Age-related reorganization of functional network architecture in semantic cognition

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.

Developmental refinements to neural attentional state during semantic memory retrieval through adolescence

Despite the fact that attention undergoes protracted development, little is known about how it may support memory refinements in childhood and adolescence. Here, we asked whether people differentially focus their attention on semantic or perceptual information over development during memory retrieval. First, we trained a multivoxel classifier to characterize whole-brain neural patterns reflecting semantic versus perceptual attention in a cued attention task. We then used this classifier to quantify how attention varied in a separate dataset in which children, adolescents, and adults retrieved autobiographical, semantic, and episodic memories. All age groups demonstrated a semantic attentional bias during memory retrieval, with significant age differences in this bias during the semantic task. Trials began with a preparatory picture cue followed by a retrieval question, which allowed us to ask whether attentional biases varied by trial period. Adults showed a semantic bias earlier during the picture cues, whereas adolescents showed this bias during the question. Adults and adolescents also engaged different brain regions-superior parietal cortex and ventral visual regions, respectively-during preparatory picture cues. Our results demonstrate that retrieval-related attention undergoes refinement beyond childhood. These findings suggest that alongside expanding semantic knowledge, attention-related changes may support the maturation of factual knowledge retrieval.

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.

Tracking Age-Related Topological Changes in Individual Brain Morphological Networks Across the Human Lifespan

BACKGROUND

Many studies have shown topological alterations associated with age in population-based brain morphological networks. However, it is not clear how individual brain morphological networks change with age across the lifespan.

PURPOSE

To characterize age-related topological changes in individual networks and investigate the relationships between individual- and group-based brain networks at the nodal, modular, and connectome levels.

STUDY TYPE

Retrospective analysis.

POPULATION

One hundred seventy-nine healthy subjects (108 males and 71 females), aged 6-85 years with a median age of 32 years and an inter-quartile range (IQR) of 26 years.

FIELD STRENGTH/SEQUENCE

T1-weighted images using the magnetization-prepared rapid gradient echo (MPRAGE) sequences.

ASSESSMENT

Two nodal-level indicators (nodal similarity and node matching), five modular-level indicators (modularity, intra/inter-module similarity, adjusted mutual information [AMI], and module variation), and five connectome-level indicators (global efficiency, characteristic path length, clustering coefficient, local efficiency, and individual contribution) were calculated in brain morphological networks. Regression models for different indicators were built to examine their lifetime trajectory patterns.

STATISTICAL TESTS

Single-sample t-test, Mantel's test, Pearson correlation coefficient. A P value <0.05 was considered statistically significant.

RESULTS

Among 68 nodes, 34 nodes showed significant age-related patterns (all P < 0.05, FDR-corrected) in nodal similarity, including linear decline and quadratic trends. The lifespan trajectory of the connectome-level topological attributes of the individual networks presented U-shaped or inverse U-shaped trends with age. Between the individual- and group-based brain networks, the average nodal similarity was 0.67 and the average AMI of module partitions was 0.57.

DATA CONCLUSION

The lifespan trajectories of the nodal similarity mainly followed linear decreasing and nonlinear trends, whereas the modularity and the global topological attributes exhibited nonlinear patterns. There was a high degree of consistency at both nodal similarity and modular division between the individual and group networks.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 1.

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.

Aging effects on dual-route speech processing networks during speech perception in noise

Healthy aging leads to complex changes in the functional network of speech processing in a noisy environment. The dual-route neural architecture has been applied to the study of speech processing. Although evidence suggests that senescent increases activity in the brain regions across the dorsal and ventral stream regions to offset reduced periphery, the regulatory mechanism of dual-route functional networks underlying such compensation remains largely unknown. Here, by utilizing functional near-infrared spectroscopy (fNIRS), we investigated the compensatory mechanism of the dual-route functional connectivity, and its relationship with healthy aging by using a speech perception task at varying signal-to-noise ratios (SNR) in healthy individuals (young adults, middle-aged adults, and older adults). Results showed that the speech perception scores showed a significant age-related decrease with the reduction of the SNR. The analysis results of dual-route speech processing networks showed that the functional connection of Wernicke's area and homolog Wernicke's area were age-related increases. Further to clarify the age-related characteristics of the dual-route speech processing networks, graph-theoretical network analysis revealed an age-related increase in the efficiency of the networks, and the age-related differences in nodal characteristics were found both in Wernicke's area and homolog Wernicke's area under noise environment. Thus, Wernicke's area might be a key network hub to maintain efficient information transfer across the speech process network with healthy aging. Moreover, older adults would recruit more resources from the homologous Wernicke's area in a noisy environment. The recruitment of the homolog of Wernicke's area might provide a means of compensation for older adults for decoding speech in an adverse listening environment. Together, our results characterized dual-route speech processing networks at varying noise environments and provided new insight for the compensatory theories of how aging modulates the dual-route speech processing functional networks.

Differential effects of ageing on the neural processing of speech and singing production

Background

Understanding healthy brain ageing has become vital as populations are ageing rapidly and age-related brain diseases are becoming more common. In normal brain ageing, speech processing undergoes functional reorganisation involving reductions of hemispheric asymmetry and overactivation in the prefrontal regions. However, little is known about how these changes generalise to other vocal production, such as singing, and how they are affected by associated cognitive demands.

Methods

The present cross-sectional fMRI study systematically maps the neural correlates of vocal production across adulthood (N=100, age 21-88 years) using a balanced 2x3 design where tasks varied in modality (speech: proverbs / singing: song phrases) and cognitive demand (repetition / completion from memory / improvisation).

Results

In speech production, ageing was associated with decreased left pre- and postcentral activation across tasks and increased bilateral angular and right inferior temporal and fusiform activation in the improvisation task. In singing production, ageing was associated with increased activation in medial and bilateral prefrontal and parietal regions in the completion task, whereas other tasks showed no ageing effects. Direct comparisons between the modalities showed larger age-related activation changes in speech than singing across tasks, including a larger left-to-right shift in lateral prefrontal regions in the improvisation task.

Conclusion

The present results suggest that the brains' singing network undergoes differential functional reorganisation in normal ageing compared to the speech network, particularly during a task with high executive demand. These findings are relevant for understanding the effects of ageing on vocal production as well as how singing can support communication in healthy ageing and neurological rehabilitation.

Cognition's dependence on functional network integrity with age is conditional on structural network integrity

Maintaining good cognitive function is crucial for well-being across the lifespan. We proposed that the degree of cognitive maintenance is determined by the functional interactions within and between large-scale brain networks. Such connectivity can be represented by the white matter architecture of structural brain networks that shape intrinsic neuronal activity into integrated and distributed functional networks. We explored how the function-structure connectivity convergence, and the divergence of functional connectivity from structural connectivity, contribute to the maintenance of cognitive function across the adult lifespan. Multivariate analyses were used to investigate the relationship between function-structure connectivity convergence and divergence with multivariate cognitive profiles, respectively. Cognitive function was increasingly dependent on function-structure connectivity convergence as age increased. The dependency of cognitive function on connectivity was particularly strong for high-order cortical networks and subcortical networks. The results suggest that brain functional network integrity sustains cognitive functions in old age, as a function of the integrity of the brain's structural connectivity.

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.

Differences in electroencephalography oscillations between normal aging and mild cognitive impairment during semantic memory retrieval

Semantic memory remains relatively stable with normal cognitive aging and declines in early stages of neurodegenerative disease. We measured electroencephalography (EEG) oscillatory correlates of semantic memory retrieval to examine the effects of normal and pathological aging. Twenty-nine cognitively healthy young adults (YA), 22 cognitively healthy aging adults (HA) and 20 patients with mild cognitive impairment (MCI) completed a semantic memory retrieval task with concurrent EEG recording in which they judged whether two words (features of objects) led to retrieval of an object (retrieval) or not (non-retrieval). Event-related power changes contrasting the two conditions (retrieval vs. non-retrieval) within theta, alpha, low-beta and high-beta EEG frequency bands were examined for normal aging (YA vs. HA) and pathological aging effects (HA vs. MCI). With no behavioural differences between the two normal age groups, we found later theta and alpha event-related power differences between conditions only in YA and a high-beta event-related power difference only in HA. For pathological aging effects, with reduced accuracy in MCI, we found different EEG patterns of early event-related beta power differences between conditions in MCI compared with HA and an event-related low-beta power difference only in HA. Beta oscillations were correlated with behavioural performance only in HA. We conclude that the aging brain relies on faster (beta) oscillations during the semantic memory task. With pathological aging, retrieval accuracy declines and pattern of beta oscillation changes. The findings provide insights about age-related neural mechanisms underlying semantic memory and have implications for early detection of pathological aging.