How does ‘cognitive reserve’ fit in with the current neurocognitive aging models?

Changes that occur with age can manifest in various ways for example in terms of biological and functional deterioration: atrophies in certain brain regions and memory problems. However older patients who have neurological symptoms do not always develop the same cognitive deficits. These results led to the question: Why are some older people better at coping with brain damage than others? This has consequently led to the model of ‘cognitive reserve’ which I will explain below. Then I will briefly look into a few of the different models that have been formulated to make sense of what happens when the brain ages and finally conclude on how cognitive reserve fits in with these models.

1. Cognitive reserve
2. Compensation and aging models
3. How does ‘cognitive reserve’ fit in with the current aging models?

1. Cognitive reserve

Firstly ‘reserve’ is used to explain this phenomenon that some people who have brain damage do not show cognitive impairment. Reserve refers to the areas that remain unaffected by brain damage.

With emphasis on the physical brain structures spared i.e. brain volume, neural count, etc., the brain reserve hypothesis suggests that people with a larger percentage of brain areas kept intact will be better at overcoming potential cognitive impairment (Satz, 1993).
Whereas cognitive reserve (Stern, 2002, 2008) focuses on how well the individual’s brain networks have maintained their efficiency and capacity to change their strategies. So the big difference between the two is that brain reserve states that this ability to cope is purely based on the machinery and there is a set threshold of brain damage that once reached will inevitably result in cognitive impairment and/or disease. The cognitive reserve hypothesis on the other hand argues that the amount of brain damage does not directly relate to cognitive disruption and varies due to individual differences so the threshold differs from person to person. These differences can be affected by multiple factors which can be biologically determined, but also from external surroundings (Stern et al., 2018).

This process is a way of coping with future atrophies in the brain and explains the observation that people with higher levels of education and intelligence did not show the cognitive effects of the same amount of brain damage as others with lower education. Essentially the more reserve one has, the better the brain is at using these other approaches and thus making it a stronger force against the biological insult.

2. Compensation models

The other form of reserve described by Stern is ‘compensation’ which is the adoption of other brain regions that are not used when the brain is not damaged (Stern, 2002).

From previous research it has been argued that older adults made use of prefrontal areas during certain tasks when younger adults did not. Also people with Alzheimer’s disease (AD) brain activity’s may differ compared to healthy people in the same age group. One PET study comparing episodic memory performance between AD patients and normal elderly adults found that both groups had similar patterns of activity, but the specific areas used were different (Bäckman, 1999). Left parietal cortex and left hippocampal formation were activated in normal elderly adults for episodic retrieval. Left orbital prefrontal cortex and left cerebellum in AD patients were activated when performing cued recall.

However one study showed that Alzheimer’s disease (AD) patients did not utilise new brain areas, but actually used the same as healthy age-matched adults whilst undertaking a visuospatial paired associates learning task (Gould et al., 2006). Differences were only found between the two groups in terms of brain activation when encoding of two object locations were successful. AD patients did display increased activity of left medial and right lateral prefrontal cortices when encoding of two object locations, whereas this was not the case in the controls when they encoded three object locations (Gould et al., 2006).

2.1 STAC (Park & Reuter-Lorenz, 2009)

‘The Scaffolding Theory of Aging and Cognition’ or STAC was first proposed in 2009 and is a cognitive aging model that explains the differences in cognitive abilities that can be explained by adverse effects and compensation that are a result of aging (Park & Reuter-Lorenz, 2009). The STAC model is based on the idea that in order to deal with the structural damage, the older brain changes itself by using other parts of the brain as ‘scaffolds’. Although the authors do emphasise that this scaffolding effect is present throughout the lifespan in order to tackle challenges and is not specific to aging. This model potentially explains why previous functional imaging research has found overactivation of the prefrontal cortex in combination with underactivation in areas such as occipital and temporal lobes - this finding is referred to posterior-anterior shift in aging or PASA (Davis et al., 2008). Therefore the activation of the prefrontal areas acts as a way of compensating for other malfunctioning areas.

2.1.1 STAC-r (Reuter-Lorenz & Park, 2014)

The additional ‘r’ in the name stands for ‘revised’ and as the name suggests is a newer version of the original STAC model. The major difference between this and the original is that it takes into consideration the positive and negative changes that occur across in ones’ lifetime e.g. education, depression.

2.2 CRUNCH (Reuter-Lorenz & Cappell, 2008)

Findings have shown that both under- and overactivation of brain areas seem to take place during cognitive tasks in older adults compared to their younger counterparts and this depended on the task at hand and the difficulty of the tasks. Compensatory-related utilisation of neural circuits hypothesis (CRUNCH) model explains that more neural resources are used by older brains in order to accomplish computational goals completed with fewer resources by younger brains. As the demand of a task increases this compensatory process reaches a ‘resource ceiling’ (Festini, Zahodne & Reuter-Lorenz, 2018) where the performance begins to suffer. So older adults are more likely than younger adults to show overactivation at lower memory loads and underactivation at higher memory loads. This is evident from one study that found older adults displayed overactivation of the dorsolateral prefrontal cortex (DLPFC) at lower memory loads and higher memory loads resulted in lower DLPFC activation compared to younger adults (Mattay et al., 2006). Performance by older adults was also worse in comparison to the younger participants.

2.3 HAROLD (Cabeza)

Hemispheric Asymmetry Reduction in Older Adults (HAROLD) is based on the findings that have shown that during a verbal recall task that older participants showed a bilateral use of the prefrontal cortex (PFC) compared to younger participants. Previously encoding and retrieval of episodic memory tasks in younger adults showed a left lateralization in the PFC for encoding and right lateralized activation for retrieval (Tulving et al., 1994). This finding suggests that the older brain is working harder to perform the task.

The use of both left and right hemispheres was present in higher performing older adults (Cabeza, 2002). Furthermore when rTMS was applied to left and right hemispheres of the DLPFC during a recognition task there were contrasting results for young vs. old participants. Older adults benefited from stimulation to both hemispheres whereas the young adults’ retrieval performance was only significantly affected by stimulation to the left hemisphere.

3. Conclusion

There is a clear relationship between the STAC model and the concepts of cognitive reserve and compensation. STAC supports the idea that novel networks are used by older adults to deal with the challenges that the aging brain faces. Secondly the individual differences found in cognitive performance can be explained by both models as they argue that the efficiency of using certain strategies. The cognitive reserve hypothesis mentions that this variation is multidimensional and can be due to factors such as education, training, exercise and this is mentioned in the STAC model as well. Although the big difference between the two being that the STAC model is not exclusive to explaining aging, but can be applied to any challenges that occur during the lifespan. Additionally the STAC-r model incorporates negative factors (cognitive reserve focuses only on enriching factors) that affect the brain in terms of its structure, function and efficiency to use networks. These factors can be present even when brain pathology is not evident.

In parallel to the STAC model, bilateral activation in older adults can be seen as a compensatory process. However the HAROLD model unlike CRUNCH is not specific to the individual and is more of a simplified approach to explain cognitive aging. Furthermore the model is centred around the prefrontal area, in contrast the CRUNCH and STAC models do not focus on this area alone. HAROLD also does not mention task difficulty as measure and how it affects cognitive performance. It can also be argued that the HAROLD model does not give any explanation to why this hemispheric manifestation occurs (Festini, Zahodne & Reuter-Lorenz, 2018). Also cognitive reserve does not fit in with this model as it focuses on the overall differences rather than the individual’s specific resilience to aging.

In summary, all of these models are based on the concept of brain plasticity, yet not one can fully explain how aging works. Aging is a complex process that is influenced by multiple factors, although the research is definitely moving towards these processes.

References

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Cabeza, R. (2002). Hemispheric asymmetry reduction in older adults: the HAROLD model. Psychology and aging, 17(1), 85.

Davis, S. W., Dennis, N. A., Daselaar, S. M., Fleck, M. S., & Cabeza, R. (2008). Que PASA? The posterior–anterior shift in aging. Cerebral cortex, 18(5), 1201-1209.

Festini, S. B., Zahodne, L., & Reuter-Lorenz, P. A. (2018). Theoretical Perspectives on Age Differences in Brain Activation: HAROLD, PASA, CRUNCH—How Do They STAC Up?. In Oxford Research Encyclopedia of Psychology.

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Satz, P. (1993). Brain reserve capacity on symptom onset after brain injury: a formulation and review of evidence for threshold theory. Neuropsychology, 7(3), 273.

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Stern, Y., Zarahn, E., Habeck, C., Holtzer, R., Rakitin, B. C., Kumar, A., … & Brown, T. (2008). A common neural network for cognitive reserve in verbal and object working memory in young but not old. Cerebral Cortex, 18(4), 959-967.

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