Cortical Networks Underpinning Compensation of Verbal Fluency in Normal Aging.
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ABSTRACT:
SUBMITTER: Gonzalez-Burgos L
PROVIDER: S-EPMC8258442 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Neural compensatory mechanisms associated with broad cognitive abilities have been studied. However, those associated with specific cognitive subdomains (e.g., verbal fluency) remain to be investigated in healthy aging. Here, we delineate: (a) neural substrates of verbal (phonemic) fluency, and (b) compensatory mechanisms mediating the association between these neural substrates and phonemic fluency. We analyzed resting-state functional magnetic resonance imaging from 133 right-handed, cognitively normal individuals who underwent the Controlled Oral Word Association Test (COWAT) to record their phonemic fluency. We evaluated functional connectivity in an established and extended language network comprising Wernicke, Broca, thalamic and anti-correlated modules. (a) We conducted voxel-wise multiple linear regression to identify the brain areas associated with phonemic fluency. (b) We used mediation effects of cognitive reserve, measured by the Wechsler Adult Intelligence Scale-Information subtest, upon the association between functional connectivity and phonemic fluency tested to investigate compensation. We found that: (a) Greater functional connectivity between the Wernicke module and brain areas within the anti-correlated module was associated with better performance in phonemic fluency, (b) Cognitive reserve was an unlikely mediator in younger adults. In contrast, cognitive reserve was a partial mediator of the association between functional connectivity and phonemic fluency in older adults, likely representing compensation to counter the effect of aging. We conclude that in healthy aging, higher performance in phonemic fluency at older ages could be attributed to greater functional connectivity partially facilitated by higher cognitive reserve, presumably reflecting compensatory mechanisms to minimize the effect of aging.
| S-EPMC8287584 | biostudies-literature
Project description:Verbal fluency has been widely studied in cognitive aging. However, compensatory mechanisms that maintain its optimal performance with increasing age are not completely understood. Using cross-sectional data, we investigated differentiation and dedifferentiation processes in verbal fluency across the lifespan by analyzing the association between verbal fluency and numerous cognitive measures within four age groups (N=446): early middle-age (32-45 years), late middle-age (46-58 years), early elderly (59-71 years), and late elderly (72-84 years). ANCOVA was used to investigate the interaction between age and fluency modality. Random forest models were conducted to study the contribution of cognition to semantic, phonemic, and action fluency. All modalities declined with increasing age, but semantic fluency was the most vulnerable to aging. The most prominent reduction in performance was observed during the transition from middle-age to early elderly, when cognitive variables stopped contributing (differentiation), and new cognitive variables started contributing (dedifferentiation). Lexical access, processing speed, and executive functions were among the most contributing functions. We conclude that the association between age and verbal fluency is masked by age-specific influences of other cognitive functions. Differentiation and dedifferentiation processes can coexist. This study provides important data for better understanding of cognitive aging and compensatory processes.
| S-EPMC6628999 | biostudies-literature
Project description:Background:The integrity and connectivity of the frontal lobe, which subserves fluency, may be compromised by both ASD and aging. Alternate networks often integrate to help compensate for compromised functions during aging. We used network analyses to study how compensation may overcome age-related compromised in individuals with ASD. Method:Participants consisted of middle-aged (40-60; n=24) or young (18-25; n=18) right-handed males who have a diagnosis of ASD, and age- and IQ-matched control participants (n=20, 14, respectively). All performed tests of language and executive functioning and a fluency functional MRI task. We first used group individual component analysis (ICA) for each of the 4 groups to determine whether different networks were engaged. An SPM analysis was used to compare activity detected in the network nodes from the ICA analyses. Results:The individuals with ASD performed more slowly on two cognitive tasks (Stroop word reading and Trailmaking Part A). The 4 groups engaged different networks during the fluency fMRI task despite equivalent performance. Comparisons of specific regions within these networks indicated younger individuals had greater engagement of the thalamus and supplementary speech area, while older adults engaged the superior temporal gyrus. Individuals with ASD did not disengage from the Default Mode Network during word generation. Conclusion:Interactions between diagnosis and aging were not found in this study of young and middle-aged men, but evidence for differential engagement of compensatory networks was observed.
| S-EPMC7304570 | biostudies-literature
Project description:Understanding how the mammalian neocortex creates cognition largely depends on knowledge about large-scale cortical organization. Accumulated evidence has illuminated cortical substrates of cognition across the lifespan, but how topological properties of cortical networks support structure-function relationships in normal aging remains an open question. Here we investigate the role of connections (i.e., short/long and direct/indirect) and node properties (i.e., centrality and modularity) in predicting functional-structural connectivity coupling in healthy elderly subjects. Connectivity networks were derived from correlations of cortical thickness and cortical glucose consumption in resting state. Local-direct connections (i.e., nodes separated by less than 30 mm) and node modularity (i.e., a set of nodes highly interconnected within a topological community and sparsely interconnected with nodes from other modules) in the functional network were identified as the main determinants of coupling between cortical networks, suggesting that the structural network in aging is mainly constrained by functional topological properties involved in the segregation of information, likely due to aging-related deficits in functional integration. This hypothesis is supported by an enhanced connectivity between cortical regions of different resting-state networks involved in sensorimotor and memory functions in detrimental to associations between fronto-parietal regions supporting executive processes. Taken collectively, these findings open new avenues to identify aging-related failures in the anatomo-functional organization of the neocortical mantle, and might contribute to early detection of prevalent neurodegenerative conditions occurring in the late life.
| S-EPMC6869592 | biostudies-literature
Project description:Visual processing and attention deficits are responsible for a substantial portion of the disability caused by schizophrenia, but the source of these deficits remains unclear. In 35 schizophrenia patients (SzP) and 34 healthy controls (HC), we used a rapid serial visual presentation (RSVP) visual search task designed to activate/deactivate the cortical components of the attentional control system (i.e. the dorsal and ventral attention networks, lateral prefrontal regions in the frontoparietal network, and cingulo-opercular/salience networks), along with resting state functional connectivity, to examine the integrity of these components. While we find that behavioral performance and activation/deactivation of the RSVP task are largely similar between groups, SzP exhibited decreased functional connectivity within late visual components and between prefrontal and other components. We also find that performance correlates with the deactivation of the ventral attention network in SzP only. This relationship is mediated by the functional connectivity of critical components of the attentional control system. In summary, our results suggest that the attentional control system is potentially used to compensate for visual cortex deficits. Furthermore, prefrontal deficits in SzP may interfere with this compensatory use of the attentional control system. In addition to highlighting focal deficits and potential compensatory mechanisms in visual processing and attention, our findings point to the attentional control system as a potential target for rehabilitation and neuromodulation-based treatments for visual processing deficits in SzP.
| S-EPMC7393326 | biostudies-literature
Project description:Individuals with Autism Spectrum Disorder (ASD) experience a variety of symptoms sometimes including atypicalities in language use. The study explored differences in semantic network organisation of adults with ASD without intellectual impairment. We assessed clusters and switches in verbal fluency tasks ('animals', 'human feature', 'verbs', 'r-words') via curve fitting in combination with corpus-driven analysis of semantic relatedness and evaluated socio-emotional and motor action related content. Compared to participants without ASD (n?=?39), participants with ASD (n?=?32) tended to produce smaller clusters, longer switches, and fewer words in semantic conditions (no p values survived Bonferroni-correction), whereas relatedness and content were similar. In ASD, semantic networks underlying cluster formation appeared comparably small without affecting strength of associations or content.
| S-EPMC7560923 | biostudies-literature
Project description:A computational approach for estimating several indices of performance on the animal category verbal fluency task was validated, and examined in a large longitudinal study of aging. The performance indices included the traditional verbal fluency score, size of semantic clusters, density of repeated words, as well as measures of semantic and lexical diversity. Change over time in these measures was modeled using mixed effects regression in several groups of participants, including those that remained cognitively normal throughout the study (CN) and those that were diagnosed with mild cognitive impairment (MCI) or Alzheimer's disease (AD) dementia at some point subsequent to the baseline visit. The results of the study show that, with the exception of mean cluster size, the indices showed significantly greater declines in the MCI and AD dementia groups as compared to CN participants. Examination of associations between the indices and cognitive domains of memory, attention and visuospatial functioning showed that the traditional verbal fluency scores were associated with declines in all three domains, whereas semantic and lexical diversity measures were associated with declines only in the visuospatial domain. Baseline repetition density was associated with declines in memory and visuospatial domains. Examination of lexical and semantic diversity measures in subgroups with high vs. low attention scores (but normal functioning in other domains) showed that the performance of individuals with low attention was influenced more by word frequency rather than strength of semantic relatedness between words. These findings suggest that various automatically semantic indices may be used to examine various aspects of cognitive performance affected by dementia.
| S-EPMC4996679 | biostudies-literature
Project description:Semantic verbal fluency (sVF) tasks are commonly used in clinical diagnostic batteries as well as in a research context. When performing sVF tasks to assess executive functions (EFs) the sum of correctly produced words is the main measure. Although previous research indicates potentially better insights into EF performance by the use of finer grained sVF information, this has not yet been objectively evaluated. To investigate the potential of employing a finer grained sVF feature set to predict EF performance, healthy monolingual German speaking participants (n = 230) were tested with a comprehensive EF test battery and sVF tasks, from which features including sum scores, error types, speech breaks and semantic relatedness were extracted. A machine learning method was applied to predict EF scores from sVF features in previously unseen subjects. To investigate the predictive power of the advanced sVF feature set, we compared it to the commonly used sum score analysis. Results revealed that 8 / 14 EF tests were predicted significantly using the comprehensive sVF feature set, which outperformed sum scores particularly in predicting cognitive flexibility and inhibitory processes. These findings highlight the predictive potential of a comprehensive evaluation of sVF tasks which might be used as diagnostic screening of EFs.
| S-EPMC7994566 | biostudies-literature
Project description:IntroductionIn recent decades, researchers have defined novel methods for scoring verbal fluency tasks. In this work, we evaluate novel scores based on speed of word responses.MethodsWe transcribed verbal fluency recordings from 641 cases of incident cognitive impairment (ICI) and matched controls, all participants in a large national epidemiological study. Timing measurements of utterances were used to calculate a speed score for each recording. Traditional raw and speed scores were entered into Cox proportional hazards (CPH) regression models predicting time to ICI.ResultsConcordance of the CPH model with speed scores was 0.599, an improvement of 3.4% over a model with only raw scores and demographics. Scores with significant effects included animals raw and speed scores, and letter F speed score.DiscussionNovel verbal fluency scores based on response times could enable use of remotely administered fluency tasks for early detection of cognitive decline.Highlights The current work evaluates prognostication with verbal fluency speed scores. These speed scores improve survival models predicting cognitive decline. Cases with progressive decline have some characteristics suggestive of Alzheimer's disease. The subset of acute decliners is probably pathologically heterogeneous.
| S-EPMC9074715 | biostudies-literature
Project description:Background: Verbal fluency (VF) has been associated with several cognitive functions, but the cognitive processes underlying verbal fluency deficits in Multiple Sclerosis (MS) are controversial. Further knowledge about VF could be useful in clinical practice, because these tasks are brief, applicable, and reliable in MS patients. In this study, we aimed to evaluate the cognitive processes related to VF and to develop machine-learning algorithms to predict those patients with cognitive deficits using only VF-derived scores. Methods: Two hundred participants with MS were enrolled and examined using a comprehensive neuropsychological battery, including semantic and phonemic fluencies. Automatic linear modeling was used to identify the neuropsychological test predictors of VF scores. Furthermore, machine-learning algorithms (support vector machines, random forest) were developed to predict those patients with cognitive deficits using only VF-derived scores. Results: Neuropsychological tests associated with attention-executive functioning, memory, and language were the main predictors of the different fluency scores. However, the importance of memory was greater in semantic fluency and clustering scores, and executive functioning in phonemic fluency and switching. Machine learning algorithms predicted general cognitive impairment and executive dysfunction, with F1-scores over 67-71%. Conclusions: VF was influenced by many other cognitive processes, mainly including attention-executive functioning, episodic memory, and language. Semantic fluency and clustering were more explained by memory function, while phonemic fluency and switching were more related to executive functioning. Our study supports that the multiple cognitive components underlying VF tasks in MS could serve for screening purposes and the detection of executive dysfunction.
| S-EPMC7859643 | biostudies-literature