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Symposium Session 1 - The hunt for the neural correlates of Cognitive Reserve

Chairs: Prof Richard Henson¹, Christian Habeck²; ¹University of Cambridge, ²Columbia University
Presenters: Richard Henson, Feng Deng, Zoya Mooraj, Christian Habeck

The term “Cognitive Reserve” was coined by neurologists to describe how people can show comparable atrophy on a clinical brain scan, owing to old age or Alzheimer’s Disease for example, yet differ markedly in their cognitive function. However, despite attempts at a consensus definition, there have been critiques of the term, and debates about how to operationalise it. One core issue is that Cognitive Reserve could simply reflect limitations of brain measurement, e.g., insufficient information disclosed by a typical clinical, “structural” MRI scan (such as gray-matter volumetrics). As a consequence, there have been recent efforts to explain Cognitive Reserve by other brain properties, such as white-matter microstructure from diffusion-weighted MRI, functional activity or connectivity measured by fMRI or M/EEG, neurovascular health measured by ASL, or even neurotransmitter concentrations measured by PET. In a sense, this “hunt” for the neural correlates of Cognitive Reserve is central to the field of cognitive neuroscience: i.e., establishing the brain bases of cognitive functions. Identifying at least some of these potential neural correlates will help illuminate the mechanisms of successful ageing and resilience to neurodegeneration, and how these relate to lifestyle factors associated with high levels of reserve, in turn informing future interventions. This symposium will bring together four speakers, diverse in their seniority, gender and geography, who will describe the results of their recent hunts.

Presentations

Re-thinking Cognitive Reserve

Richard Henson¹; ¹University of Cambridge

I will briefly introduce the history and various definitions of Cognitive Reserve, e.g., in relation to brain reserve and brain maintenance, and propose a formal definition based on simulations of a simple model that relates age, brain and cognition. I will then describe findings from the Cambridge Centre of Ageing and Neuroscience (Cam-CAN) that demonstrate that white-matter integrity (mean signal kurtosis from diffusion-weighted MRI) and functional connectivity (from resting-state fMRI) both explain unique variance in fluid intelligence beyond the grey-matter volumetrics normally examined on a clinical T1-weighted scan. I will talk about research on lifestyles that might boost cognitive reserve, in particular our findings that mid-life activities outside the work-place make a unique contribution to fluid intelligence decades later in late life, and attenuate the relationship between fluid intelligence and total grey-matter volume (as would be expected for cognitive reserve). I will finish with our hunt for the neural correlates of such mid-life activities, focusing in particular on the system segregation of functional brain networks.

Cognitive Reserve in Midlife: Lifestyle Factors Decouple Cognition from Functional Segregation in Healthy Individuals at Risk for Late-Onset Dementia

Feng Deng¹; ¹Shenzhen University

The concept of cognitive reserve seeks to explain the discrepancy between the degree of brain pathology and clinical manifestations of cognitive decline in conditions such as Alzheimer’s disease. However, its neural underpinnings remain poorly understood. In this presentation, I will share findings from the PREVENT Dementia study demonstrating that reduced network segregation, particularly within the default mode network, is associated with both APOE ε4 genetic risk and lower cognitive performance in cognitively healthy middle-aged adults enriched with Alzheimer’s disease risk factors. Critically, we found that mid-life engagement in cognitively stimulating activities moderates the relationship between cognitive ability and network segregation. Specifically, individuals with higher levels of engagement—particularly those at elevated genetic risk—show a weaker dependence of cognition on functional network segregation. These findings suggest that an active and stimulating lifestyle may enhance cognitive reserve by decoupling cognitive performance from underlying functional network alterations, thereby promoting resilience in the presence of early Alzheimer’s pathology. This work positions functional network segregation as a promising brain health marker, particularly in populations without substantial structural decline, suggesting that it may serve as a sensitive indicator of early, functional alterations prior to observable anatomical changes. Moreover, it highlights the protective potential of modifiable mid-life lifestyle factors.

Shared and Unique Neural Contributions to Cognitive Reserve

Zoya Mooraj¹; ¹Max Planck Institute for Human Development

The concept of Cognitive Reserve arose from observations of some individuals displaying marked brain atrophy without expected cognitive deficits. While this discrepancy has stimulated decades of research, a central limitation lies in making inferences of cognitive relevance based on brain structure alone. I will first outline why such inferences are logically problematic, requiring convergent evidence of shared variance between brain structure, cognition, and task-based brain function. Furthermore, given the complex and multifaceted neurobiology of aging, it is unlikely that any single modality in isolation will fully explain the neural underpinnings of cognitive aging. I will thus describe our perspective on why the cognitive neuroscience of aging must prioritize a multimodally-imaged, functionally-interrogated approach to understand brain-behaviour relationships and uncover the neural correlates of Cognitive Reserve. Building on this perspective, I will present work integrating longitudinal structural MRI, task-based fMRI, and dopaminergic PET data from 120 older adults (aged 64-68 at baseline) measured twice over 5-years. Using whole-brain voxel-wise multivariate analyses, we aimed to disentangle the joint and unique influences of changes in brain structure, function, and neurochemistry to changing cognition in aging. We find that (a) nearly all variance in cognition explained by brain structure is shared with task-based function, and (b) task-based function additionally accounts for substantial unique variance beyond other measures. These findings strengthen our call for a reorientation of the cognitive neuroscience of aging towards a functional future. Such a multimodal, functionally-anchored approach will likely prove promising in uncovering the neural mechanisms underlying Cognitive Reserve.

Cognitive Reserve in the NIH-funded “Reserve and Resilience” initiative

Christian Habeck¹; ¹Columbia University

Cognitive Reserve has been a flourishing area of neuroscience research since the late 1980s when autopsy studies revealed striking disjunctures between the degree of pathology and late-life clinical impairment in some dementia patients. Despite the importance of Cognitive Reserve (CR) to cognitive aging, research communication and the accumulation of knowledge have been hampered by a lack of common framework of definitions. To this end, the ongoing NIH-funded “Reserve and Resilience” Collaboratory has worked on conceptual and operational definitions for CR research since 2019. (See https://reserveandresilience.com/.) After introducing the Collaboratory and the framework, I will motivate our research program to identify CR as network-based mechanisms measurable with fMRI that confer cognitive benefit beyond brain-structural endowments. I will provide several examples in the lifespan cohort of the Columbia Reference Ability Neural Network (RANN) study. In our data, which encompass fMRI activation for 12 cognitive tasks pertaining to 4 cognitive domains (memory, reasoning, speed, and vocabulary), we can compute convergent and discriminant validity of task activation patterns within subject, which quantify to what extent activation patterns are similar within cognitive domain, and different between cognitive domains, respectively. Both validity measures can be summarized into one scalar measure that operationalizes the cognitive specificity of fMRI activation patterns. This cognitive specificity is related to higher general task performance beyond regional cortical thickness and cortical volume in our data, and qualifies as one mechanism of CR.