Age-Dependent Contribution of Domain-General Networks to Semantic Cognition

Does age affect metacognition? A cross-domain investigation using a hierarchical Bayesian framework

According to previous research, the accuracy of metacognitive judgments in aging depends on the cognitive domain involved in the task, the experimental design, and the metacognitive index used. Older adults are frequently less accurate than younger adults in judging their episodic memory, while no difference is typically observed for semantic metamemory. In addition, age-related changes in metaperception appear to be highly task-dependent. Other metacognitive domains (such as metacognition of executive functioning) have been seldom explored. This study aimed to integrate methodological and theoretical advances in the study of metacognition to answer the question of whether metacognition is impaired in healthy aging. Data were collected in a large sample (n = 443) of participants aged 18 to 79. Participants provided retrospective confidence judgments in four domains: episodic memory, semantic memory, executive functioning, and visual perception. Our measure of accuracy, metacognitive efficiency, was estimated using a hierarchical Bayesian implementation of the meta-d' model. Results showed that metacognitive efficiency decreased with age in the episodic task and increased with age in the semantic task. There was no effect of age on metacognitive efficiency in the executive and perception tasks. Moreover, metacognitive efficiency appeared to rely on a domain-general process in older adults. Explaining the episodic metamemory deficit in aging could help understand the difficulties of older adults to use inferential processes for memory search and retrieval as well as their difficulties to implement memory strategies.

Prediction of Verbal Abilities From Brain Connectivity Data Across the Lifespan Using a Machine Learning Approach

Compared to nonverbal cognition such as executive or memory functions, language-related cognition generally appears to remain more stable until later in life. Nevertheless, different language-related processes, for example, verbal fluency versus vocabulary knowledge, appear to show different trajectories across the life span. One potential explanation for differences in verbal functions may be alterations in the functional and structural network architecture of different large-scale brain networks. For example, differences in verbal abilities have been linked to the communication within and between the frontoparietal (FPN) and default mode network (DMN). It, however, remains open whether brain connectivity within these networks may be informative for language performance at the individual level across the life span. Further information in this regard may be highly desirable as verbal abilities allow us to participate in daily activities, are associated with quality of life, and may be considered in preventive and interventional setups to foster cognitive health across the life span. So far, mixed prediction results based on resting-state functional connectivity (FC) and structural connectivity (SC) data have been reported for language abilities across different samples, age groups, and machine-learning (ML) approaches. Therefore, the current study set out to investigate the predictability of verbal fluency and vocabulary knowledge based on brain connectivity data in the DMN, FPN, and the whole brain using an ML approach in a lifespan sample (N = 717; age range: 18-85) from the 1000BRAINS study. Prediction performance was, thereby, systematically compared across (i) verbal [verbal fluency and vocabulary knowledge] and nonverbal abilities [processing speed and visual working memory], (ii) modalities [FC and SC data], (iii) feature sets [DMN, FPN, DMN-FPN, and whole brain], and (iv) samples [total, younger, and older aged group]. Results from the current study showed that verbal abilities could not be reliably predicted from FC and SC data across feature sets and samples. Thereby, no predictability differences emerged between verbal fluency and vocabulary knowledge across input modalities, feature sets, and samples. In contrast to verbal functions, nonverbal abilities could be moderately predicted from connectivity data, particularly SC, in the total and younger age group. Satisfactory prediction performance for nonverbal cognitive functions based on currently chosen connectivity data was, however, not encountered in the older age group. Current results, hence, emphasized that verbal functions may be more difficult to predict from brain connectivity data in domain-general cognitive networks and the whole brain compared to nonverbal abilities, particularly executive functions, across the life span. Thus, it appears warranted to more closely investigate differences in predictability between different cognitive functions and age groups.

On the complexity of metacognitive judgments of memory: evidence from retrospective confidence, feeling of knowing, and older adults

Dissociations in types of memory tasks emerge when comparing feeling-of-knowing (FOK) judgments, predictions of upcoming performance, and retrospective confidence. This pattern has been used to construct theories of metacognitive access to memory, particularly in memory-impaired groups. In particular, older adults' metacognitive sensitivity appears to vary between episodic (impaired) and semantic (intact) memory. However, this could be explained by the limitations of metacognitive measures and/or memory differences. We aimed to test these dissociations of metacognition with aging by comparing metacognitive efficiency in episodic and semantic tasks using two types of judgment: retrospective confidence judgments (RCJs) and FOK judgments. Metacognitive efficiency was estimated in 240 participants aged 19-79 years using a hierarchical Bayesian framework. Results showed that metacognitive efficiency for RCJs declined with age in the semantic task, even though task performance increased with age, while metacognitive efficiency was stable in the episodic task. Surprisingly, metacognitive efficiency was very low (although significantly higher than zero) for both FOK tasks regardless of age compared to similar previous studies. We suggested this might be due to the online testing. These results point to metacognition being multifaceted and varying according to judgment, domains, and populations.

Semantic Integration Demands Modulate Large-Scale Network Interactions in the Brain

The ability to integrate semantic information into the context of a sentence is essential for human communication. Several studies have shown that the predictability of a final keyword based on the sentence context influences semantic integration on the behavioral, neurophysiological, and neural level. However, the architecture of the underlying network interactions for semantic integration across the lifespan remains unclear. In this study, 32 healthy participants (30-75 years) performed an auditory cloze probability task during functional magnetic resonance imaging (fMRI), requiring lexical decisions on the sentence's final words. Semantic integration demands were implicitly modulated by presenting sentences with expected, unexpected, anomalous, or pseudoword endings. To elucidate network interactions supporting semantic integration, we combined univariate task-based fMRI analyses with seed-based connectivity and between-network connectivity analyses. Behavioral data revealed typical semantic integration effects, with increased integration demands being associated with longer response latencies and reduced accuracy. Univariate results demonstrated increased left frontal and temporal brain activity for sentences with higher integration demands. Between-network interactions highlighted the role of task-positive and default mode networks for sentence processing with increased semantic integration demands. Furthermore, increasing integration demands led to a higher number of behaviorally relevant network interactions, suggesting that the increased between-network coupling becomes more relevant for successful task performance as integration demands increase. Our findings elucidate the complex network interactions underlying semantic integration across the aging continuum. Stronger interactions between various task-positive and default mode networks correlated with more efficient processing of sentences with increased semantic integration demands. These results may inform future studies with healthy old and clinical populations.

Midlife dynamics of white matter architecture in lexical production

We aimed to examine the white matter changes associated with lexical production difficulties, beginning in midlife with increased naming latencies. To delay lexical production decline, middle-aged adults may rely on domain-general and language-specific compensatory mechanisms proposed by the LARA model (Lexical Access and Retrieval in Aging). However, the white matter changes supporting these mechanisms remains largely unknown. Using data from the CAMCAN cohort, we employed an unsupervised and data-driven methodology to examine the relationships between diffusion-weighted imaging and lexical production. Our findings indicate that midlife is marked by alterations in brain structure within distributed dorsal, ventral, and anterior cortico-subcortical networks, marking the onset of lexical production decline around ages 53-54. Middle-aged adults may initially adopt a "semantic strategy" to compensate for lexical production challenges, but this strategy seems compromised later (ages 55-60) as semantic control declines. These insights underscore the interplay between domain-general and language-specific processes in the trajectory of lexical production performance in healthy aging and hint at potential biomarkers for language-related neurodegenerative pathologies.

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.

The Quebec Semantic Memory Battery: Development, Standardization, and Psychometric Assessment of a Semantic Memory Battery in French

OBJECTIVE

People with aphasia often experience semantic memory (SM) impairment. To improve diagnostic outcomes, SM tasks should recruit various sensory input channels (oral, written, and pictographic), permitting accessible, complete evaluation. There is a need for SM batteries for French-speaking Quebecers that use multiple input channels. The present study, therefore, describes the development of a novel French-language semantic battery: la Batterie québécoise de la mémoire sémantique (BQMS), the assessment of the BQMS's psychometric properties, and the establishment of normative data for the BQMS.

METHOD

We first developed eight SM tasks. Following a pilot validation study, we determined the BQMS's reliability and validity, to ensure consistent, accurate detection of SM impairment. Among French-speaking Quebecers with cerebrovascular aphasia (n = 10), people with the semantic variant of Primary Progressive Aphasia (n = 4), and healthy controls (n = 14), we examined its convergent validity, concurrent validity, test-retest reliability, and internal consistency. Finally, we established normative data for the BQMS by calculating cut-off scores per task that indicate SM impairment (in 93 cognitively healthy French-speaking Quebecers), stratified by sociodemographic variables associated with performance.

RESULTS

The BQMS shows high concurrent, discriminant, and convergent validity, as well as good test-retest reliability and internal consistency. The cut-off score indicating SM impairment ranged from the 2nd to 25th percentiles (stratified by task, age, and sex).

CONCLUSIONS

The BQMS's psychometric properties indicate that it could be a valuable clinical tool for detecting SM impairment. Our normative data will help clinicians detect such impairments.

Bayesian modelling disentangles language versus executive control disruption in stroke

Stroke is the leading cause of long-term disability worldwide. Incurred brain damage can disrupt cognition, often with persisting deficits in language and executive capacities. Yet, despite their clinical relevance, the commonalities and differences between language versus executive control impairments remain under-specified. To fill this gap, we tailored a Bayesian hierarchical modelling solution in a largest-of-its-kind cohort (1080 patients with stroke) to deconvolve language and executive control with respect to the stroke topology. Cognitive function was assessed with a rich neuropsychological test battery including global cognitive function (tested with the Mini-Mental State Exam), language (assessed with a picture naming task), executive speech function (tested with verbal fluency tasks), executive control functions (Trail Making Test and Digit Symbol Coding Task), visuospatial functioning (Rey Complex Figure), as well as verbal learning and memory function (Soul Verbal Learning). Bayesian modelling predicted interindividual differences in eight cognitive outcome scores three months after stroke based on specific tissue lesion topologies. A multivariate factor analysis extracted four distinct cognitive factors that distinguish left- and right-hemispheric contributions to ischaemic tissue lesions. These factors were labelled according to the neuropsychological tests that had the strongest factor loadings: One factor delineated language and general cognitive performance and was mainly associated with damage to left-hemispheric brain regions in the frontal and temporal cortex. A factor for executive control summarized mental flexibility, task switching and visual-constructional abilities. This factor was strongly related to right-hemispheric brain damage of posterior regions in the occipital cortex. The interplay of language and executive control was reflected in two distinct factors that were labelled as executive speech functions and verbal memory. Impairments on both factors were mainly linked to left-hemispheric lesions. These findings shed light onto the causal implications of hemispheric specialization for cognition; and make steps towards subgroup-specific treatment protocols after stroke.

Modeling the neurocognitive dynamics of language across the lifespan

Healthy aging is associated with a heterogeneous decline across cognitive functions, typically observed between language comprehension and language production (LP). Examining resting-state fMRI and neuropsychological data from 628 healthy adults (age 18-88) from the CamCAN cohort, we performed state-of-the-art graph theoretical analysis to uncover the neural mechanisms underlying this variability. At the cognitive level, our findings suggest that LP is not an isolated function but is modulated throughout the lifespan by the extent of inter-cognitive synergy between semantic and domain-general processes. At the cerebral level, we show that default mode network (DMN) suppression coupled with fronto-parietal network (FPN) integration is the way for the brain to compensate for the effects of dedifferentiation at a minimal cost, efficiently mitigating the age-related decline in LP. Relatedly, reduced DMN suppression in midlife could compromise the ability to manage the cost of FPN integration. This may prompt older adults to adopt a more cost-efficient compensatory strategy that maintains global homeostasis at the expense of LP performances. Taken together, we propose that midlife represents a critical neurocognitive juncture that signifies the onset of LP decline, as older adults gradually lose control over semantic representations. We summarize our findings in a novel synergistic, economical, nonlinear, emergent, cognitive aging model, integrating connectomic and cognitive dimensions within a complex system perspective.

Age differences in the neural processing of semantics, within and beyond the core semantic network

Aging is associated with functional activation changes in domain-specific regions and large-scale brain networks. This preregistered Functional magnetic resonance imaging (fMRI) study investigated these effects within the domain of semantic cognition. Participants completed 1 nonsemantic and 2 semantic tasks. We found no age differences in semantic activation in core semantic regions. However, the right inferior frontal gyrus showed difficulty-related increases in both age groups. This suggests that age-related upregulation of this area may be a compensatory response to increased processing demands. At a network level, older people showed more engagement in the default mode network and less in the executive multiple-demand network, aligning with older people's greater knowledge reserves and executive declines. In contrast, activation was age-invariant in semantic control regions. Finally, older adults showed reduced demand-related modulation of multiple-demand network activation in the nonsemantic task but not the semantic tasks. These findings provide a new perspective on the neural basis of semantic cognition in aging, suggesting that preserved function in specialized semantic networks may help to maintain semantic cognition in later life.

Higher subjective socioeconomic status is linked to increased charitable giving and mentalizing-related neural value coding

Socioeconomic status (SES), a concept related to an individual's economic and social position relative to others, can shape social interactions like altruistic behaviors. However, little is known about the exact neurocognitive mechanisms that link SES with altruism. Our study aimed to provide a comprehensive account of the sociocognitive and neural mechanisms through which SES affects charitable giving - an important variant of human altruism. To this end, participants completed a charitable donation task while their brain activity was measured using functional magnetic resonance imaging (fMRI). We also assessed participants' socio-cognitive ability to infer other people's mental states (i.e., mentalizing) - a driver of prosocial behavior - in an independent social task. Behaviorally, we found that both charitable giving and social cognition were status-dependent, as subjective SES positively predicted donations and mentalizing capacity. Moreover, the link between SES and charitable giving was mediated by individuals' mentalizing capacity. At the neural level, a multivariate pattern analysis of fMRI data revealed that higher subjective SES was associated with stronger value coding in the right temporoparietal junction (rTPJ). The strength of this value representation predicted charitable giving and was linked to mentalizing. Furthermore, we observed an increased negative functional coupling between rTPJ and left putamen with higher SES. Together, increased charitable giving in higher-status individuals could be explained by status-dependent recruitment of mentalizing-related value coding and altered functional connectivity in the brain. Our findings provide insights into the socio- and neurocognitive mechanisms explaining why and when higher SES leads to prosociality, which might ultimately inform targeted interventions to promote prosocial behavior in human societies.

Bayesian modeling disentangles language versus executive control disruption in stroke

Stroke is the leading cause of long-term disability worldwide. Incurred brain damage disrupts cognition, often with persisting deficits in language and executive capacities. Despite their clinical relevance, the commonalities, and differences of language versus executive control impairments remain under-specified. We tailored a Bayesian hierarchical modeling solution in a largest-of-its-kind cohort (1080 stroke patients) to deconvolve language and executive control in the brain substrates of stroke insults. Four cognitive factors distinguished left- and right-hemispheric contributions to ischemic tissue lesion. One factor delineated language and general cognitive performance and was mainly associated with damage to left-hemispheric brain regions in the frontal and temporal cortex. A factor for executive control summarized control and visual-constructional abilities. This factor was strongly related to right-hemispheric brain damage of posterior regions in the occipital cortex. The interplay of language and executive control was reflected in two factors: executive speech functions and verbal memory. Impairments on both were mainly linked to left-hemispheric lesions. These findings shed light onto the causal implications of hemispheric specialization for cognition; and make steps towards subgroup-specific treatment protocols after stroke.

TMS over the pre-SMA enhances semantic cognition via remote network effects on task-based activity and connectivity

BACKGROUND

The continuous decline of executive abilities with age is mirrored by increased neural activity of domain-general networks during task processing. So far, it remains unclear how much domain-general networks contribute to domain-specific processes such as language when cognitive demands increase. The current neuroimaging study explored the potential of intermittent theta-burst stimulation (iTBS) over a domain-general hub to enhance executive and semantic processing in healthy middle-aged to older adults.

METHODS

We implemented a cross-over within-subject study design with three task-based neuroimaging sessions per participant. Using an individualized stimulation approach, each participant received once effective and once sham iTBS over the pre-supplementary motor area (pre-SMA), a region of domain-general control. Subsequently, task-specific stimulation effects were assessed in functional MRI using a semantic and a non-verbal executive task with varying cognitive demand.

RESULTS

Effective stimulation increased activity only during semantic processing in visual and dorsal attention networks. Further, iTBS induced increased seed-based connectivity in task-specific networks for semantic and executive conditions with high cognitive load but overall reduced whole-brain coupling between domain-general networks. Notably, stimulation-induced changes in activity and connectivity related differently to behavior: While stronger activity of the parietal dorsal attention network was linked to poorer semantic performance, its enhanced coupling with the pre-SMA was associated with more efficient semantic processing.

CONCLUSIONS

iTBS modulates networks in a task-dependent manner and generates effects at regions remote to the stimulation site. These neural changes are linked to more efficient semantic processing, which underlines the general potential of network stimulation approaches in cognitive aging.

Investigating the effects of the aging brain on real tool use performance-an fMRI study

Introduction

Healthy aging affects several domains of cognitive and motor performance and is further associated with multiple structural and functional neural reorganization patterns. However, gap of knowledge exists, referring to the impact of these age-related alterations on the neural basis of tool use-an important, complex action involved in everyday life throughout the entire lifespan. The current fMRI study aims to investigate age-related changes of neural correlates involved in planning and executing a complex object manipulation task, further providing a better understanding of impaired tool use performance in apraxia patients.

Methods

A balanced number of sixteen older and younger healthy adults repeatedly manipulated everyday tools in an event-related Go-No-Go fMRI paradigm.

Results

Our data indicates that the left-lateralized network, including widely distributed frontal, temporal, parietal and occipital regions, involved in tool use performance is not subjected to age-related functional reorganization processes. However, age-related changes regarding the applied strategical procedure can be detected, indicating stronger investment into the planning, preparatory phase of such an action in older participants.

Task difficulty modulates age-related differences in functional connectivity during word production

Older adults typically report increased difficulty with language production, while its neural bases are less clear. The current study investigated the neural bases of age-related differences in language production at the word level and the modulating effect of task difficulty, focusing on task-based functional connectivity. Using an English phonological Go/No-Go picture naming task, task difficulty was manipulated by varying the proportion of naming trials (Go trials) and inhibition trials (No-Go trials) across runs. Behaviorally, compared to younger adults, older adults performed worse, and showed larger effects of task difficulty. Neurally, older adults had lower within language network connectivity compared to younger adults. Moreover, older adults' language network became less segregated as task difficulty increased. These results are consistent with the Compensation-Related Utilization of Neural Circuits Hypothesis, suggesting that the brain becomes less specified and efficient with increased task difficulty, and that these effects are stronger among older adults (i.e., more dedifferentiated).

Age-related reorganization of functional network architecture in semantic cognition

Cognitive aging is associated with widespread neural reorganization processes in the human brain. However, the behavioral impact of such reorganization is not well understood. The current neuroimaging study investigated age differences in the functional network architecture during semantic word retrieval in young and older adults. Combining task-based functional connectivity, graph theory and cognitive measures of fluid and crystallized intelligence, our findings show age-accompanied large-scale network reorganization even when older adults have intact word retrieval abilities. In particular, functional networks of older adults were characterized by reduced decoupling between systems, reduced segregation and efficiency, and a larger number of hub regions relative to young adults. Exploring the predictive utility of these age-related changes in network topology revealed high, albeit less efficient, performance for older adults whose brain graphs showed stronger dedifferentiation and reduced distinctiveness. Our results extend theoretical accounts on neurocognitive aging by revealing the compensational potential of the commonly reported pattern of network dedifferentiation when older adults can rely on their prior knowledge for successful task processing. However, we also demonstrate the limitations of such compensatory reorganization and show that a youth-like network architecture in terms of balanced integration and segregation is associated with more economical processing.

The role of the angular gyrus in semantic cognition: a synthesis of five functional neuroimaging studies

Semantic knowledge is central to human cognition. The angular gyrus (AG) is widely considered a key brain region for semantic cognition. However, the role of the AG in semantic processing is controversial. Key controversies concern response polarity (activation vs. deactivation) and its relation to task difficulty, lateralization (left vs. right AG), and functional-anatomical subdivision (PGa vs. PGp subregions). Here, we combined the fMRI data of five studies on semantic processing (n = 172) and analyzed the response profiles from the same anatomical regions-of-interest for left and right PGa and PGp. We found that the AG was consistently deactivated during non-semantic conditions, whereas response polarity during semantic conditions was inconsistent. However, the AG consistently showed relative response differences between semantic and non-semantic conditions, and between different semantic conditions. A combined analysis across all studies revealed that AG responses could be best explained by separable effects of task difficulty and semantic processing demand. Task difficulty effects were stronger in PGa than PGp, regardless of hemisphere. Semantic effects were stronger in left than right AG, regardless of subregion. These results suggest that the AG is engaged in both domain-general task-difficulty-related processes and domain-specific semantic processes. In semantic processing, we propose that left AG acts as a "multimodal convergence zone" that binds different semantic features associated with the same concept, enabling efficient access to task-relevant features.

Centrality and interhemispheric coordination are related to different clinical/behavioral factors in attention deficit/hyperactivity disorder: a resting-state fMRI study

Eigenvector-Centrality (EC) has shown promising results in the field of Psychiatry, with early results also pertaining to ADHD. Parallel efforts have focused on the description of aberrant interhemispheric coordination in ADHD, as measured by Voxel-Mirrored-Homotopic-Connectivity (VMHC), with early evidence of altered Resting-State fMRI. A sample was collected from the ADHD200-NYU initiative: 86 neurotypicals and 89 participants with ADHD between 7 and 18 years old were included after quality control for motion. After preprocessing, voxel-wise EC and VMHC values between diagnostic groups were compared, and network-level values from 15 functional networks extracted. Age, ADHD severity (Connor's Parent Rating-Scale), IQ (Wechsler-Abbreviated-Scale), and right-hand dominance were correlated with EC/VMHC values in the whole sample and within groups, both at the voxel-wise and network-level. Motion was controlled by censoring time-points with Framewise-Displacement > 0.5 mm, as well as controlling for group differences in mean Framewise-Displacement values. EC was significantly higher in ADHD compared to neurotypicals in the left inferior Frontal lobe, Lingual gyri, Peri-Calcarine cortex, superior and middle Occipital lobes, right inferior Occipital lobe, right middle Temporal gyrus, Fusiform gyri, bilateral Cuneus, right Precuneus, and Cerebellum (FDR-corrected-p = 0.05). No differences were observed between groups in voxel-wise VMHC. EC was positively correlated with ADHD severity scores at the network level (at p-value < 0.01, Inattentive: Cerebellum rho = 0.273; Hyper/Impulsive: High-Visual Network rho = 0.242, Cerebellum rho = 0.273; Global Index Severity: High-Visual Network rho = 0.241, Cerebellum rho = 0.293). No differences were observed between groups for motion (p = 0.443). While EC was more related to ADHD psychopathology, VMHC was consistently and negatively correlated with age across all networks.

Functional connectivity of brain networks during semantic processing in older adults

The neural systems underlying semantic processing have been characterized with functional neuroimaging in young adults. Whether the integrity of these systems degrade with advanced age remains unresolved. The current study examined functional connectivity during abstract and concrete word processing. Thirty-eight adults, aged 55–91, engaged in semantic association decision tasks during a mixed event-related block functional magnetic resonance imaging (fMRI) paradigm. During the semantic trials, the task required participants to make a judgment as to whether pairs were semantically associated. During the rhyme trials, the task required participants to determine if non-word pairs rhymed. Seeds were placed in putative semantic hubs of the left anterior middle temporal gyrus (aMTG) and the angular gyrus (AG), and also in the left inferior frontal gyrus (IFG), an area considered important for semantic control. Greater connectivity between aMTG, AG, and IFG and multiple cortical areas occurred during semantic processing. Connectivity from the three seeds differed during semantic processing: the left AG and aMTG were strongly connected with frontal, parietal, and occipital areas bilaterally, whereas the IFG was most strongly connected with other frontal cortical areas and the AG in the ipsilateral left hemisphere. Notably, the strength and extent of connectivity differed for abstract and concrete semantic processing; connectivity from the left aMTG and AG to bilateral cortical areas was greater during abstract processing, whereas IFG connectivity with left cortical areas was greater during concrete processing. With advanced age, greater connectivity occurred only between the left AG and supramarginal gyrus during the processing of concrete word-pairs, but not abstract word-pairs. Among older adults, robust functional connectivity of the aMTG, AG, and IFG to widely distributed bilateral cortical areas occurs during abstract and concrete semantic processing in a manner consistent with reports from past studies of young adults. There was not a significant degradation of functional connectivity during semantic processing between the ages of 55 and 85 years. As the study focused on semantic functioning in older adults, a comparison group of young adults was not included, limiting generalizability. Future longitudinal neuroimaging studies that compare functional connectivity of young and older adults under different semantic demands will be valuable.