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BACKGROUND: Both sleep deficiencies and Alzheimers disease (AD) disproportionately affect older African Americans. Genetic susceptibility to AD further compounds risk for cognitive decline in this population. Aside from APOE ɛ4, ABCA7 rs115550680 is the strongest genetic locus associated with late-onset AD in African Americans. While sleep and ABCA7 rs115550680 independently influence late-life cognitive outcomes, we know too little about the interplay between these two factors on cognitive function. OBJECTIVE: We investigated the interaction between sleep and ABCA7 rs115550680 on hippocampal-dependent cognitive function in older African Americans. METHODS: One-hundred fourteen cognitively healthy older African Americans were genotyped for ABCA7 risk (n = 57 carriers of risk G allele; n = 57 non-carriers), responded to lifestyle questionnaires, and completed a cognitive battery. Sleep was assessed via a self-reported rating of sleep quality (poor, average, good). Covariates included age and years of education. RESULTS: Using ANCOVA, we found that carriers of the risk genotype who reported poor or average sleep quality demonstrated significantly poorer generalization of prior learning-a cognitive marker of AD-compared to their non-risk counterparts. Conversely, there was no genotype-related difference in generalization performance in individuals who reported good sleep quality. CONCLUSION: These results indicate that sleep quality may be neuroprotective against genetic risk for AD. Future studies employing more rigorous methodology should investigate the mechanistic role of sleep neurophysiology in the pathogenesis and progression of AD associated with ABCA7. There is also need for the continued development of non-invasive sleep interventions tailored to racial groups with specific AD genetic risk profiles.

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.

Contemporary evidence suggests that sleep contributes to theextraction of gist from previously encoded experiences, aprocess that relies on compressed memory replay. While thefunctional significance of the time compression is not fullyunderstood, a recent ‘temporal scaffolding’ model suggestedthat compression allows associating encoded events thathappened in disparate times, a critical feature when extractinggist of a temporal nature. We examined this hypothesis usinga novel behavioral paradigm. Subjects were first presentedwith word pairs that could form a new composite word ifcombined (e.g., car, pet --> carpet), and then tested onwhether they falsely recognize seeing the composite word.When subjects napped in between exposure and testing, falsememories of composite words increased, with reaction timesfor false recognition correlating to time spent in slow wavesleep. These results confirm the functional role of timecompression in memory replay, supporting the temporalscaffolding model.

Objectives The objectives of this project were to: (1) examine the relationship between the number of biological children and hippocampal-dependent cognitive performance among older African American women and (2) determine the influence of socioeconomic status (i.e. age, education, marital status, median household income), if any, on this relationship. Methods A total of 146 cognitively unimpaired African American women aged 60 and older were recruited from the greater Newark area and reported their number of biological children, marital status, educational level, and age. We retrieved median household income from census tract data based on the participants' addresses. Participants' cognitive performance was assessed using the Rey Auditory Verbal Learning Test (RAVLT) long delay recall and a Rutgers generalization task (Concurrent Discrimination and Transfer Task). Results As the number of biological children a woman has had increases, the number of generalization errors also increased, indicating poorer hippocampal-dependent cognitive performance when controlling for age, education, marital status, and median household income. There was no significant relationship between the number of children and performance on a standardized neuropsychological measure of episodic memory (RAVLT), although education was a significant covariate. Discussion Generalization tasks may better capture early changes in cognitive performance in older African American women who have had children than standardized neuropsychological assessments. This finding may be explained by the fluctuations in estrogen associated with having children. Future studies should explore how these findings can be applied to protecting cognitive function and preventing Alzheimer's disease in older African American women who have had children. [ABSTRACT FROM AUTHOR]

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]

Depression is highly comorbid among individuals with Parkinson's Disease (PD), who often experience unique challenges to accessing and benefitting from empirically supported interventions like Cognitive Behavioral Therapy (CBT). Given the role of reward processing in both depression and PD, this study analyzed a subset (N = 25) of participants who participated in a pilot telemedicine intervention of PD-informed CBT, and also completed a Reward- and Punishment-Learning Task (RPLT) at baseline. At the conclusion of CBT, participants were categorized into treatment responders (n = 14) and non-responders (n = 11). Responders learned more optimally from negative rather than positive feedback on the RPLT, while this pattern was reversed in non-responders. Computational modeling suggested group differences in learning rate to negative feedback may drive the observed differences. Overall, the results suggest that a within-subject bias for punishment-based learning might help to predict response to CBT intervention for depression in those with PD. Plain Language Summary Performance on a Computerized Task may predict which Parkinson's Disease Patients benefit from Cognitive Behavioral Treatment of Clinical Depression Why was the study done? Clinical depression regularly arises in individuals with Parkinson's Disease (PD) due to the neurobiological changes with the onset and progression of the disease as well as the unique psychosocial difficulties associated with living with a chronic condition. Nonetheless, psychiatric disorders among individuals with PD are often underdiagnosed and likewise undertreated for a variety of reasons. The results of our study have implications about how to improve the accuracy and specificity of mental health treatment recommendations in the future to maximize benefits for individuals with PD, who often face additional barriers to accessing quality mental health treatment. What did the researchers do? We explored whether performance on a computerized task called the Reward- and Punishment-Learning Task (RPLT) helped to predict response to Cognitive Behavioral Therapy (CBT) for depression better than other predictors identified in previous studies. Twenty-five individuals with PD and clinical depression that completed a 10-week telehealth CBT program were assessed for: Demographics (Age, gender, etc.); Clinical information (PD duration, mental health diagnoses, levels of anxiety/depression, etc.); Neurocognitive performance (Memory, processing speed, impulse control, etc.); and RPLT performance. What did the researchers find? A total of 14 participants significantly benefitted from CBT treatment while 11 did not significantly benefit from treatment. There were no differences before treatment in the demographics, clinical information, and neurocognitive performance of those participants who ended up benefitting from the treatment versus those who did not. There were, however, differences before treatment in RPLT performance so that those individuals that benefitted from CBT seemed to learn better from negative feedback. What do the findings mean? Our results suggest that the CBT program benefitted those PD patients with clinical depression that seemed to overall learn best from avoiding punishment rather than obtaining reward which was targeted in CBT by focusing on increasing engagement in rewarding activities. The Reward- and Punishment-Learning Task hence may be a useful tool to help predict treatment response and provide more individualized recommendations on how to best maximize the benefits of psychotherapy for individuals with PD that may struggle to connect to mental health care. Caution is recommended about interpretating these results beyond this study as the overall number of participants was small and the data for this study were collected as part of a previous study so there was no opportunity to include additional measurements of interest. [ABSTRACT FROM AUTHOR]

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.

Humans show consistent differences in the extent to which their behavior reflects a bias toward appetitive approach-related behavior or avoidance of aversive stimuli [Elliot, A. J. Approach and avoidance motivation. In A. J. Elliot (Ed.), Handbook of approach and avoidance motivation (pp. 3-14). New York: Psychology Press, 2008]. We examined the hypothesis that in healthy participants this motivational bias (assessed by self-report and by a probabilistic learning task that allows direct comparison of the relative sensitivity to reward and punishment) reflects lateralization of dopamine signaling. Using [F-18]fallypride to measure D2/D3 binding, we found that self-reported motivational bias was predicted by the asymmetry of frontal D2 binding. Similarly, striatal and frontal asymmetries in D2 dopamine receptor binding, rather than absolute binding levels, predicted individual differences in learning from reward versus punishment. These results suggest that normal variation in asymmetry of dopamine signaling may, in part, underlie human personality and cognition.

We propose a computational theory of hippocampalsystem function in mediating stimulus representation in associative learning. A connectionist model based on this theory is described here, in which the hippocampal system develc^s new and adaptive stimulus repesentations which are predictive, distributed, and compressed: other cortical and cerebellar modules are presumed to use these hippocampal representations to recode their o w n stimulus representations. This computational theory can been seen as an extension and/or refinement of several prior characterizations of hippocampal function. including theories of chunking, stimulus selection, cue-configuration, and contextual coding. The theory does not address temporal aspects of hippocampal function. SimulaticMis of the intact and lesioned model provide an account of data on diverse effects of hippocampal-region lesions, including simple discrimination learning, sensory preconditioning. reversal training, latent inhibition, contextual shifts, and ccMifigural learning. Potential implications of this theory for understanding human declarative m e m o y , temporal processing. and neural mechanisms are briefly discussed.

Recent engineering considerations have prompted an improvement to the least mean squares (LMS) learning rule for training one-layer adaptive networks; incorporating a dynamically modifiable learning rate for each associative weight accellerates overall learning and provides a mechanism for adjusting the salience of individual cues (Sutton, 1992a,b). Prior research has established that the standard L M S rule can characterize aspects of animal learning (Rescorla & Wagner, 1972) and human category learning (Gluck & Bower, 1988a,b). W e illustrate here how this enhanced L M S rule is analogous to adding a cue-salience or attentional component to the psychological model, giving the network model a means for discriminating between relevant and irrelevant cues. W e then demonstrate the effectiveness of this enhanced L M S rule for modeling human performance in two non-stationary learning tasks for which the standard L M S network model fails to adequately account for the data (Hurwitz, 1990; Gluck, Glauthier, & Sutton, in preparation).

The goal of the present study was to elucidate the role of the human striatum in learning via reward and punishment during an associative learning task. Previous studies have identified the striatum as a critical component in the neural circuitry of reward-related learning. It remains unclear, however, under what task conditions, and to what extent, the striatum is modulated by punishment during an instrumental learning task. Using high-resolution functional magnetic resonance imaging (fMRI) during a reward- and punishment-based probabilistic associative learning task, we observed activity in the ventral putamen for stimuli learned via reward regardless of whether participants were correct or incorrect (i.e., outcome). In contrast, activity in the dorsal caudate was modulated by trials that received feedback--either correct reward or incorrect punishment trials. We also identified an anterior/posterior dissociation reflecting reward and punishment prediction error estimates. Additionally, differences in patterns of activity that correlated with the amount of training were identified along the anterior/posterior axis of the striatum. We suggest that unique subregions of the striatum--separated along both a dorsal/ventral and anterior/posterior axis--differentially participate in the learning of associations through reward and punishment.

Most existing models of dopamine and learning in Parkinson disease (PD) focus on simulating the role of basal ganglia dopamine in reinforcement learning. Much data argue, however, for a critical role for prefrontal cortex (PFC) dopamine in stimulus selection in attentional learning. Here, we present a new computational model that simulates performance in multicue category learning, such as the "weather prediction" task. The model addresses how PD and dopamine medications affect stimulus selection processes, which mediate reinforcement learning. In this model, PFC dopamine is key for attentional learning, whereas basal ganglia dopamine, consistent with other models, is key for reinforcement and motor learning. The model assumes that competitive dynamics among PFC neurons is the neural mechanism underlying stimulus selection with limited attentional resources, whereas competitive dynamics among striatal neurons is the neural mechanism underlying action selection. According to our model, PD is associated with decreased phasic and tonic dopamine levels in both PFC and basal ganglia. We assume that dopamine medications increase dopamine levels in both the basal ganglia and PFC, which, in turn, increase tonic dopamine levels but decrease the magnitude of phasic dopamine signaling in these brain structures. Increase of tonic dopamine levels in the simulated PFC enhances attentional shifting performance. The model provides a mechanistic account for several phenomena, including (a) medicated PD patients are more impaired at multicue probabilistic category learning than unmedicated patients and (b) medicated PD patients opt out of reversal when there are alternative and redundant cue dimensions.