tDCS of right-hemispheric Wernicke's area homologue affects contextual learning of novel lexicon.

Numerous studies have shown robust evidence of the right hemisphere's involvement in the language function, for instance in the processing of intonation, grammar, word meanings, metaphors, etc. However, its role in lexicon acquisition remains obscure. We applied transcranial direct current stimulation (tDCS) over the right-hemispheric homologue of Wernicke's area to assess its putative involvement in the processing of different types of novel semantics. After receiving 15 min of anodal, cathodal, or sham (placebo) tDCS, three groups of healthy participants learnt novel concrete and abstract words in the context of short stories. Learning outcomes were assessed using a battery of tests immediately after this contextual learning session and 24 h later. As a result, an inhibitory effect of cathodal tDCS and a facilitatory effect of anodal tDCS were found for abstract word acquisition only. We also found a significant drop in task performance on the second day of the assessment for both word types in all the stimulation groups, suggesting no significant influence of tDCS on the post-learning consolidation of new memory traces. The results suggest an involvement of Wernicke's right-hemispheric counterpart in initial encoding (but not consolidation) of abstract semantics, which may be explained either by the right hemispheres direct role in processing lexical semantics or by an indirect impact of tDCS on contralateral (left-hemispheric) cortical areas through cross-callosal connections.

TACO: A Turkish database for abstract concepts.

The organization of abstract concepts reflects different dimensions, grounded in the brain regions coding for the corresponding experience. Normative measures of linguistic stimuli offer noteworthy insights into the organization of conceptual knowledge, but studies differ in the dimensions and classes of concepts considered. Additionally, most of the available information has been collected in English, without considering possible linguistic and cultural differences. Here, we aimed to create a comprehensive Turkish database for abstract concepts (TACO), including rarely investigated classes such as political concepts. We included 503 words-78 concrete (fruits, animals, tools) and 425 abstract (emotions, social, mental states, theoretical, quantity, space, political)-rated by 134 Turkish speakers for familiarity, imageability, age of acquisition, valence, arousal, quantity, space, theoretical, social, mental state, and political dimensions. We calculated dominance and exclusivity, indicating the dimension receiving the highest mean score for each word, and the position of the word along the unidimensional-multidimensional continuum, respectively. A principal component analysis (PCA) was conducted on the semantic dimensions. The results showed that mental state was the dominant dimension for most concepts. Moderate to low levels of exclusivity indicated that the concepts were multidimensional. PCA revealed three components: Component 1 captured the juxtaposition between social/mental state and magnitude polarities, Component 2 highlighted affective components, and Component 3 grouped together political and theoretical dimensions. The introduction of political concepts provided insights into the multidimensional nature of this unexplored class, closely intertwined with the theoretical dimension. TACO constitutes the first comprehensive Turkish database covering several abstract dimensions, paving the way for cross-linguistic and cross-cultural studies of semantic representations.

Grounding of abstract concepts related to power.

Grounded cognition assumes that language and concepts are understood using simulations in different modalities. Evidence for this assumption mainly stems from studies using concrete concepts. Less evidence for grounding exists for abstract concepts, which are assumed to be grounded via metaphors associated with them or via experiences with them in specific situations. In the present study, we developed a new paradigm and investigated grounding of abstract concepts related to power or the exercise of power. As stimulus material, we chose pairs of concepts, for example, democracy and dictatorship. Participants were presented each concept separately and were asked to create a visual image in their mind. Then they were asked to rate images on several aspects. Afterwards they were asked to draw a sketch of the image. Results showed that drawings of high-power concepts had a larger vertical extension than low-power concepts. Results of the questions depended on the specific concepts. For instance, wealth (high-power) was rated as more colorful than poverty (low-power), but democracy (low-power) was rated as more colorful than dictatorship (high-power). These results may partly be explained by the valence of the concepts. Drawings often contained persons, objects, and situations, but were rarely abstract. Sometimes drawings contained metaphorical content and sometimes the content of drawings related to specific experiences. In conclusion, abstract concepts related to power can be depicted visually via grounding in different ways, such as using metaphors, experiences, and actions.

Category production norms for 117 concrete and abstract categories.

We present a database of category production (aka semantic fluency) norms collected in the UK for 117 categories (67 concrete and 50 abstract). Participants verbally named as many category members as possible within 60 seconds, resulting in a large variety of over 2000 generated member concepts. The norms feature common measures of category production (production frequency, mean ordinal rank, first-rank frequency), as well as response times for all first-named category members, and typicality ratings collected from a separate participant sample. We provide two versions of the dataset: a referential version that groups together responses that relate to the same referent (e.g., hippo, hippopotamus) and a full version that retains all original responses to enable future lexical analysis. Correlational analyses with previous norms from the USA and UK demonstrate both consistencies and differences in English-language norms over time and between geographical regions. Further exploration of the norms reveals a number of structural and psycholinguistic differences between abstract and concrete categories. The data and analyses will be of use in the fields of cognitive psychology, neuropsychology, psycholinguistics, and cognitive modelling, and to any researchers interested in semantic category structure. All data, including original participant recordings, are available at https://osf.io/jgcu6/ .

SymCog: An open-source toolkit for assessing human symbolic cognition.

Symbol systems have a profound influence on human behavior, spanning countless modalities such as natural language, clothing styles, monetary systems, and gestural conventions (e.g., handshaking). Selective impairments in understanding and manipulating symbols are collectively known as asymbolia. Here we address open questions about the nature of asymbolia in the context of both historical and contemporary approaches to human symbolic cognition. We describe a tripartite perspective on symbolic cognition premised upon (1) mental representation of a concept, (2) a stored pool of symbols segregated from their respective referents, and (3) fast and accurate mapping between concepts and symbols. We present an open-source toolkit for assessing symbolic knowledge premised upon matching animated video depictions of abstract concepts to their corresponding verbal and nonverbal symbols. Animations include simple geometric shapes (e.g., filled circles, squares) moving in semantically meaningful ways. For example, a rectangle bending under the implied weight of a large square denotes "heaviness." We report normative data for matching words and images to these target animations. In a second norming study, participants rated target animations across a range of semantic dimensions (e.g., valence, dominance). In a third study, we normed a set of concepts familiar to American English speakers but lacking verbal labels (e.g., the feeling of a Sunday evening). We describe how these tools may be used to assess human symbolic processing and identify asymbolic deficits across the span of human development.

Differential temporo-spatial pattern of electrical brain activity during the processing of abstract concepts related to mental states and verbal associations.

Refined grounded cognition accounts propose that abstract concepts might be grounded in brain circuits involved in mentalizing. In the present event-related potential (ERP) study, we compared the time course of neural processing in response to semantically predefined abstract mental states and verbal association concepts during a lexical decision task. In addition to scalp ERPs, source estimates of underlying volume brain activity were determined to reveal spatio-temporal clusters of greater electrical brain activity to abstract mental state vs. verbal association concepts, and vice versa. Source estimates suggested early (onset 194 ms), but short-lived enhanced activity (offset 210 ms) to verbal association concepts in left occipital regions. Increased occipital activity might reflect retrieval of visual word form or access to visual conceptual features of associated words. Increased estimated source activity to mental state concepts was obtained in visuo-motor (superior parietal, pre- and postcentral areas) and mentalizing networks (lateral and medial prefrontal areas, insula, precuneus, temporo-parietal junction) with an onset of 212 ms, which extended to later time windows. The time course data indicated two processing phases: An initial conceptual access phase, in which linguistic and modal brain circuits rapidly process features depending on their relevance, and a later conceptual elaboration phase, in which elaborative processing within feature-specific networks further refines the concept. This study confirms the proposal that abstract concepts are based on representations in distinct neural circuits depending on their semantic feature content. The present research also highlights the importance of investigating sets of abstract concepts with a defined semantic content.

Similarities and differences in the neural representations of abstract concepts across English and Mandarin.

Recent research suggests there is a neural organization for representing abstract concepts that is common across English speakers. To investigate the possible role of language on the representation of abstract concepts, multivariate pattern analytic (MVPA) techniques were applied to fMRI data to compare the neural representations of 28 individual abstract concepts between native English and Mandarin speakers. Factor analyses of the activation patterns of the 28 abstract concepts from both languages characterized this commonality in terms of a set of four underlying neurosemantic dimensions, indicating the degree to which a concept is verbally represented, internal to the person, contains social content, and is rule-based. These common semantic dimensions (factors) underlying the 28 concepts provided a sufficient basis for reliably identifying the individual abstract concepts from their neural signature in the other language with a mean rank accuracy of 0.65 (p < .001). Although the neural dimensions used for representing abstract concepts are common across languages, differences in the meaning of some individual concepts can be accommodated in terms of differential salience of particular dimensions. These semantic dimensions constitute a set of neurocognitive resources for abstract concept representations within a larger set of regions responsible for general semantic processing.

Broca's area involvement in abstract and concrete word acquisition: tDCS evidence.

Broca's area in the left hemisphere of the human neocortex has been suggested as a major hub for acquisition, storage, and access of linguistic information, abstract words in particular. Direct causal evidence for the latter, however, is still scarce; filling this gap was the goal of the present study. Using transcranial direct current stimulation (tDCS) of Broca's region, we aimed to delineate the involvement of this area in abstract and concrete word acquisition. The experiment used a between-subject design and involved 15 min of anodal or cathodal tDCS over Broca's area, or a sham/placebo control condition. The stimulation procedure was followed by a contextual learning session, in which participants were exposed to new concrete and abstract words embedded into short five-sentence texts. Finally, a set of behavioural assessment tasks was run to assess the learning outcomes immediately after the training (Day 1) and with a 24-hour delay (Day 2). The results showed that participants recognised novel abstract words more accurately after both anodal and cathodal tDCS in comparison with the sham condition on Day 1, which was also accompanied by longer recognition times (presumably due to deeper lexico-semantic processing), supporting the role of Broca's region in acquisition of abstract semantics. They were also more successful when recalling concrete words after cathodal tDCS, which indicates a degree of Broca's area involvement in forming memory circuits for concrete words as well. A decrease in the accuracy of recall of word forms and their meanings, as well as in recognition, was observed for all stimulation groups and both types of semantics on Day 2. The results suggest that both anodal and cathodal tDCS of Broca's area improves immediate contextual learning of novel vocabulary, predominantly affecting abstract semantics.

Relative numerical middle in rhesus monkeys.

Animals show vast numerical competence in tasks that require both ordinal and cardinal numerical representations, but few studies have addressed whether animals can identify the numerical middle in a sequence. Two rhesus monkeys (Macaca mulatta) learned to select the middle dot in a horizontal sequence of three dots on a touchscreen. When subsequently presented with longer sequences composed of 5, 7 or 9 items, monkeys transferred the middle rule. Accuracy decreased as the length of the sequence increased. In a second test, we presented monkeys with asymmetrical sequences composed of nine items, where the numerical and spatial middle were distinct and both monkeys selected the numerical middle over the spatial middle. Our results demonstrate that rhesus macaques can extract an abstract numerical rule to bisect a discrete set of items.

Embodiment and learning of abstract concepts (such as algebraic topology and regression to the mean).

This video is a proof of concept that ideas from embodied cognition can be used to understand how the brain and cognitive systems deal with very abstract concepts. The video teaches regression to the mean using three ideas. The first idea is directly related to embodied cognition: abstract concepts are grounded in perceptual, motor, and emotional systems by using successive levels of grounding within an extended procedure. The second idea is that this sort of grounding often requires formal instruction: a teacher needs to develop the sequence in which the concepts are grounded and the methods of grounding. That is, at least some abstract concepts are unlikely to be learned through an individual's unstructured interactions with the world. The third idea is that humans are hyper-social, thus making formal instruction possible. To the extent that the viewer learns the abstract concept of regression to the mean, then the video demonstrates how an embodied theory of abstract concepts could work.

Images of the unseen: extrapolating visual representations for abstract and concrete words in a data-driven computational model.

Theories of grounded cognition assume that conceptual representations are grounded in sensorimotor experience. However, abstract concepts such as jealousy or childhood have no directly associated referents with which such sensorimotor experience can be made; therefore, the grounding of abstract concepts has long been a topic of debate. Here, we propose (a) that systematic relations exist between semantic representations learned from language on the one hand and perceptual experience on the other hand, (b) that these relations can be learned in a bottom-up fashion, and (c) that it is possible to extrapolate from this learning experience to predict expected perceptual representations for words even where direct experience is missing. To test this, we implement a data-driven computational model that is trained to map language-based representations (obtained from text corpora, representing language experience) onto vision-based representations (obtained from an image database, representing perceptual experience), and apply its mapping function onto language-based representations for abstract and concrete words outside the training set. In three experiments, we present participants with these words, accompanied by two images: the image predicted by the model and a random control image. Results show that participants' judgements were in line with model predictions even for the most abstract words. This preference was stronger for more concrete items and decreased for the more abstract ones. Taken together, our findings have substantial implications in support of the grounding of abstract words, suggesting that we can tap into our previous experience to create possible visual representation we don't have.

Encoding and inhibition of arbitrary episodic context with abstract concepts.

Context is critical for conceptual processing, but the mechanism underpinning its encoding and reinstantiation during abstract concept processing is unclear. Context may be especially important for abstract concepts-we investigated whether episodic context is recruited differently when processing abstract compared with concrete concepts. Experiments 1 and 2 presented abstract and concrete words in arbitrary contexts at encoding (Experiment 1: red/green colored frames; Experiment 2: male/female voices). Recognition memory for these contexts was worse for abstract concepts. Again using frame color and voice as arbitrary contexts, respectively, Experiments 3 and 4 presented words from encoding in the same or different context at test to determine whether there was a greater recognition memory benefit for abstract versus concrete concepts when the context was unchanged between encoding and test. Instead, abstract concepts were less likely to be remembered when context was retained. This suggests that at least some types of episodic context-when arbitrary-are attended less, and may even be inhibited, when processing abstract concepts. In Experiment 5, we utilized a context-spatial location-which (as we show) tends to be relevant during real-world processing of abstract concepts. We presented words in different locations, preserving or changing location at test. Location retention conferred a recognition memory advantage for abstract concepts. Thus, episodic context may be encoded with abstract concepts when context is relevant to real-world processing. The systematic contexts necessary for understanding abstract concepts may lead to arbitrary context inhibition, but greater attention to contexts that tend to be more relevant during real-world processing.

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.

The neural representation of abstract words may arise through grounding word meaning in language itself.

In order to describe how humans represent meaning in the brain, one must be able to account for not just concrete words but, critically, also abstract words, which lack a physical referent. Hebbian formalism and optimization are basic principles of brain function, and they provide an appealing approach for modeling word meanings based on word co-occurrences. We provide proof of concept that a statistical model of the semantic space can account for neural representations of both concrete and abstract words, using MEG. Here, we built a statistical model using word embeddings extracted from a text corpus. This statistical model was used to train a machine learning algorithm to successfully decode the MEG signals evoked by written words. In the model, word abstractness emerged from the statistical regularities of the language environment. Representational similarity analysis further showed that this salient property of the model co-varies, at 280-420 ms after visual word presentation, with activity in regions that have been previously linked with processing of abstract words, namely the left-hemisphere frontal, anterior temporal and superior parietal cortex. In light of these results, we propose that the neural encoding of word meanings can arise through statistical regularities, that is, through grounding in language itself.

Different types of abstract concepts: evidence from two neurodegenerative patients.

The observation of neurological patients showing selective impairments for specific conceptual categories contributed in the development of semantic memory theories. Here, we studied two patients (P01, P02), affected, respectively, by the semantic variant of Primary Progressive Aphasia (sv-PPA) and Cortico-Basal Syndrome (CBS). An implicit lexical decision task, including concrete (animals, tools) and abstract (emotions, social, quantity) concepts, was administered to patients and healthy controls.P01 and P02 showed an abolished priming effect for social and quantity-related concepts, respectively. This double dissociation suggests a role of different brain areas in representing specific abstract categories, giving insights for current semantic memory theories.

Neural Representations of Abstract Concepts: Identifying Underlying Neurosemantic Dimensions.

The abstractness of concepts is sometimes defined indirectly as lacking concreteness, this view provides little insight into their cognitive or neural basis. Multivariate pattern analytic techniques applied to functional magnetic resonance imaging data were used to characterize the neural representations of 28 individual abstract concepts. A classifier trained on the concepts' neural signatures reliably decoded their neural representations in an independent subset of data for each participant. There was considerable commonality of the neural representations across participants as indicated by the accurate classification of each participant's concepts based on the neural signatures obtained in other participants. Group-level factor analysis revealed 3 semantic dimensions underlying the 28 concepts, suggesting a brain-based ontology for this set of abstract concepts. The 3 dimensions corresponded to 1) the degree a concept was Verbally Represented; 2) whether a concept was External (or Internal) to the individual, and 3) whether the concept contained Social Content. Further exploration of the Verbal Representation dimension suggests that the degree a concept is verbally represented can be construed as a point on a continuum between language faculties and perceptual faculties. A predictive model, based on independent behavioral ratings of the 28 concepts along the 3 factor dimensions, provided converging evidence for the interpretations.

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/ ).

Situational systematicity: A role for schema in understanding the differences between abstract and concrete concepts.

concepts differ from concrete concepts in several ways. Here, we focus on what we refer to as situational systematicity: The objects and relations that constitute an abstract concept (e.g., justice) are more dispersed through space and time than are those that typically constitute a concrete concept (e.g., chair); a larger set of objects and relations constitute an abstract concept than a concrete one; and exactly which objects and relations constitute a concept is more context-dependent for abstract concepts. We thus refer to abstract concepts as having low situational systematicity. We contend that situational systematicity, rather than abstractness per se, is a critical determinant of the cognitive, behavioural, and neural phenomena associated with concepts. Further, viewing concepts as schema provides insight into (i) the situation-based dynamics of concept learning and representation and (ii) the functional significance of the brain regions and their interactions that comprise the schema control network.

Animated Guide to Represent a Novel Means of Gut-Brain Axis Communication.

Novel scientific concepts must be made understandable to allow their further development, highlighting the need for better communication of abstract ideas that these discoveries are built upon. This project focused on visually communicating the discovery of microbiome-derived molecules that play a major role in microbiome-gut-brain axis communication through multimedia learning.A 4-min animated video that was segmented and used a combination of 2D and 3D models was created. It communicated the important information about the process of discovering the molecules in mouse models, their production by bacteria and their potential implications for human health. The animation was then provided to a scientific audience, alongside a short-answer survey and a Likert scale, to assess how visual aspects accompanied with narration compare to learning and comprehension of the same content if it is read.The findings are based on the total of 15 participants, 9 of which were exposed to the information via animation (Group A) and 6 who were given information in a form of written narrative (Group B). It was found that Group A scored average M = 15 (out of 25) on the post assessment compared to Group B with an average of M = 7. Higher scores correlated with higher rating on questions about perceived understanding through animated media. Additionally, the animation scored higher on helpfulness in learning abstract ideas, especially having to do with structure and spatial navigation. This indicates that scientific abstract concepts that are likely comprehended are needed in order to make definite conclusions.

On abstraction: decoupling conceptual concreteness and categorical specificity.

Conceptual concreteness and categorical specificity are two continuous variables that allow distinguishing, for example, justice (low concreteness) from banana (high concreteness) and furniture (low specificity) from rocking chair (high specificity). The relation between these two variables is unclear, with some scholars suggesting that they might be highly correlated. In this study, we operationalize both variables and conduct a series of analyses on a sample of > 13,000 nouns, to investigate the relationship between them. Concreteness is operationalized by means of concreteness ratings, and specificity is operationalized as the relative position of the words in the WordNet taxonomy, which proxies this variable in the hypernym semantic relation. Findings from our studies show only a moderate correlation between concreteness and specificity. Moreover, the intersection of the two variables generates four groups of words that seem to denote qualitatively different types of concepts, which are, respectively, highly specific and highly concrete (typical concrete concepts denoting individual nouns), highly specific and highly abstract (among them many words denoting human-born creation and concepts within the social reality domains), highly generic and highly concrete (among which many mass nouns, or uncountable nouns), and highly generic and highly abstract (typical abstract concepts which are likely to be loaded with affective information, as suggested by previous literature). These results suggest that future studies should consider concreteness and specificity as two distinct dimensions of the general phenomenon called abstraction.