Biology subjects

Tsvetanov, K. A.

Publications and source records attributed to Tsvetanov, K. A..

17 recordsLinked to original sources

bioRxiv2026

Integrating Functional Transdiagnostic Dimensions of Psychopathology with Cortical Organization

Childhood and adolescence represent a critical period in which neurodevelopmental psychiatric conditions emerge; traditional case-control approaches often underestimate the complexity and co-occurrence of psychiatric conditions, calling for a transdiagnostic approach as a complementary measure. Open-access data sharing initiatives provide an opportunity to decipher structural- and functional-based organisational constraints on the relationship between brain connectivity and psychopathology. Using a highly heterogenous and comorbid neurodevelopmental sample of children and adolescents aged between 6 and 17 years old at-risk of neurodevelopmental conditions (N = 174, 114 males, mean age 10.72 {+/-} 2.21 years), and age-matched neurotypical controls (N = 27, 12 males, mean age 10.65 {+/-} 2.07 years), we identified a multivariate association, or latent variable, between resting-state functional connectivity and psychopathology. We extensively benchmarked this latent construct to develop a more parsimonious account of childhood psychopathology though an analytical framework spanning biological maps, brain connectivity, and behaviour. Participant-level expression of this latent brain-behaviour association differed by diagnostic burden and symptomatology, and pre-empted longitudinal psychopathology. Whilst diagnostic status was useful for interpretation, the latent construct transcended traditional diagnostic borders, revealing a neurotypical-neurodivergent continuum. The relationship between functional connectivity and neurodevelopmental psychopathology was circumscribed by functional connectivity networks (visual, fronto-parietal, and dorsal attention) and cytoarchitectonic class (primary/secondary sensory and primary sensory cortices). The latent variable aligned with magnetoencephalography-defined electrophysiological alpha (), high-gamma ({gamma}), and theta ({theta}) frequency bands, and was enriched across cortical distributions of astrocytes and excitatory neurones. The connectivity signature was significantly aligned with the archetypal sensorimotor-to-association axis and validated in an independent sample of pre-adolescents (N = 3504), with the strongest alignment with the principal component of gene expression and myelination and were relatively less enriched in cortical regions related to language, indicating a protective effect, and more positively enriched in regions related to executive functioning, conferring greater risk of psychopathology. Together, our findings suggest that the predictive link between functional connectivity and common symptoms of neurodevelopmental psychopathology are circumscribed by underlying macroscale anatomical, functional, and cognitive-related hierarchies.

neuroscience↗

bioRxiv2025

Complementary MR measures of white matter and their relation to cardiovascular health and cognition

Magnetic Resonance Imaging (MRI) offers many ways to non-invasively estimate the properties of white matter (WM) in the brain. In addition to the various metrics derived from diffusion-weighted MRI, one can estimate total WM volume from T1-weighted MRI, WM hyper-intensities from T2-weighted MRI, myelination from the T1:T2 ratio, or from the magnetisation-transfer ratio (MTR). Here we utilise the presence of all of these MR contrasts in a population based life-span cohort of 650 healthy adults [CamCAN cohort] to identify the latent factors underlying the covariance of 11 commonly-used WM metrics. Four factors were needed to explain 89% of the variance, which we interpreted in terms of 1) fibre density / myelination, 2) free-water / tissue damage, 3) fibre-crossing complexity and 4) microstructural complexity. These factors showed distinct effects of age and sex. To test the validity of these factors, we related them to measures of cardiovascular health and cognitive performance. Specifically, we ran path analyses 1) linking cardio-vascular measures to the WM factors, given the idea that WM health is related to cardiovascular health, and 2) linking the WM factors to cognitive measure, given the idea that WM health is important for cognition. Even after adjusting for age, we found that a vascular factor related to pulse pressure predicted the WM factor capturing free-water / tissue damage, and that several WM factors made unique predictions for fluid intelligence and processing speed. Our results show that there is both complementary and redundant information across common MR measures of WM, and their underlying latent factors may be useful for pinpointing the differential causes and contributions of white matter health in healthy aging.

neuroscience↗

bioRxiv2023

Lifestyle and brain health determinants of word-finding failures in healthy ageing

Cognitive decline associated with healthy ageing is multifactorial: brain-based and lifestyle factors uniquely and jointly contribute to distinct neurocognitive trajectories of ageing. To evaluate existing models of neurocognitive ageing such as compensation, maintenance, or reserve, we explore how various known brain-based and cardiorespiratory fitness factors intersect to better understand cognitive decline. In a pre-registered study (https://osf.io/6fqg7), we tested 73 healthy older adults aged 60--81 (M = 65.51, SD = 4.94) and collected neuroimaging (functional, structural, and perfusion MRI), cardiorespiratory fitness, and cognitive data to investigate a prominent challenge for older adults: word-finding failures. fMRI signal was recorded while participants responded to a definition-based tip-of-the-tongue task, T1-weighted imaging estimated grey matter volume, and cerebral blood flow was indexed using multi-delay pseudo-continuous arterial spin labelling. Commonality analyses were used to analyse these multi-domain data (neuroimaging, cardiorespiratory fitness, language skills, demographic characteristics) and uncover associations between predictors in explaining age-related tip-of-the-tongue rates. Commonality analyses revealed that functional activation of language networks associated with tip-of-the-tongue states is in part linked with age and, interestingly, cardiorespiratory fitness: the combination of higher cardiorespiratory fitness and functional recruitment in some older adults offsets part of the age-related variance in tip-of-the-tongues. Moreover, age-associated atrophy and perfusion in regions other than those showing functional differences accounted for variance in tip-of-the-tongues. Our findings can be interpreted in the context of the classic models of neurocognitive ageing, suggesting compensation. Brain health indices in concordance with cardiorespiratory fitness can provide a more holistic explanation of individual differences in age-related cognitive decline. HighlightsO_LIWord-finding problems are linked to brain health and cardiorespiratory fitness (CRF) C_LIO_LIBrain activity linked to word-finding failures is modulated by CRF and age C_LIO_LIDistinct contribution of structure and perfusion also associated with word-finding C_LIO_LILinking brain and CRF factors provides better account of age-related cognitive decline C_LI

neuroscience↗

bioRxiv2023

Neural Evidence of Functional Compensation for Fluid Intelligence in Healthy Ageing

Functional compensation is a common notion in the neuroscience of healthy ageing, whereby older adults are proposed to recruit additional brain activity to compensate for reduced cognitive function. However, whether this additional brain activity in older participants actually helps their cognitive performance remains debated. We examined brain activity and cognitive performance in a human lifespan sample (N=223) while they performed a problem-solving task (based on Cattells test of fluid intelligence) during functional magnetic resonance imaging (fMRI). Whole-brain univariate analysis revealed that activity in bilateral cuneal cortex for hard vs. easy problems increased both with age and with performance, even when adjusting for an estimate of age-related differences in cerebrovascular reactivity. Multivariate Bayesian decoding further demonstrated that age increased the likelihood that activation patterns in this cuneal region provided non-redundant information about the two task conditions, beyond that of the multiple-demand network generally activated in this task. This constitutes some of the strongest evidence yet for functional compensation in healthy ageing, at least in this brain region during visual problem-solving.

neuroscience↗

bioRxiv2023

Evaluating models of the ageing BOLD response

Neural activity cannot be directly observed using fMRI; rather it must be inferred from the hemodynamic responses that neural activity causes. Solving this inverse problem is made possible through the use of forward models, which generate predicted hemodynamic responses given hypothesised underlying neural activity. Commonly-used hemodynamic models were developed to explain data from healthy young participants; however studies of ageing and dementia are increasingly shifting the focus towards elderly populations. We evaluated the validity of a range of hemodynamic models across the healthy adult lifespan: from basis sets for the linear convolution models commonly used to analyse fMRI studies, to more advanced models including nonlinear fitting of a parameterised hemodynamic response function (HRF) and nonlinear fitting of a biophysical generative model (hemodynamic modelling, HDM). Using an exceptionally large sample of participants, and a sensorimotor task optimized for detecting the shape of the BOLD response to brief stimulation, we first characterised the effects of age on descriptive features of the response (e.g., peak amplitude and latency). We then compared these to features from more complex nonlinear models, fit to four regions of interest engaged by the task, namely left auditory cortex, bilateral visual cortex, left (contralateral) motor cortex and right (ipsilateral) motor cortex. Finally, we validated the extent to which parameter estimates from these models have predictive validity, in terms of how well they predict age in cross-validated multiple regression. We conclude that age-related differences in the BOLD response can be captured effectively by models with three free parameters. Furthermore, we show that biophysical models like the HDM have predictive validity comparable to more common models, while additionally providing insights into underlying mechanisms, which go beyond descriptive features like peak amplitude or latency, and include estimation of nonlinear effects. Here, the HDM revealed that most of the effects of age on the BOLD response could be explained by an increased rate of vasoactive signal decay and decreased transit rate of blood, rather than changes in neural activity per se. However, in the absence of other types of neural/hemodynamic data, unique interpretation of HDM parameters is difficult from fMRI data alone, and some brain regions in some tasks (e.g, ipsilateral motor cortex) can show responses that are more difficult to capture using current models.

neuroscience↗

bioRxiv2023

Cognition's dependence on functional network integrity with age is conditional on structural network integrity

Maintaining good cognitive function is crucial for well-being across the lifespan. We proposed that the degree of cognitive maintenance is determined by the functional interactions within and between large-scale brain networks. Such connectivity can be represented by the white matter architecture of structural brain networks that shape intrinsic neuronal activity into integrated and distributed functional networks. We explored how the function-structure connectivity convergence, and the divergence of functional connectivity from structural connectivity, contribute to the maintenance of cognitive function across the adult lifespan. Multivariate analyses were used to investigate the relationship between function-structure connectivity convergence and divergence with multivariate cognitive profiles, respectively. Cognitive function was increasingly dependent on function-structure connectivity convergence as age increased. The dependency of cognitive function on connectivity was particularly strong for high-order cortical networks and subcortical networks. The results suggest that brain functional network integrity sustains cognitive functions in old age, as a function of the integrity of the brains structural connectivity.

neuroscience↗

bioRxiv2022

Lifespan differences in visual short-term memory load-modulated functional connectivity

Working memory is critical to higher-order executive processes and declines throughout the adult lifespan. However, our understanding of the neural mechanisms underlying this decline is limited. Recent work suggests that functional connectivity between frontal control and posterior visual regions may be critical, but examinations of age differences therein have been limited to a small set of brain regions and extreme group designs (i.e., comparing young and older adults). In this study, we build on previous research by using a lifespan cohort and a whole-brain approach to investigate working memory load-modulated functional connectivity in relation to age and performance. The article reports on analysis of the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) data. Participants from a population-based lifespan cohort (N=111, age 23-86) performed a visual short-term memory task during functional magnetic resonance imaging. Visual short-term memory was measured with a delayed recall task for visual motion with three different loads. Whole-brain load-modulated connectivity was estimated using psychophysiological interactions in a hundred regions of interest, sorted into seven networks (Schaefer et al., 2018, Yeo et al., 2011). Results showed that load-modulated functional connectivity was strongest within the dorsal attention network followed by the visual network during encoding and maintenance. With increasing age, load-modulated functional connectivity strength decreased throughout the cortex. Within the dorsal attention network, increased load-modulated connectivity strength was related to better task performance in an age-invariant way. Our results demonstrate the widespread negative impact of age on the modulation of functional connectivity by working memory load. Older adults might already be close to ceiling in terms of their resources at the lowest load and therefore less able to further increase connectivity with increasing task demands. HighlightsO_LIWe examine visual short-term memory load-related functional connectivity C_LIO_LIAnd how age and performance affect modulation of connectivity by memory load C_LIO_LIModulation of connectivity is strongest in dorsal attention and visual networks C_LIO_LILoad-modulated connectivity strength decreases with increasing age C_LIO_LILoad-modulated connectivity in the dorsal attention network relates to performance C_LI

neuroscience↗

bioRxiv2022

Quality assessment of anatomical MRI images from Generative Adversarial Networks: human assessment and image quality metrics

BackgroundGenerative Adversarial Networks (GANs) can synthesize brain images from image or noise input. So far, the gold standard for assessing the quality of the generated images has been human expert ratings. However, due to limitations of human assessment in terms of cost, scalability, and the limited sensitivity of the human eye to more subtle statistical relationships, a more automated approach towards evaluating GANs is required. New methodWe investigated to what extent visual quality can be assessed using image quality metrics and we used group analysis and spatial independent components analysis to verify that the GAN reproduces multivariate statistical relationships found in real data. Reference human data was obtained by recruiting neuroimaging experts to assess real Magnetic Resonance (MR) images and images generated by a Wasserstein GAN. Image quality was manipulated by exporting images at different stages of GAN training. Results: Experts were sensitive to changes in image quality as evidenced by ratings and reaction times, and the generated images reproduced group effects (age, gender) and spatial correlations moderately well. We also surveyed a number of image quality metrics which consistently failed to fully reproduce human data. While the metrics Structural Similarity Index Measure (SSIM) and Naturalness Image Quality Evaluator (NIQE) showed good overall agreement with human assessment for lower-quality images (i.e. images from early stages of GAN training), only a Deep Quality Assessment (QA) model trained on human ratings was sensitive to the subtle differences between higher-quality images. ConclusionsWe recommend a combination of group analyses, spatial correlation analyses, and both distortion metrics (SSIM, NIQE) and perceptual models (Deep QA) for a comprehensive evaluation and comparison of brain images produced by GANs.

neuroscience↗

bioRxiv2021

Multimodal fusion analysis of functional, cerebrovascular and structural neuroimaging in healthy ageing subjects

Brain ageing is a complex process which requires a multimodal approach. Neuroimaging can provide insights into brain morphology, functional organization and vascular dynamics. However, most neuroimaging studies of ageing have focused on each imaging modality separately, limiting the understanding of interrelations between processes identified by different modalities and their relevance to cognitive decline in ageing. Here, we used a data-driven multimodal approach, linked independent component analysis (ICA), to jointly analyze magnetic resonance imaging of grey matter volume, cerebrovascular, and functional network topographies in relation to measures of fluid intelligence. Neuroimaging and cognitive data from the Cambridge Centre for Ageing and Neuroscience study were used, with healthy participants aged 18 to 88 years (main dataset n = 215; secondary dataset n = 433). Using linked ICA, functional network activities were characterized in independent components but not captured in the same component as structural and cerebrovascular patterns. Split-sample (n = 108/107) and out-of-sample (n = 433) validation analyses using linked ICA were also performed. Global grey matter volume with regional cerebrovascular changes and the right frontoparietal network activity were correlated with age-related and individual differences in fluid intelligence. This study presents the insights from linked ICA to bring together measurements from multiple imaging modalities, with independent and additive information. We propose that integrating multiple neuroimaging modalities allows better characterization of brain pattern variability and changes associated with healthy ageing.

neuroscience↗

bioRxiv2021

Cerebral blood flow predicts multiple demand network activity and fluid intelligence across the lifespan

The preservation of cognitive function into old age is a public health priority. Cerebral hypoperfusion is a hallmark of dementia but its impact on maintaining cognitive ability across the lifespan is less clear. We investigated the relationship between baseline cerebral blood flow (CBF) and blood oxygenation level-dependent (BOLD) response during a fluid reasoning task in a population-based adult lifespan cohort (N=227, age 18-88 years). As age differences in baseline CBF could lead to non-neuronal contributions to the BOLD signal, we introduced commonality analysis to neuroimaging, in order to dissociate performance-related CBF effects from the physiological confounding effects of CBF on the BOLD response. Accounting for CBF, we confirmed that performance- and age-related differences in BOLD responses in the multiple-demand network (MDN) implicated in fluid reasoning. Differences in baseline CBF across the lifespan explained not only performance-related BOLD responses, but also performance-independent BOLD responses. Our results suggest that baseline CBF is important for maintaining cognitive function, while its non-neuronal contributions to BOLD signals reflect an age-related confound. Maintaining perfusion into old age may serve to support brain function with behavioural advantage, regulating brain health.

neuroscience↗

bioRxiv2021

The "neural shift" of sleep quality and cognitive ageing: A resting-state MEG study of transient neural dynamics

Sleep quality changes dramatically from young to old age, but its effects on brain dynamics and cognitive functions are not yet fully specified. We applied Hidden Markov Models (HMMs) to resting-state MEG data from a large cohort (N=564) of population-based adults (aged 18-88), in order to characterize transient neural networks and to relate their temporal dynamics to sleep quality and to cognitive performance. Using multivariate analyses of brain-sleep profiles and of brain-cognition profiles, we found that an age-related "neural shift", expressed as decreased occurrence of "lower-order" brain networks, coupled with increased occurrence of "higher-order" networks, was associated with both increased sleep dysfunction and decreased fluid intelligence above and beyond age. These results suggest that poor sleep quality, as evident in ageing, may lead to a behavior-related shift in neural dynamics.

neuroscience↗

bioRxiv2020

Genetic signatures of human brain structure: A comparison between GWAS and relatedness-based regression

Identifying the genetic variations impacting human brain structure and their further effects on cognitive functions, is important for our understanding of the fundamental bases of cognition. In this study, we take two different approaches to this issue: classical genome-wide association analysis (GWAS) and a relatedness-based regression approach (REL) to search for associations between genotype and brain structural measures of gray matter and white matter. Instead of searching genetic variants by testing the association between a phenotype trait and the genotype of each single-nucleotide polymorphism (SNP) as in GWAS, REL takes advantage of multiple SNPs within a genomic window as a single measure, which potentially find associations wherever the functional SNP is in linkage disequilibrium (LD) with SNPs that have been sampled. We also conducted a simulation analysis to systemically compare GWAS and REL with respect to different levels of LD. Both methods succeed in identifying genetic variations associated with regional and global brain structural measures and tend to give complementary results due to the different aspects of genetic properties used. Simulation results suggest that GWAS outperforms REL when the signal is relatively weak. However, the collective effects due to local LD boost the performance of REL with increasing signal strength, resulting in better performance than GWAS. Our study suggests that the optimal approach may vary across the genome and that pre-testing for LD could allow GWAS to be preferred where LD is high and REL to be used where LD is low, or the local pattern of LD is complex.

genetics↗

bioRxiv2020

Transient resting-state network dynamics in cognitive ageing

It is important to maintain cognitive function in old age, yet the neural substrates that support successful cognitive ageing remain unclear. One factor that might be crucial, but has been overlooked due to limitations of previous data and methods, is the ability of brain networks to flexibly reorganise and coordinate over a millisecond time-scale. Magnetoencephalography (MEG) provides such temporal resolution, and can be combined with Hidden Markov Models (HMMs) to characterise transient neural states. We applied HMMs to resting-state MEG data from a large cohort (N=594) of population-based adults (aged 18-88), who also completed a range of cognitive tasks. Using multivariate analysis of neural and cognitive profiles, we found that decreased occurrence of "lower-order" brain networks, coupled with increased occurrence of "higher-order" networks, was associated with both increasing age and impaired fluid intelligence. These results favour theories of age-related reductions in neural efficiency over current theories of age-related functional compensation.

neuroscience↗

bioRxiv2020

Dispersion of functional gradients across the lifespan

Ageing is commonly associated with changes to segregation and integration of functional brain networks, but, in isolation, current network-based approaches struggle to elucidate changes across the many axes of functional organisation. However, the advent of gradient mapping techniques to neuroimaging provides a new means of studying functional organisation in a multi-dimensional connectivity space. Here, we studied ageing and behaviourally-relevant differences in a three-dimensional connectivity space using the Cambridge Centre for Ageing Neuroscience cohort (n=643). Building on gradient mapping techniques, we developed a set of measures to quantify the dispersion within and between functional communities. We detected a strong shift of the visual network across the lifespan from an extreme to a more central position in the 3D gradient space. In contrast, the dispersion distance of transmodal communities (dorsal attention, ventral attention, frontoparietal and default mode) did not change. However, these communities were increasingly dispersed with increasing age, reflecting more dissimilar functional connectivity profiles within each community. Increasing dispersion of frontoparietal and ventral attention networks, in particular, was associated negatively with cognition, measured by fluid intelligence. By using a technique that explicitly captures the ordering of functional systems in a multi-dimensional hierarchical framework, we identified behaviorally-relevant age-related differences of within and between network organisation. We propose that the study of functional gradients across the lifespan could provide insights that may facilitate the development of new strategies to maintain cognitive ability across the lifespan in health and disease.

neuroscience↗

bioRxiv2020

An in vivo Probabilistic Atlas of the Human Locus Coeruleus at Ultra-high Field

Early and profound pathological changes are evident in the locus coeruleus (LC) in dementia and Parkinsons disease, with effects on arousal, attention, cognitive and motor control. The LC can be identified in vivo using non-invasive magnetic resonance imaging techniques which have potential as biomarkers for detecting and monitoring disease progression. Technical limitations of existing imaging protocols have impaired the sensitivity to regional contrast variance or the spatial variability on the rostrocaudal extent of the LC, with spatial mapping consistent with post mortem findings. The current study employs a sensitive magnetisation transfer sequence using ultrahigh field 7T MRI to investigate the LC structure in vivo at high-resolution (resolution 0.4x0.4x0.5 mm, duration seven minutes). Magnetisation transfer images from 53 healthy older volunteers (52-84 years) revealed the spatial features of the LC and were used to create a probabilistic LC atlas for older adults, appropriate for clinical research. Consistent rostrocaudal gradients of slice-wise volume, contrast and variance differences of the LC were observed, mirroring distinctive ex vivo spatial distributions of LC cells in its subregions. The contrast-to-noise ratios were calculated for the peak voxels, and for the averaged signals within the atlas, to accommodate the volumetric differences in estimated contrast. The probabilistic atlas is freely available, and the MRI dataset is available for researchers, for replication or to facilitate accurate LC localisation and unbiased contrast extraction in future studies.

neuroscience↗

bioRxiv2019

The effects of age on resting-state BOLD signal variability is explained by cardiovascular and neurovascular factors

Accurate identification of brain function is necessary to understand neurocognitive ageing, and thereby promote health and well-being. Many studies of neurocognitive aging have investigated brain function with the blood-oxygen level-dependent (BOLD) signal measured by functional magnetic resonance imaging. However, the BOLD signal is a composite of neural and vascular signals, which are differentially affected by aging. It is therefore essential to distinguish the age effects on vascular versus neural function. The BOLD signal variability at rest (known as resting state fluctuation amplitude, RSFA), is a safe, scalable and robust means to calibrate vascular responsivity, as an alternative to breath-holding and hypercapnia. However, the use of RSFA for normalization of BOLD imaging assumes that age differences in RSFA reflecting only vascular factors, rather than age-related differences in neural function (activity) or neuronal loss (atrophy). Previous studies indicate that two vascular factors, cardiovascular health and cerebrovascular function, are insufficient when used alone to fully explain age-related differences in RSFA. It remains possible that their joint consideration is required to fully capture age differences in RSFA. We tested the hypothesis that RSFA no longer varies with age after adjusting for a combination of cardiovascular and cerebrovascular measures. We also tested the hypothesis that RSFA variation with age is not associated with atrophy. We used data from the population-based, lifespan Cam-CAN cohort. After controlling for cardiovascular and cerebrovascular estimates alone, the residual variance in RSFA across individuals was significantly associated with age. However, when controlling for both cardiovascular and cerebrovascular estimates, the variance in RSFA was no longer associated with age. Grey matter volumes did not explain age-differences in RSFA, after controlling for cardiovascular health. The results were consistent between voxel-level analysis and independent component analysis. Our findings indicate that cardiovascular and cerebrovascular signals are together sufficient predictors of age differences in RSFA. We suggest that RSFA can be used to separate vascular from neuronal factors, to characterise neurocognitive aging. We discuss the implications and make recommendations for the use of RSFA in the research of aging.

neuroscience↗

bioRxiv2018

Motor learning decline with age is related to differences in the explicit memory system

The ability to adapt ones movements to changes in the environment is fundamental in everyday life, but this ability changes across the lifespan. Although often regarded as an implicit process, recent research has also linked motor adaptation with explicit learning processes. To understand how these processes contribute to differences in motor adaptation with age, we combined a visuomotor learning paradigm with cognitive tasks that measure implicit and explicit processes, and structural brain imaging. In a large population-based cohort from the Cambridge Centre for Ageing and Neuroscience (n=322, aged 18-89 years) we first confirmed that the degree of adaptation to an angular perturbation of visual feedback declined with age. There were no associations between adaptation and sensory attenuation, which has been previously hypothesised to contribute to implicit motor learning. However, interactions between age and scores on two independent memory tasks showed that explicit memory performance was a progressively stronger determinant of motor learning with age. Similarly, interactions between age and grey matter volume in the medial temporal lobe, amygdala and hippocampus showed that grey matter volume in these regions became a stronger determinant of adaptation in older adults. The convergent behavioural and structural imaging results suggest that age-related differences in the explicit memory system is a contributor to the decline in motor adaptation in older age. These results may reflect the more general compensatory reliance on cognitive strategies to maintain motor performance with age.\n\nSIGNIFICANCE STATEMENTThe central nervous system has a remarkable capacity to learn new motor skills and adapt to new environmental dynamics. This capacity is impaired with age, and in many brain disorders. We find that explicit memory performance and its associated medial temporal brain regions deteriorate with age, but the association between this brain system and individual differences in motor learning becomes stronger in older adults. We propose that these results reflect an increased reliance on cognition in order to maintain adaptive motor skill performance. This difference in learning strategy has implications for interventions to improve motor skills in older adults.

neuroscience↗