Theoretical Perspectives on Age Differences in Brain Activation: HAROLD, PASA, CRUNCH—How Do They STAC Up?

Cognitive neuroimaging studies often report that older adults display more activation of neural networks relative to younger adults, referred to as overactivation. Greater or more widespread activity frequently involves bilateral recruitment of both cerebral hemispheres, especially the frontal cortex. In many reports, overactivation has been associated with superior cognitive performance, suggesting that this activity may reflect compensatory processes that offset age-related decline and maintain behavior. Several theories have been proposed to account for age differences in brain activation, including the Hemispheric Asymmetry Reduction in Older Adults (HAROLD) model, the Posterior-Anterior Shift in Aging (PASA) theory, the Compensation-Related Utilization of Neural Circuits Hypothesis (CRUNCH), and the Scaffolding Theory of Aging and Cognition (STAC and STAC-r). Each model has a different explanatory scope with regard to compensatory processes, and each has been highly influential in the field. HAROLD contrasts the general pattern of bilateral prefrontal activation in older adults with that of more unilateral activation in younger adults. PASA describes both anterior (e.g., frontal) overactivation and posterior (e.g., occipital) underactivation in older adults relative to younger adults. CRUNCH emphasizes that the level or extent of brain activity can change in response to the level of task demand at any age. Finally, STAC and STAC-r take the broadest perspective to incorporate individual differences in brain structure, the capacity to implement functional scaffolding, and life-course neural enrichment and depletion factors to predict cognition and cognitive change across the lifespan. Extant empirical work has documented that compensatory overactivation can be observed in regions beyond the prefrontal cortex, that variations in task difficulty influence the degree of brain activation, and that younger adults can show compensatory overactivation under high mental demands. Additional research utilizing experimental designs (e.g., transcranial magnetic stimulation), longitudinal assessments, greater regional precision, both verbal and nonverbal material, and measures of individual difference factors will continue to refine our understanding of age-related activation differences and adjudicate among these various accounts of neurocognitive aging.

[1]  R. Cabeza,et al.  Frontal lobes and aging : Deterioration and Compensation , 2011 .

[2]  Vijeth Iyengar,et al.  Less wiring, more firing: low-performing older adults compensate for impaired white matter with greater neural activity. , 2015, Cerebral cortex.

[3]  L. M. Sacheli,et al.  With time on our side? Task-dependent compensatory processes in graceful aging , 2010, Experimental Brain Research.

[4]  S. MacDonald,et al.  Dopamine D1 receptors and age differences in brain activation during working memory , 2011, Neurobiology of Aging.

[5]  P. Baltes,et al.  Emergence of a powerful connection between sensory and cognitive functions across the adult life span: a new window to the study of cognitive aging? , 1997, Psychology and aging.

[6]  L. Nyberg,et al.  Memory aging and brain maintenance , 2012, Trends in Cognitive Sciences.

[7]  Jonas Persson,et al.  Longitudinal structure-function correlates in elderly reveal MTL dysfunction with cognitive decline. , 2012, Cerebral cortex.

[8]  P. Greenwood Functional plasticity in cognitive aging: review and hypothesis. , 2007, Neuropsychology.

[9]  J D E Gabrieli,et al.  Age-associated reduction of asymmetry in prefrontal function and preservation of conceptual repetition priming , 2009, NeuroImage.

[10]  Victoria J. Williams,et al.  FMRI activity during associative encoding is correlated with cardiorespiratory fitness and source memory performance in older adults , 2017, Cortex.

[11]  Keith A. Johnson,et al.  Amyloid Deposition Is Associated with Impaired Default Network Function in Older Persons without Dementia , 2009, Neuron.

[12]  Hans-Jochen Heinze,et al.  Functional phenotyping of successful aging in long‐term memory: Preserved performance in the absence of neural compensation , 2010, Hippocampus.

[13]  David Badre,et al.  Cognitive control, hierarchy, and the rostro–caudal organization of the frontal lobes , 2008, Trends in Cognitive Sciences.

[14]  Claudio Babiloni,et al.  Age-Related Functional Changes of Prefrontal Cortex in Long-Term Memory: A Repetitive Transcranial Magnetic Stimulation Study , 2004, The Journal of Neuroscience.

[15]  Kristen M. Kennedy,et al.  Age trajectories of functional activation under conditions of low and high processing demands: An adult lifespan fMRI study of the aging brain , 2015, NeuroImage.

[16]  R. Cabeza,et al.  Neuroimaging of Healthy Cognitive Aging , 2011 .

[17]  Cheryl L. Grady,et al.  Increased activity in frontal motor cortex compensates impaired speech perception in older adults , 2016, Nature Communications.

[18]  Peter Thier,et al.  Bilateral recruitment of prefrontal cortex in working memory is associated with task demand but not with age , 2017, Proceedings of the National Academy of Sciences.

[19]  Pamela K. Smith,et al.  Models of visuospatial and verbal memory across the adult life span. , 2002, Psychology and aging.

[20]  Robert C. Welsh,et al.  Aging and the Neural Correlates of Successful Picture Encoding: Frontal Activations Compensate for Decreased Medial-Temporal Activity , 2005, Journal of Cognitive Neuroscience.

[21]  L. Nyberg,et al.  Functional brain imaging of episodic memory decline in ageing , 2017, Journal of internal medicine.

[22]  Stephen C. Strother,et al.  The Associative Memory Deficit in Aging Is Related to Reduced Selectivity of Brain Activity during Encoding , 2016, Journal of Cognitive Neuroscience.

[23]  E. Paulesu,et al.  Reassessing the HAROLD model: Is the hemispheric asymmetry reduction in older adults a special case of compensatory-related utilisation of neural circuits? , 2013, Experimental Brain Research.

[24]  R. N. Spreng,et al.  Executive functions and neurocognitive aging: dissociable patterns of brain activity , 2012, Neurobiology of Aging.

[25]  N. Raz,et al.  Appraising the Role of Iron in Brain Aging and Cognition: Promises and Limitations of MRI Methods , 2015, Neuropsychology Review.

[26]  Y. Stern,et al.  Efficiency, capacity, compensation, maintenance, plasticity: emerging concepts in cognitive reserve , 2013, Trends in Cognitive Sciences.

[27]  Brittany R. Alperin,et al.  Investigating the age-related "anterior shift" in the scalp distribution of the P3b component using principal component analysis. , 2014, Psychophysiology.

[28]  Denise C. Park,et al.  The adaptive brain: aging and neurocognitive scaffolding. , 2009, Annual review of psychology.

[29]  Anthony R. McIntosh,et al.  Age-Related Differences in Neural Activity during Memory Encoding and Retrieval: A Positron Emission Tomography Study , 1997, The Journal of Neuroscience.

[30]  A. Meyer-Lindenberg,et al.  Neurophysiological correlates of age-related changes in working memory capacity , 2006, Neuroscience Letters.

[31]  Kristen M. Kennedy,et al.  Effects of beta-amyloid accumulation on neural function during encoding across the adult lifespan , 2012, NeuroImage.

[32]  Bart Rypma,et al.  Neural and vascular variability and the fMRI-BOLD response in normal aging. , 2010, Magnetic resonance imaging.

[33]  Denise C. Park,et al.  Neural Broadening or Neural Attenuation? Investigating Age-Related Dedifferentiation in the Face Network in a Large Lifespan Sample , 2012, The Journal of Neuroscience.

[34]  David Maillet,et al.  Context Memory Decline in Middle Aged Adults is Related to Changes in Prefrontal Cortex Function. , 2016, Cerebral cortex.

[35]  Patricia A. Reuter-Lorenz,et al.  How Does it STAC Up? Revisiting the Scaffolding Theory of Aging and Cognition , 2014, Neuropsychology Review.

[36]  R. N. Spreng,et al.  Reliable differences in brain activity between young and old adults: A quantitative meta-analysis across multiple cognitive domains , 2010, Neuroscience & Biobehavioral Reviews.

[37]  Edward E. Smith,et al.  Age Differences in the Frontal Lateralization of Verbal and Spatial Working Memory Revealed by PET , 2000, Journal of Cognitive Neuroscience.

[38]  P. Reuter-Lorenz New visions of the aging mind and brain , 2002, Trends in Cognitive Sciences.

[39]  M. Banich The Missing Link: The Role of Interhemispheric Interaction in Attentional Processing , 1998, Brain and Cognition.

[40]  Denise C. Park,et al.  Both left and right posterior parietal activations contribute to compensatory processes in normal aging , 2012, Neuropsychologia.

[41]  C. Grady The cognitive neuroscience of ageing , 2012, Nature Reviews Neuroscience.

[42]  Robert A. Koeppe,et al.  Age Differences in Behavior and PET Activation Reveal Differences in Interference Resolution in Verbal Working Memory , 2000, Journal of Cognitive Neuroscience.

[43]  M. Andersson,et al.  Longitudinal evidence for diminished frontal cortex function in aging , 2010, Proceedings of the National Academy of Sciences.

[44]  Ulman Lindenberger,et al.  Trajectories of brain aging in middle-aged and older adults: Regional and individual differences , 2010, NeuroImage.

[45]  S. Belleville,et al.  Relationships between years of education, regional grey matter volumes, and working memory-related brain activity in healthy older adults , 2017, Brain Imaging and Behavior.

[46]  Louise Stanczak,et al.  Neural Recruitment and Cognitive Aging: Two Hemispheres Are Better Than One, Especially as You Age , 1999 .

[47]  Cindy Lustig,et al.  Brain aging: reorganizing discoveries about the aging mind , 2005, Current Opinion in Neurobiology.

[48]  M. Rajah,et al.  Association between prefrontal activity and volume change in prefrontal and medial temporal lobes in aging and dementia: A review , 2013, Ageing Research Reviews.

[49]  P. Baltes,et al.  Intellectual functioning in old and very old age: cross-sectional results from the Berlin Aging Study. , 1997, Psychology and aging.

[50]  Jonas Persson,et al.  Local brain atrophy accounts for functional activity differences in normal aging , 2012, Neurobiology of Aging.

[51]  R. Cabeza,et al.  Task-independent and task-specific age effects on brain activity during working memory, visual attention and episodic retrieval. , 2004, Cerebral cortex.

[52]  P. Reuter-Lorenz,et al.  The Aging Mind and Brain: Implications of Enduring Plasticity for Behavioral and Cultural Change , 2020 .

[53]  Carles Falcón,et al.  Repetitive transcranial magnetic stimulation effects on brain function and cognition among elders with memory dysfunction. A randomized sham-controlled study. , 2006, Cerebral cortex.

[54]  Hauke R. Heekeren,et al.  Performance level modulates adult age differences in brain activation during spatial working memory , 2009, Proceedings of the National Academy of Sciences.

[55]  P. Reuter-Lorenz,et al.  Neurocognitive Aging and the Compensation Hypothesis , 2008 .

[56]  K. Walhovd,et al.  Structural Brain Changes in Aging: Courses, Causes and Cognitive Consequences , 2010, Reviews in the neurosciences.

[57]  Bradley P. Sutton,et al.  Span, CRUNCH, and Beyond: Working Memory Capacity and the Aging Brain , 2010, Journal of Cognitive Neuroscience.

[58]  E. Balteau,et al.  Neural correlates of successful memory retrieval in aging: Do executive functioning and task difficulty matter? , 2016, Brain Research.

[59]  James B. Rowe,et al.  The effect of ageing on fMRI: Correction for the confounding effects of vascular reactivity evaluated by joint fMRI and MEG in 335 adults , 2015, Human brain mapping.

[60]  B. Biswal,et al.  Correspondence of executive function related functional and anatomical alterations in aging brain , 2014, Progress in Neuro-Psychopharmacology and Biological Psychiatry.

[61]  L. Nyberg,et al.  Brain Characteristics of Individuals Resisting Age-Related Cognitive Decline over Two Decades , 2013, The Journal of Neuroscience.

[62]  Mathias Benedek,et al.  Neural efficiency as a function of task demands , 2014, Intelligence.

[63]  Denise C Park,et al.  Neural Specificity Predicts Fluid Processing Ability in Older Adults , 2010, The Journal of Neuroscience.

[64]  Leslie G. Ungerleider,et al.  Age-related changes in cortical blood flow activation during visual processing of faces and location , 1994, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[65]  Priti Shah,et al.  Aging, Training, and the Brain: A Review and Future Directions , 2009, Neuropsychology Review.

[66]  David J. Freedman,et al.  The prefrontal cortex: categories, concepts and cognition. , 2002, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[67]  Alexa M. Morcom,et al.  Neural Reorganization and Compensation in Aging , 2015, Journal of Cognitive Neuroscience.

[68]  S. MacDonald,et al.  Simulating Neurocognitive Aging: Effects of a Dopaminergic Antagonist on Brain Activity During Working Memory , 2010, Biological Psychiatry.

[69]  Christopher A. Brown,et al.  Longitudinal alterations to brain function, structure, and cognitive performance in healthy older adults: A fMRI-DTI study , 2015, Neuropsychologia.

[70]  R. Cabeza Hemispheric asymmetry reduction in older adults: the HAROLD model. , 2002, Psychology and aging.

[71]  Patricia A. Reuter-Lorenz,et al.  Human Neuroscience , 2022 .

[72]  C. Miniussi,et al.  Successful physiological aging and episodic memory: A brain stimulation study , 2011, Behavioural Brain Research.

[73]  X. Zuo,et al.  Neuroscience and Biobehavioral Reviews Putting Age-related Task Activation into Large-scale Brain Networks: a Meta-analysis of 114 Fmri Studies on Healthy Aging , 2022 .

[74]  Y. Stern What is cognitive reserve? Theory and research application of the reserve concept , 2002, Journal of the International Neuropsychological Society.

[75]  J. Logan,et al.  Under-Recruitment and Nonselective Recruitment Dissociable Neural Mechanisms Associated with Aging , 2002, Neuron.