Neural Dedifferentiation in the Aging Brain

doi:10.1016/j.tics.2019.04.012

Trends in Cognitive Sciences

Volume 23, Issue 7, July 2019, Pages 547-559

https://doi.org/10.1016/j.tics.2019.04.012 Get rights and content

Highlights

Research over the past two decades has significantly improved our understanding of the plethora of factors contributing to cognitive aging.
We provide a selective review of studies investigating age differences in neural differentiation, as defined by measures of neural selectivity or specificity.
The evidence indicates that neural differentiation decreases in healthy older adults and predicts performance across multiple cognitive domains in an age-invariant manner.
Many factors likely contribute to age-related neural dedifferentiation, including age differences in neuromodulatory drive, the efficacy of inhibitory neurotransmission, response to task demands, and cumulative life experience.
The current evidence raises the possibility that neural dedifferentiation does not exclusively reflect detrimental consequences of brain aging.

Many cognitive abilities decline with age even in the absence of detectable pathology. Recent evidence indicates that age-related neural dedifferentiation, operationalized in terms of neural selectivity, may contribute to this decline. We review here work exploring the relationship between neural dedifferentiation, cognition, and age. Compelling evidence for age effects on neural selectivity comes from both non-human animal and human research. However, current data suggest that age does not moderate the observed relationships between neural dedifferentiation and cognitive performance. We propose that functionally significant variance in measures of neural dedifferentiation reflects both age-dependent and age-independent factors. We further propose that the effects of age on neural dedifferentiation do not exclusively reflect detrimental consequences of aging.

Section snippets

Determinants of Cognitive Aging

Many cognitive abilities, including episodic memory, executive control, and processing speed, decline with increasing age, even in the absence of detectable pathology 1., 2., 3.. Given how quickly human populations are aging (the United Nations projects that the global population aged 80 years or older will rise from 137 million to 437 million between 2017 and 2050 [4]), understanding the causes of, and factors moderating, age-related cognitive decline are urgent goals. The use of functional

Aging and Cognitive Dedifferentiation

The concept of age-related dedifferentiation pre-dates functional neuroimaging, and was developed in response to psychometric evidence that across-participant correlations between performance on different cognitive and sensory tasks strengthen over the adult lifespan 13., 14., 15., 16., 17.. The term dedifferentiation was used to contrast these findings from those indicating that cognitive abilities differentiate (i.e., become less strongly correlated) during childhood 17., 18., 19., 20..

Neural Dedifferentiation as a Cause of Cognitive Aging

Before turning our attention to the neural dedifferentiation literature we first briefly discuss the influential computational model of Li and colleagues 9., 10., 11., 12.. The model provides a neurobiological basis for age-related cognitive dedifferentiation (which, as noted above, is controversial) and cognitive aging more generally. The model proposes that cognitive aging and dedifferentiation both result from reduced neural efficiency caused by a reduction in the integrity of ascending

Establishing Criteria for Neural Dedifferentiation

The notion of dedifferentiation has been invoked to account for a wide array of findings in the cognitive neuroscience of aging literature (e.g., 24., 42., 43., 44., 45., 46.). In this section we advance a definition of neural dedifferentiation, and in this light consider the scope of relevant findings. Following others 24., 47., we propose that neural dedifferentiation (or, reciprocally, differentiation) is ideally operationalized in terms of the selectivity of neural activity. This

Relationship between Neural Differentiation and Behavior

The computational model of Li and colleagues 9., 10., 11., 12. proposes that neural dedifferentiation is an important determinant of cognitive aging. Nonetheless, only a handful of studies have examined whether measures of neural dedifferentiation correlate with cognitive performance, and even fewer have directly examined whether such correlations are moderated by age. We briefly review here studies that have examined this question, asking whether, as postulated by Li and colleagues, neural

Age-Related Neural Dedifferentiation and Lifetime Experience

Explanations of age-related neural dedifferentiation will need to accommodate two aspects of the findings reported above. First, they will need to link the findings from single-neuron studies in non-human animals with those from functional neuroimaging studies in humans. Second, they will need to account for findings suggesting that, in humans at least, age-related neural dedifferentiation is evident only for some stimulus categories. Undoubtedly any explanation will implicate multiple and,

Concluding Remarks

When operationalized in terms of the selectivity of neural responses, evidence that neural differentiation decreases with increasing age is strong and is consistent with longstanding ideas about the effects of age on neural distinctiveness at both the cellular and population levels. In what might be a challenge to these ideas, however, age-related neural dedifferentiation appears to be evident for only some classes of perceptual input. Moreover, the existing data suggest that age does not

Outstanding Questions

What does age-related neural dedifferentiation look like from a longitudinal rather than a cross-sectional perspective? Do changes in neural differentiation over time predict cognitive change? What are the neural correlates of dynamic cognitive dedifferentiation?
Does age modulate the relationship between neural differentiation and cognitive performance in large, diverse samples of participants, including individuals beyond their eighth decade of life? Do these brain–behavior relationships

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Physical activity-related individual differences in functional human connectome are linked to fluid intelligence in older adults
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The study examined resting state functional connectivity (rs-FC) associated with moderate-to-vigorous physical activity (MV-PA), sedentary time (ST), TV viewing, computer use, and their relationship to cognitive performance in older adults. We used pre-intervention data from 119 participants from the Fit & Active Seniors trial. Multivariate pattern analysis revealed two seeds associated with MV-PA: right superior frontal gyrus (SFG; spanning frontoparietal [FPN] and ventral attention networks [VAN]) and right precentral (PrG) and postcentral gyri (PoG) of the somatosensory network (SN). A positive correlation between the right SFG seed and a cluster spanning default mode (DMN), dorsal attention (DAN), FPN, and visual networks (VIS) was linked to higher fluid intelligence, as was FC between the right PrG/PoG seed and a cluster in VIS. No significant rs-FC patterns associated with ST, TV viewing, or computer use were found. Our findings suggest that greater functional integration within networks implementing top-down control and within those supporting visuospatial abilities, paired with segregation between networks critical and those not critical to top-down control, may help promote cognitive reserve in more physically active seniors.
Greater up-modulation of intra-individual brain signal variability makes a high-load cognitive task more arduous for older adults
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The extent to which brain responses are less distinctive across varying cognitive loads in older adults is referred to as neural dedifferentiation. Moment-to-moment brain signal variability, an emerging indicator, reveals not only the adaptability of an individual's brain as an inter-individual trait, but also the allocation of neural resources within an individual due to ever-changing task demands, thus shedding novel insight into the process of neural dedifferentiation. However, how the modulation of intra-individual brain signal variability reflects behavioral differences related to cognitively demanding tasks remains unclear. In this study, we employed functional near-infrared spectroscopy (fNIRS) imaging to capture the variability of brain signals, which was quantified by the standard deviation, during both the resting state and an n-back task (n = 1, 2, 3) in 57 healthy older adults. Using multivariate Partial Least Squares (PLS) analysis, we found that fNIRS signal variability increased from the resting state to the task and increased with working memory load in older adults. We further confirmed that greater fNIRS signal variability generally supported faster and more stable response time in the 2- and 3-back conditions. However, the intra-individual level analysis showed that the greater the up-modulation in fNIRS signal variability with cognitive loads, the more its accuracy decreases and mean response time increases, suggesting that a greater intra-individual brain signal variability up-modulation may reflect decreased efficiency in neural information processing. Taken together, our findings offer new insights into the nature of brain signal variability, suggesting that inter- and intra-individual brain signal variability may index distinct theoretical constructs.
Age-related similarities and differences in cognitive and neural processing revealed by task-related microstate analysis
2024, Neurobiology of Aging
We explored neural processing differences associated with aging across four cognitive functions. In addition to ERP analysis, we included task-related microstate analyses, which identified stable states of neural activity across the scalp over time, to explore whole-head neural activation differences. Younger and older adults (YA, OA) completed face perception (N170), word-pair judgment (N400), visual oddball (P3), and flanker (ERN) tasks. Age-related effects differed across tasks. Despite age-related delayed latencies, N170 ERP and microstate analyses indicated no age-related differences in amplitudes or microstates. However, age-related condition differences were found for P3 and N00 amplitudes and scalp topographies: smaller condition differences were found for in OAs as well as broader centroparietal scalp distributions. Age group comparisons for the ERN revealed similar focal frontocentral activation loci, but differential activation patterns. Our findings of differential age effects across tasks are most consistent with the STAC-r framework which proposes that age-related effects differ depending on the resources available and the kinds of processing and cognitive load required of various tasks.
Information decomposition and the informational architecture of the brain
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To explain how the brain orchestrates information-processing for cognition, we must understand information itself. Importantly, information is not a monolithic entity. Information decomposition techniques provide a way to split information into its constituent elements: unique, redundant, and synergistic information. We review how disentangling synergistic and redundant interactions is redefining our understanding of integrative brain function and its neural organisation. To explain how the brain navigates the trade-offs between redundancy and synergy, we review converging evidence integrating the structural, molecular, and functional underpinnings of synergy and redundancy; their roles in cognition and computation; and how they might arise over evolution and development. Overall, disentangling synergistic and redundant information provides a guiding principle for understanding the informational architecture of the brain and cognition.
Erratum: Aging alters functional connectivity of motor theta networks during sensorimotor reactions (Clinical Neurophysiology (2024) 159 (96), (S1388245724000087), (10.1016/j.clinph.2024.01.001))
2024, Clinical Neurophysiology
Both cognitive and primary motor networks alter with advancing age in humans. The networks activated in response to external environmental stimuli supported by theta oscillations remain less well explored. The present study aimed to characterize the effects of aging on the functional connectivity of response-related theta networks during sensorimotor tasks.
Electroencephalographic signals were recorded in young and middle-to-older age adults during three tasks performed in two modalities, auditory and visual: a simple reaction task, a Go-NoGo task, and a choice-reaction task. Response-related theta oscillations were computed. The phase-locking value (PLV) was used to analyze the spatial synchronization of primary motor and motor control theta networks.
Performance was overall preserved in older adults. Independently of the task, aging was associated with reorganized connectivity of the contra-lateral primary motor cortex. In younger adults, it was synchronized with motor control regions (intra-hemispheric premotor/frontal and medial frontal). In older adults, it was only synchronized with intra-hemispheric sensorimotor regions.
Motor theta networks of older adults manifest a functional decoupling between the response-generating motor cortex and motor control regions, which was not modulated by task variables. The overall preserved performance in older adults suggests that the increased connectivity within the sensorimotor network is associated with an excessive reliance on sensorimotor feedback during movement execution compensating for a deficient cognitive regulation of motor regions during sensorimotor reactions.
New evidence is provided for the reorganization of motor networks during sensorimotor reactions already at the transition from middle to old age.
Aging alters functional connectivity of motor theta networks during sensorimotor reactions
2024, Clinical Neurophysiology
Both cognitive and primary motor networks alter with advancing age in humans. The networks activated in response to external environmental stimuli supported by theta oscillations remain less well explored. The present study aimed to characterize the effects of aging on the functional connectivity of response-related theta networks during sensorimotor tasks.
Electroencephalographic signals were recorded in young and middle-to-older age adults during three tasks performed in two modalities, auditory and visual: a simple reaction task, a Go-NoGo task, and a choice-reaction task. Response-related theta oscillations were computed. The phase-locking value (PLV) was used to analyze the spatial synchronization of primary motor and motor control theta networks.
Performance was overall preserved in older adults. Independently of the task, aging was associated with reorganized connectivity of the contra-lateral primary motor cortex. In younger adults, it was synchronized with motor control regions (intra-hemispheric premotor/frontal and medial frontal). In older adults, it was only synchronized with intra-hemispheric sensorimotor regions.
Motor theta networks of older adults manifest a functional decoupling between the response-generating motor cortex and motor control regions, which was not modulated by task variables. The overall preserved performance in older adults suggests that the increased connectivity within the sensorimotor network is associated with an excessive reliance on sensorimotor feedback during movement execution compensating for a deficient cognitive regulation of motor regions during sensorimotor reactions.
New evidence is provided for the reorganization of motor networks during sensorimotor reactions already at the transition from middle to old age.

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Trends in Cognitive Sciences

OpinionNeural Dedifferentiation in the Aging Brain

Highlights

Section snippets

Determinants of Cognitive Aging

Aging and Cognitive Dedifferentiation

Neural Dedifferentiation as a Cause of Cognitive Aging

Establishing Criteria for Neural Dedifferentiation

Relationship between Neural Differentiation and Behavior

Age-Related Neural Dedifferentiation and Lifetime Experience

Concluding Remarks

Outstanding Questions

Clin. Geriatr. Med.

Neurocomputing

Trends Cogn. Sci.

Curr. Opin. Neurobiol.

Intelligence

Intelligence

Intelligence

Intelligence

Neurosci. Biobehav. Rev.

Trends Cogn. Sci.

Neurosci. Biobehav. Rev.

Neuron

Neurobiol. Aging

Brain Res.

Neurobiol. Aging

Neuroscience

Neuroscience

Neurobiol. Aging

Vis. Res.

Vis. Res.

Trends Cogn. Sci.

Neurobiol. Aging

Neurobiol. Aging

NeuroImage

NeuroImage

Curr. Opin. Neurobiol.

NeuroImage

Trends Cogn. Sci.

NeuroImage

Major Issues in Cognitive Aging

Trajectories of normal cognitive aging

Psychol. Aging

World Population Prospects: The 2017 Revision, Key Findings and Advance Tables

Maintenance, reserve and compensation: the cognitive neuroscience of healthy ageing

Nat. Rev. Neurosci.

How does it STAC up? Revisiting the scaffolding theory of aging and cognition

Neuropsychol. Rev.

The cognitive neuroscience of ageing

Nat. Rev. Neurosci.

Successful memory aging

Annu. Rev. Psychol.

Cross-level unification: a computational exploration of the link between deterioration of neurotransmitter systems and dedifferentiation of cognitive abilities in old age

Integration versus differentiation of fluid/crystallized intelligence in old age

Dev. Psychol.

Emergence of a powerful connection between sensory and cognitive functions across the adult life span: a new window to the study of cognitive aging?

Psychol. Aging

Intellectual functioning in old and very old age: cross-sectional results from the Berlin Aging Study

Psychol. Aging

Transformations in the couplings among intellectual abilities and constituent cognitive processes across the life span

Psychol. Sci.

An analysis of the mental factors of various age groups from nine to sixty

Genet. Psychol. Monogr.

A developmental theory of intelligence

Am. Psychol.

The differentiation of intellectual ability

Br. J. Educ. Psychol.

Cognitive and sensory declines in old age: gauging the evidence for a common cause

Psychol. Aging

Differential trajectories of age-related changes in components of executive and memory processes

Psychol. Aging

The Seattle longitudinal studies of adult intelligence

Curr. Dir. Psychol. Sci.

Aging reduces neural specialization in ventral visual cortex

Proc. Natl. Acad. Sci.

Exploring dedifferentiation across the adult lifespan

Psychol. Aging

Cross-sectional and longitudinal patterns of dedifferentiation in late-life cognitive and sensory function: the effects of age, ability, attrition, and occasion of measurement

J. Exp. Psychol. Gen.

Opinion
Neural Dedifferentiation in the Aging Brain