifically when the child represents an interlocutor as a real, physical "ready to help actor" who can help her in forming categories and in explaining the meaning of words that do not possess a concrete referent. Once abstract concepts are acquired, they can work as social tools: the social metacognition mechanism (awareness of our concepts and of our need of the help of others) can evoke the presence of a "ready to help actor" in an implicit way, as a predisposition to ask information to fill the knowledge gaps.

Abstract, emotional and concrete concepts and the activation of mouth-hand effectors

According to embodied and grounded theories, concepts are grounded in sensorimotor systems. The majority of evidence supporting these views concerns concepts referring to objects or actions, while evidence on abstract concepts is more scarce. Explaining how abstract concepts such as “freedom” are represented would thus be pivotal for grounded theories. According to some recent proposals, abstract concepts are grounded in both sensorimotor and linguistic experience, thus they activate the mouth motor system more than concrete concepts. Two experiments are reported, aimed at verifying whether abstract, concrete and emotional words activate the mouth and the hand effectors. In both experiments participants performed first a lexical decision, then a recognition task. In Experiment 1 participants responded by pressing a button either with the mouth or with the hand, in Experiment 2 responses were given with the foot, while a button held either in the mouth or in the hand was used to respond to catch-trials. Abstract words were slower to process in both tasks (concreteness effect). Across the tasks and experiments, emotional concepts had instead a fluctuating pattern, different from those of both concrete and abstract concepts, suggesting that they cannot be considered as a subset of abstract concepts. The interaction between type of concept (abstract, concrete and emotional) and effector (mouth, hand) was not significant in the lexical decision task, likely because it emerged only with tasks implying a deeper processing level. It reached significance, instead, in the recognition tasks. In both experiments abstract concepts were facilitated in the mouth condition compared to the hand condition, supporting our main prediction. Emotional concepts instead had a more variable pattern. Overall, our findings indicate that various kinds of concepts differently activate the mouth and hand effectors, but they also suggest that concepts activate effectors in a flexible and task-dependent way.

Modeling the Structure and Dynamics of Semantic Processing

The contents and structure of semantic memory have been the focus of much recent research, with major advances in the development of distributional models, which use word co-occurrence information as a window into the semantics of language. In parallel, connectionist modeling has extended our knowledge of the processes engaged in semantic activation. However, these two lines of investigation have rarely been brought together. Here, we describe a processing model based on distributional semantics in which activation spreads throughout a semantic network, as dictated by the patterns of semantic similarity between words. We show that the activation profile of the network, measured at various time points, can successfully account for response times in lexical and semantic decision tasks, as well as for subjective concreteness and imageability ratings. We also show that the dynamics of the network is predictive of performance in relational semantic tasks, such as similarity/relatedness rating. Our results indicate that bringing together distributional semantic networks and spreading of activation provides a good fit to both automatic lexical processing (as indexed by lexical and semantic decisions) as well as more deliberate processing (as indexed by ratings), above and beyond what has been reported for previous models that take into account only similarity resulting from network structure.

Word Frequency Effects in Naturalistic Reading

Word frequency is a central psycholinguistic variable that accounts for substantial variance in language processing. A number of neuroimaging studies have examined frequency at a single word level, typically demonstrating a strong negative, and sometimes positive correlation between frequency and hemodynamic response. Here, 40 subjects read passages of text in an MRI scanner while their eye movements were recorded. We used fixation-related analysis to identify neural activity tied to the frequency of each fixated word. We found that negative correlations with frequency were reduced, while strong positive correlations were found in the temporal and parietal areas associated with semantics. We propose that the processing cost of low frequency words is reduced due to contextual cues. Meanings of high frequency words are more readily accessed and integrated with context resulting in enhanced processing in the semantic system. The results demonstrate similarities and differences between single word and naturalistic text processing.

The Semantic Content of Abstract Concepts: A Property Listing Study of 296 Abstract Words

The relation of abstract concepts to the modality-specific systems is discussed controversially. According to classical approaches, the semantic content of abstract concepts can only be coded by amodal or verbal-symbolic representations distinct from the sensory and motor systems, because abstract concepts lack a clear physical referent. Grounded cognition theories, in contrast, propose that abstract concepts do not depend only on the verbal system, but also on a variety of modal systems involving perception, action, emotion and internal states. In order to contribute to this debate, we investigated the semantic content of abstract concepts using a property generation task. Participants were asked to generate properties for 296 abstract concepts, which are relevant for constituting their meaning. These properties were categorized by a coding-scheme making a classification into modality-specific and verbal contents possible. Words were additionally rated with regard to concreteness/abstractness and familiarity. To identify possible subgroups of abstract concepts with distinct profiles of generated features, hierarchical cluster analyses were conducted. Participants generated a substantial proportion of introspective, affective, social, sensory and motor-related properties, in addition to verbal associations. Cluster analyses revealed different subcategories of abstract concepts, which can be characterized by the dominance of certain conceptual features. The present results are therefore compatible with grounded cognition theories, which emphasize the importance of linguistic, social, introspective and affective experiential information for the representation of abstract concepts. Our findings also indicate that abstract concepts are highly heterogeneous requiring the investigation of well-specified subcategories of abstract concepts, for instance as revealed by the present cluster analyses. The present study could thus guide future behavioral or imaging work further elucidating the representation of abstract concepts.

Abstract concepts, language and sociality: from acquisition to inner speech

The problem of representation of abstract concepts, such as 'freedom' and 'justice', has become particularly crucial in recent years, owing to the increased success of embodied and grounded views of cognition. We will present a novel view on abstract concepts and abstract words. Since abstract concepts do not have single objects as referents, children and adults might rely more on input from others to learn them; we, therefore, suggest that linguistic and social experience play an important role for abstract concepts. We will discuss evidence obtained in our and other laboratories showing that processing of abstract concepts evokes linguistic interaction and social experiences, leading to the activation of the mouth motor system. We will discuss the possible mechanisms that underlie this activation. Mouth motor system activation can be due to re-enactment of the experience of conceptual acquisition, which occurred through the mediation of language. Alternatively, it could be due to the re-explanation of the word meaning, possibly through inner speech. Finally, it can be due to a metacognitive process revealing low confidence in the meaning of our concepts. This process induces in us the need to rely on others to ask/negotiate conceptual meaning. We conclude that with abstract concepts language works as a social tool: it extends our thinking abilities and pushes us to rely on others to integrate our knowledge.This article is part of the theme issue 'Varieties of abstract concepts: development, use, and representation in the brain'.

Reliability in content analysis: The case of semantic feature norms classification

Semantic feature norms (e.g., STIMULUS: car → RESPONSE: <has four wheels>) are commonly used in cognitive psychology to look into salient aspects of given concepts. Semantic features are typically collected in experimental settings and then manually annotated by the researchers into feature types (e.g., perceptual features, taxonomic features, etc.) by means of content analyses-that is, by using taxonomies of feature types and having independent coders perform the annotation task. However, the ways in which such content analyses are typically performed and reported are not consistent across the literature. This constitutes a serious methodological problem that might undermine the theoretical claims based on such annotations. In this study, we first offer a review of some of the released datasets of annotated semantic feature norms and the related taxonomies used for content analysis. We then provide theoretical and methodological insights in relation to the content analysis methodology. Finally, we apply content analysis to a new dataset of semantic features and show how the method should be applied in order to deliver reliable annotations and replicable coding schemes. We tackle the following issues: (1) taxonomy structure, (2) the description of categories, (3) coder training, and (4) sustainability of the coding scheme-that is, comparison of the annotations provided by trained versus novice coders. The outcomes of the project are threefold: We provide methodological guidelines for semantic feature classification; we provide a revised and adapted taxonomy that can (arguably) be applied to both concrete and abstract concepts; and we provide a dataset of annotated semantic feature norms.

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.

The Calgary semantic decision project: concrete/abstract decision data for 10,000 English words

Psycholinguistic research has been advanced by the development of word recognition megastudies. For instance, the English Lexicon Project (Balota et al., 2007) provides researchers with access to naming and lexical-decision latencies for over 40,000 words. In the present work, we extended the megastudy approach to a task that emphasizes semantic processing. Using a concrete/abstract semantic decision (i.e., does the word refer to something concrete or abstract?), we collected decision latencies and accuracy rates for 10,000 English words. The stimuli were concrete and abstract words selected from Brysbaert, Warriner, and Kuperman's (2013) comprehensive list of concreteness ratings. In total, 321 participants provided responses to 1,000 words each. Whereas semantic effects tend to be quite modest in naming and lexical decision studies, analyses of the concrete/abstract semantic decision responses show that a substantial proportion of variance can be explained by semantic variables. The item-level and trial-level data will be useful for other researchers interested in the semantic processing of concrete and abstract words.

Effects of semantic neighborhood density in abstract and concrete words

Concrete and abstract words are thought to differ along several psycholinguistic variables, such as frequency and emotional content. Here, we consider another variable, semantic neighborhood density, which has received much less attention, likely because semantic neighborhoods of abstract words are difficult to measure. Using a corpus-based method that creates representations of words that emphasize featural information, the current investigation explores the relationship between neighborhood density and concreteness in a large set of English nouns. Two important observations emerge. First, semantic neighborhood density is higher for concrete than for abstract words, even when other variables are accounted for, especially for smaller neighborhood sizes. Second, the effects of semantic neighborhood density on behavior are different for concrete and abstract words. Lexical decision reaction times are fastest for words with sparse neighborhoods; however, this effect is stronger for concrete words than for abstract words. These results suggest that semantic neighborhood density plays a role in the cognitive and psycholinguistic differences between concrete and abstract words, and should be taken into account in studies involving lexical semantics. Furthermore, the pattern of results with the current feature-based neighborhood measure is very different from that with associatively defined neighborhoods, suggesting that these two methods should be treated as separate measures rather than two interchangeable measures of semantic neighborhoods.

Pacifier Overuse and Conceptual Relations of Abstract and Emotional Concepts

This study explores the impact of the extensive use of an oral device since infancy (pacifier) on the acquisition of concrete, abstract, and emotional concepts. While recent evidence showed a negative relation between pacifier use and children's emotional competence (Niedenthal et al., 2012), the possible interaction between use of pacifier and processing of emotional and abstract language has not been investigated. According to recent theories, while all concepts are grounded in sensorimotor experience, abstract concepts activate linguistic and social information more than concrete ones. Specifically, the Words As Social Tools (WAT) proposal predicts that the simulation of their meaning leads to an activation of the mouth (Borghi and Binkofski, 2014; Borghi and Zarcone, 2016). Since the pacifier affects facial mimicry forcing mouth muscles into a static position, we hypothesize its possible interference on acquisition/consolidation of abstract emotional and abstract not-emotional concepts, which are mainly conveyed during social and linguistic interactions, than of concrete concepts. Fifty-nine first grade children, with a history of different frequency of pacifier use, provided oral definitions of the meaning of abstract not-emotional, abstract emotional, and concrete words. Main effect of concept type emerged, with higher accuracy in defining concrete and abstract emotional concepts with respect to abstract not-emotional concepts, independently from pacifier use. Accuracy in definitions was not influenced by the use of pacifier, but correspondence and hierarchical clustering analyses suggest that the use of pacifier differently modulates the conceptual relations elicited by abstract emotional and abstract not-emotional. While the majority of the children produced a similar pattern of conceptual relations, analyses on the few (6) children who overused the pacifier (for more than 3 years) showed that they tend to distinguish less clearly between concrete and abstract emotional concepts and between concrete and abstract not-emotional concepts than children who did not use it (5) or used it for short (17). As to the conceptual relations they produced, children who overused the pacifier tended to refer less to their experience and to social and emotional situations, use more exemplifications and functional relations, and less free associations.

The role of variability in the property listing task

It is generally believed that concepts can be characterized by their properties (or features). When investigating concepts encoded in language, researchers often ask subjects to produce lists of properties that describe them (i.e., the Property Listing Task, PLT). These lists are accumulated to produce Conceptual Property Norms (CPNs). CPNs contain frequency distributions of properties for individual concepts. It is widely believed that these distributions represent the underlying semantic structure of those concepts. Here, instead of focusing on the underlying semantic structure, we aim at characterizing the PLT. An often disregarded aspect of the PLT is that individuals show intersubject variability (i.e., they produce only partially overlapping lists). In our study we use a mathematical analysis of this intersubject variability to guide our inquiry. To this end, we resort to a set of publicly available norms that contain information about the specific properties that were informed at the individual subject level. Our results suggest that when an individual is performing the PLT, he or she generates a list of properties that is a mixture of general and distinctive properties, such that there is a non-linear tendency to produce more general than distinctive properties. Furthermore, the low generality properties are precisely those that tend not to be repeated across lists, accounting in this manner for part of the intersubject variability. In consequence, any manipulation that may affect the mixture of general and distinctive properties in lists is bound to change intersubject variability. We discuss why these results are important for researchers using the PLT.

Integrative Priming of Compositional and Locative Relations

Integrative priming refers to the facilitated recognition of a target word (bench) as a real word following a prime (park). Prior integrative priming studies have used a wide variety of integrative relations including temporal (summer rain), topical (travel book), locative (forest river), and compositional (peach pie) relations. Yet differences in the types of integrative relations may yield differences in the underlying explanatory processes of integrative priming. In this study, we compared the magnitude, time course, and three theoretically based correlates of integrative priming for compositional (stone table) and locative (patio table) pairs in a lexical decision task across four stimulus onset asynchronies (SOAs; 50, 300, 800, and 1,600 ms). Based on the Complementary Role Activation theory, integrative ratings (the extent to which the prime and target can be combined into a meaningful phrase) were predicted to facilitate target RTs. Based on the Embodied Conceptual Combination (ECCo) theory, the local co-occurrence of the prime and target, and the ability to perceptually simulate (visually experience) the prime-target pair were tested as predictors. In comparison to unrelated pairs (nose table), target RTs were faster for the compositional and locative pairs, though did not differ between these relations. In support of the Complementary Role Activation theory, integrative ratings predicted target RTs above and beyond our control variables. In support of the ECCo theory, co-occurrence emerged as an early predictor of target RTs, and visual experience ratings was a reliable predictor at the 300 ms SOA, though only for the compositional relations.

Grounded understanding of abstract concepts: The case of STEM learning

Characterizing the neural implementation of abstract conceptual representations has long been a contentious topic in cognitive science. At the heart of the debate is whether the "sensorimotor" machinery of the brain plays a central role in representing concepts, or whether the involvement of these perceptual and motor regions is merely peripheral or epiphenomenal. The domain of science, technology, engineering, and mathematics (STEM) learning provides an important proving ground for sensorimotor (or grounded) theories of cognition, as concepts in science and engineering courses are often taught through laboratory-based and other hands-on methodologies. In this review of the literature, we examine evidence suggesting that sensorimotor processes strengthen learning associated with the abstract concepts central to STEM pedagogy. After considering how contemporary theories have defined abstraction in the context of semantic knowledge, we propose our own explanation for how body-centered information, as computed in sensorimotor brain regions and visuomotor association cortex, can form a useful foundation upon which to build an understanding of abstract scientific concepts, such as mechanical force. Drawing from theories in cognitive neuroscience, we then explore models elucidating the neural mechanisms involved in grounding intangible concepts, including Hebbian learning, predictive coding, and neuronal recycling. Empirical data on STEM learning through hands-on instruction are considered in light of these neural models. We conclude the review by proposing three distinct ways in which the field of cognitive neuroscience can contribute to STEM learning by bolstering our understanding of how the brain instantiates abstract concepts in an embodied fashion.

Grounding Abstractness: Abstract Concepts and the Activation of the Mouth

One key issue for theories of cognition is how abstract concepts, such as freedom, are represented. According to the WAT (Words As social Tools) proposal, abstract concepts activate both sensorimotor and linguistic/social information, and their acquisition modality involves the linguistic experience more than the acquisition of concrete concepts. We report an experiment in which participants were presented with abstract and concrete definitions followed by concrete and abstract target-words. When the definition and the word matched, participants were required to press a key, either with the hand or with the mouth. Response times and accuracy were recorded. As predicted, we found that abstract definitions and abstract words yielded slower responses and more errors compared to concrete definitions and concrete words. More crucially, there was an interaction between the target-words and the effector used to respond (hand, mouth). While responses with the mouth were overall slower, the advantage of the hand over the mouth responses was more marked with concrete than with abstract concepts. The results are in keeping with grounded and embodied theories of cognition and support the WAT proposal, according to which abstract concepts evoke linguistic-social information, hence activate the mouth. The mechanisms underlying the mouth activation with abstract concepts (re-enactment of acquisition experience, or re-explanation of the word meaning, possibly through inner talk) are discussed. To our knowledge this is the first behavioral study demonstrating with real words that the advantage of the hand over the mouth is more marked with concrete than with abstract concepts, likely because of the activation of linguistic information with abstract concepts.

Semantic Neighborhood Effects for Abstract versus Concrete Words

Studies show that semantic effects may be task-specific, and thus, that semantic representations are flexible and dynamic. Such findings are critical to the development of a comprehensive theory of semantic processing in visual word recognition, which should arguably account for how semantic effects may vary by task. It has been suggested that semantic effects are more directly examined using tasks that explicitly require meaning processing relative to those for which meaning processing is not necessary (e.g., lexical decision task). The purpose of the present study was to chart the processing of concrete versus abstract words in the context of a global co-occurrence variable, semantic neighborhood density (SND), by comparing word recognition response times (RTs) across four tasks varying in explicit semantic demands: standard lexical decision task (with non-pronounceable non-words), go/no-go lexical decision task (with pronounceable non-words), progressive demasking task, and sentence relatedness task. The same experimental stimulus set was used across experiments and consisted of 44 concrete and 44 abstract words, with half of these being low SND, and half being high SND. In this way, concreteness and SND were manipulated in a factorial design using a number of visual word recognition tasks. A consistent RT pattern emerged across tasks, in which SND effects were found for abstract (but not necessarily concrete) words. Ultimately, these findings highlight the importance of studying interactive effects in word recognition, and suggest that linguistic associative information is particularly important for abstract words.

Cognitive and anatomic double dissociation in the representation of concrete and abstract words in semantic variant and behavioral variant frontotemporal degeneration

We examine the anatomic basis for abstract and concrete lexical representations in semantic memory by assessing patients with focal neurodegenerative disease. Prior evidence from healthy adult studies suggests that there may be an anatomical dissociation between abstract and concrete representations: abstract words more strongly activate the left inferior frontal gyrus relative to concrete words, while concrete words more strongly activate left anterior-inferior temporal regions. However, this double dissociation has not been directly examined. We test this dissociation in two patient groups with focal cortical atrophy in each of these regions, the behavioral variant of Frontotemporal Degeneration (bvFTD) and the semantic variant of Primary Progressive Aphasia (svPPA). We administered an associativity judgment task for abstract and concrete words, where subjects select which of two words is best associated with a given target word. Both bvFTD and svPPA patients were significantly impaired in their overall performance compared to controls. While controls treated concrete and abstract words equally, we found a category-specific double dissociation in patients' judgments: bvFTD patients showed a concreteness effect (CE), with significantly worse performance for abstract compared to concrete words, while svPPA patients showed reversal of the CE, with significantly worse performance for concrete over abstract words. Regression analyses also revealed an anatomic double dissociation: The CE is associated with inferior frontal atrophy in bvFTD, while reversal of the CE is associated with left anterior-inferior temporal atrophy in svPPA. These results support a cognitive and anatomic model of semantic memory organization where abstract and concrete representations are supported by dissociable neuroanatomic substrates.