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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., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Feedback-based associative learning (e.g., acquiring new associations from positive or negative outcomes) and generalization (e.g., applying past learning to new settings) are important cognitive skills that enable people to make economic decisions or social judgments. This ability to acquire new skills based on feedback and transfer those experiences to predict positive outcomes in novel situations is essential at all ages, but especially among older adults who must continually adapt to new people, environments, and technologies. Ample evidence from animal work, clinical research, and computational modeling has demonstrated that feedback-based associative learning is sensitive to basal ganglia dysfunction and generalization to medial temporal lobe dysfunction. This dissociation is relevant because of recent evidence that has suggested healthy aging compromises the basal ganglia system earlier than the medial temporal lobes. However, few studies have investigated how healthy aging influences these cognitive processes. Here, we examined both feedback-based associative learning and generalization in younger, middle-aged, and older adults using a computerized acquired equivalence task. Results revealed a significant effect of age group on feedback-based associative learning, consistent with evidence of persistent age-related declines in the basal ganglia. In contrast, generalization was spared in all but the oldest adult group, likely reflecting preserved medial temporal lobe function until advanced old age. Our findings add behavioral evidence to the emerging view that healthy aging affects the striatal system before the medial temporal lobes. Although further evidence is needed, this finding may shed light on the possible time course of neural system dysfunction in healthy aging., (PsycINFO Database Record (c) 2013 APA, all rights reserved.)

We have pursued an interdisciplinary research program to develop novel behavioral assessment tools for evaluating specific memory impairments following damage to the medial temporal lobe, including the hippocampus and associated structures that show pathology early in the course of Alzheimer's disease (AD). Our approach uses computational models to identify the functional consequences of hippocampal-region damage, leading to testable predictions in both rodents and humans. Our modeling argues that hippocampal-region dysfunction may selectively impair the ability to generalize when familiar information is presented in novel recombinations. Previous research has shown that specific reductions in hippocampal volume in non-demented elderly individuals correlate with future development of AD. In two previous studies, we tested non-demented elderly with and without mild hippocampal atrophy (HA) on stimulus-response learning tasks. Individuals with and without HA could learn the initial information, but the HA group was selectively impaired on transfer tests where familiar features and objects were recombined. This suggests that such generalization deficits may be behavioral markers of HA, and an early indicator of risk for subsequent cognitive decline. Converging support for the relevance of these tasks to aging and Alzheimer's disease comes from our recent fMRI studies of individuals with mild cognitive impairment (MCI). Activity in the hippocampus declines with progressive training on these tasks, suggesting that the hippocampus is important for learning new stimulus representations that support subsequent transfer. Individuals with HA may be able to learn, but in a more hippocampal-independent fashion that does not support later transfer. Ultimately, this line of research could lead to a novel battery of behavioral tests sensitive to very mild hippocampal atrophy and risk for decline to AD, allowing early diagnosis and also allowing researchers to test new Alzheimer's drugs that target individuals in the earliest stages of the disease - before significant cognitive decline. A new mouse version of one of our tasks shows promise for translating these paradigms into rodents, allowing for future studies of therapeutic interventions in transgenic mouse models of AD.

Probabilistic category learning engages neural circuitry that includes the prefrontal cortex and caudate nucleus, two regions that show prominent changes with normal aging. However, the specific contributions of these brain regions are uncertain, and the effects of normal aging have not been examined previously in probabilistic category learning. In the present study, using a blood oxygenation level-dependent functional magnetic resonance imaging block design, 18 healthy young adults (mean age, 25.5 +/- 2.6 years) and 15 older adults (mean age, 67.1 +/- 5.3 years) were assessed on the probabilistic category learning "weather prediction" test. Whole-brain functional images acquired using a 1.5T scanner (General Electric, Milwaukee, WI) with gradient echo, echo planar imaging (3/1 mm; repetition time, 3000 ms; echo time, 50 ms) were analyzed using second-level random-effects procedures [SPM99 (Statistical Parametric Mapping)]. Young and older adults displayed equivalent probabilistic category learning curves, used similar strategies, and activated analogous neural networks, including the prefrontal and parietal cortices and the caudate nucleus. However, the extent of caudate and prefrontal activation was less and parietal activation was greater in older participants. The percentage correct and reaction time were mainly positively correlated with caudate and prefrontal activation in young individuals but positively correlated with prefrontal and parietal cortices in older individuals. Differential activation within a circumscribed neural network in the context of equivalent learning suggests that some brain regions, such as the parietal cortices, may provide a compensatory mechanism for healthy older adults in the context of deficient prefrontal cortex and caudate nuclei responses.

Recent work has conceptualized the brain as a network comprised of groups of sub-networks or modules. "Flexibility" of brain network(s) indexes the dynamic reconfiguration of comprising modules. Using novel techniques from dynamic network neuroscience applied to high-resolution resting-state functional magnetic resonance imaging (fMRI), the present study investigated the effects of an aerobic exercise intervention on the dynamic rearrangement of modular community structure-a measure of neural flexibility-within the medial temporal lobe (MTL) network. The MTL is one of the earliest brain regions impacted by Alzheimer's disease. It is also a major site of neuroplasticity that is sensitive to the effects of exercise. In a two-group non-randomized, repeated measures and matched control design with 34 healthy older adults, we observed an exercise-related increase in flexibility within the MTL network. Furthermore, MTL network flexibility mediated the beneficial effect aerobic exercise had on mnemonic flexibility, as measured by the ability to generalize past learning to novel task demands. Our results suggest that exercise exerts a rehabilitative and protective effect on MTL function, resulting in dynamically evolving networks of regions that interact in complex communication patterns. These reconfigurations may underlie exercise-induced improvements on cognitive measures of generalization, which are sensitive to subtle changes in the MTL.

Using high-resolution resting state functional magnetic resonance imaging (fMRI), the present study tested the hypothesis that ABCA7 genetic risk differentially affects intra-medial temporal lobe (MTL) functional connectivity between MTL subfields, versus internetwork connectivity of the MTL with the medial prefrontal cortex (mPFC), in nondemented older African Americans. Although the association of ABCA7 risk variants with Alzheimer's disease (AD) has been confirmed worldwide, its effect size on the relative odds of being diagnosed with AD is significantly higher in African Americans. However, little is known about the neural correlates of cognitive function in older African Americans and how they relate to AD risk conferred by ABCA7. In a case-control fMRI study of 36 healthy African Americans, we observed ABCA7 related impairments in behavioral generalization that was mediated by dissociation in entorhinal cortex (EC) resting state functional connectivity. Specifically, ABCA7 risk variant was associated with EC-hippocampus hyper-synchronization and EC-mPFC hypo-synchronization. Carriers of the risk genotype also had a significantly smaller anterolateral EC, despite our finding no group differences on standardized neuropsychological tests. Our findings suggest a model where impaired cortical connectivity leads to a more functionally isolated EC at rest, which translates into aberrant EC-hippocampus hyper-synchronization resulting in generalization deficits. While we cannot identify the exact mechanism underlying the observed alterations in EC structure and network function, considering the relevance of Aβ in ABCA7 related AD pathogenesis, the results of our study may reflect the synergistic reinforcement between amyloid and tau pathology in the EC, which significantly increases tau-induced neuronal loss and accelerates synaptic alterations. Finally, our results add to a growing literature suggesting that generalization of learning may be a useful tool for assessing the mild cognitive deficits seen in the earliest phases of prodromal AD, even before the more commonly reported deficits in episodic memory arise.

African Americans are 1.4 times more likely than European Americans to carry the apolipoprotein E (APOE) ε4 allele, a risk factor for Alzheimer's disease (AD). However, little is known about the neural correlates of cognitive function in older African Americans and how they relate to genetic risk for AD. In particular, no past study on African Americans has examined the effect of APOE ε4 status on pattern separation-mnemonic discrimination performance and its corresponding neural computations in the hippocampus. Previous work using the mnemonic discrimination paradigm has localized increased activation in the DG/CA3 hippocampal subregions as being correlated with discrimination deficits. In a case-control high-resolution functional magnetic resonance imaging study of 30 healthy African Americans, aged 60 years and older, we observed APOE ε4-related impairments in mnemonic discrimination, coincident with dysfunctional hyperactivation in the DG/CA3, and CA1 regions, despite no evidence of structural differences in the hippocampus between carriers and noncarriers. Our results add to the growing body of evidence that deficits in pattern separation may be an early marker for AD-related neuronal dysfunction.

African Americans experience higher incidence and prevalence of Alzheimer's disease (AD). Yet, they continue to be underrepresented in AD research, limiting the ability to generalize findings to the increasingly diverse US population. To reduce AD disparities, targeted efforts are needed to increase the representation of African Americans in AD research. This mini review identified evidence-based strategies that increased research participation among older African Americans. Four recruitment strategies emerged from eight published peer-reviewed studies that directly evaluated the effectiveness of strategies aimed at increasing the number of African American participants in Alzheimer's research. The strategies include community outreach and education, face-to-face discussions, remote access, and referral and partnership with local organizations. Across different locations, these strategies increased the number of African Americans enrolled into AD research, the number of people that signed up to donate their brains for AD research upon death, and the knowledge and perception of AD in the communities. Targeted efforts are effective in increasing AD research participation among older African Americans, especially when combined with approaches that emphasize transparency and mutual trust and involve the community as stakeholders in the research process. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The African-American Brain Health Initiative at Rutgers University-Newark is a university-community partnership combining community engagement, education and training, and brain health research. Partnering with community-based organizations, it promotes brain health literacy, Alzheimer's awareness, brain-healthy lifestyle choices, and participation in brain research for older African Americans in Greater Newark, New Jersey. Our approach to recruitment relies on building trust through long-term relationships; communicating health knowledge through trusted community leaders; recruiting subjects through targeted efforts; and cultivating research participants as ambassadors. [ABSTRACT FROM AUTHOR]

This study examines whether behavioral measures obtained in nondemented elderly can predict cognitive status at 2-year follow-up. Prior studies have established that delayed paragraph recall can help predict short-term risk for decline to mild cognitive impairment and Alzheimer disease. It was examined whether prediction accuracy can be improved by adding a discrimination-and-generalization task that has previously been shown to be disrupted in nondemented elderly with hippocampal atrophy, a risk factor for Alzheimer disease. Fifty nondemented, medically healthy elderly patients received baseline clinical diagnosis and cognitive testing; 2 years later, patients received a clinical diagnosis of normal, mild cognitive impairment, or probable Alzheimer disease. In all, 2 baseline variables, delayed paragraph recall and generalization performance, were predictive of follow-up outcome with sensitivity of 81% and specificity of 91%-better than the classification accuracy based on either of these measures alone. These preliminary results suggest that these behavioral tasks may be useful tools in predicting short-term cognitive outcome in nondemented elderly. follow-up [ABSTRACT FROM AUTHOR]

The ability to form associations between choice alternatives and their contingent outcomes is an important aspect of learning that may be sensitive to hippocampal dysfunction in memory disorders of aging such as amnestic mild cognitive impairment (MCIa), or early Alzheimer disease. In this preliminary study we examined brain activation using functional magnetic resonance imaging (fMRI) in 12 healthy elderly participants and nine patients with MCIa during an associative learning task. Using a high-field 3.0-Tesla MRI scanner, we examined the dynamic neural response during associative learning over trials. The slope of signal attenuation associated with learning was analyzed for differences between groups within an a priori defined hippocampal region. Results indicated dynamic signal attenuation associated with learning in the healthy elderly sample, but not in MCIa. The absence of an associative learning effect in the MCIa sample reaffirms an important link between the learning difficulties that are commonly encountered in MCIa and the mesial temporal region. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]