Concepts, control, and context: A connectionist account of normal and disordered semantic cognition

What we mean when we say semantic: Toward a multidisciplinary semantic glossary

Tulving characterized semantic memory as a vast repository of meaning that underlies language and many other cognitive processes. This perspective on lexical and conceptual knowledge galvanized a new era of research undertaken by numerous fields, each with their own idiosyncratic methods and terminology. For example, "concept" has different meanings in philosophy, linguistics, and psychology. As such, many fundamental constructs used to delineate semantic theories remain underspecified and/or opaque. Weak construct specificity is among the leading causes of the replication crisis now facing psychology and related fields. Term ambiguity hinders cross-disciplinary communication, falsifiability, and incremental theory-building. Numerous cognitive subdisciplines (e.g., vision, affective neuroscience) have recently addressed these limitations via the development of consensus-based guidelines and definitions. The project to follow represents our effort to produce a multidisciplinary semantic glossary consisting of succinct definitions, background, principled dissenting views, ratings of agreement, and subjective confidence for 17 target constructs (e.g., abstractness, abstraction, concreteness, concept, embodied cognition, event semantics, lexical-semantic, modality, representation, semantic control, semantic feature, simulation, semantic distance, semantic dimension). We discuss potential benefits and pitfalls (e.g., implicit bias, prescriptiveness) of these efforts to specify a common nomenclature that other researchers might index in specifying their own theoretical perspectives (e.g., They said X, but I mean Y).

Language with vision: A study on grounded word and sentence embeddings

Grounding language in vision is an active field of research seeking to construct cognitively plausible word and sentence representations by incorporating perceptual knowledge from vision into text-based representations. Despite many attempts at language grounding, achieving an optimal equilibrium between textual representations of the language and our embodied experiences remains an open field. Some common concerns are the following. Is visual grounding advantageous for abstract words, or is its effectiveness restricted to concrete words? What is the optimal way of bridging the gap between text and vision? To what extent is perceptual knowledge from images advantageous for acquiring high-quality embeddings? Leveraging the current advances in machine learning and natural language processing, the present study addresses these questions by proposing a simple yet very effective computational grounding model for pre-trained word embeddings. Our model effectively balances the interplay between language and vision by aligning textual embeddings with visual information while simultaneously preserving the distributional statistics that characterize word usage in text corpora. By applying a learned alignment, we are able to indirectly ground unseen words including abstract words. A series of evaluations on a range of behavioral datasets shows that visual grounding is beneficial not only for concrete words but also for abstract words, lending support to the indirect theory of abstract concepts. Moreover, our approach offers advantages for contextualized embeddings, such as those generated by BERT (Devlin et al, 2018), but only when trained on corpora of modest, cognitively plausible sizes. Code and grounded embeddings for English are available at ( https://github.com/Hazel1994/Visually_Grounded_Word_Embeddings_2 ).

Functional integration and segregation during semantic cognition: Evidence across age groups

Semantic cognition is underpinned by ventral anterior temporal lobe (vATL) which encodes knowledge representations and inferior frontal gyrus (IFG), which controls activation of knowledge based on the needs of the current context. This core semantic network has been validated in substantial empirical findings in the past. However, it remains unclear how these core semantic areas dynamically communicate with each other, and with other neural networks, to achieve successful semantic processing. Here, we investigated this question by testing functional connectivity in the core semantic network during semantic tasks and whether these connections were affected by cognitive ageing. Compared to a non-semantic task, semantic tasks increased the connectivity between left and right IFGs, indicating a bilateral semantic control system. Strengthened connectivity was also found between left IFG and left vATL, and this effect was stronger in the young group. At a whole-brain scale, IFG and vATL increased their coupling with multiple-demand regions during semantic tasks, even though these areas were deactivated relative to non-semantic tasks. This suggests that the domain-general executive network contributes to semantic processing. In contrast, IFG and vATL decreased their interaction with default mode network (DMN) areas during semantic tasks, even though these areas were positively activated by the task. This suggests that DMN areas do not contribute to all semantic tasks: their activation may sometimes reflect automatic retrieval of task-irrelevant memories and associations. Taken together, our study characterizes a dynamic connectivity mechanism supporting semantic cognition within and beyond core semantic regions.

Semantic Stroop interference is modulated by the availability of executive resources: Insights from delta-plot analyses and cognitive load manipulation

We investigated whether, during visual word recognition, semantic processing is modulated by attentional control mechanisms directed at matching semantic information with task-relevant goals. In previous research, we analyzed the semantic Stroop interference as a function of response latency (delta-plot analyses) and found that this phenomenon mainly occurs in the slowest responses. Here, we investigated whether this pattern is due to reduced ability to proactively maintain the task goal in these slowest trials. In two pairs of experiments, participants completed two semantic Stroop tasks: a classic semantic Stroop task (Experiment 1A and 2A) and a semantic Stroop task combined with an n-back task (Experiment 1B and 2B). The two pairs of experiments only differed in the trial pace, which was slightly faster in Experiments 2A and 2B than in Experiments 1A and 1B. By taxing the executive control system, the n-back task was expected to hinder proactive control. Delta-plot analyses of the semantic Stroop task replicated the enhanced effect in the slowest responses, but only under sufficient time pressure. Combining the semantic Stroop task with the n-back task produced a change in the distributional profile of semantic Stroop interference, which we ascribe to a general difficulty in the use of proactive control. Our findings suggest that semantic Stroop interference is, to some extent, dependent on the available executive resources, while also being sensitive to subtle variations in task conditions.

Flexibility in conceptual combinations: A neural network model of gradable adjective modification

Our ability to combine simple constituents into more complex conceptual combinations is a fundamental aspect of cognition. Gradable adjectives (e.g., 'tall' and 'light') are a critical example of this process, as their meanings vary depending on the noun with which they are combined. For example, a dark diamond is less dark than dark charcoal. Here, we investigate how a neural network encodes the flexible nature of gradable adjectives in adjective-noun pairs, using the perceptual feature of brightness as a test case. We trained a neural network to predict human brightness ratings for unmodified nouns and adjective-noun pairs and assessed its ability to generalize to untrained combinations (e.g., 'light paint' vs. 'dark paint'). We also explored how this information is encoded. We found that flexible learning of gradable adjectives was possible, with neural networks first making predictions based on the adjective alone, and then modulating these with information from the noun later in learning. We also found that model outputs mimicked the kind of non-additive feature modulation present in human data. Our results have implications for understanding how semantic composition occurs and generate testable predictions for future work.

A neuroanatomical and cognitive model of impaired social behaviour in frontotemporal dementia

Impaired social cognition is a core deficit in frontotemporal dementia (FTD). It is most commonly associated with the behavioural-variant of FTD, with atrophy of the orbitofrontal and ventromedial prefrontal cortex. Social cognitive changes are also common in semantic dementia, with atrophy centred on the anterior temporal lobes. The impairment of social behaviour in FTD has typically been attributed to damage to the orbitofrontal cortex and/or temporal poles and/or the uncinate fasciculus that connects them. However, the relative contributions of each region are unresolved. In this review, we present a unified neurocognitive model of controlled social behaviour that not only explains the observed impairment of social behaviours in FTD, but also assimilates both consistent and potentially contradictory findings from other patient groups, comparative neurology and normative cognitive neuroscience. We propose that impaired social behaviour results from damage to two cognitively- and anatomically-distinct components. The first component is social-semantic knowledge, a part of the general semantic-conceptual system supported by the anterior temporal lobes bilaterally. The second component is social control, supported by the orbitofrontal cortex, medial frontal cortex and ventrolateral frontal cortex, which interacts with social-semantic knowledge to guide and shape social behaviour.

Healthy ageing has divergent effects on verbal and non-verbal semantic cognition

Semantic cognition refers to the storage and appropriate use of knowledge acquired over the lifespan and underpins our everyday verbal and non-verbal behaviours. Successful semantic cognition requires representation of knowledge and control processes which ensure that currently relevant aspects of knowledge are retrieved and selected. Although these abilities have been widely studied in healthy young populations and semantically impaired patients, it is unclear how they change as a function of healthy ageing, especially for non-verbal semantic processing. Here, we addressed this issue by comparing the performance profiles of young and older people on a semantic knowledge task and a semantic control task, across verbal (word) and non-verbal (picture) versions. The results revealed distinct patterns of change during adulthood for semantic knowledge and semantic control. Older people performed better in both verbal and non-verbal knowledge tasks than young people. However, although the older group showed preserved controlled retrieval for verbal semantics, they demonstrated a specific impairment for non-verbal semantic control. These findings indicate that the effects of ageing on semantic cognition are more complex than previously assumed, and that input modality plays an important role in the shifting cognitive architecture of semantics in later life.

Flexible Conceptual Representations

A view that has been gaining prevalence over the past decade is that the human conceptual system is malleable, dynamic, context-dependent, and task-dependent, that is, flexible. Within the flexible conceptual representation framework, conceptual representations are constructed ad hoc, forming a different, idiosyncratic instantiation upon each occurrence. In this review, we scrutinize the neurocognitive literature to better understand the nature of this flexibility. First, we identify some key characteristics of these representations. Next, we consider how these flexible representations are constructed by addressing some of the open questions in this framework: We review the age-old question of how to reconcile flexibility with the apparent need for shareable stable definitions to anchor meaning and come to mutual understanding, as well as some newer questions we find critical, namely, the nature of relations among flexible representations, the role of feature saliency in activation, and the viability of all-or-none feature activations. We suggest replacing the debate about the existence of a definitional stable core that is obligatorily activated with a question of the degree and probability of activation of the information constituting a conceptual representation. We rely on published works to suggest that (1) prior featural salience matters, (2) feature activation may be graded, and (3) Bayesian updating of prior information according to current demands offers a viable account of how flexible representations are constructed. This proposal provides a theoretical mechanism for incorporating a changing momentary context into a constructed representation, while still preserving some of the concept's constituent meaning.

The neural basis of naturalistic semantic and social cognition

Decoding social environments and engaging meaningfully with other people are critical aspects of human cognition. Multiple cognitive systems, including social and semantic cognition, work alongside each other to support these processes. This study investigated shared processing between social and semantic systems using neuroimaging data collected during movie-viewing, which captures the multimodal environment in which social knowledge is exchanged. Semantic and social content from movie events (event-level) and movie transcripts (word-level) were used in parametric modulation analyses to test (1) the degree to which semantic and social information is processed within each respective network and (2) engagement of the same cross-network regions or the same domain-general hub located within the semantic network during semantic and social processing. Semantic word and event-level content engaged the same fronto-temporo-parietal network and a portion of the semantic hub in the anterior temporal lobe (ATL). Social word and event-level content engaged the supplementary motor area and right angular gyrus within the social network, but only social words engaged the domain-general semantic hub in left ATL. There was evidence of shared processing between the social and semantic systems in the dorsolateral portion of right ATL which was engaged by word and event-level semantic and social content. Overlap between the semantic and social word and event results was highly variable within and across participants, with the most consistent loci of overlap occurring in left inferior frontal, bilateral precentral and supramarginal gyri for social and semantic words and in bilateral superior temporal gyrus extending from ATL posteriorly into supramarginal gyri for social and semantic events. These results indicate a complex pattern of shared and distinct regions for social and semantic cognition during naturalistic processing. PROTOCOL REGISTRATION: The stage 1 protocol for this Registered Report was accepted in principle on October 11, 2022. The protocol, as accepted by the journal, can be found at: https://doi.org/10.17605/OSF.IO/ACWQY .

Experiential grounding of abstract concepts: Processing of abstract mental state concepts engages brain regions involved in mentalizing, automatic speech, and lip movements

concepts like mental state concepts lack a physical referent, which can be directly perceived. Classical theories therefore claim that abstract concepts require amodal representations detached from experiential brain systems. However, grounded cognition approaches suggest an involvement of modal experiential brain regions in the processing of abstract concepts. In the present functional magnetic resonance imaging study, we investigated the relation of the processing of abstract mental state concepts to modal experiential brain systems in a fine-grained fashion. Participants performed lexical decisions on abstract mental state as well as on verbal association concepts as control category. Experiential brain systems related to the processing of mental states, generating verbal associations, automatic speech as well as hand and lip movements were determined by corresponding localizer tasks. Processing of abstract mental state concepts neuroanatomically overlapped with activity patterns associated with processing of mental states, generating verbal associations, automatic speech and lip movements. Hence, mental state concepts activate the mentalizing brain network, complemented by perceptual-motor brain regions involved in simulation of visual or action features associated with social interactions, linguistic brain regions as well as face-motor brain regions recruited for articulation. The present results provide compelling evidence for the rich grounding of abstract mental state concepts in experiential brain systems related to mentalizing, verbal communication and mouth action.

Unraveling lexical semantics in the brain: Comparing internal, external, and hybrid language models

To explain how the human brain represents and organizes meaning, many theoretical and computational language models have been proposed over the years, varying in their underlying computational principles and in the language samples based on which they are built. However, how well they capture the neural encoding of lexical semantics remains elusive. We used representational similarity analysis (RSA) to evaluate to what extent three models of different types explained neural responses elicited by word stimuli: an External corpus-based word2vec model, an Internal free word association model, and a Hybrid ConceptNet model. Semantic networks were constructed using word relations computed in the three models and experimental stimuli were selected through a community detection procedure. The similarity patterns between language models and neural responses were compared at the community, exemplar, and word node levels to probe the potential hierarchical semantic structure. We found that semantic relations computed with the Internal model provided the closest approximation to the patterns of neural activation, whereas the External model did not capture neural responses as well. Compared with the exemplar and the node levels, community-level RSA demonstrated the broadest involvement of brain regions, engaging areas critical for semantic processing, including the angular gyrus, superior frontal gyrus and a large portion of the anterior temporal lobe. The findings highlight the multidimensional semantic organization in the brain which is better captured by Internal models sensitive to multiple modalities such as word association compared with External models trained on text corpora.

Are valence and arousal related to the development of amodal representations of words? A computational study

In this study, we analyzed the relationship between the amodal (semantic) development of words and two popular emotional norms (emotional valence and arousal) in English and Spanish languages. To do so, we combined the strengths of semantics from vector space models (vector length, semantic diversity, and word maturity measures), and feature-based models of emotions. First, we generated a common vector space representing the meaning of words at different developmental stages (five and four developmental stages for English and Spanish, respectively) using the Word Maturity methodology to align different vector spaces. Second, we analyzed the amodal development of words through mixed-effects models with crossed random effects for words and variables using a continuous time metric. Third, the emotional norms were included as covariates in the statistical models. We evaluated more than 23,000 words, whose emotional norms were available for more than 10,000 words, in each language separately. Results showed a curve of amodal development with an increasing linear effect and a small quadratic deceleration. A relevant influence on the amodal development of words was found only for emotional valence (not for arousal), suggesting that positive words have an earlier amodal development and a less pronounced semantic change across early lifespan.

Neuropsychological differential diagnosis of Alzheimer's disease and vascular dementia: a systematic review with meta-regressions

Introduction

Diagnostic classification systems and guidelines posit distinguishing patterns of impairment in Alzheimer's (AD) and vascular dementia (VaD). In our study, we aim to identify which diagnostic instruments distinguish them.

Methods

We searched PubMed and PsychInfo for empirical studies published until December 2020, which investigated differences in cognitive, behavioral, psychiatric, and functional measures in patients older than 64 years and reported information on VaD subtype, age, education, dementia severity, and proportion of women. We systematically reviewed these studies and conducted Bayesian hierarchical meta-regressions to quantify the evidence for differences using the Bayes factor (BF). The risk of bias was assessed using the Newcastle-Ottawa-Scale and funnel plots.

Results

We identified 122 studies with 17,850 AD and 5,247 VaD patients. Methodological limitations of the included studies are low comparability of patient groups and an untransparent patient selection process. In the digit span backward task, AD patients were nine times more probable (BF = 9.38) to outperform VaD patients (β g = 0.33, 95% ETI = 0.12, 0.52). In the phonemic fluency task, AD patients outperformed subcortical VaD (sVaD) patients (β g = 0.51, 95% ETI = 0.22, 0.77, BF = 42.36). VaD patients, in contrast, outperformed AD patients in verbal (β g = -0.61, 95% ETI = -0.97, -0.26, BF = 22.71) and visual (β g = -0.85, 95% ETI = -1.29, -0.32, BF = 13.67) delayed recall. We found the greatest difference in verbal memory, showing that sVaD patients outperform AD patients (β g = -0.64, 95% ETI = -0.88, -0.36, BF = 72.97). Finally, AD patients performed worse than sVaD patients in recognition memory tasks (β g = -0.76, 95% ETI = -1.26, -0.26, BF = 11.50).

Conclusion

Our findings show inferior performance of AD in episodic memory and superior performance in working memory. We found little support for other differences proposed by diagnostic systems and diagnostic guidelines. The utility of cognitive, behavioral, psychiatric, and functional measures in differential diagnosis is limited and should be complemented by other information. Finally, we identify research areas and avenues, which could significantly improve the diagnostic value of cognitive measures.

Lateralized Learning to Solve Complex Boolean Problems

Modern classifier systems can effectively classify targets that consist of simple patterns. However, they can fail to detect hierarchical patterns of features that exist in many real-world problems, such as understanding speech or recognizing object ontologies. Biological nervous systems have the ability to abstract knowledge from simple and small-scale problems in order to then apply it to resolve more complex problems in similar and related domains. It is thought that lateral asymmetry of biological brains allows modular learning to occur at different levels of abstraction, which can then be transferred between tasks. This work develops a novel evolutionary machine-learning (EML) system that incorporates lateralization and modular learning at different levels of abstraction. The results of analyzable Boolean tasks show that the lateralized system has the ability to encapsulate underlying knowledge patterns in the form of building blocks of knowledge (BBK). Lateralized abstraction transforms complex problems into simple ones by reusing general patterns (e.g., any parity problem becomes a sequence of the 2-bit parity problem). By enabling abstraction in evolutionary computation, the lateralized system is able to identify complex patterns (e.g., in hierarchical multiplexer (HMux) problems) better than existing systems.

Brain Signatures of Embodied Semantics and Language: A Consensus Paper

According to embodied theories (including embodied, embedded, extended, enacted, situated, and grounded approaches to cognition), language representation is intrinsically linked to our interactions with the world around us, which is reflected in specific brain signatures during language processing and learning. Moving on from the original rivalry of embodied vs. amodal theories, this consensus paper addresses a series of carefully selected questions that aim at determining when and how rather than whether motor and perceptual processes are involved in language processes. We cover a wide range of research areas, from the neurophysiological signatures of embodied semantics, e.g., event-related potentials and fields as well as neural oscillations, to semantic processing and semantic priming effects on concrete and abstract words, to first and second language learning and, finally, the use of virtual reality for examining embodied semantics. Our common aim is to better understand the role of motor and perceptual processes in language representation as indexed by language comprehension and learning. We come to the consensus that, based on seminal research conducted in the field, future directions now call for enhancing the external validity of findings by acknowledging the multimodality, multidimensionality, flexibility and idiosyncrasy of embodied and situated language and semantic processes.

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.

Divergent semantic integration (DSI): Extracting creativity from narratives with distributional semantic modeling

We developed a novel conceptualization of one component of creativity in narratives by integrating creativity theory and distributional semantics theory. We termed the new construct divergent semantic integration (DSI), defined as the extent to which a narrative connects divergent ideas. Across nine studies, 27 different narrative prompts, and over 3500 short narratives, we compared six models of DSI that varied in their computational architecture. The best-performing model employed Bidirectional Encoder Representations from Transformers (BERT), which generates context-dependent numerical representations of words (i.e., embeddings). BERT DSI scores demonstrated impressive predictive power, explaining up to 72% of the variance in human creativity ratings, even approaching human inter-rater reliability for some tasks. BERT DSI scores showed equivalently high predictive power for expert and nonexpert human ratings of creativity in narratives. Critically, DSI scores generalized across ethnicity and English language proficiency, including individuals identifying as Hispanic and L2 English speakers. The integration of creativity and distributional semantics theory has substantial potential to generate novel hypotheses about creativity and novel operationalizations of its underlying processes and components. To facilitate new discoveries across diverse disciplines, we provide a tutorial with code (osf.io/ath2s) on how to compute DSI and a web app ( osf.io/ath2s ) to freely retrieve DSI scores.

A common neural code for meaning in discourse production and comprehension

How does the brain code the meanings conveyed by language? Neuroimaging studies have investigated this by linking neural activity patterns during discourse comprehension to semantic models of language content. Here, we applied this approach to the production of discourse for the first time. Participants underwent fMRI while producing and listening to discourse on a range of topics. We used a distributional semantic model to quantify the similarity between different speech passages and identified where similarity in neural activity was predicted by semantic similarity. When people produced discourse, speech on similar topics elicited similar activation patterns in a widely distributed and bilateral brain network. This network was overlapping with, but more extensive than, the regions that showed similarity effects during comprehension. Critically, cross-task neural similarities between comprehension and production were also predicted by similarities in semantic content. This result suggests that discourse semantics engages a common neural code that is shared between comprehension and production. Effects of semantic similarity were bilateral in all three RSA analyses, even while univariate activation contrasts in the same data indicated left-lateralised BOLD responses. This indicates that right-hemisphere regions encode semantic properties even when they are not activated above baseline. We suggest that right-hemisphere regions play a supporting role in processing the meaning of discourse during both comprehension and production.

Bigram semantic distance as an index of continuous semantic flow in natural language: Theory, tools, and applications

Much of our understanding of word meaning has been informed through studies of single words. High-dimensional semantic space models have recently proven instrumental in elucidating connections between words. Here we show how bigram semantic distance can yield novel insights into conceptual cohesion and topic flow when computed over continuous language samples. For example, "Cats drink milk" is comprised of an ordered vector of bigrams (cat-drink, drink-milk). Each of these bigrams has a unique semantic distance. These distances in turn may provide a metric of dispersion or the flow of concepts as language unfolds. We offer an R-package ("semdistflow") that transforms any user-specified language transcript into a vector of ordered bigrams, appending two metrics of semantic distance to each pair. We validated these distance metrics on a continuous stream of simulated verbal fluency data assigning predicted switch markers between alternating semantic clusters (animals, musical instruments, fruit). We then generated bigram distance norms on a large sample of text and demonstrated applications of the technique to a classic work of short fiction, To Build a Fire (London, 1908). In one application, we showed that bigrams spanning sentence boundaries are punctuated by jumps in the semantic distance. We discuss the promise of this technique for characterizing semantic processing in real-world narratives and for bridging findings at the single word level with macroscale discourse analyses. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Novel participant-level meta-analytic evidence for AbSANT efficacy

The current study employed interrupted time series (ITS) models to analyze all available (published and unpublished) Abstract Semantic Associative Network Training (AbSANT) data. AbSANT is a semantically focused anomia treatment that targets not only concrete but abstract words, unique among existing anomia treatments. However, evidence to date for the positive effects of AbSANT comes only from small-sample, single-subject design studies, limiting the strength of this evidence and the inferences that can be drawn from it. The statistical power and greater representativeness afforded by this larger aggregated sample enabled us to look for group-level efficacy evidence for AbSANT, examine specific questions about AbSANT's direct training and generalization effects, and identify potential predictors and mechanisms of AbSANT treatment response. We found that across 33 participants from four different data sources, AbSANT appears to be a robust word retrieval therapy protocol, with overall direct training and generalization effects that were more meaningful than exposure effects. Similar to previous smaller-sample study conclusions, we found that in this large sample, training abstract words results not only in larger direct training effects than training concrete words, but also larger generalization effects, suggesting that while AbSANT successfully improves both abstract and concrete word retrieval, it may be better suited for training abstract words. In general, direct training effects were more persistent after treatment ended than generalization effects and effects for concrete words were more persistent than for abstract words. Additionally, the effects of generalization appear to be distinct from the effects of simple exposure to words, and generalization effects are consistent with AbSANT's hypothesized mechanism of action: spreading activation from directly trained concepts to related concepts. Also consistent with this mechanism, we found that milder aphasia and both conceptual and lexical semantic processing ability predicted both direct training and generalization gains, and that executive function was predictive of generalization effects. These factors are thus important to consider when evaluating the appropriateness of AbSANT for individual clients.

The words that little by little revealed everything: Neural response to lexical-semantic content during narrative comprehension

The ease with which narratives are understood belies the complexity of the information being conveyed and the cognitive processes that support comprehension. The meanings of the words must be rapidly accessed and integrated with the reader's mental representation of the overarching, unfolding scenario. A broad, bilateral brain network is engaged by this process, but it is not clear how words that vary on specific semantic dimensions, such as ambiguity, emotion, or socialness, engage the semantic, semantic control, or social cognition systems. In the present study, data from 48 participants who listened to The Little Prince audiobook during MRI scanning were selected from the Le Petit Prince dataset. The lexical and semantic content within the narrative was quantified from the transcript words with factor scores capturing Word Length, Semantic Flexibility, Emotional Strength, and Social Impact. These scores, along with word quantity variables, were used to investigate where these predictors co-vary with activation across the brain. In contrast to studies of isolated word processing, large networks were found to co-vary with the lexical and semantic content within the narrative. An increase in semantic content engaged the ventral portion of ventrolateral ATL, consistent with its role as a semantic hub. Decreased semantic content engaged temporal pole and inferior parietal lobule, which may reflect semantic integration. The semantic control network was engaged by words with low Semantic Flexibility, perhaps due to the demand required to process infrequent, less semantically diverse language. Activation in ATL co-varied with an increase in Social Impact, which is consistent with the claim that social knowledge is housed within the neural architecture of the semantic system. These results suggest that current models of language processing may present an impoverished estimate of the neural systems that coordinate to support narrative comprehension, and, by extension, real-world language processing.

Uncertainty aversion predicts the neural expansion of semantic representations

Correctly identifying the meaning of a stimulus requires activating the appropriate semantic representation among many alternatives. One way to reduce this uncertainty is to differentiate semantic representations from each other, thereby expanding the semantic space. Here, in four experiments, we test this semantic-expansion hypothesis, finding that uncertainty-averse individuals exhibit increasingly differentiated and separated semantic representations. This effect is mirrored at the neural level, where uncertainty aversion predicts greater distances between activity patterns in the left inferior frontal gyrus when reading words, and enhanced sensitivity to the semantic ambiguity of these words in the ventromedial prefrontal cortex. Two direct tests of the behavioural consequences of semantic expansion further reveal that uncertainty-averse individuals exhibit reduced semantic interference and poorer generalization. Together, these findings show that the internal structure of our semantic representations acts as an organizing principle to make the world more identifiable.

Distinct but cooperating brain networks supporting semantic cognition

Semantic cognition is a complex multifaceted brain function involving multiple processes including sensory, semantic, and domain-general cognitive systems. However, it remains unclear how these systems cooperate with each other to achieve effective semantic cognition. Here, we used independent component analysis (ICA) to investigate the functional brain networks that support semantic cognition. We used a semantic judgment task and a pattern-matching control task, each with 2 levels of difficulty, to disentangle task-specific networks from domain-general networks. ICA revealed 2 task-specific networks (the left-lateralized semantic network [SN] and a bilateral, extended semantic network [ESN]) and domain-general networks including the frontoparietal network (FPN) and default mode network (DMN). SN was coupled with the ESN and FPN but decoupled from the DMN, whereas the ESN was synchronized with the FPN alone and did not show a decoupling with the DMN. The degree of decoupling between the SN and DMN was associated with semantic task performance, with the strongest decoupling for the poorest performing participants. Our findings suggest that human higher cognition is achieved by the multiple brain networks, serving distinct and shared cognitive functions depending on task demands, and that the neural dynamics between these networks may be crucial for efficient semantic cognition.

When a Sunny Day Gives You Butterflies: An Electrophysiological Investigation of Concreteness and Context Effects in Semantic Word Processing

Theories on controlled semantic cognition assume that word concreteness and linguistic context interact during semantic word processing. Methodological approaches and findings on how this interaction manifests at the electrophysiological and behavioral levels are heterogeneous. We measured ERPs and RTs applying a validated cueing paradigm with 19 healthy participants, who performed similarity judgments on concrete or abstract words (e.g., "butterfly" or "tolerance") after reading contextual and irrelevant sentential cues. Data-driven analyses showed that concreteness increased and context decreased negative-going deflections in broadly distributed bilateral clusters covering the N400 and N700/late positive component time range, whereas both reduced RTs. Crucially, within a frontotemporal cluster in the N400 time range, contextual (vs. irrelevant) information reduced negative-going amplitudes in response to concrete but not abstract words, whereas a contextual cue reduced RTs only in response to abstract but not concrete words. The N400 amplitudes did not explain additional variance in the RT data, which showed a stronger contextual facilitation for abstract than concrete words. Our results support separate but interacting effects of concreteness and context on automatic and controlled stages of contextual semantic processing and suggest that effects on the electrophysiological versus behavioral level obtained with this paradigm are dissociated.

Composite Indices of the Color-Picture Version of Boston Naming Test Have Better Discriminatory Power: Reliability and Validity in a Chinese Sample with Diverse Neurodegenerative Diseases

BACKGROUND

The Boston Naming Test (BNT) is the most widely used measure to assess anomia. However, it has been criticized for failing to differentiate the underlying cognitive process of anomia.

OBJECTIVE

We validated the color-picture version of BNT (CP-BNT) in a sample with diverse neurodegenerative dementia diseases (NDDs). We also verified the differential ability of the composite indices of CP-BNT across NDDs groups.

METHODS

The present study included Alzheimer's disease (n = 132), semantic variant primary progressive aphasia (svPPA, n = 53), non-svPPA (n = 33), posterior cortical atrophy (PCA, n = 35), and normal controls (n = 110). We evaluated psychometric properties of CP-BNT for the spontaneous naming (SN), the percentage of correct responses on semantic cuing and word recognition cuing (% SC, % WR). Receiver operating characteristic analysis was used to examine the discriminatory power of SN alone and the composite indices (SN, % SC, and % WR).

RESULTS

The CP-BNT had sufficient internal consistency, good convergent, divergent validity, and criterion validity. Different indices of CP-BNT demonstrated distinct cognitive underpinnings. Category fluency was the strongest predictor of SN (β= 0.46, p < 0.001). Auditory comprehension tests highly associated with % WR (Sentence comprehension: β= 0.22, p = 0.001; Word comprehension: β= 0.20, p = 0.001), whereas a lower visuospatial score predicted % SC (β= -0.2, p = 0.001). Composite indices had better predictability than the SN alone when differentiating between NDDs, especially for PCA versus non-svPPA (area under the curve increased from 63.9% to 81.2%).

CONCLUSION

The CP-BNT is a highly linguistically relevant test with sufficient reliability and validity. Composite indices could provide more differential information beyond SN and should be used in clinical practice.

Child-oriented word associations improve models of early word learning

How words are associated within the linguistic environment conveys semantic content; however, different contexts induce different linguistic patterns. For instance, it is well known that adults speak differently to children than to other adults. We present results from a new word association study in which adult participants were instructed to produce either unconstrained or child-oriented responses to each cue, where cues included 672 nouns, verbs, adjectives, and other word forms from the McArthur-Bates Communicative Development Inventory (CDI; Fenson et al., 2006). Child-oriented responses consisted of higher frequency words with fewer letters, earlier ages of acquisition, and higher contextual diversity. Furthermore, the correlations among the responses generated for each pair of cues differed between unconstrained (adult-oriented) and child-oriented responses, suggesting that child-oriented associations imply different semantic structure. A comparison of growth models guided by a semantic network structure revealed that child-oriented associations are more predictive of early lexical growth. Additionally, relative to a growth model based on a corpus of naturalistic child-directed speech, the child-oriented associations explain added unique variance to lexical growth. Thus, these new child-oriented word association norms provide novel insight into the semantic context of young children and early lexical development.

Academic training increases grounding of scientific concepts in experiential brain systems

Scientific concepts typically transcendent our sensory experiences. Traditional approaches to science education therefore assume a shift towards amodal or verbal knowledge representations during academic training. Grounded cognition approaches, in contrast, predict a maintenance of grounding of the concepts in experiential brain networks or even an increase. To test these competing approaches, the present study investigated the semantic content of scientific psychological concepts and identified the corresponding neural circuits using functional magnetic resonance imaging (fMRI) in undergraduate psychology students (beginners) and in graduated psychologists (advanced learners). During fMRI scanning, participants were presented with words denoting scientific psychological concepts within a lexical decision task (e.g. "conditioning", "habituation"). The individual semantic property content of each concept was related to brain activity during abstract concept processing. In both beginners and advanced learners, visual and motor properties activated brain regions also involved in perception and action, while mental state properties increased activity in brain regions also recruited by emotional-social scene observation. Only in advanced learners, social constellation properties elicited brain activity overlapping with emotional-social scene observation. In line with grounded cognition approaches, the present results highlight the importance of experiential information for constituting the meaning of abstract scientific concepts during the course of academic training.

Distinct roles for the anterior temporal lobe and angular gyrus in the spatiotemporal cortical semantic network

Semantic knowledge is supported by numerous brain regions, but the spatiotemporal configuration of the network that links these areas remains an open question. The hub-and-spokes model posits that a central semantic hub coordinates this network. In this study, we explored distinct aspects that define a semantic hub, as reflected in the spatiotemporal modulation of neural activity and connectivity by semantic variables, from the earliest stages of semantic processing. We used source-reconstructed electro/magnetoencephalography, and investigated the concreteness contrast across three tasks. In a whole-cortex analysis, the left anterior temporal lobe (ATL) was the only area that showed modulation of evoked brain activity from 100 ms post-stimulus. Furthermore, using Dynamic Causal Modeling of the evoked responses, we investigated effective connectivity amongst the candidate semantic hub regions, that is, left ATL, supramarginal/angular gyrus (SMG/AG), middle temporal gyrus, and inferior frontal gyrus. We found that models with a single semantic hub showed the highest Bayesian evidence, and the hub region was found to change from ATL (within 250 ms) to SMG/AG (within 450 ms) over time. Our results support a single semantic hub view, with ATL showing sustained modulation of neural activity by semantics, and both ATL and AG underlying connectivity depending on the stage of semantic processing.

A test of indirect grounding of abstract concepts using multimodal distributional semantics

How are abstract concepts grounded in perceptual experiences for shaping human conceptual knowledge? Recent studies on abstract concepts emphasizing the role of language have argued that abstract concepts are grounded indirectly in perceptual experiences and language (or words) functions as a bridge between abstract concepts and perceptual experiences. However, this “indirect grounding” view remains largely speculative and has hardly been supported directly by empirical evidence. In this paper, therefore, we test the indirect grounding view by means of multimodal distributional semantics, in which the meaning of a word (i.e., a concept) is represented as the combination of textual and visual vectors. The newly devised multimodal distributional semantic model incorporates the indirect grounding view by computing the visual vector of an abstract word through the visual vectors of concrete words semantically related to that abstract word. An evaluation experiment is conducted in which conceptual representation is predicted from multimodal vectors using a multilayer feed-forward neural network. The analysis of prediction performance demonstrates that the indirect grounding model achieves significantly better performance in predicting human conceptual representation of abstract words than other models that mimic competing views on abstract concepts, especially than the direct grounding model in which the visual vectors of abstract words are computed directly from the images of abstract concepts. This result lends some plausibility to the indirect grounding view as a cognitive mechanism of grounding abstract concepts.

Direct Neural Evidence for the Contrastive Roles of the Complementary Learning Systems in Adult Acquisition of Native Vocabulary

The Complementary Learning Systems (CLS) theory provides a powerful framework for considering the acquisition, consolidation, and generalization of new knowledge. We tested this proposed neural division of labor in adults through an investigation of the consolidation and long-term retention of newly learned native vocabulary with post-learning functional neuroimaging. Newly learned items were compared with two conditions: 1) previously known items to highlight the similarities and differences with established vocabulary and 2) unknown/untrained items to provide a control for non-specific perceptual and motor speech output. Consistent with the CLS, retrieval of newly learned items was supported by a combination of regions associated with episodic memory (including left hippocampus) and the language-semantic areas that support established vocabulary (left inferior frontal gyrus and left anterior temporal lobe). Furthermore, there was a shifting division of labor across these two networks in line with the items' consolidation status; faster naming was associated with more activation of language-semantic areas and lesser activation of episodic memory regions. Hippocampal activity during naming predicted more than half the variation in naming retention 6 months later.

Neural sensitivity to semantic neighbors is stable across the adult lifespan

As we age, language reflects patterns of both stability and change. On the one hand, vocabulary and semantic abilities are largely stable across the adult lifespan, yet lexical retrieval is often slower and less successful (i.e., slower picture naming times, increased tip of the tongue incidents). Although the behavioral bases of these effects have been well established, less is known about the brain regions that support these age-related differences. We used functional Magnetic Resonance Imaging (fMRI) to examine the neural basis of picture naming. Specifically, we were interested in whether older adults would be equally sensitive to semantic characteristics, specifically the number of semantic near neighbors. Near neighbors, defined here as items with a high degree of semantic feature overlap, were of interest as these are thought to elicit competition among potential candidates and increase naming difficulty. Consistent with prior reports, pictures with more semantic near neighbors were named more slowly and less accurately for all adults. Additionally, this interference for naming times was larger as age increased, starting around 30 years old. In contrast to the age-related behavioral slowing, the neural basis of these effects was stable across adulthood. Across all adults, a number of language-relevant regions including left posterior middle temporal gyrus and left inferior frontal gyrus, pars triangularis were sensitive to the number of near neighbors. Our results suggest that although middle-aged and older adults' picture naming is more slowed by increased semantic competition, the brain regions supporting semantic processes remain stable across the adult lifespan.

Motivated semantic control: Exploring the effects of extrinsic reward and self-reference on semantic retrieval in semantic aphasia

Recent insights show that increased motivation can benefit executive control, but this effect has not been explored in relation to semantic cognition. Patients with deficits of controlled semantic retrieval in the context of semantic aphasia (SA) after stroke may benefit from this approach since 'semantic control' is considered an executive process. Deficits in this domain are partially distinct from the domain-general deficits of cognitive control. We assessed the effect of both extrinsic and intrinsic motivation in healthy controls and SA patients. Experiment 1 manipulated extrinsic reward using high or low levels of points for correct responses during a semantic association task. Experiment 2 manipulated the intrinsic value of items using self-reference, allocating pictures of items to the participant ('self') or researcher ('other') in a shopping game before participants retrieved their semantic associations. These experiments revealed that patients, but not controls, showed better performance when given an extrinsic reward, consistent with the view that increased external motivation may help ameliorate patients' semantic control deficits. However, while self-reference was associated with better episodic memory, there was no effect on semantic retrieval. We conclude that semantic control deficits can be reduced when extrinsic rewards are anticipated; this enhanced motivational state is expected to support proactive control, for example, through the maintenance of task representations. It may be possible to harness this modulatory impact of reward to combat the control demands of semantic tasks in SA patients.

What determines cognitive estimation ability? Changing contributions of semantic and executive domains as a function of age

The Cognitive Estimation Test (CET) is commonly used in neuropsychological assessment. It is typically assumed to load on executive functions, although research has shown that CET performance also depends on access to semantic knowledge. It is unknown whether these contributions vary with age. It is important to examine this question as these abilities have divergent life course trajectories: executive functions tend to decline as people age but semantic knowledge continues to accrue. In addition, previous research has not examined potential contributions to CET performance from semantic control abilities, that is cognitive control processes involved specifically in the retrieval and use of semantic information. To address these questions, we investigated cognitive predictors of CET performance in healthy young and older adults. We found that better executive function was associated with more accurate estimation in both age groups. However, the effect of semantic knowledge on CET performance was significantly larger in older people, having no predictive power in the younger group. The ability to detect weak semantic associations, which is thought to index controlled search and retrieval of semantic information, also had divergent effects on CET performance in the two age groups. Our results provide empirical support for the idea that older people are more reliant on semantic knowledge when estimating quantities, which may explain why age‐related decline in CET scores is not typically found. We conclude that deficits on the CET may be indicative either of semantic or executive impairments, particularly in older age groups.

The functional dissociation of posterior parietal regions during multimodal memory formation

The incidental acquisition of multimodal associations is a key memory function for everyday life. While the posterior parietal cortex has been frequently shown to be involved for these memory functions, ventral and dorsal regions revealed differences in their functional recruitment and the precise difference in multimodal memory processing with respect to the associative process has not been differentiated. Using an incidental multimodal learning task, we isolated the associative process during multimodal learning and recollection. The result of the present functional magnetic resonance imaging (fMRI) study demonstrated that during both learning and recollection a clear functional differentiation between ventral and dorsal posterior parietal regions was found and can be related directly to the associative process. The recruitment of a ventral region, the angular gyrus, was specific for learning and recollection of multimodal associations. In contrast, a dorsal region, the superior parietal lobule, could be attributed to memory guided attentional processing. Independent of the memory stage, we assumed a general role for the angular gyrus in the generation of associative representations and updating of fixed association, episodic memory.

K-clique percolation in free association networks and the possible mechanism behind the [Formula: see text] law

It is important to reveal the mechanisms of propagation in different cognitive networks. In this study, we discuss the k-clique percolation phenomenon as related to the free association networks including the English Small World of Words project (SWOW-EN). We compared different semantic networks and networks of free associations for various languages. Surprisingly, k-clique percolation for all [Formula: see text] 6-7 is possible on free association networks of different languages. Our analysis suggests new universality patterns for a community organization of free association networks. We conjecture that our result can provide a qualitative explanation of Miller's [Formula: see text] rule for the capacity limit of working memory. A new model of network evolution extending the preferential attachment is suggested, providing the observed value of [Formula: see text].

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.

Decoding the information structure underlying the neural representation of concepts

The ability to identify individual objects or events as members of a kind (e.g., “knife,” “dog,” or “party”) is a fundamental aspect of human cognition. It allows us to quickly access a wealth of information pertaining to a newly encountered object or event and use it to guide our behavior. How is this information represented in the brain? We used functional MRI to analyze patterns of brain activity corresponding to hundreds of familiar concepts and quantitatively characterized the informational structure of these patterns. Our results indicate that conceptual knowledge is stored as patterns of neural activity that encode sensory-motor and affective information about each concept, contrary to the long-held idea that concept representations are independent of sensory-motor experience.

The nature of the representational code underlying conceptual knowledge remains a major unsolved problem in cognitive neuroscience. We assessed the extent to which different representational systems contribute to the instantiation of lexical concepts in high-level, heteromodal cortical areas previously associated with semantic cognition. We found that lexical semantic information can be reliably decoded from a wide range of heteromodal cortical areas in the frontal, parietal, and temporal cortex. In most of these areas, we found a striking advantage for experience-based representational structures (i.e., encoding information about sensory-motor, affective, and other features of phenomenal experience), with little evidence for independent taxonomic or distributional organization. These results were found independently for object and event concepts. Our findings indicate that concept representations in the heteromodal cortex are based, at least in part, on experiential information. They also reveal that, in most heteromodal areas, event concepts have more heterogeneous representations (i.e., they are more easily decodable) than object concepts and that other areas beyond the traditional “semantic hubs” contribute to semantic cognition, particularly the posterior cingulate gyrus and the precuneus.

Validated measures of semantic knowledge and semantic control: normative data from young and older adults for more than 300 semantic judgements

Recent studies suggest that knowledge representations and control processes are the two key components underpinning semantic cognition, and are also crucial indicators of the shifting cognitive architecture of semantics in later life. Although there are many standardized assessments that provide measures of the quantity of semantic knowledge participants possess, normative data for tasks that probe semantic control processes are not yet available. Here, we present normative data from more than 200 young and older participants on a large set of stimuli in two semantic tasks, which probe controlled semantic processing (feature-matching task) and semantic knowledge (synonym judgement task). We verify the validity of our norms by replicating established age- and psycholinguistic-property-related effects on semantic cognition. Specifically, we find that older people have more detailed semantic knowledge than young people but have less effective semantic control processes. We also obtain expected effects of word frequency and inter-item competition on performance. Parametrically varied difficulty levels are defined for half of the stimuli based on participants' behavioural performance, allowing future studies to produce customized sets of experimental stimuli based on our norms. We provide all stimuli, data and code used for analysis, in the hope that they are useful to other researchers.

Similar Neural Networks Respond to Coherence during Comprehension and Production of Discourse

When comprehending discourse, listeners engage default-mode regions associated with integrative semantic processing to construct a situation model of its content. We investigated how similar networks are engaged when we produce, as well as comprehend, discourse. During functional magnetic resonance imaging, participants spoke about a series of specific topics and listened to discourse on other topics. We tested how activation was predicted by natural fluctuations in the global coherence of the discourse, that is, the degree to which utterances conformed to the expected topic. The neural correlates of coherence were similar across speaking and listening, particularly in default-mode regions. This network showed greater activation when less coherent speech was heard or produced, reflecting updating of mental representations when discourse did not conform to the expected topic. In contrast, regions that exert control over semantic activation showed task-specific effects, correlating negatively with coherence during listening but not during production. Participants who showed greater activation in left inferior prefrontal cortex also produced more coherent discourse, suggesting a specific role for this region in goal-directed regulation of speech content. Results suggest strong correspondence of discourse representations during speaking and listening. However, they indicate that the semantic control network plays different roles in comprehension and production.

Different types of semantic interference, same lapses of attention: Evidence from Stroop tasks

This research investigated the possibility that semantic control mechanisms are recruited only when the interfering semantic information does not overlap with task-relevant semantic dimensions. To reach this goal, we investigated two semantic types of Stroop interference-the semantic and the taboo Stroop effects-and used delta-plots to investigate the role of attentional and semantic control in these two interference phenomena. The semantic Stroop effect, where interference stems from the task-relevant color-related information, was absent in faster responses, whereas it steeply increased in the slowest ones. Contrary to our predictions, the same pattern was detected even for the taboo Stroop interference, with no trace of selective suppression of the interfering semantic connotation, despite its dissociation from any task-relevant semantic dimension. Further, there was a significant correlation between the increase of the two effects in the slowest responses, pointing towards a common underlying processing dynamic. We identified such common background with lapses of executive attention in maintaining task goals and schema, which in turn make the participants performance more prone to interference phenomena. Finally, the absence of any interference effects in the fastest responses suggests that an effective filtering of the distracting word stimuli can be implemented in the context of Stroop paradigms.

Latent Semantic Structure of the WMS-III Verbal Paired-Associates

OBJECTIVE

To investigate the factor structure of the verbal paired-associates (VPA) subtest in the WMS-III using a theoretically driven model of semantic processing previously found to be well-fitting for the WMS-IV version of the test.

METHOD

Archival data were used from 267 heterogeneous neurosciences patients and 223 seizure disorder patients who completed the WMS-III as part of a standard neuropsychological evaluation. Confirmatory factor analysis was used to test theoretically driven models for VPA based on principles of semantic processing. Four nested models of different complexities were examined and compared for goodness-of-fit using chi-squared difference testing. Measurement invariance testing was conducted across heterogeneous neuroscience and seizure disorder samples to test generality of the factor model.

RESULTS

After removing items with limited variability (very easy or very hard; 12 of 40 items), a four-factor model was found to be best-fitting in the present patient samples. The four factors were "recreational", "functional", "material", and "symbolic", each representing semantic knowledge associated with the function of the target word referent. This model subsequently met the criteria for the strict measurement invariance, showing good overall fit when factor loadings, thresholds, and residuals were held to equality across samples.

CONCLUSIONS

The results of this study provide further evidence that "arbitrary" associations between word pairs in VPA items have an underlying semantic structure, challenging the idea that unrelated hard-pairs are semantic-free. These results suggest that a semantic-structure model may be implemented as an alternative scoring in future editions of the WMS to facilitate interpretation.

The limits of automatic sensorimotor processing during word processing: investigations with repeated linguistic experience, memory consolidation during sleep, and rich linguistic learning contexts

While a number of studies have repeatedly demonstrated an automatic activation of sensorimotor experience during language processing in the form of action-congruency effects, as predicted by theories of grounded cognition, more recent research has not found these effects for words that were just learned from linguistic input alone, without sensorimotor experience with their referents. In the present study, we investigate whether this absence of effects can be attributed to a lack of repeated experience and consolidation of the associations between words and sensorimotor experience in memory. To address these issues, we conducted four experiments in which (1 and 2) participants engaged in two separate learning phases in which they learned novel words from language alone, with an intervening period of memory-consolidating sleep, and (3 and 4) we employed familiar words whose referents speakers have no direct experience with (such as plankton). However, we again did not observe action-congruency effects in subsequent test phases in any of the experiments. This indicates that direct sensorimotor experience with word referents is a necessary requirement for automatic sensorimotor activation during word processing.

Neuro-cognitive development of semantic and syntactic bootstrapping in 6- to 7.5-year-old children

The present study examined the longitudinal relations of brain and behavior from ages 6-7.5 years old to test the bootstrapping account of language development. Prior work suggests that children's vocabulary development is foundational for acquiring grammar (e.g., semantic bootstrapping) and that children rely on the syntactic context of sentences to learn the meaning of new words (e.g., syntactic bootstrapping). Yet, little is known about the dynamics underlying semantic and syntactic development as children enter elementary school. In a series of preregistered and exploratory analyses, we tested how semantic and syntactic behavioral skills may influence the development of brain regions implicated in these processes, i.e. left posterior middle temporal gyrus (pMTG) and inferior frontal gyrus (pars opercularis, IFGop), respectively. Vice-a-versa, we tested how these brain regions may influence the development of children's semantic and syntactic behavioral skills. We assessed semantic (N = 26) and syntactic (N = 30) processes behaviorally and in the brain when children were ages 5.5-6.5 years old (Time 1) and again at 7-8 years old (Time 2). All brain-behavior analyses controlled for T1 autoregressive effects and phonological memory. Exploratory hierarchical regression analyses suggested bi-directional influences, but with greater support for syntactic bootstrapping. Across the analyses, there was a small to medium effect of change in variance in models where semantics predicted syntax. Conversely, there was medium to large change in variance in models where syntax predicted semantics. In line with prior literature, results suggest a close relationship between lexical and grammatical development in children ages 6-7.5 years old. However, there was more robust evidence for syntactic bootstrapping, suggesting that acquisition of phrase structure in school age children may allow for more effective learning of word meanings. This complements prior behavioral studies and suggests a potential shift in the early reliance on semantics to later reliance on syntax in development.

Transcranial Direct Current Stimulation Over the Right Anterior Temporal Lobe Does Not Modulate False Recognition

Non-invasive transcranial direct current stimulation (tDCS) over the left anterior temporal lobe (ATL) has been shown to cause a reduction in the rate of false memories with semantically related words. Such a reduction seems to be specific to false memories induced by the study of associative lists, but is not observed when the studied lists are categorical in nature. These findings are interpreted as evidence that the left ATL functions as an integration hub that is crucial for the binding of semantic information into coherent representations of concepts. In order to investigate whether the right ATL might also contribute to semantic integration in the processing of verbal associative material, a follow-up tDCS study was conducted with the stimulation at study lateralized on the right ATL. A sample of 75 undergraduate students participated in an experiment in which they studied 8 associative lists and 8 categorical lists. One third of the participants studied all their word lists under anodal stimulation, another third studied under cathodal stimulation and the other third under sham stimulation. Results showed that stimulation of the right ATL by tDCS does not modulate false recognition for either association-related critical words or category-related critical words. These results provide preliminary support to views positing asymmetric connectivity between the anterior temporal lobes and the semantic representational network, and provide evidence for understanding bilateral brain dynamics and the nature of semantically induced memory distortions.

Stimulus-independent neural coding of event semantics: Evidence from cross-sentence fMRI decoding

Multivariate neuroimaging studies indicate that the brain represents word and object concepts in a format that readily generalises across stimuli. Here we investigated whether this was true for neural representations of simple events described using sentences. Participants viewed sentences describing four events in different ways. Multivariate classifiers were trained to discriminate the four events using a subset of sentences, allowing us to test generalisation to novel sentences. We found that neural patterns in a left-lateralised network of frontal, temporal and parietal regions discriminated events in a way that generalised successfully over changes in the syntactic and lexical properties of the sentences used to describe them. In contrast, decoding in visual areas was sentence-specific and failed to generalise to novel sentences. In the reverse analysis, we tested for decoding of syntactic and lexical structure, independent of the event being described. Regions displaying this coding were limited and largely fell outside the canonical semantic network. Our results indicate that a distributed neural network represents the meaning of event sentences in a way that is robust to changes in their structure and form. They suggest that the semantic system disregards the surface properties of stimuli in order to represent their underlying conceptual significance.

Disentangling Semantic Composition and Semantic Association in the Left Temporal Lobe

Although composing two words into a complex representation (e.g., "coffee cake") is conceptually different from forming associations between a pair of words (e.g., "coffee, cake"), the brain regions supporting semantic composition have also been implicated for associative encoding. Here, we adopted a two-word magnetoencephalography (MEG) paradigm which varies compositionality ("French/Korean cheese" vs "France/Korea cheese") and strength of association ("France/French cheese" vs "Korea/Korean cheese") between the two words. We collected MEG data while 42 English speakers (24 females) viewed the two words successively in the scanner, and we applied both univariate regression analyses and multivariate pattern classification to the source estimates of the two words. We show that the left anterior temporal lobe (LATL) and left middle temporal lobe (LMTL) are distinctively modulated by semantic composition and semantic association. Specifically, the LATL is mostly sensitive to high-association compositional phrases, while the LMTL responds more to low-association compositional phrases. Pattern-based directed connectivity analyses further revealed a continuous information flow from the anterior to the middle temporal region, suggesting that the integration of adjective and noun properties originated earlier in the LATL is consistently delivered to the LMTL when the complex meaning is newly encountered. Taken together, our findings shed light into a functional dissociation within the left temporal lobe for compositional and distributional semantic processing.SIGNIFICANCE STATEMENT Prior studies on semantic composition and associative encoding have been conducted independently within the subfields of language and memory, and they typically adopt similar two-word experimental paradigms. However, no direct comparison has been made on the neural substrates of the two processes. The current study relates the two streams of literature, and appeals to audiences in both subfields within cognitive neuroscience. Disentangling the neural computations for semantic composition and association also offers insight into modeling compositional and distributional semantics, which has been the subject of much discussion in natural language processing and cognitive science.

Emotional Valence Precedes Semantic Maturation of Words: A Longitudinal Computational Study of Early Verbal Emotional Anchoring

We present a longitudinal computational study on the connection between emotional and amodal word representations from a developmental perspective. In this study, children's and adult word representations were generated using the latent semantic analysis (LSA) vector space model and Word Maturity methodology. Some children's word representations were used to set a mapping function between amodal and emotional word representations with a neural network model using ratings from 9-year-old children. The neural network was trained and validated in the child semantic space. Then, the resulting neural network was tested with adult word representations using ratings from an adult data set. Samples of 1210 and 5315 words were used in the child and the adult semantic spaces, respectively. Results suggested that the emotional valence of words can be predicted from amodal vector representations even at the child stage, and accurate emotional propagation was found in the adult word vector representations. In this way, different propagative processes were observed in the adult semantic space. These findings highlight a potential mechanism for early verbal emotional anchoring. Moreover, different multiple linear regression and mixed-effect models revealed moderation effects for the performance of the longitudinal computational model. First, words with early maturation and subsequent semantic definition promoted emotional propagation. Second, an interaction effect between age of acquisition and abstractness was found to explain model performance. The theoretical and methodological implications are discussed.

Prepotent task-irrelevant semantic information is dampened by domain-specific control mechanisms during visual word recognition

We investigated whether semantic interference occurring during visual word recognition is resolved using domain-general control mechanisms or using more specific mechanisms related to semantic processing. We asked participants to perform a lexical decision task with taboo stimuli, which induce semantic interference, as well as a semantic Stroop task and a Simon task, intended as benchmarks of linguistic-semantic and non-linguistic interference, respectively. Using a correlational approach, we investigated potential similarities between effects produced in the three tasks, both at the level of overall means and as a function of response speed (delta-plot analysis). Correlations selectively surfaced between the lexical decision and the semantic Stroop task. These findings suggest that, during visual word recognition, semantic interference is controlled by semantic-specific mechanisms, which intervene to face prepotent but task-irrelevant semantic information interfering with the accomplishment of the task's goal.

Incidental Verbal Semantic Processing Recruits the Fronto-temporal Semantic Control Network

The frontoparietal semantic network, encompassing the inferior frontal gyrus and the posterior middle temporal cortex, is considered to be involved in semantic control processes. The explicit versus implicit nature of these control processes remains however poorly understood. The present study examined this question by assessing regional brain responses to the semantic attributes of an unattended stream of auditory words while participants' top-down attentional control processes were absorbed by a demanding visual search task. Response selectivity to semantic aspects of verbal stimuli was assessed via a functional magnetic resonance imaging response adaptation paradigm. We observed that implicit semantic processing of an unattended verbal stream recruited not only unimodal and amodal cortices in posterior supporting semantic knowledge areas, but also inferior frontal and posterior middle temporal areas considered to be part of the semantic control network. These results indicate that frontotemporal semantic networks support incidental semantic (control) processes.