The neural and computational bases of semantic cognition

The role of the right hemispheric homologous language pathways in recovery from post-stroke aphasia: A systematic review

The involvement of the right hemisphere, mainly the activation of the right cerebral regions, in recovery from post-stroke aphasia has been widely recognized. In contrast, the role of the right white matter pathways in the recovery from post-stroke aphasia is rarely understood. In this study, we aimed to provide a primary overview of the correlation between the structural integrity of the right hemispheric neural tracts based on the dual-stream model of language organization and recovery from post-stroke aphasia by systematically reviewing prior longitudinal interventional studies. By searching electronic databases for relevant studies according to a standard protocol, a total of 10 records (seven group studies and three case studies) including 79 participants were finally included. After comprehensively analyzing these studies and reviewing the literature, although no definite correlation was found between the right hemispheric neural tracts and recovery from post-stroke aphasia, our review provideds a new perspective for investigating the linguistic role of the right hemispheric neural tracts. This suggests that the involvement of the right hemispheric neural tracts in recovery from post-stroke aphasia may be mediated by multiple factors; thus, this topic should be comprehensively investigated in the future.

Longitudinal associations between language network characteristics in the infant brain and school-age reading abilities are mediated by early-developing phonological skills

Reading acquisition is a prolonged learning process relying on language development starting in utero. Behavioral longitudinal studies reveal prospective associations between infant language abilities and preschool/kindergarten phonological development that relates to subsequent reading performance. While recent pediatric neuroimaging work has begun to characterize the neural network underlying language development in infants, how this neural network scaffolds long-term language and reading acquisition remains unknown. We addressed this question in a 7-year longitudinal study from infancy to school-age. Seventy-six infants completed resting-state fMRI scanning, and underwent standardized language assessments in kindergarten. Of this larger cohort, forty-one were further assessed on their emergent word reading abilities after receiving formal reading instructions. Hierarchical clustering analyses identified a modular infant language network in which functional connectivity (FC) of the inferior frontal module prospectively correlated with kindergarten-age phonological skills and emergent word reading abilities. These correlations were obtained when controlling for infant age at scan, nonverbal IQ and parental education. Furthermore, kindergarten-age phonological skills mediated the relationship between infant FC and school-age reading abilities, implying a critical mid-way milestone for long-term reading development from infancy. Overall, our findings illuminate the neurobiological mechanisms by which infant language capacities could scaffold long-term reading acquisition.

Macroscale brain states support the control of semantic cognition

A crucial aim in neuroscience is to understand how the human brain adapts to varying cognitive demands. This study investigates network reconfiguration during controlled semantic retrieval in differing contexts. We analyze brain responses to two semantic tasks of varying difficulty - global association and feature matching judgments - which are contrasted with non-semantic tasks on the cortical surface and within a whole-brain state space. Demanding semantic association tasks elicit activation in anterior prefrontal and temporal regions, while challenging semantic feature matching and non-semantic tasks predominantly activate posterior regions. Task difficulty also modulates activation along different dimensions of functional organization, suggesting different mechanisms of cognitive control. More demanding semantic association judgments engage cognitive control and default mode networks together, while feature matching and non-semantic tasks are skewed towards cognitive control networks. These findings highlight the brain's dynamic ability to tailor its networks to support diverse neurocognitive states, enriching our understanding of controlled cognition.

Overlapping neural correlates underpin theory of mind and semantic cognition: Evidence from a meta-analysis of 344 functional neuroimaging studies

Key unanswered questions for cognitive neuroscience include whether social cognition is underpinned by specialised brain regions and to what extent it simultaneously depends on more domain-general systems. Until we glean a better understanding of the full set of contributions made by various systems, theories of social cognition will remain fundamentally limited. In the present study, we evaluate a recent proposal that semantic cognition plays a crucial role in supporting social cognition. While previous brain-based investigations have focused on dissociating these two systems, our primary aim was to assess the degree to which the neural correlates are overlapping, particularly within two key regions, the anterior temporal lobe (ATL) and the temporoparietal junction (TPJ). We focus on activation associated with theory of mind (ToM) and adopt a meta-analytic activation likelihood approach to synthesise a large set of functional neuroimaging studies and compare their results with studies of semantic cognition. As a key consideration, we sought to account for methodological differences across the two sets of studies, including the fact that ToM studies tend to use nonverbal stimuli while the semantics literature is dominated by language-based tasks. Overall, we observed consistent overlap between the two sets of brain regions, especially in the ATL and TPJ. This supports the claim that tasks involving ToM draw upon more general semantic retrieval processes. We also identified activation specific to ToM in the right TPJ, bilateral anterior mPFC, and right precuneus. This is consistent with the view that, nested amongst more domain-general systems, there is specialised circuitry that is tuned to social processes.

Choice-dependent delta-band neural trajectory during semantic category decision making in the human brain

Recent human brain imaging studies have identified widely distributed cortical areas that represent information about the meaning of language. Yet, the dynamic nature of widespread neural activity as a correlate of the semantic information processing remains poorly explored. Our state space analysis of electroencephalograms (EEGs) recorded during semantic match-to-category task show that depending on the semantic category and decision path chosen by participants, whole-brain delta-band dynamics follow distinct trajectories that are correlated with participants' response time on a trial-by-trial basis. Especially, the proximity of the neural trajectory to category decision-specific region in the state space was predictive of participants' decision-making reaction times. We also found that posterolateral regions primarily encoded word categories while postero-central regions encoded category decisions. Our results demonstrate the role of neural dynamics embedded in the evolving multivariate delta-band activity patterns in processing the semantic relatedness of words and the semantic category-based decision-making.

Quantifier processing and semantic flexibility in patients with aphasia

Processing of quantifiers such as "many" and "few" relies on number knowledge, linguistic abilities, and working memory. Negative quantifiers (e.g., "few," "less than half") induce higher processing costs than their positive counterparts. Furthermore, the meaning of some quantifiers is flexible and thus adaptable. Importantly, in neurotypical individuals, changing the meaning of one quantifier also leads to a generalized change in meaning for its polar opposite (e.g., the change of the meaning of "many" leads to the change of that of "few"). Here, we extended this research to patients with fluent and non-fluent aphasia after stroke. In two experiments, participants heard sentences of the type "Many/few of the circles are yellow/blue," each followed by a picture with different quantities of blue and yellow circles. The participants judged whether the sentence adequately described the picture. Each experiment consisted of three blocks: a baseline block to assess the participants' criteria for both quantifiers, a training block to shift the criteria for "many," and a test block, identical to the baseline to capture any changes in quantifier semantics. In Experiment 1, the change of the meaning of "many" was induced by using adaptation to small numbers (20-50%) of circles of the named color. In Experiment 2, explicit feedback was given in the training block after each response to rate proportions of 40% (or higher) as "many," whereas 40% is normally rather rated as "few." The objective was to determine whether people with fluent or non-fluent aphasia were able to process quantifiers appropriately and whether generalized semantic flexibility was present after brain damage. Sixteen out of 21 patients were able to perform the task. People with fluent aphasia showed the expected polarity effect in the reaction times and shifted their criteria for "many" with generalization to the untrained quantifier "few." This effect, however, was only obtained after explicit feedback (Experiment 2) but not by mere adaptation (Experiment 1). In contrast, people with non-fluent aphasia did not change the quantifier semantics in either experiment. This study contributes to gaining new insights into quantifier processing and semantic flexibility in people with aphasia and general underlying processing mechanisms.

Comprehension of English for-adverbials: The Nature of Lexical Meanings and the Neurocognitive Architecture of Language

What is the nature of lexical meanings such that they can both compose with others and also appear boundless? We investigate this question by examining the compositional properties of for-time adverbial as in "Ana jumped for an hour." At issue is the source of the associated iterative reading which lacks overt morphophonological support, yet, the iteration is not disconnected from the lexical meanings in the sentence. This suggests an analysis whereby the iterative reading is the result of the interaction between lexical meanings under a specific compositional configuration. We test the predictions of two competing accounts: Mismatch-and-Repair and Partition-Measure. They differ in their assumptions about lexical meanings: assumptions that have implications for the possible compositional mechanisms that each can invoke. Mismatch-and-Repair assumes that lexical meaning representations are discrete, separate from the conceptual system from which they originally emerged and brought into sentence meaning through syntactic composition. Partition-Measure assumes that lexical meanings are contextually salient conceptual structures substantially indistinguishable from the conceptual system that they inhabit. During comprehension, lexical meanings construe a conceptual representation, in parallel, morphosyntactic and morphophonological composition as determined by the lexical items involved in the sentence. Whereas both hypotheses capture the observed cost in the punctual predicate plus for-time adverbial composition (e.g., jump (vs. swim) for an hour), their predictions differ regarding iteration with durative predicates; for example, swim for a year (vs. for an hour). Mismatch-and-Repair predicts contrasting processing profiles and nonoverlapping activation patterns along punctuality differences. Partition-Measure predicts overlapping processing and cortical distribution profiles, along the presence of iterativity. Results from a self-paced reading and an functional Magnetic Resonance Imaging (fMRI) studies bear out the predictions of the Partition-Measure account, supporting a view of linguistic meaning composition in line with an architecture of language whereby combinatoriality and generativity are distributed, carried out in parallel across linguistic and nonlinguistic subsystems.

The role of alpha oscillations in free- and goal-directed semantic associations

Alpha oscillations are known to play a central role in several higher-order cognitive functions, especially selective attention, working memory, semantic memory, and creative thinking. Nonetheless, we still know very little about the role of alpha in the generation of more remote semantic associations, which is key to creative and semantic cognition. Furthermore, it remains unclear how these oscillations are shaped by the intention to "be creative," which is the case in most creativity tasks. We aimed to address these gaps in two experiments. In Experiment 1, we compared alpha oscillatory activity (using a method which distinguishes genuine oscillatory activity from transient events) during the generation of free associations which were more vs. less distant from a given concept. In Experiment 2, we replicated these findings and also compared alpha oscillatory activity when people were generating free associations versus associations with the instruction to be creative (i.e. goal-directed). We found that alpha was consistently higher during the generation of more distant semantic associations, in both experiments. This effect was widespread, involving areas in both left and right hemispheres. Importantly, the instruction to be creative seems to increase alpha phase synchronisation from left to right temporal brain areas, suggesting that intention to be creative changed the flux of information in the brain, likely reflecting an increase in top-down control of semantic search processes. We conclude that goal-directed generation of remote associations relies on top-down mechanisms compared to when associations are freely generated.

Verbal short term memory contribution to sentence comprehension decreases with increasing syntactic complexity in people with aphasia

Sentence comprehension requires the integration of linguistic units presented in a temporal sequence based on a non-linear underlying syntactic structure. While it is uncontroversial that storage is mandatory for this process, there are opposing views regarding the relevance of general short-term-/working-memory capacities (STM/WM) versus language specific resources. Here we report results from 43 participants with an acquired brain lesion in the extended left hemispheric language network and resulting language deficits, who performed a sentence-to-picture matching task and an experimental task assessing phonological short-term memory. The sentence task systematically varied syntactic complexity (embedding depth and argument order) while lengths, number of propositions and plausibility were kept constant. Clinical data including digit-/ block-spans and lesion size and site were additionally used in the analyses. Correlational analyses confirm that performance on STM/WM-tasks (experimental task and digit-span) are the only two relevant predictors for correct sentence-picture-matching, while reaction times only depended on age and lesion size. Notably increasing syntactic complexity reduced the correlational strength speaking for the additional recruitment of language specific resources independent of more general verbal STM/WM capacities, when resolving complex syntactic structure. The complementary lesion-behaviour analysis yielded different lesion volumes correlating with either the sentence-task or the STM-task. Factoring out STM measures lesions in the anterior temporal lobe correlated a larger decrease in accuracy with increasing syntactic complexity. We conclude that overall sentence comprehension depends on STM/WM capacity, while increases in syntactic complexity tax another independent cognitive resource.

Perceptual and semantic deficits in face recognition in semantic dementia

State of the art

Semantic dementia (SD) patients including semantic variant primary progressive aphasia (svPPA) and semantic behavioral variant frontotemporal dementia (sbvFTD) patients show semantic difficulties identifying faces and known people related to right anterior temporal lobe (ATL) atrophy. However, it remains unclear whether they also have perceptual deficits in face recognition.

Methodology

We selected 74 SD patients (54 with svPPA and predominant left ATL atrophy and 20 with sbvFTD and predominant right ATL atrophy) and 36 cognitively healthy controls (HC) from UCSF Memory and Aging Center. They underwent a perceptual face processing test (Benton facial recognition test-short version; BFRT-S), and semantic face processing tests (UCSF Famous people battery - Recognition, Naming, Semantic associations - pictures and words subtests), as well as structural magnetic resonance imaging (MRI). Neural correlates with the task's performance were conducted with a Voxel-based morphometry approach using CAT12.

Results

svPPA and sbvFTD patients were impaired on all semantic face processing tests, with sbvFTD patients performing significantly lower on the famous faces' recognition task in comparison to svPPA, and svPPA performing significantly lower on the naming task in comparison to sbvFTD. These tasks predominantly correlated with gray matter (GM) volumes in the right and left ATL, respectively. Compared to HC, both svPPA and sbvFTD patients showed preserved performance on the perceptual face processing test (BFRT-S), and performance on the BFRT-S negatively correlated with GM volume in the right posterior superior temporal sulcus (pSTS).

Conclusion

Our results suggest that early in the disease, with the atrophy mostly restricted to the anterior temporal regions, SD patients do not present with perceptual deficits. However, more severe SD cases with atrophy in right posterior temporal regions might show lower performance on face perception tests, in addition to the semantic face processing deficits. Early sparing of face perceptual deficits in SD patients, regardless of hemispheric lateralization, furthers our understanding of clinical phenomenology and therapeutical approaches of this complex disease.

Multiscale chemogenetic dissection of fronto-temporal top-down regulation for object memory in primates

Visual object memory is a fundamental element of various cognitive abilities, and the underlying neural mechanisms have been extensively examined especially in the anterior temporal cortex of primates. However, both macroscopic large-scale functional network in which this region is embedded and microscopic neuron-level dynamics of top-down regulation it receives for object memory remains elusive. Here, we identified the orbitofrontal node as a critical partner of the anterior temporal node for object memory by combining whole-brain functional imaging during rest and a short-term object memory task in male macaques. Focal chemogenetic silencing of the identified orbitofrontal node downregulated both the local orbitofrontal and remote anterior temporal nodes during the task, in association with deteriorated mnemonic, but not perceptual, performance. Furthermore, imaging-guided neuronal recordings in the same monkeys during the same task causally revealed that orbitofrontal top-down modulation enhanced stimulus-selective mnemonic signal in individual anterior temporal neurons while leaving bottom-up perceptual signal unchanged. Furthermore, similar activity difference was also observed between correct and mnemonic error trials before silencing, suggesting its behavioral relevance. These multifaceted but convergent results provide a multiscale causal understanding of dynamic top-down regulation of the anterior temporal cortex along the ventral fronto-temporal network underpinning short-term object memory in primates.

Clinical recognition of frontotemporal dementia with right anterior temporal predominance: A multicenter retrospective cohort study

INTRODUCTION

Although frontotemporal dementia (FTD) with right anterior temporal lobe (RATL) predominance has been recognized, a uniform description of the syndrome is still missing. This multicenter study aims to establish a cohesive clinical phenotype.

METHODS

Retrospective clinical data from 18 centers across 12 countries yielded 360 FTD patients with predominant RATL atrophy through initial neuroimaging assessments.

RESULTS

Common symptoms included mental rigidity/preoccupations (78%), disinhibition/socially inappropriate behavior (74%), naming/word-finding difficulties (70%), memory deficits (67%), apathy (65%), loss of empathy (65%), and face-recognition deficits (60%). Real-life examples unveiled impairments regarding landmarks, smells, sounds, tastes, and bodily sensations (74%). Cognitive test scores indicated deficits in emotion, people, social interactions, and visual semantics however, lacked objective assessments for mental rigidity and preoccupations.

DISCUSSION

This study cumulates the largest RATL cohort unveiling unique RATL symptoms subdued in prior diagnostic guidelines. Our novel approach, combining real-life examples with cognitive tests, offers clinicians a comprehensive toolkit for managing these patients.

HIGHLIGHTS

This project is the first international collaboration and largest reported cohort. Further efforts are warranted for precise nomenclature reflecting neural mechanisms. Our results will serve as a clinical guideline for early and accurate diagnoses.

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.

From long-term to short-term: Distinct neural networks underlying semantic knowledge and its recruitment in working memory

Although numerous studies suggest that working memory (WM) and semantic long-term knowledge interact, the nature and underlying neural mechanisms of this intervention remain poorly understood. Using functional magnetic resonance imaging (fMRI), this study investigated the extent to which neural markers of semantic knowledge in long-term memory (LTM) are activated during the WM maintenance stage in 32 young adults. First, the multivariate neural patterns associated with four semantic categories were determined via an implicit semantic activation task. Next, the participants maintained words - the names of the four semantic categories implicitly activated in the first task - in a verbal WM task. Multi-voxel pattern analyses showed reliable neural decoding of the four semantic categories in the implicit semantic activation and the verbal WM tasks. Critically, however, no between-task classification of semantic categories was observed. Searchlight analyses showed that for the WM task, semantic category information could be decoded in anterior temporal areas associated with abstract semantic category knowledge. In the implicit semantic activation task, semantic category information was decoded in superior temporal, occipital and frontal cortices associated with domain-specific semantic feature representations. These results indicate that item-level semantic activation during verbal WM involves shallow rather than deep semantic information.

Linguistic network in early deaf individuals: A neuroimaging meta-analysis

This meta-analysis summarizes evidence from 44 neuroimaging experiments and characterizes the general linguistic network in early deaf individuals. Meta-analytic comparisons with hearing individuals found that a specific set of regions (in particular the left inferior frontal gyrus and posterior middle temporal gyrus) participates in supramodal language processing. In addition to previously described modality-specific differences, the present study showed that the left calcarine gyrus and the right caudate were additionally recruited in deaf compared with hearing individuals. In addition, this study showed that the bilateral posterior superior temporal gyrus is shaped by cross-modal plasticity, whereas the left frontotemporal areas are shaped by early language experience. Although an overall left-lateralized pattern for language processing was observed in the early deaf individuals, regional lateralization was altered in the inferior temporal gyrus and anterior temporal lobe. These findings indicate that the core language network functions in a modality-independent manner, and provide a foundation for determining the contributions of sensory and linguistic experiences in shaping the neural bases of language processing.

Creative connections: the neural correlates of semantic relatedness are associated with creativity

The associative theory of creativity proposes that creative ideas result from connecting remotely related concepts in memory. Previous research found that higher creative individuals exhibit a more flexible organization of semantic memory, generate more uncommon word associations, and judge remote concepts as more related. In this study (N = 93), we used fMRI to investigate brain regions involved in judging the relatedness of concepts that vary in their semantic distance, and how such neural involvement relates to individual differences in creativity. Brain regions where activity increased with semantic relatedness mainly overlapped with default, control, salience, semantic control, and multiple demand networks. The default and semantic control networks exhibited increased involvement when evaluating more remote associations. Finally, higher creative people, who provided higher relatedness judgements on average, exhibited lower activity in those regions, possibly reflecting higher neural efficiency. We discuss these findings in the context of the neurocognitive processing underlying creativity. Overall, our findings indicate that judging remote concepts as related reflects a cognitive mechanism underlying creativity and shed light on the neural correlates of this mechanism.

MEG Evidence That Modality-Independent Conceptual Representations Contain Semantic and Visual Features

The semantic knowledge stored in our brains can be accessed from different stimulus modalities. For example, a picture of a cat and the word "cat" both engage similar conceptual representations. While existing research has found evidence for modality-independent representations, their content remains unknown. Modality-independent representations could be semantic, or they might also contain perceptual features. We developed a novel approach combining word/picture cross-condition decoding with neural network classifiers that learned latent modality-independent representations from MEG data (25 human participants, 15 females, 10 males). We then compared these representations to models representing semantic, sensory, and orthographic features. Results show that modality-independent representations correlate both with semantic and visual representations. There was no evidence that these results were due to picture-specific visual features or orthographic features automatically activated by the stimuli presented in the experiment. These findings support the notion that modality-independent concepts contain both perceptual and semantic representations.

Long-term motor training enhances functional connectivity between semantic and motor regions in an effector-specific manner: evidence from elite female football athletes

The relation between the action verb semantic processing and sensorimotor experience remains controversial. In this study, we examined whether plasticity changes in brain are specifically related to semantic processing of foot action verbs when long-term motor training is mainly aimed at the foot. To address this question, we acquired resting-state functional magnetic resonance imaging scans and behavioral data from a verb two-choice task from female expertise football players and football novices. We compared the resting-state functional connectivity (rsFC) differences between experts and novices using motor execution regions and general semantic regions (left anterior temporal lobe, lATL) as seed, and explored the neural correlates of behavioral performance. Here, the drift rate (v) parameter of the drift diffusion model (DDM) was used to capture the semantic processing capability. We found experts showed increased correlation between lATL subregions and important brain regions for motor processing, including supplementary motor area (SMA), bilateral paracentral lobule (PL), superior parietal lobule and inferior parietal lobule, in contrast to novices. Further predictive model analysis showed the FC found in rsFC analysis can significantly predict drift rate of foot action verb in both experts and novices, but not drift rate of hand action verb. Our findings therefore establish a connection between effector-related semantic processing and the plasticity changes in brain functional connectivity, attributable to long-term foot-related motor training. This provides evidence supporting the view that semantic processing is fundamentally rooted in the sensorimotor system.

Spatiotemporal Properties of Common Semantic Categories for Words and Pictures

The timing of semantic processing during object recognition in the brain is a topic of ongoing discussion. One way of addressing this question is by applying multivariate pattern analysis to human electrophysiological responses to object images of different semantic categories. However, although multivariate pattern analysis can reveal whether neuronal activity patterns are distinct for different stimulus categories, concerns remain on whether low-level visual features also contribute to the classification results. To circumvent this issue, we applied a cross-decoding approach to magnetoencephalography data from stimuli from two different modalities: images and their corresponding written words. We employed items from three categories and presented them in a randomized order. We show that if the classifier is trained on words, pictures are classified between 150 and 430 msec after stimulus onset, and when training on pictures, words are classified between 225 and 430 msec. The topographical map, identified using a searchlight approach for cross-modal activation in both directions, showed left lateralization, confirming the involvement of linguistic representations. These results point to semantic activation of pictorial stimuli occurring at ∼150 msec, whereas for words, the semantic activation occurs at ∼230 msec.

Temporal tau asymmetry spectrum influences divergent behavior and language patterns in Alzheimer's disease

Understanding the psychiatric symptoms of Alzheimer s disease (AD) is crucial for advancing precision medicine and therapeutic strategies. The relationship between AD behavioral symptoms and asymmetry in spatial tau PET patterns is not well-known. Braak tau progression implicates the temporal lobes early. However, the clinical and pathological implications of temporal tau laterality remain unexplored. This cross-sectional study investigated the correlation between temporal tau PET asymmetry and behavior assessed using the neuropsychiatric inventory and composite scores for memory, executive function, and language, using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. In the entire cohort, continuous right and left temporal tau contributions to behavior and cognition were evaluated, controlling for age, sex, education, and tau burden on the contralateral side. Additionally, a temporal tau laterality index was calculated to define "asymmetry-extreme" groups (individuals with laterality indices greater than two standard deviations from the mean). 695 individuals (age = 73.9 ± 7.6 years, 372 (53.5 %) females) were included, comprising 281 (40%) cognitively unimpaired (CU) amyloid negative, 185 (27%) CU amyloid positive, and 229 (33%) impaired (CI) amyloid positive participants. In the full cohort analysis, right temporal tau was associated with worse behavior (B = 8.14, p-value = 0.007), and left temporal tau was associated with worse language (B = 1.4, p-value < 0.001). Categorization into asymmetry-extreme groups revealed 20 right- and 27 left-asymmetric participants. Within these extreme groups, there was additional heterogeneity along the anterior-posterior dimension. Asymmetrical tau burden is associated with distinct behavioral and cognitive profiles. Wide multi-cultural implementation of social cognition measures is needed to understand right-sided asymmetry in AD.

Mapping semantic space: Exploring the higher-order structure of word meaning

Multiple representation theories posit that concepts are represented via a combination of properties derived from sensorimotor, affective, and linguistic experiences. Recently, it has been proposed that information derived from social experience, or socialness, represents another key aspect of conceptual representation. How these various dimensions interact to form a coherent conceptual space has yet to be fully explored. To address this, we capitalized on openly available word property norms for 6339 words and conducted a large-scale investigation into the relationships between 18 dimensions. An exploratory factor analysis reduced the dimensions to six higher-order factors: sub-lexical, distributional, visuotactile, body action, affective and social interaction. All these factors explained unique variance in performance on lexical and semantic tasks, demonstrating that they make important contributions to the representation of word meaning. An important and novel finding was that the socialness dimension clustered with the auditory modality and with mouth and head actions. We suggest this reflects experiential learning from verbal interpersonal interactions. Moreover, formally modelling the network structure of semantic space revealed pairwise partial correlations between most dimensions and highlighted the centrality of the interoception dimension. Altogether, these findings provide new insights into the architecture of conceptual space, including the importance of inner and social experience, and highlight promising avenues for future research.

Semantic encoding during language comprehension at single-cell resolution

From sequences of speech sounds1,2 or letters3, humans can extract rich and nuanced meaning through language. This capacity is essential for human communication. Yet, despite a growing understanding of the brain areas that support linguistic and semantic processing4-12, the derivation of linguistic meaning in neural tissue at the cellular level and over the timescale of action potentials remains largely unknown. Here we recorded from single cells in the left language-dominant prefrontal cortex as participants listened to semantically diverse sentences and naturalistic stories. By tracking their activities during natural speech processing, we discover a fine-scale cortical representation of semantic information by individual neurons. These neurons responded selectively to specific word meanings and reliably distinguished words from nonwords. Moreover, rather than responding to the words as fixed memory representations, their activities were highly dynamic, reflecting the words' meanings based on their specific sentence contexts and independent of their phonetic form. Collectively, we show how these cell ensembles accurately predicted the broad semantic categories of the words as they were heard in real time during speech and how they tracked the sentences in which they appeared. We also show how they encoded the hierarchical structure of these meaning representations and how these representations mapped onto the cell population. Together, these findings reveal a finely detailed cortical organization of semantic representations at the neuron scale in humans and begin to illuminate the cellular-level processing of meaning during language comprehension.

Time setting errors in the Clock Drawing Test are associated with both semantic and executive deficits

The common requirement to set the time to "10 past 11" on the Clock Drawing Test is intended to elicit a stimulus bound response (SBR), in which the responder is "pulled" to the salient stimulus "10," resulting in hands set at "10 before 11." SBRs are considered markers of executive dysfunction, although this assumption has not yet been validated. We compared SBR and other time-setting errors on inhibitory control tests, hypothesizing that they represent related constructs. The role of semantic dysfunction in the formation of those errors was also investigated. We examined baseline test performance of participants with Mild Cognitive Impairment or a history of depression, and control participants, enrolled in a dementia prevention study. Among 258 participants, we identified clocks with SBRs (n = 16), other time errors (n = 22), or no errors at all (n = 42). Performance between the groups with SBRs and other time-setting errors did not differ on any of the executive tests, and both error groups performed significantly worse than the No Error group on the semantic tests. Control for covariates further supported semantic and executive components in time-setting errors. Both semantic and inhibitory control deficits may underlie time representation errors in general.

The neural correlates of limb apraxia: An anatomical likelihood estimation meta-analysis of lesion-symptom mapping studies in brain-damaged patients

Limb apraxia is a motor disorder frequently observed following a stroke. Apraxic deficits are classically assessed with four tasks: tool use, pantomime of tool use, imitation, and gesture understanding. These tasks are supported by several cognitive processes represented in a left-lateralized brain network including inferior frontal gyrus, inferior parietal lobe (IPL), and lateral occipito-temporal cortex (LOTC). For the past twenty years, voxel-wise lesion symptom mapping (VLSM) studies have been used to unravel the neural correlates associated with apraxia, but none of them has proposed a comprehensive view of the topic. In the present work, we proposed to fill this gap by performing a systematic Anatomic Likelihood Estimation meta-analysis of VLSM studies which included tasks traditionally used to assess apraxia. We found that the IPL was crucial for all the tasks. Moreover, lesions within the LOTC were more associated with imitation deficits than tool use or pantomime, confirming its important role in higher visual processing. Our results questioned traditional neurocognitive models on apraxia and may have important clinical implications.

Mendelian randomization analyses reveal causal relationships between brain functional networks and risk of psychiatric disorders

Dysfunction of brain resting-state functional networks has been widely reported in psychiatric disorders. However, the causal relationships between brain resting-state functional networks and psychiatric disorders remain largely unclear. Here we perform bidirectional two-sample Mendelian randomization (MR) analyses to investigate the causalities between 191 resting-state functional magnetic resonance imaging (rsfMRI) phenotypes (n = 34,691 individuals) and 12 psychiatric disorders (n = 14,307 to 698,672 individuals). Forward MR identified 8 rsfMRI phenotypes causally associated with the risk of psychiatric disorders. For example, the increase in the connectivity of motor, subcortical-cerebellum and limbic network was associated with lower risk of autism spectrum disorder. In adddition, increased connectivity in the default mode and central executive network was associated with lower risk of post-traumatic stress disorder and depression. Reverse MR analysis revealed significant associations between 4 psychiatric disorders and 6 rsfMRI phenotypes. For instance, the risk of attention-deficit/hyperactivity disorder increases the connectivity of the attention, salience, motor and subcortical-cerebellum network. The risk of schizophrenia mainly increases the connectivity of the default mode and central executive network and decreases the connectivity of the attention network. In summary, our findings reveal causal relationships between brain functional networks and psychiatric disorders, providing important interventional and therapeutic targets for psychiatric disorders at the brain functional network level.

Retrieving and reconstructing conceptually similar images from fMRI with latent diffusion models and a neuro-inspired brain decoding model

Objective.Brain decoding is a field of computational neuroscience that aims to infer mental states or internal representations of perceptual inputs from measurable brain activity. This study proposes a novel approach to brain decoding that relies on semantic and contextual similarity.Approach.We use several functional magnetic resonance imaging (fMRI) datasets of natural images as stimuli and create a deep learning decoding pipeline inspired by the bottom-up and top-down processes in human vision. Our pipeline includes a linear brain-to-feature model that maps fMRI activity to semantic visual stimuli features. We assume that the brain projects visual information onto a space that is homeomorphic to the latent space of last layer of a pretrained neural network, which summarizes and highlights similarities and differences between concepts. These features are categorized in the latent space using a nearest-neighbor strategy, and the results are used to retrieve images or condition a generative latent diffusion model to create novel images.Main results.We demonstrate semantic classification and image retrieval on three different fMRI datasets: Generic Object Decoding (vision perception and imagination), BOLD5000, and NSD. In all cases, a simple mapping between fMRI and a deep semantic representation of the visual stimulus resulted in meaningful classification and retrieved or generated images. We assessed quality using quantitative metrics and a human evaluation experiment that reproduces the multiplicity of conscious and unconscious criteria that humans use to evaluate image similarity. Our method achieved correct evaluation in over 80% of the test set.Significance.Our study proposes a novel approach to brain decoding that relies on semantic and contextual similarity. The results demonstrate that measurable neural correlates can be linearly mapped onto the latent space of a neural network to synthesize images that match the original content. These findings have implications for both cognitive neuroscience and artificial intelligence.

Registered report: Age-preserved semantic memory and the CRUNCH effect manifested as differential semantic control networks: An fMRI study

Semantic memory representations are generally well maintained in aging, whereas semantic control is thought to be more affected. To explain this phenomenon, this study tested the predictions of the Compensation-Related Utilization of Neural Circuits Hypothesis (CRUNCH), focusing on task demands in aging as a possible framework. The CRUNCH effect would manifest itself in semantic tasks through a compensatory increase in neural activation in semantic control network regions but only up to a certain threshold of task demands. This study compares 39 younger (20-35 years old) with 39 older participants (60-75 years old) in a triad-based semantic judgment task performed in an fMRI scanner while manipulating task demand levels (low versus high) through semantic distance. In line with the CRUNCH predictions, differences in neurofunctional activation and behavioral performance (accuracy and response times) were expected in younger versus older participants in the low- versus high-demand conditions, which should be manifested in semantic control Regions of Interest (ROIs). Our older participants had intact behavioral performance, as proposed in the literature for semantic memory tasks (maintained accuracy and slower response times (RTs)). Age-invariant behavioral performance in the older group compared to the younger one is necessary to test the CRUNCH predictions. The older adults were also characterized by high cognitive reserve, as our neuropsychological tests showed. Our behavioral results confirmed that our task successfully manipulated task demands: error rates, RTs and perceived difficulty increased with increasing task demands in both age groups. We did not find an interaction between age group and task demand, or a statistically significant difference in activation between the low- and high-demand conditions for either RTs or accuracy. As for brain activation, we did not find the expected age group by task demand interaction, or a significant main effect of task demand. Overall, our results are compatible with some neural activation in the semantic network and the semantic control network, largely in frontotemporoparietal regions. ROI analyses demonstrated significant effects (but no interactions) of task demand in the left and right inferior frontal gyrus, the left posterior middle temporal gyrus, the posterior inferior temporal gyrus and the prefrontal gyrus. Overall, our test did not confirm the CRUNCH predictions.

Age-related differences in the intrinsic connectivity of the hippocampus and ventral temporal lobe in autistic individuals

Introduction

Although memory challenges in autistic individuals have been characterized recently, the functional connectivity of the hippocampus and ventral temporal lobe, two structures important for episodic and semantic memory functions, are poorly understood in autistic individuals. Moreover, age-related differences in the functional connectivity associated with these two memory networks are unrevealed.

Methods

The current study investigated age-related differences in intrinsic connectivity of the hippocampal and ventral temporal lobe (vTL) memory networks in well-matched ASD (n = 73; age range: 10.23-55.40 years old) and Non-ASD groups (n = 74; age range: 10.46-56.20 years old) from the open dataset ABIDE-I. Both theory-driven ROI-to-ROI approach and exploratory seed-based whole-brain approach were used.

Results and discussion

Our findings revealed reduced connectivity in ASD compared to Non-ASD peers, as well as an age-related reduction in the connectivity of hippocampal and vTL networks with triple networks, namely, the default mode network (DMN), the central executive network (CEN), and the salience network (SN), potentially underpinning their challenges in memory, language, and social functions. However, we did not observe reliable differences in age-related effects between the ASD and Non-ASD groups. Our study underscores the importance of understanding memory network dysfunctions in ASD across the lifespan to inform educational and clinical practices.

Longitudinal associations between language network characteristics in the infant brain and school-age reading abilities are mediated by early-developing phonological skills

Reading acquisition is a prolonged learning process relying on language development starting in utero. Behavioral longitudinal studies reveal prospective associations between infant language abilities and preschool/kindergarten phonological development that relates to subsequent reading performance. While recent pediatric neuroimaging work has begun to characterize the neural network underlying language development in infants, how this neural network scaffolds long-term language and reading acquisition remains unknown. We addressed this question in a 7-year longitudinal study from infancy to school-age. Seventy-six infants completed resting-state fMRI scanning, and underwent standardized language assessments in kindergarten. Of this larger cohort, forty-one were further assessed on their emergent word reading abilities after receiving formal reading instructions. Hierarchical clustering analyses identified a modular infant language network in which functional connectivity (FC) of the inferior frontal module prospectively correlated with kindergarten-age phonological skills and emergent word reading abilities. These correlations were obtained when controlling for infant age at scan, nonverbal IQ and parental education. Furthermore, kindergarten-age phonological skills mediated the relationship between infant FC and school-age reading abilities, implying a critical mid-way milestone for long-term reading development from infancy. Overall, our findings illuminate the neurobiological mechanisms by which infant language capacities could scaffold long-term reading acquisition.

The neuropsychological evaluation of face identity recognition

Facial identity recognition (FIR) is arguably the ultimate form of recognition for the adult human brain. Even if the term prosopagnosia is reserved for exceptionally rare brain-damaged cases with a category-specific abrupt loss of FIR at adulthood, subjective and objective impairments or difficulties of FIR are common in the neuropsychological population. Here we provide a critical overview of the evaluation of FIR both for clinicians and researchers in neuropsychology. FIR impairments occur following many causes that should be identified objectively by both general and specific, behavioral and neural examinations. We refute the commonly used dissociation between perceptual and memory deficits/tests for FIR, since even a task involving the discrimination of unfamiliar face images presented side-by-side relies on cortical memories of faces in the right-lateralized ventral occipito-temporal cortex. Another frequently encountered confusion is between specific deficits of the FIR function and a more general impairment of semantic memory (of people), the latter being most often encountered following anterior temporal lobe damage. Many computerized tests aimed at evaluating FIR have appeared over the last two decades, as reviewed here. However, despite undeniable strengths, they often suffer from ecological limitations, difficulties of instruction, as well as a lack of consideration for processing speed and qualitative information. Taking into account these issues, a recently developed behavioral test with natural images manipulating face familiarity, stimulus inversion, and correct response times as a key variable appears promising. The measurement of electroencephalographic (EEG) activity in the frequency domain from fast periodic visual stimulation also appears as a particularly promising tool to complete and enhance the neuropsychological assessment of FIR.

Verbal semantic expertise is associated with reduced functional connectivity between left and right anterior temporal lobes

The left and right anterior temporal lobes (ATLs) encode semantic representations. They show graded hemispheric specialization in function, with the left ATL contributing preferentially to verbal semantic processing. We investigated the cognitive correlates of this organization, using resting-state functional connectivity as a measure of functional segregation between ATLs. We analyzed two independent resting-state fMRI datasets (n = 86 and n = 642) in which participants' verbal semantic expertise was measured using vocabulary tests. In both datasets, people with more advanced verbal semantic knowledge showed weaker functional connectivity between left and right ventral ATLs. This effect was highly specific. It was not observed for within-hemisphere connections between semantic regions (ventral ATL and inferior frontal gyrus (IFG), though it was found for left-right IFG connectivity in one dataset). Effects were not found for tasks probing semantic control, nonsemantic cognition, or face recognition. Our results suggest that hemispheric specialization in the ATLs is not an innate property but rather emerges as people develop highly detailed verbal semantic representations. We speculate that this effect is a consequence of the left ATL's greater connectivity with left-lateralized written word recognition regions, which causes it to preferentially represent meaning for advanced vocabulary acquired primarily through reading.

Basal temporal language area revisited in Japanese language with a language function density map

We revisited the anatomo-functional characteristics of the basal temporal language area (BTLA), first described by Lüders et al. (1986), using electrical cortical stimulation (ECS) in the context of Japanese language and semantic networks. We recruited 11 patients with focal epilepsy who underwent chronic subdural electrode implantation and ECS mapping with multiple language tasks for presurgical evaluation. A semiquantitative language function density map delineated the anatomo-functional characteristics of the BTLA (66 electrodes, mean 3.8 cm from the temporal tip). The ECS-induced impairment probability was higher in the following tasks, listed in a descending order: spoken-word picture matching, picture naming, Kanji word reading, paragraph reading, spoken-verbal command, and Kana word reading. The anterior fusiform gyrus (FG), adjacent anterior inferior temporal gyrus (ITG), and the anterior end where FG and ITG fuse, were characterized by stimulation-induced impairment during visual and auditory tasks requiring verbal output or not, whereas the middle FG was characterized mainly by visual input. The parahippocampal gyrus was the least impaired of the three gyri in the basal temporal area. We propose that the BTLA has a functional gradient, with the anterior part involved in amodal semantic processing and the posterior part, especially the middle FG in unimodal semantic processing.

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.

The Language Network Reliably "Tracks" Naturalistic Meaningful Nonverbal Stimuli

The language network, comprised of brain regions in the left frontal and temporal cortex, responds robustly and reliably during language comprehension but shows little or no response during many nonlinguistic cognitive tasks (e.g., Fedorenko & Blank, 2020). However, one domain whose relationship with language remains debated is semantics-our conceptual knowledge of the world. Given that the language network responds strongly to meaningful linguistic stimuli, could some of this response be driven by the presence of rich conceptual representations encoded in linguistic inputs? In this study, we used a naturalistic cognition paradigm to test whether the cognitive and neural resources that are responsible for language processing are also recruited for processing semantically rich nonverbal stimuli. To do so, we measured BOLD responses to a set of ∼5-minute-long video and audio clips that consisted of meaningful event sequences but did not contain any linguistic content. We then used the intersubject correlation (ISC) approach (Hasson et al., 2004) to examine the extent to which the language network "tracks" these stimuli, that is, exhibits stimulus-related variation. Across all the regions of the language network, meaningful nonverbal stimuli elicited reliable ISCs. These ISCs were higher than the ISCs elicited by semantically impoverished nonverbal stimuli (e.g., a music clip), but substantially lower than the ISCs elicited by linguistic stimuli. Our results complement earlier findings from controlled experiments (e.g., Ivanova et al., 2021) in providing further evidence that the language network shows some sensitivity to semantic content in nonverbal stimuli.

Multimodal study of multilevel pulvino-temporal connections: a new piece in the puzzle of lexical retrieval networks

Advanced methods of imaging and mapping the healthy and lesioned brain have allowed for the identification of the cortical nodes and white matter tracts supporting the dual neurofunctional organization of language networks in a dorsal phonological and a ventral semantic stream. Much less understood are the anatomical correlates of the interaction between the two streams; one hypothesis being that of a subcortically mediated interaction, through crossed cortico-striato-thalamo-cortical and cortico-thalamo-cortical loops. In this regard, the pulvinar is the thalamic subdivision that has most regularly appeared as implicated in the processing of lexical retrieval. However, descriptions of its connections with temporal (language) areas remain scarce. Here we assess this pulvino-temporal connectivity using a combination of state-of-the-art techniques: white matter stimulation in awake surgery and postoperative diffusion MRI (n = 4), virtual dissection from the Human Connectome Project 3 and 7 T datasets (n = 172) and operative microscope-assisted post-mortem fibre dissection (n = 12). We demonstrate the presence of four fundamental fibre contingents: (i) the anterior component (Arnold's bundle proper) initially described by Arnold in the 19th century and destined to the anterior temporal lobe; (ii) the optic radiations-like component, which leaves the pulvinar accompanying the optical radiations and reaches the posterior basal temporal cortices; (iii) the lateral component, which crosses the temporal stem orthogonally and reaches the middle temporal gyrus; and (iv) the auditory radiations-like component, which leaves the pulvinar accompanying the auditory radiations to the superomedial aspect of the temporal operculum, just posteriorly to Heschl's gyrus. Each of those components might correspond to a different level of information processing involved in the lexical retrieval process of picture naming.

An inclusive multivariate approach to neural localization of language components

To determine how language is implemented in the brain, it is important to know which brain areas are primarily engaged in language processing and which are not. Existing protocols for localizing language are typically univariate, treating each small unit of brain volume as independent. One prominent example that focuses on the overall language network in functional magnetic resonance imaging (fMRI) uses a contrast between neural responses to sentences and sets of pseudowords (pronounceable nonwords). This contrast reliably activates peri-sylvian language areas but is less sensitive to extra-sylvian areas that are also known to support aspects of language such as word meanings (semantics). In this study, we assess areas where a multivariate, pattern-based approach shows high reproducibility across multiple measurements and participants, identifying these areas as multivariate regions of interest (mROI). We then perform a representational similarity analysis (RSA) of an fMRI dataset where participants made familiarity judgments on written words. We also compare those results to univariate regions of interest (uROI) taken from previous sentences > pseudowords contrasts. RSA with word stimuli defined in terms of their semantic distance showed greater correspondence with neural patterns in mROI than uROI. This was confirmed in two independent datasets, one involving single-word recognition, and the other focused on the meaning of noun-noun phrases by contrasting meaningful phrases > pseudowords. In all cases, areas of spatial overlap between mROI and uROI showed the greatest neural association. This suggests that ROIs defined in terms of multivariate reproducibility can help localize components of language such as semantics. The multivariate approach can also be extended to focus on other aspects of language such as phonology, and can be used along with the univariate approach for inclusively mapping language cortex.

Irreducibility of sensory experiences: Dual representations lead to dual context biases

There are three views of cognitive representation: the amodal, strong-embodiment, and weak-embodiment views of cognition. The present research provides support for the weak-embodiment view by demonstrating that two representational systems, one conceptual and one perceptual, underlie the cognitive processing of sensory experiences. We find that an initial sensory experience can exert two independent influences on judgments about a subsequent sensory experience. Specifically, we show that the conceptual representation of an initial sensory experience creates an expectation that biases judgments of the subsequent experience toward the initial experience (i.e., an assimilation bias), while the perceptual representation of an initial sensory experience creates a comparison standard that biases judgments of the subsequent experience away from the initial experience (i.e., a contrast bias). Documenting concurrent assimilation and contrast biases supports the claim of a dual representational system espoused by the weak-embodiment view. In so doing, we update the classic literature on context effects and contribute to the debate on representational systems in cognition.

How the intrinsic functional connectivity patterns of the semantic network support semantic processing

Semantic processing, a core of language comprehension, involves the activation of brain regions dispersed extensively across the frontal, temporal, and parietal cortices that compose the semantic network. To comprehend the functional structure of this semantic network and how it prepares for semantic processing, we investigated its intrinsic functional connectivity (FC) and the relation between this pattern and semantic processing ability in a large sample from the Human Connectome Project (HCP) dataset. We first defined a well-studied brain network for semantic processing, and then we characterized the within-network connectivity (WNC) and the between-network connectivity (BNC) within this network using a voxel-based global brain connectivity (GBC) method based on resting-state functional magnetic resonance imaging (fMRI). The results showed that 97.73% of the voxels in the semantic network displayed considerably greater WNC than BNC, demonstrating that the semantic network is a fairly encapsulated network. Moreover, multiple connector hubs in the semantic network were identified after applying the criterion of WNC > 1 SD above the mean WNC of the semantic network. More importantly, three of these connector hubs (i.e., the left anterior temporal lobe, angular gyrus, and orbital part of the inferior frontal gyrus) were reliably associated with semantic processing ability. Our findings suggest that the three identified regions use WNC as the central mechanism for supporting semantic processing and that task-independent spontaneous connectivity in the semantic network is essential for semantic processing.

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.

Semantic processing in older adults is associated with distributed neural activation which varies by association and abstractness of words

The extent to which the neural systems underlying semantic processes degrade with advanced age remains unresolved, which motivated the current study of neural activation on functional magnetic resonance imaging (fMRI) during semantic judgments of associated vs. unassociated, semantic vs. rhyme, and abstract vs. rhyme word pairs. Thirty-eight older adults, 55-85 years of age, performed semantic association decision tasks in a mixed event-related block fMRI paradigm involving binary judgments as to whether word pairs were related (i.e., semantically associated). As hypothesized, significantly greater activation was evident during processing of associated (vs. unassociated) word pairs in cortical areas implicated in semantic processing, including the angular gyrus, temporal cortex, and inferior frontal cortex. Cortical areas showed greater activation to unassociated (vs. associated) word pairs, primarily within a large occipital cluster. Greater activation was evident in cortical areas when response to semantic vs. phonemic word pairs. Contrasting activation during abstract vs. concrete semantic processing revealed areas of co-activation to both semantic classes, and areas that had greater response to either abstract or concrete word pairs. Neural activation across conditions did not vary as a function of greater age, indicating only minimal age-associated perturbation in neural activation during semantic processing. Therefore, the response of the semantic hubs, semantic control, and secondary association areas appear to be largely preserved with advanced age among older adults exhibiting successful cognitive aging. These findings may provide a useful clinical contrast if compared to activation among adults experiencing cognitive decline due Alzheimer's, frontal-temporal dementia, and other neurodegenerative diseases.

Using drawings and deep neural networks to characterize the building blocks of human visual similarity

Early in life and without special training, human beings discern resemblance between abstract visual stimuli, such as drawings, and the real-world objects they represent. We used this capacity for visual abstraction as a tool for evaluating deep neural networks (DNNs) as models of human visual perception. Contrasting five contemporary DNNs, we evaluated how well each explains human similarity judgments among line drawings of recognizable and novel objects. For object sketches, human judgments were dominated by semantic category information; DNN representations contributed little additional information. In contrast, such features explained significant unique variance perceived similarity of abstract drawings. In both cases, a vision transformer trained to blend representations of images and their natural language descriptions showed the greatest ability to explain human perceptual similarity-an observation consistent with contemporary views of semantic representation and processing in the human mind and brain. Together, the results suggest that the building blocks of visual similarity may arise within systems that learn to use visual information, not for specific classification, but in service of generating semantic representations of objects.

Predicting the next sentence (not word) in large language models: What model-brain alignment tells us about discourse comprehension

Current large language models (LLMs) rely on word prediction as their backbone pretraining task. Although word prediction is an important mechanism underlying language processing, human language comprehension occurs at multiple levels, involving the integration of words and sentences to achieve a full understanding of discourse. This study models language comprehension by using the next sentence prediction (NSP) task to investigate mechanisms of discourse-level comprehension. We show that NSP pretraining enhanced a model's alignment with brain data especially in the right hemisphere and in the multiple demand network, highlighting the contributions of nonclassical language regions to high-level language understanding. Our results also suggest that NSP can enable the model to better capture human comprehension performance and to better encode contextual information. Our study demonstrates that the inclusion of diverse learning objectives in a model leads to more human-like representations, and investigating the neurocognitive plausibility of pretraining tasks in LLMs can shed light on outstanding questions in language neuroscience.

Drawing from name in semantic dementia reveals graded object knowledge representations in anterior temporal lobe

Semantic dementia (SD) is characterized by progressive impairment in conceptual knowledge due to anterior temporal lobe (ATL) neurodegeneration. Extended neuropsychological assessments can quantitatively demonstrate the semantic impairment, but this graded loss of knowledge can also be readily observed in the qualitative observation of patients' recall of single concepts. Here, we present the results of a simple task of object drawing-from-name, by patients with SD (N = 19), who have isolated atrophy of the ATL bilaterally. Both cross-sectionally and longitudinally, patient drawings demonstrated a pattern of degradation in which rare and distinctive features (such as the hump on a camel) were lost earliest in disease course, and there was an increase in the intrusion of prototypical features (such as the typical small ears of most mammals on an elephant) with more advanced disease. Crucially, patient drawings showed a continuum of conceptual knowledge loss rather than a binary 'present' or 'absent' state. Overall, we demonstrate that qualitative evaluation of line drawings of animals and objects provides fascinating insights into the transmodal semantic deficit in SD. Our results are consistent with a distributed-plus-hub model of semantic memory. The graded nature of the deficit in semantic performance observed in our subset of longitudinally observed patients suggests that the temporal lobe binds feature-based semantic attributes in its central convergence zone.

Distinctive and Complementary Roles of Default Mode Network Subsystems in Semantic Cognition

The default mode network (DMN) typically deactivates to external tasks, yet supports semantic cognition. It comprises medial temporal (MT), core, and frontotemporal (FT) subsystems, but its functional organization is unclear: the requirement for perceptual coupling versus decoupling, input modality (visual/verbal), type of information (social/spatial), and control demands all potentially affect its recruitment. We examined the effect of these factors on activation and deactivation of DMN subsystems during semantic cognition, across four task-based human functional magnetic resonance imaging (fMRI) datasets, and localized these responses in whole-brain state space defined by gradients of intrinsic connectivity. FT showed activation consistent with a central role across domains, tasks, and modalities, although it was most responsive to abstract, verbal tasks; this subsystem uniquely showed more "tuned" states characterized by increases in both activation and deactivation when semantic retrieval demands were higher. MT also activated to both perceptually coupled (scenes) and decoupled (autobiographical memory) tasks and showed stronger responses to picture associations, consistent with a role in scene construction. Core DMN consistently showed deactivation, especially to externally oriented tasks. These diverse contributions of DMN subsystems to semantic cognition were related to their location on intrinsic connectivity gradients: activation was closer to the sensory-motor cortex than deactivation, particularly for FT and MT, while activation for core DMN was distant from both visual cortex and cognitive control. These results reveal distinctive yet complementary DMN responses: MT and FT support different memory-based representations that are accessed externally and internally, while deactivation in core DMN is associated with demanding, external semantic tasks.

Anti-phasic oscillatory development for speech and noise processing in cochlear implanted toddlers

Human brain demonstrates amazing readiness for speech and language learning at birth, but the auditory development preceding such readiness remains unknown. Cochlear implanted (CI) children (n = 67; mean age 2.77 year ± 1.31 SD; 28 females) with prelingual deafness provide a unique opportunity to study this stage. Using functional near-infrared spectroscopy, it was revealed that the brain of CI children was irresponsive to sounds at CI hearing onset. With increasing CI experiences up to 32 months, the brain demonstrated function, region and hemisphere specific development. Most strikingly, the left anterior temporal lobe showed an oscillatory trajectory, changing in opposite phases for speech and noise. The study provides the first longitudinal brain imaging evidence for early auditory development preceding speech acquisition.

Finding the Words: How Does the Aging Brain Process Language? A Focused Review of Brain Connectivity and Compensatory Pathways

As people age, there is a natural decline in cognitive functioning and brain structure. However, the relationship between brain function and cognition in older adults is neither straightforward nor uniform. Instead, it is complex, influenced by multiple factors, and can vary considerably from one person to another. Reserve, compensation, and maintenance mechanisms may help explain why some older adults can maintain high levels of performance while others struggle. These mechanisms are often studied concerning memory and executive functions that are particularly sensitive to the effects of aging. However, language abilities can also be affected by age, with changes in production fluency. The impact of brain changes on language abilities needs to be further investigated to understand the dynamics and patterns of aging, especially successful aging. We previously modeled several compensatory profiles of language production and lexical access/retrieval in aging within the Lexical Access and Retrieval in Aging (LARA) model. In the present paper, we propose an extended version of the LARA model, called LARA-Connectivity (LARA-C), incorporating recent evidence on brain connectivity. Finally, we discuss factors that may influence the strategies implemented with aging. The LARA-C model can serve as a framework to understand individual performance and open avenues for possible personalized interventions.

The different effects of a sensorimotor grounding on AoA between bilingual concepts

Introduction

Psycholinguistic studies have argued for the age of acquisition (AoA) of words as a marker of concept learning, showing that the semantic features of concepts themselves influence the age at which their labels are learned. However, empirical evidence suggests that semantic features such as imageability and linguistic phenomena such as frequency do not adequately predict AoA. The present study takes the developmental approach of embodied cognition and investigates the effects of sensorimotor experiences on the ease of acquisition of the concept acquired in bilinguals. Specifically, we investigated (1) whether the sensorimotor experience can explain AoA beyond frequency; (2) and whether these patterns are consistent across L1 Chinese and L2 English.

Methods

We conducted sensorimotor rating measures in both Chinese and English on 207 items in which Chinese-English bilingual adults were requested to evaluate the extent to which they experienced concepts by employing six perceptual senses and five effectors for actions located in various regions of the body. Meanwhile, data on AoA and frequency were collected.

Results

The present study showed the sensorimotor experience was closely linked with AoAs in both languages. However, the correlation analysis revealed a trend of higher correlations between AoAs for the same concepts and L1 Chinese, relative to L2 English for the present Chinese-English bilinguals. Importantly, the hierarchical regression analysis demonstrated that after controlling for frequency, sensorimotor experience explained additional variance in L1 AoA. However, L2 sensorimotor experience did not explain the variance in L2 AoA. Sensorimotor experience explained more share of variance in L1 AoA but frequency accounted for more variance in L2 AoA.

Discussion

The findings suggest that concept acquisition should consider the grounding in appropriate sensorimotor experience beyond linguistic phenomena like frequency.

(What) can patients with semantic dementia learn?

Semantic Dementia (SD) is a neurodegenerative disease characterised by progressive deterioration of semantic knowledge, resulting in diminished understanding of concepts, whether encountered in verbal or non-verbal form. Over the past three decades, a number of studies employing a range of treatment techniques and learning methods have examined whether patients with SD can relearn previously known concepts or learn and retain new information. In this article, we review this research, addressing two main questions: a) Can aspects of semantic knowledge that are 'lost' due to degeneration be re-acquired? b) How much do other memory systems (working and episodic memory) interact with and depend on semantic memory? Several studies demonstrate successful relearning of previously known words and concepts in SD, particularly after regular, prolonged practice; but this success tends to diminish once practice ceases, and furthermore often fails to generalise to other instances of the same object/concept. This pattern suggests that, with impaired semantic knowledge, learning relies to an abnormal extent on perceptual factors, making it difficult to abstract away from the specific visual or other perceptual format in which a given concept has been trained. Furthermore, the impact of semantic 'status' of a word or object on both working and episodic memory indicates pervasive interaction of these other memory systems with conceptual knowledge.