Converging evidence from fMRI and aphasia that the left temporoparietal cortex has an essential role in representing abstract semantic knowledge

Functional magnetic resonance imaging of taxonomic and thematic processing of abstract and concrete word pairs

This study used fMRI to examine the effect that the abstract-concrete dimension may have on the thematic-taxonomic distinction. The dual hub theory (DHT) posits that left angular gyrus supports thematic relationships and left temporal pole supports taxonomic relationships; however, the DHT is largely based on evidence from concrete words. It is important that theories of semantic organization include abstract words as they are ubiquitous in everyday discourse (Lupyan & Winter, Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 2018, 373, 20170137). Additionally, there is reason to believe that there may bean interaction between the abstract-concrete dimension and the thematic-taxonomic distinction, based on the different representational frameworks (DRF) hypothesis, which posits that abstract concepts are primarily organized by association/theme, and that concrete concepts are primarily organized by similarity/taxonomy. However, there appears to be a mismatch among the DHT, predictions of the DRF hypothesis for brain activation, and existing neuroimaging data for the concreteness effect. Thus, we sought to include abstract words in a test of the DHT and determine whether any interactions exist between the abstract-concrete dimension and the thematic-taxonomic distinction. While we replicated the localization of abstract and concrete word processing, we did not extend the DHT to include abstract words, nor did we find an interaction that would support the DRF hypothesis. Rather, our results align more closely with the hub-and-spoke model (Patterson et al., Nature Reviews Neuroscience, 2007, 8, 976).

Representational similarity analysis of self- versus other-processing: Effect of trait aggressiveness

In this study, using the self/other adjective judgment task, we aimed to explore how people perceive themselves in comparison to various other people, including friends, strangers, and those they dislike. Next, using representational similarity analysis, we sought to elucidate how these perceptual similarities and differences are represented in brain activity and how aggressiveness is related to these representations. Behavioral ratings show that, on average, people tend to consider themselves more like their friends than neutral strangers, and least like people they dislike. This pattern of similarity is positively correlated with neural representation in social and cognitive circuits of the brain and negatively correlated with neural representation in emotional centers that may represent emotional arousal associated with various social objects. Aggressiveness seems to predispose a person to a pattern of behavior that is the opposite of the average pattern, that is, a tendency to think of oneself as less like one's friends and more like one's enemies. This corresponds to an increase in the similarity of the behavioral representation with the representation in the emotional centers and a decrease in its similarity with the representation in the social and cognitive centers. This can be seen as evidence that in individuals prone to aggression, behavior in the social environment may depend to a greater extent on the representation of social objects in the emotional rather than social and cognitive brain circuits.

Taxonomic and thematic relations rely on different types of semantic features: Evidence from an fMRI meta-analysis and a semantic priming study

Taxonomic and thematic relations are major components of semantic representation but their neurocognitive underpinnings are still debated. We hypothesised that taxonomic relations preferentially activate parts of anterior temporal lobe (ATL) because they rely more on colour and shape features, while thematic relations preferentially activate temporoparietal cortex (TPC) because they rely more on action and location knowledge. We first conducted activation likelihood estimation (ALE) meta-analysis to assess evidence for neural specialisation in the existing fMRI literature (Study 1), then used a primed semantic judgement task to examine if the two relations are primed by different feature types (Study 2). We find that taxonomic relations show minimal feature-based specialisation but preferentially activate the lingual gyrus. Thematic relations are more dependent on action and location features and preferentially engage TPC. The meta-analysis also showed that lateral ATL is preferentially engaged by Thematic relations, which may reflect their greater reliance on verbal associations.

Recollection and prior knowledge recruit the left angular gyrus during recognition

The human angular gyrus (AG) is implicated in recollection, or the ability to retrieve detailed memory content from a specific episode. A separate line of research examining the neural bases of more general mnemonic representations, extracted over multiple episodes, also highlights the AG as a core region of interest. To reconcile these separate views of AG function, the present fMRI experiment used a Remember-Know paradigm with famous (prior knowledge) and non-famous (no prior knowledge) faces to test whether AG activity could be modulated by both task-specific recollection and general prior knowledge within the same individuals. Increased BOLD activity in the left AG was observed during both recollection in the absence of prior knowledge (recollected > non-recollected or correctly rejected non-famous faces) and when prior knowledge was accessed in the absence of experiment-specific recollection (famous > non-famous correct rejections). This pattern was most prominent for the left AG as compared to the broader inferior parietal lobe. Recollection-related responses in the left AG increased with encoding duration and prior knowledge, despite prior knowledge being incidental to the recognition decision. Overall, the left AG appears sensitive to both task-specific recollection and the incidental access of general prior knowledge, thus broadening our notions of the kinds of mnemonic representations that drive activity in this region.

Algebra dissociates from arithmetic in the brain semantic network

Background

Mathematical expressions mainly include arithmetic (such as 8 − (1 + 3)) and algebra (such as a − (b + c)). Previous studies have shown that both algebraic processing and arithmetic involved the bilateral parietal brain regions. Although previous studies have revealed that algebra was dissociated from arithmetic, the neural bases of the dissociation between algebraic processing and arithmetic is still unclear. The present study uses functional magnetic resonance imaging (fMRI) to identify the specific brain networks for algebraic and arithmetic processing.

Methods

Using fMRI, this study scanned 30 undergraduates and directly compared the brain activation during algebra and arithmetic. Brain activations, single-trial (item-wise) interindividual correlation and mean-trial interindividual correlation related to algebra processing were compared with those related to arithmetic. The functional connectivity was analyzed by a seed-based region of interest (ROI)-to-ROI analysis.

Results

Brain activation analyses showed that algebra elicited greater activation in the angular gyrus and arithmetic elicited greater activation in the bilateral supplementary motor area, left insula, and left inferior parietal lobule. Interindividual single-trial brain-behavior correlation revealed significant brain-behavior correlations in the semantic network, including the middle temporal gyri, inferior frontal gyri, dorsomedial prefrontal cortices, and left angular gyrus, for algebra. For arithmetic, the significant brain-behavior correlations were located in the phonological network, including the precentral gyrus and supplementary motor area, and in the visuospatial network, including the bilateral superior parietal lobules. For algebra, significant positive functional connectivity was observed between the visuospatial network and semantic network, whereas for arithmetic, significant positive functional connectivity was observed only between the visuospatial network and phonological network.

Conclusion

These findings suggest that algebra relies on the semantic network and conversely, arithmetic relies on the phonological and visuospatial networks.

Acquisition of concrete and abstract words is modulated by tDCS of Wernicke's area

Previous behavioural and neuroimaging research suggested distinct cortical systems involved in processing abstract and concrete semantics; however, there is a dearth of causal evidence to support this. To address this, we applied anodal, cathodal, or sham (placebo) tDCS over Wernicke’s area before a session of contextual learning of novel concrete and abstract words (n = 10 each), presented five times in short stories. Learning effects were assessed at lexical and semantic levels immediately after the training and, to attest any consolidation effects of overnight sleep, on the next day. We observed successful learning of all items immediately after the session, with decreased performance in Day 2 assessment. Importantly, the results differed between stimulation conditions and tasks. Whereas the accuracy of semantic judgement for abstract words was significantly lower in the sham and anodal groups on Day 2 vs. Day 1, no significant performance drop was observed in the cathodal group. Similarly, the cathodal group showed no significant overnight performance reduction in the free recall task for either of the stimuli, unlike the other two groups. Furthermore, between-group analysis showed an overall better performance of both tDCS groups over the sham group, particularly expressed for abstract semantics and cathodal stimulation. In sum, the results suggest overlapping but diverging brain mechanisms for concrete and abstract semantics and indicate a larger degree of involvement of core language areas in storing abstract knowledge. Furthermore, they demonstrate a possiblity to improve learning outcomes using neuromodulatory techniques.

A lesion and connectivity-based hierarchical model of chronic aphasia recovery dissociates patients and healthy controls

Traditional models of left hemisphere stroke recovery propose that reactivation of remaining ipsilesional tissue is optimal for language processing whereas reliance on contralesional right hemisphere homologues is less beneficial or possibly maladaptive in the chronic recovery stage. However, neuroimaging evidence for this proposal is mixed. This study aimed to elucidate patterns of effective connectivity in patients with chronic aphasia in light of healthy control connectivity patterns and in relation to damaged tissue within left hemisphere regions of interest and according to performance on a semantic decision task. Using fMRI and dynamic causal modeling, biologically-plausible models within four model families were created to correspond to potential neural recovery patterns, including Family A: Left-lateralized connectivity (i.e., no/minimal damage), Family B: Bilateral anterior-weighted connectivity (i.e., posterior damage), Family C: Bilateral posterior-weighted connectivity (i.e., anterior damage) and Family D: Right-lateralized connectivity (i.e., extensive damage). Controls exhibited a strong preference for left-lateralized network models (Family A) whereas patients demonstrated a split preference for Families A and C. At the level of connections, controls exhibited stronger left intrahemispheric task-modulated connections than did patients. Within the patient group, damage to left superior frontal structures resulted in greater right intrahemispheric connectivity whereas damage to left ventral structures resulted in heightened modulation of left frontal regions. Lesion metrics best predicted accuracy on the fMRI task and aphasia severity whereas left intrahemispheric connectivity predicted fMRI task reaction times. These results are discussed within the context of the hierarchical recovery model of chronic aphasia.

•

The semantic network in neurologically-intact, healthy controls was characterized by left-lateralized connectivity.

•

Patient connectivity was split between left-lateralized and bilateral, posterior-weighted (i.e., anterior damage) models.

•

Controls solely recruited LITG-driven connections whereas patients recruited a distributed network of connections.

•

Within the patient group, intra- and inter-hemispheric connections were related to lesion site and/or size. Lesion size predicted aphasia severity and fMRI task accuracy, and effective connectivity predicted task reaction times.

Statistical and methodological problems with concreteness and other semantic variables: A list memory experiment case study

The purpose of this article is to highlight problems with a range of semantic psycholinguistic variables (concreteness, imageability, individual modality norms, and emotional valence) and to provide a way of avoiding these problems. Focusing on concreteness, I show that for a large class of words in the Brysbaert, Warriner, and Kuperman (Behavior Research Methods 46: 904–911, 2013) concreteness norms, the mean concreteness values do not reflect the judgments that actual participants made. This problem applies to nearly every word in the middle of the concreteness scale. Using list memory experiments as a case study, I show that many of the “abstract” stimuli in concreteness experiments are not unequivocally abstract. Instead, they are simply those words about which participants tend to disagree. I report three replications of list memory experiments in which the contrast between concrete and abstract stimuli was maximized, so that the mean concreteness values were accurate reflections of participants’ judgments. The first two experiments did not produce a concreteness effect. After I introduced an additional control, the third experiment did produce a concreteness effect. The article closes with a discussion of the implications of these results, as well as a consideration of variables other than concreteness. The sensorimotor experience variables (imageability and individual modality norms) show the same distribution as concreteness. The distribution of emotional valence scores is healthier, but variability in ratings takes on a special significance for this measure because of how the scale is constructed. I recommend that researchers using these variables keep the standard deviations of the ratings of their stimuli as low as possible.

Brain networks for engaging oneself in positive-social emotion regulation

Positive emotions facilitate cognitive performance, and their absence is associated with burdening psychiatric disorders. However, the brain networks regulating positive emotions are not well understood, especially with regard to engaging oneself in positive-social situations. Here we report convergent evidence from a multimodal approach that includes functional magnetic resonance imaging (fMRI) brain activations, meta-analytic functional characterization, Bayesian model-driven analysis of effective brain connectivity, and personality questionnaires to identify the brain networks mediating the cognitive up-regulation of positive-social emotions. Our comprehensive approach revealed that engaging in positive-social emotion regulation with a self-referential first-person perspective is characterized by dynamic interactions between functionally specialized prefrontal cortex (PFC) areas, the temporoparietal junction (TPJ) and the amygdala. Increased top-down connectivity from the superior frontal gyrus (SFG) controls affective valuation in the ventromedial and dorsomedial PFC, self-referential processes in the TPJ, and modulate emotional responses in the amygdala via the ventromedial PFC. Understanding the brain networks engaged in the regulation of positive-social emotions that involve a first-person perspective is important as they are known to constitute an effective strategy in therapeutic settings.

Neural Representations of Belief Concepts: A Representational Similarity Approach to Social Semantics

The present experiment identified neural regions that represent a class of concepts that are independent of perceptual or sensory attributes. During functional magnetic resonance imaging scanning, participants viewed names of social groups (e.g. Atheists, Evangelicals, and Economists) and performed a one-back similarity judgment according to 1 of 2 dimensions of belief attributes: political orientation (Liberal to Conservative) or spiritualism (Spiritualist to Materialist). By generalizing across a wide variety of social groups that possess these beliefs, these attribute concepts did not coincide with any specific sensory quality, allowing us to target conceptual, rather than perceptual, representations. Multi-voxel pattern searchlight analysis was used to identify regions in which activation patterns distinguished the 2 ends of both dimensions: Conservative from Liberal social groups when participants focused on the political orientation dimension, and spiritual from Materialist groups when participants focused on the spiritualism dimension. A cluster in right precuneus exhibited such a pattern, indicating that it carries information about belief-attribute concepts and forms part of semantic memory—perhaps a component particularly concerned with psychological traits. This region did not overlap with the theory of mind network, which engaged nearby, but distinct, parts of precuneus. These findings have implications for the neural organization of conceptual knowledge, especially the understanding of social groups.

Linking left hemispheric tissue preservation to fMRI language task activation in chronic stroke patients

The preservation of near-typical function in distributed brain networks is associated with less severe deficits in chronic stroke patients. However, it remains unclear how task-evoked responses in networks that support complex cognitive functions such as semantic processing relate to the post-stroke brain anatomy. Here, we used recently developed methods for the analysis of multimodal MRI data to investigate the relationship between regional tissue concentration and functional MRI activation evoked during auditory semantic decisions in a sample of 43 chronic left hemispheric stroke patients and 43 age, handedness, and sex-matched controls. Our analyses revealed that closer-to-normal levels of tissue concentration in left temporo-parietal cortex and the underlying white matter correlated with the level of task-evoked activation in distributed regions associated with the semantic network. This association was not attributable to the effects of left hemispheric lesion or brain volumes, and similar results were obtained when using explicit lesion data. Left temporo-parietal tissue concentration and the associated task-evoked activations predicted patient performance on the in-scanner task, and also predicted patient performance on out-of-scanner naming and verbal fluency tasks. Exploratory analyses using the average HCP-842 tractography dataset revealed the presence of fronto-temporal, fronto-parietal, and temporo-parietal semantic network connections in the locations where tissue concentration was found to correlate with task-evoked activation in the semantic network. In summary, our results link the preservation of left posterior temporo-parietal structures with the preservation of task-evoked semantic network function in chronic left hemispheric stroke patients. Speculatively, this relationship may reflect the status of posterior temporo-parietal areas as cortical and white matter convergence zones that support coordinated processing in the distributed semantic network. Damage to these regions may contribute to atypical task-evoked responses during semantic processing in chronic stroke patients.

Comprehension of concrete and abstract words in semantic variant primary progressive aphasia and Alzheimer's disease: A behavioral and neuroimaging study

The aim of this study was to investigate the comprehension of concrete, abstract and abstract emotional words in semantic variant primary progressive aphasia (svPPA), Alzheimer's disease (AD), and healthy elderly adults (HE) Three groups of participants (9 svPPA, 12 AD, 11 HE) underwent a general neuropsychological assessment, a similarity judgment task, and structural brain MRI. The three types of words were processed similarly in the group of AD participants. In contrast, patients in the svPPA group were significantly more impaired at processing concrete words than abstract words, while comprehension of abstract emotional words was in between. VBM analyses showed that comprehension of concrete words relative to abstract words was significantly correlated with atrophy in the left anterior temporal lobe. These results support the view that concrete words are disproportionately impaired in svPPA, and that concrete and abstract words may rely upon partly dissociable brain regions.

Taxonomic and thematic semantic systems

Object concepts are critical for nearly all aspects of human cognition, from perception tasks like object recognition, to understanding and producing language, to making meaningful actions. Concepts can have 2 very different kinds of relations: similarity relations based on shared features (e.g., dog-bear), which are called "taxonomic" relations, and contiguity relations based on co-occurrence in events or scenarios (e.g., dog-leash), which are called "thematic" relations. Here, we report a systematic review of experimental psychology and cognitive neuroscience evidence of this distinction in the structure of semantic memory. We propose 2 principles that may drive the development of distinct taxonomic and thematic semantic systems: differences between which features determine taxonomic versus thematic relations, and differences in the processing required to extract taxonomic versus thematic relations. This review brings together distinct threads of behavioral, computational, and neuroscience research on semantic memory in support of a functional and neural dissociation, and defines a framework for future studies of semantic memory. (PsycINFO Database Record

Damage to white matter bottlenecks contributes to language impairments after left hemispheric stroke

Damage to the white matter underlying the left posterior temporal lobe leads to deficits in multiple language functions. The posterior temporal white matter may correspond to a bottleneck where both dorsal and ventral language pathways are vulnerable to simultaneous damage. Damage to a second putative white matter bottleneck in the left deep prefrontal white matter involving projections associated with ventral language pathways and thalamo-cortical projections has recently been proposed as a source of semantic deficits after stroke. Here, we first used white matter atlases to identify the previously described white matter bottlenecks in the posterior temporal and deep prefrontal white matter. We then assessed the effects of damage to each region on measures of verbal fluency, picture naming, and auditory semantic decision-making in 43 chronic left hemispheric stroke patients. Damage to the posterior temporal bottleneck predicted deficits on all tasks, while damage to the anterior bottleneck only significantly predicted deficits in verbal fluency. Importantly, the effects of damage to the bottleneck regions were not attributable to lesion volume, lesion loads on the tracts traversing the bottlenecks, or damage to nearby cortical language areas. Multivariate lesion-symptom mapping revealed additional lesion predictors of deficits. Post-hoc fiber tracking of the peak white matter lesion predictors using a publicly available tractography atlas revealed evidence consistent with the results of the bottleneck analyses. Together, our results provide support for the proposal that spatially specific white matter damage affecting bottleneck regions, particularly in the posterior temporal lobe, contributes to chronic language deficits after left hemispheric stroke. This may reflect the simultaneous disruption of signaling in dorsal and ventral language processing streams.

Semantic representations in the temporal pole predict false memories

Recent advances in neuroscience have given us unprecedented insight into the neural mechanisms of false memory, showing that artificial memories can be inserted into the memory cells of the hippocampus in a way that is indistinguishable from true memories. However, this alone is not enough to explain how false memories can arise naturally in the course of our daily lives. Cognitive psychology has demonstrated that many instances of false memory, both in the laboratory and the real world, can be attributed to semantic interference. Whereas previous studies have found that a diverse set of regions show some involvement in semantic false memory, none have revealed the nature of the semantic representations underpinning the phenomenon. Here we use fMRI with representational similarity analysis to search for a neural code consistent with semantic false memory. We find clear evidence that false memories emerge from a similarity-based neural code in the temporal pole, a region that has been called the "semantic hub" of the brain. We further show that each individual has a partially unique semantic code within the temporal pole, and this unique code can predict idiosyncratic patterns of memory errors. Finally, we show that the same neural code can also predict variation in true-memory performance, consistent with an adaptive perspective on false memory. Taken together, our findings reveal the underlying structure of neural representations of semantic knowledge, and how this semantic structure can both enhance and distort our memories.

Semantic Neighborhood Effects for Abstract versus Concrete Words

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