Cognitive compensatory mechanisms in normal aging: a study on verbal fluency and the contribution of other cognitive functions

Abstract

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.

The Interplay Between Gray Matter and White Matter Neurodegeneration in Subjective Cognitive Decline

“…A total of 225 individuals were selected from the GENIC cohort [35], a community-based study from the Canary Islands (Spain). Inclusion criteria for the current study were in accord with the basic SCD criteria published by the SCD initiative (SCD-I) working group [4]: (1) Normal cognitive performance in comprehensive neuropsychological assessment using pertinent clinical normative data (i.e., individuals did not ful ll cognitive criteria for mild cognitive impairment or dementia); (2) preserved activities of daily living and global cognition, operationalized as a Blessed Rating Dementia Scale (BRDS) [36] score ≤ 4, a Functional Activity Questionnaire (FAQ) [37] score ≤ 5, and a Mini-Mental State Examination (MMSE) [38] score ≥ 24; (3) No abnormal ndings such as stroke, tumors, hippocampal sclerosis, etc., in MRI according to an experienced neuroradiologist; (4) no medical history of neurological or psychiatric disorders (including a diagnosis of major depression), systemic diseases or head trauma; and (5) no history of substance abuse.…”

Cognitive reserve and network efficiency as compensatory mechanisms of the effect of aging on phonemic fluency

“…In our previous study, we showed that the contribution of cognitive functions to verbal fluency differed across age groups, and we suggested that this could be due to compensatory processes [ 9 ]. In the current study, we confirm that hypothesis and show that high CR and efficiency levels could be at the base of compensatory mechanisms to maintain performance in phonemic fluency with increasing age.…”

“…Compensation refers to the maintenance or enhancement of performance by recruiting brain areas or networks not normally used for a specific task, as a response to brain deterioration [ 7 ] or high cognitive demands [ 8 ]. From a cognitive perspective, compensation can be approached by investigating how different cognitive functions are associated with or contribute to language abilities [ 9 ]. In particular, performance in phonemic fluency has been associated with processing speed [ 10 – 12 ], attention [ 13 , 14 ], lexical access [ 15 ], executive functions [ 14 , 16 – 19 ], and memory [ 14 , 20 ].…”

“…Due to the complexity of human cognition, an interesting approach is to investigate the contribution of different cognitive functions to verbal fluency by using multivariate methods for data analysis. We previously used the random forest multivariate method to investigate the contribution of 45 cognitive variables to phonemic fluency [ 9 ]. In younger individuals, lexical access, working memory, processing speed, and visuoconstructive abilities were the most contributing functions to performance in phonemic fluency.…”

Cognitive‐communication difficulties following traumatic brain injury sustained in older adulthood: a scoping review

“…Linguistic tasks including accuracy and speed of confrontational picture naming (Tsang and Lee 2003) and those mediated by cognitive processes, such as verbal fluency (Gonzalez‐Burgos et al . 2019), have also been shown to be vulnerable to age. Further, non‐uniform differences in some aspects of discourse production of older adults have been demonstrated with age (Sherratt and Bryan 2019).…”