Iron content affects age group differences in associative learning-related fMRI activity.

Brain regions accumulate different amounts of iron with age, with older adults having higher iron in the basal ganglia (globus pallidus, putamen, caudate) relative to the hippocampus. This has important implications for functional magnetic resonance imaging (fMRI) studies in aging as the presence of iron may influence both neuronal functioning as well as the measured fMRI (BOLD) signal, and these effects will vary across age groups and brain regions. To test this hypothesis, the current study examined the effect of iron on age group differences in task-related activity within each basal nuclei and the hippocampus. Twenty-eight younger and 22 older adults completed an associative learning task during fMRI acquisition. Iron content (QSM, R2*) was estimated from a multi-echo gradient echo sequence. As previously reported, older adults learned significantly less than younger adults and age group differences in iron content were largest in the basal ganglia (putamen, caudate). In the hippocampus (early task stage) and globus pallidus (late task stage), older adults had significantly higher learning-related activity than younger adults both before and after controlling for iron. In the putamen (late task stage), however, younger adults had significantly higher learning-related activity than older adults that was only seen after controlling for iron. These findings support the notion that age-related differences in iron influence both neuronal functioning and the measured fMRI signal in select basal nuclei. Moreover, previous fMRI studies in aging populations may have under-reported age group differences in task-related activity by not accounting for iron within these regions.

Impaired executive functioning mediates the association between aging and deterministic sequence learning.

Sensitivity to the fixed ordering of actions and events, or deterministic sequence learning, is an important skill throughout adulthood. Yet, it remains unclear whether age deficits in sequencing exist, and we lack a firm understanding of which factors might contribute to age-related impairments when they arise. Though debated, executive functioning, governed by the frontal lobe, may underlie age-related sequence learning deficits in older adults. The present study asked if age predicts errors in deterministic sequence learning across the older adult lifespan (ages 55-89), and whether executive functioning accounts for any age-related declines. Healthy older adults completed a comprehensive measure of frontal-based executive abilities as well as a deterministic sequence learning task that required the step-by-step acquisition of associations through trial-and-error feedback. Among those who met a performance-based criterion, increasing age was positively correlated with higher sequencing errors; however, this relationship was no longer significant after controlling for executive functioning. Moreover, frontal-based executive abilities mediated the relationship between age and sequence learning performance. These findings suggest that executive or frontal functioning may underlie age deficits in learning judgment-based, deterministic serial operations.

Age group differences in learning-related activity reflect task stage, not learning stage.

Healthy aging is accompanied by declines in the ability to learn associations between events, even when their relationship cannot be described. Previous functional magnetic resonance imaging (fMRI) studies have attributed these implicit associative learning (IAL) deficits to differential engagement of the hippocampus and basal ganglia in older relative to younger adults in early and late stages of the task, respectively. However, these task stages have been confounded with age group differences in learning performance that emerge later and to a lesser degree in older adults. To disentangle the effects of task stage from learning stage (i.e., when there is significant evidence of learning) on age group differences in the neural substrates of IAL, we acquired fMRI data while 28 younger (20.8 ± 2.3 years) and 22 older (73.6 ± 6.8 years) healthy adults completed the Triplets Learning Task, in which the location of two cues predicted the location of a target with high (HF) or low (LF) frequency. When matched for task stage, results revealed worse learning performance and increased IAL-related activity in the hippocampus during the early stage and in the globus pallidum during the late stage in older relative to younger adults. However, when matched for learning stage, there were no significant age group differences in learning performance or IAL-related activity. Thus, although learning emerges later for older adults, they are engaging similar brain regions as younger adults when learning the associations, suggesting that previous reports of age group differences reflect effects of age on task stage, but not learning stage.

Implicit associative learning relates to basal ganglia gray matter microstructure in young and older adults.

Older adults are impaired at implicit associative learning (IAL), or the learning of relationships between stimuli in the environment without conscious awareness. These age effects have been attributed to differential engagement of the basal ganglia (e.g. caudate, globus pallidus) and hippocampus throughout learning. However, no studies have examined gray matter diffusion relations with IAL, which can reveal microstructural properties that vary with age and contribute to learning. In this study, young (18-29 years) and older (65-87 years) adults completed the Triplet Learning Task, in which participants implicitly learn that the location of cues predict the target location on some trials (high frequency triplets). Diffusion imaging was also acquired and multicompartment diffusion metrics were calculated using neurite orientation dispersion and density imaging (NODDI). As expected, results revealed age deficits in IAL (smaller differences in performance to high versus low frequency triplets in the late learning stage) and age-related differences in basal ganglia and hippocampus free, hindered, and restricted diffusion. Significant correlations were seen between restricted caudate diffusion and early IAL and between hindered globus pallidus diffusion and late IAL, which were not moderated by age group. These findings indicate that individual differences in basal ganglia, but not hippocampal, gray matter microstructure contribute to learning, independent of age, further supporting basal ganglia involvement in IAL.

Age-Related Decline in Learning Deterministic Judgment-Based Sequences.

OBJECTIVES: Because sequence learning is integral to cognitive functions across the life span, the present study examined the effect of healthy aging on deterministic judgment-based sequence learning. METHODS: College-aged, younger-old (YO), and older-old (OO) adults completed a judgment-based sequence learning task which required them to learn a full sequence by chaining together single stimulus-response associations in a step-by-step fashion. RESULTS: Results showed that younger adults outperformed YO and OO adults; older adults were less able to acquire the full sequence and committed significantly more errors during learning. Additionally, higher sequence learning errors were associated with advancing age among older adults, even when controlling for other factors known to contribute to sequence learning abilities. Such impairments were selective to learning sequential information, because adults of all ages performed equivalently on postlearning probe trials, as well as on learning simple stimulus-response associations. DISCUSSION: This pattern of age deficits during deterministic sequence learning challenges past reports of age preservation. Though the neural processes underlying learning cannot be determined here, our patterns of age deficits and preservation may reflect different brain regions that are involved in the task phases, adding behavioral evidence to the emerging hypothesis of frontostriatal declines despite spared hippocampal function with age.

Dyslexia-related impairments in sequence learning predict linguistic abilities.

Dyslexia is often characterized by disordered word recognition and spelling, though dysfunction on various non-linguistic tasks suggests a more pervasive deficit may underlie reading and spelling abilities. The serial-order learning impairment in dyslexia (SOLID) hypothesis proposes that sequence learning impairments fundamentally disrupt cognitive abilities, including linguistic processes, among individuals with dyslexia; yet only some studies report sequence learning deficits in people with dyslexia relative to controls. Evidence may be mixed because traditional sequence learning tasks often require strong motor demands, working memory processes and/or executive functions, wherein people with dyslexia can show impairments. Thus, observed sequence learning deficits in dyslexia may only appear to the extent that comorbid motor-based processes, memory capacity, or executive processes are involved. The present study measured sequence learning in college-aged students with and without dyslexia using a single task that evaluates sequencing and non-sequencing components but without strong motor, executive, or memory demands. During sequencing, each additional link in a sequence of stimuli leading to a reward is trained step-by-step, until a complete sequence is acquired. People with dyslexia made significantly more sequencing errors than controls, despite equivalent performance on non-sequencing components. Mediation analyses further revealed that sequence learning accounted for a large portion of the variance between dyslexia status and linguistic abilities, particularly pseudo-word reading. These findings extend the SOLID hypothesis by showing difficulties in the ability to acquire sequences that may play an underlying role in literacy acquisition.

Age affects reinforcement learning through dopamine-based learning imbalance and high decision noise-not through Parkinsonian mechanisms.

Probabilistic reinforcement learning declines in healthy cognitive aging. While some findings suggest impairments are especially conspicuous in learning from rewards, resembling deficits in Parkinson's disease, others also show impairments in learning from punishments. To reconcile these findings, we tested 252 adults from 3 age groups on a probabilistic reinforcement learning task, analyzed trial-by-trial performance with a Q-reinforcement learning model, and correlated both fitted model parameters and behavior to polymorphisms in dopamine-related genes. Analyses revealed that learning from both positive and negative feedback declines with age but through different mechanisms: when learning from negative feedback, older adults were slower due to noisy decision-making; when learning from positive feedback, they tended to settle for a nonoptimal solution due to an imbalance in learning from positive and negative prediction errors. The imbalance was associated with polymorphisms in the DARPP-32 gene and appeared to arise from mechanisms different from those previously attributed to Parkinson's disease. Moreover, this imbalance predicted previous findings on aging using the Probabilistic Selection Task, which were misattributed to Parkinsonian mechanisms.

Impairment of memory generalization in preclinical autosomal dominant Alzheimer's disease mutation carriers.

Fast, inexpensive, and noninvasive identification of Alzheimer's disease (AD) before clinical symptoms emerge would augment our ability to intervene early in the disease. Individuals with fully penetrant genetic mutations causing autosomal dominant Alzheimer's disease (ADAD) are essentially certain to develop the disease, providing a unique opportunity to examine biomarkers during the preclinical stage. Using a generalization task that has previously shown to be sensitive to medial temporal lobe pathology, we compared preclinical individuals carrying ADAD mutations to noncarrying kin to determine whether generalization (the ability to transfer previous learning to novel but familiar recombinations) is vulnerable early, before overt cognitive decline. As predicted, results revealed that preclinical ADAD mutation carriers made significantly more errors during generalization than noncarrying kin, despite no differences between groups during learning or retention. This impairment correlated with the left hippocampal volume, particularly in mutation carriers. Such identification of generalization deficits in early ADAD may provide an easily implementable and potentially linguistically and culturally neutral way to identify and track cognition in ADAD.

Aging and a genetic KIBRA polymorphism interactively affect feedback- and observation-based probabilistic classification learning.

Probabilistic category learning involves complex interactions between the hippocampus and striatum that may depend on whether acquisition occurs via feedback or observation. Little is known about how healthy aging affects these processes. We tested whether age-related behavioral differences in probabilistic category learning from feedback or observation depend on a genetic factor known to influence individual differences in hippocampal function, the KIBRA gene (single nucleotide polymorphism rs17070145). Results showed comparable age-related performance impairments in observational as well as feedback-based learning. Moreover, genetic analyses indicated an age-related interactive effect of KIBRA on learning: among older adults, the beneficial T-allele was positively associated with learning from feedback, but negatively with learning from observation. In younger adults, no effects of KIBRA were found. Our results add behavioral genetic evidence to emerging data showing age-related differences in how neural resources relate to memory functions, namely that hippocampal and striatal contributions to probabilistic category learning may vary with age. Our findings highlight the effects genetic factors can have on differential age-related decline of different memory functions.

Individual Differences in Cognitive Function in Older Adults Predicted by Neuronal Selectivity at Corresponding Brain Regions.

Relating individual differences in cognitive abilities to neural substrates in older adults is of significant scientific and clinical interest, but remains a major challenge. Previous functional magnetic resonance imaging (fMRI) studies of cognitive aging have mainly focused on the amplitude of fMRI response, which does not measure neuronal selectivity and has led to some conflicting findings. Here, using local regional heterogeneity analysis, or Hcorr , a novel fMRI analysis technique developed to probe the sparseness of neuronal activations as an indirect measure of neuronal selectivity, we found that individual differences in two different cognitive functions, episodic memory and letter verbal fluency, are selectively related to Hcorr -estimated neuronal selectivity at their corresponding brain regions (hippocampus and visual-word form area, respectively). This suggests a direct relationship between cognitive function and neuronal selectivity at the corresponding brain regions in healthy older adults, which in turn suggests that age-related neural dedifferentiation might contribute to rather than compensate for cognitive decline in healthy older adults. Additionally, the capability to estimate neuronal selectivity across brain regions with a single data set and link them to cognitive performance suggests that, compared to fMRI-adaptation-the established fMRI technique to assess neuronal selectivity, Hcorr might be a better alternative in studying normal aging and neurodegenerative diseases, both of which are associated with widespread changes across the brain.