Study provides an important advancement of knowledge by showing neural compensation in healthy aging brains

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A recent study posted eLife Preprint server, researchers performed voxel-wise functional magnetic resonance imaging (fMRI) of the whole brain to identify brain regions with functional type compensation. They investigated the neurophysiological changes that maintain cognitive function in older adults.

Study: Neural evidence of functional compensation for fluid intelligence in healthy aging.  Image credit: LightField Studios/Shutterstock.com
Study: Neural evidence of functional compensation for fluid intelligence in healthy aging. Image credit: LightField Studios/Shutterstock.com

*Important Notice: Preprint Preliminary scientific reports are published that are not peer-reviewed and, therefore, should not be considered conclusive, guidelines for clinical practice/health-related behavior, or established information.

Background

Age-related functional compensatory mechanisms are controversial in the cognitive neurobiology of healthy aging, according to which older individuals increase brain activity to compensate for cognitive decline. However, whether extra brain activity helps cognitive performance is uncertain. Neuroimaging reveals that the human brain can adapt to tissue damage by increasing brain activity to maintain cognitive function. Age similarly affects fluid intelligence, a cognitive skill.

About the study

In the current study, researchers used fMRI data from a fluid intelligence test to identify brain regions involved in functional compensation and to understand the brain’s responses to tissue damage. They explored the relationship between age-related changes in brain activation and cognitive performance, particularly fluid intelligence tasks.

The team analyzed data from 223 adult participants in the Cambridge Center for Aging Neuroscience (CAM-CAN) study to examine the relationship between age, cognitive performance and brain activation patterns. Participants were aged 19 to 87 years, fluent in English, and mentally and physically fit, with MRI contraindications, poor Mini-Mental State Examination (MMSE) scores, and psychiatric, medical, visual, or hearing impairments.

The team performed functional and structural neuroimaging to study the relationship between age, cognitive performance and brain activation patterns. They performed a problem-solving task based on the modified Cattle Culture Fair Intelligence Test during fMRI. They scanned participants during a Cattle Fluid Intelligence task, completing puzzles from two difficulty levels, to determine whether candidate compensatory regions exhibited multimodal evidence of compensation.

Dependent variables were functional MRI activation differences for hard vs. Simple task block. The team used multivariate Bayesian decoding (MVB) to explore the role of multivoxel patterning in providing additional data about task difficulty. They predicted that regions associated with functional compensation would have more work-related data with age. MVB was used to identify areas with additional multivariate data and to support functional-type compensation, which involves increased brain activity to support cognitive functions in response to tissue damage.

To identify patterns of brain activation, the team examined maps for positive effects of age and brain function, hard vs. Simple contrast. They used multiple regressions for analysis, with activation maps reflecting the unique effects of each. The team repeated multiple regressions after scaling the effect of cathel activation by estimating the resting state fluctuation amplitude (RSFA) for each region of interest (ROI) from an independent resting-state scan for each participant.

The team analyzed participants’ data using boxcar functions and statistical parametric mapping (SPM) hemodynamic response functions, fitting a model to each voxel. They defined functional compensation ROIs, cuneal and frontal cortex, by empirical Bayes approach. They standardized and treated age and behavioral performance variables as linear predictors.

result

Bilateral cuneal cortical activity increased with performance and hard versus age. simple problem, even after adjusting for age-related differences in cerebrovascular reactivation. The cuneus region showed multivariate data supporting functional compensation, and age raised the possibility of activation patterns, providing non-redundant data beyond the MDN task typically activated in the task.

A modified Cattle task showed a decline in behavioral performance with age during fMRI scans. A strong correlation was found between fMRI and standard cattle task performance measures when performed one to three years earlier. Bilateral activation in multiple demand network (MDN) regions, including the intraparietal sulcus, middle/inferior frontal gyri, anterior cingulate cortical region, anterior insula, and lateral and ventral occipital temporal cortical regions, was observed, presumably due to visual-type tasks. such as problem solving and fluid intelligence.

Age-related increases in activity in regions between the frontal gyrus, precuneus, and motor supplementary areas were positively associated with performance in regions with stiff versus high activity. easy job

Two brain regions, bilateral cuneal and frontal cortical regions, exhibited spatially overlapping positive effects of performance and age, indicating an age-related compensatory response. However, the frontal area demonstrated additional effects of both study variables, while the cuneus area showed signs of interaction. Studies have shown that age significantly affects performance because older people engage in compensatory patterns.

Conclusion

Overall, the results of the study showed that healthy older adults compensate for fluid intelligence during visual problem-solving tasks by increasing the recruitment of bilateral cingulate cortex. Compensation allows the brain to respond to tissue damage by increasing cognitive function, known as functional compensation. Fluid intelligence, which involves abstract problem solving, declines with age. Involvement of the MDN in fluid-intelligence tasks tends to decline with age. The cuneus region may play a role in functional compensation and its activation increases with age.

*Important Notice: Preprint Preliminary scientific reports are published that are not peer-reviewed and, therefore, should not be considered conclusive, guidelines for clinical practice/health-related behavior, or established information.



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