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A meta–analytic study was conducted to examine the hypothesis that aerobic fitness training enhances the cognitive vitality of healthy but sedentary older adults. Eighteen intervention studies published between 1966 and 2001 were entered into the analysis. Several theoretically and practically important results were obtained. Most important, fitness training was found to have robust but selective benefits for cognition, with the largest fitness–induced benefits occurring for executive–control processes. The magnitude of fitness effects on cognition was also moderated by a number of programmatic and methodological factors, including the length of the fitness–training intervention, the type of the intervention, the duration of training sessions, and the gender of the study participants. The results are discussed in terms of recent neuroscientific and psychological data that indicate cognitive and neural plasticity is maintained throughout the life span. [ABSTRACT FROM AUTHOR]

The instructions for most explicit memory tests use language that emphasizes the memorial component of the task. This language may put older adults at a disadvantage relative to younger adults because older adults believe that their memories have deteriorated. Consequently, typical explicit memory tests may overestimate age-related decline in cognitive performance. In 2 experiments, older and younger adults performed a memory test on newly learned trivia. In both experiments, age differences were obtained when the instructions emphasized the memory component of the task (memory emphasis) but not when the instructions did not emphasize memory (memory neutral). These findings suggest that aspects of the testing situation. such as experimental instructions, may exaggerate age differences in memory performance and need to be considered when designing studies investigating age differences in memory. [ABSTRACT FROM AUTHOR]

Brain age, a measure of biological aging in the brain, has been linked to psychiatric illness, principally in adult populations. Components of socioeconomic status (SES) associate with differences in brain structure and psychiatric risk across the lifespan. This study aimed to investigate the influence of SES on brain aging in childhood and adolescence, a period of rapid neurodevelopment and peak onset for many psychiatric disorders. We reanalyzed data from the Healthy Brain Network to examine the influence of SES components (occupational prestige, public assistance enrollment, parent education, and household income-to-needs ratio [INR]) on relative brain age (RBA). Analyses included 470 youth (5-17 years; 61.3% men), self-identifying as White (55%), African American (15%), Hispanic (9%), or multiracial (17.2%). Household income was 3.95 ± 2.33 (mean ± SD ) times the federal poverty threshold. RBA quantified differences between chronological age and brain age using covariation patterns of morphological features and total volumes. We also examined associations between RBA and psychiatric symptoms (Child Behavior Checklist [CBCL]). Models covaried for sex, scan location, and parent psychiatric diagnoses. In a linear regression, lower RBA is associated with lower parent occupational prestige ( p = .01), lower public assistance enrollment ( p = .03), and more parent psychiatric diagnoses ( p = .01), but not parent education or INR. Lower parent occupational prestige ( p = .02) and lower RBA ( p = .04) are associated with higher CBCL anxious/depressed scores. Our findings underscore the importance of including SES components in developmental brain research. Delayed brain aging may represent a potential biological pathway from SES to psychiatric risk. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Evidence of comparing neural network differences between anxiety disorder subtypes is limited, while it is crucial to reveal the pathogenesis of anxiety disorders. The present study aimed to investigate specific and common resting-state functional connectivity (FC) networks in generalized anxiety disorder (GAD), panic disorder (PD), and healthy controls (HC). We employed the gRAICAR algorithm to decompose the resting-state fMRI into independent components and align the components across 61 subjects (22 GAD, 18 PD and 21 HC). The default mode network and precuneus network exhibited GAD-specific aberrance, the anterior default mode network showed atypicality specific to PD, and the right fronto-parietal network showed aberrance common to GAD and PD. Between GAD-specific networks, FC between bilateral dorsolateral prefrontal cortex (DLPFC) was positively correlated with interoceptive sensitivity. In the common network, altered FCs between DLPFC and angular gyrus, and between orbitofrontal cortex and precuneus, were positively correlated with anxiety severity and interoceptive sensitivity. The pathological mechanism of PD could closely relate to the dysfunction of prefrontal cortex, while GAD could involve more extensive brain areas, which may be related to fear generalization., Competing Interests: Declaration of Competing Interest None., (Copyright © 2022. Published by Elsevier B.V.)

Arterial spin labeled (ASL) magnetic resonance imaging (MRI) is the primary method for noninvasively measuring regional brain perfusion in humans. We introduce ASLPrep, a suite of software pipelines that ensure the reproducible and generalizable processing of ASL MRI data., (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Pediatric brain imaging holds significant promise for understanding neurodevelopment. However, the requirement to remain still inside a noisy, enclosed scanner remains a challenge. Verbal or visual descriptions of the process, and/or practice in MRI simulators are the norm in preparing children. Yet, the factors predictive of successfully obtaining neuroimaging data remain unclear. We examined data from 250 children (6-12 years, 197 males) with autism and/or attention-deficit/hyperactivity disorder. Children completed systematic MRI simulator training aimed to habituate to the scanner environment and minimize head motion. An MRI session comprised multiple structural, resting-state, task and diffusion scans. Of the 201 children passing simulator training and attempting scanning, nearly all (94%) successfully completed the first structural scan in the sequence, and 88% also completed the following functional scan. The number of successful scans decreased as the sequence progressed. Multivariate analyses revealed that age was the strongest predictor of successful scans in the session, with younger children having lower success rates. After age, sensorimotor atypicalities contributed most to prediction. Results provide insights on factors to consider in designing pediatric brain imaging protocols., (Copyright © 2021. Published by Elsevier Ltd.)

New large neuroimaging studies, such as the Adolescent Brain Cognitive Development study (ABCD) and Human Connectome Project (HCP) Development studies are adopting a new T1-weighted imaging sequence with prospective motion correction (PMC) in favor of the more traditional 3-Dimensional Magnetization-Prepared Rapid Gradient-Echo Imaging (MPRAGE) sequence. Here, we used a developmental dataset (ages 5-21, N = 348) from the Healthy Brain Network (HBN) Initiative to directly compare two widely used MRI structural sequences: one based on the Human Connectome Project (MPRAGE) and another based on the ABCD study (MPRAGE+PMC). We aimed to determine if the morphometric measurements obtained from both protocols are equivalent or if one sequence has a clear advantage over the other. The sequences were also compared through quality control measurements. Inter- and intra-sequence reliability were assessed with another set of participants (N = 71) from HBN that performed two MPRAGE and two MPRAGE+PMC sequences within the same imaging session, with one MPRAGE (MPRAGE1) and MPRAGE+PMC (MPRAGE+PMC1) pair at the beginning of the session and another pair (MPRAGE2 and MPRAGE+PMC2) at the end of the session. Intraclass correlation coefficients (ICC) scores for morphometric measurements such as volume and cortical thickness showed that intra-sequence reliability is the highest with the two MPRAGE+PMC sequences and lowest with the two MPRAGE sequences. Regarding inter-sequence reliability, ICC scores were higher for the MPRAGE1 - MPRAGE+PMC1 pair at the beginning of the session than the MPRAGE1 - MPRAGE2 pair, possibly due to the higher motion artifacts in the MPRAGE2 run. Results also indicated that the MPRAGE+PMC sequence is robust, but not impervious, to high head motion. For quality control metrics, the traditional MPRAGE yielded better results than MPRAGE+PMC in 5 of the 8 measurements. In conclusion, morphometric measurements evaluated here showed high inter-sequence reliability between the MPRAGE and MPRAGE+PMC sequences, especially in images with low head motion. We suggest that studies targeting hyperkinetic populations use the MPRAGE+PMC sequence, given its robustness to head motion and higher reliability scores. However, neuroimaging researchers studying non-hyperkinetic participants can choose either MPRAGE or MPRAGE+PMC sequences, but should carefully consider the apparent tradeoff between relatively increased reliability, but reduced quality control metrics when using the MPRAGE+PMC sequence., Competing Interests: Declaration of Competing Interest All authors declare that they do not have any conflicts of interest., (Copyright © 2020. Published by Elsevier Inc.)

Multilayer network models have been proposed as an effective means of capturing the dynamic configuration of distributed neural circuits and quantitatively describing how communities vary over time. Beyond general insights into brain function, a growing number of studies have begun to employ these methods for the study of individual differences. However, test-retest reliabilities for multilayer network measures have yet to be fully quantified or optimized, potentially limiting their utility for individual difference studies. Here, we systematically evaluated the impact of multilayer community detection algorithms, selection of network parameters, scan duration, and task condition on test-retest reliabilities of multilayer network measures (i.e., flexibility, integration, and recruitment). A key finding was that the default method used for community detection by the popular generalized Louvain algorithm can generate erroneous results. Although available, an updated algorithm addressing this issue is yet to be broadly adopted in the neuroimaging literature. Beyond the algorithm, the present work identified parameter selection as a key determinant of test-retest reliability; however, optimization of these parameters and expected reliabilities appeared to be dataset-specific. Once parameters were optimized, consistent with findings from the static functional connectivity literature, scan duration was a much stronger determinant of reliability than scan condition. When the parameters were optimized and scan duration was sufficient, both passive (i.e., resting state, Inscapes, and movie) and active (i.e., flanker) tasks were reliable, although reliability in the movie watching condition was significantly higher than in the other three tasks. The minimal data requirement for achieving reliable measures for the movie watching condition was 20 min, and 30 min for the other three tasks. Our results caution the field against the use of default parameters without optimization based on the specific datasets to be employed - a process likely to be limited for most due to the lack of test-retest samples to enable parameter optimization., (Copyright © 2020. Published by Elsevier Inc.)

Humans often face sequential decision-making problems, in which information about the environmental reward structure is detached from rewards for a subset of actions. In the current exploratory study, we introduce an information-selective symmetric reversal bandit task to model such situations and obtained choice data on this task from 24 participants. To arbitrate between different decision-making strategies that participants may use on this task, we developed a set of probabilistic agent-based behavioral models, including exploitative and explorative Bayesian agents, as well as heuristic control agents. Upon validating the model and parameter recovery properties of our model set and summarizing the participants' choice data in a descriptive way, we used a maximum likelihood approach to evaluate the participants' choice data from the perspective of our model set. In brief, we provide quantitative evidence that participants employ a belief state-based hybrid explorative-exploitative strategy on the information-selective symmetric reversal bandit task, lending further support to the finding that humans are guided by their subjective uncertainty when solving exploration-exploitation dilemmas., Supplementary Information: The online version contains supplementary material available at 10.1007/s42113-021-00112-3., Competing Interests: Conflict of InterestsThe authors declare no competing interests., (© The Author(s) 2021.)

The collection of eye gaze information during functional magnetic resonance imaging (fMRI) is important for monitoring variations in attention and task compliance, particularly for naturalistic viewing paradigms (e.g., movies). However, the complexity and setup requirements of current in-scanner eye tracking solutions can preclude many researchers from accessing such information. Predictive eye estimation regression (PEER) is a previously developed support vector regression-based method for retrospectively estimating eye gaze from the fMRI signal in the eye's orbit using a 1.5-min calibration scan. Here, we provide confirmatory validation of the PEER method's ability to infer eye gaze on a TR-by-TR basis during movie viewing, using simultaneously acquired eye tracking data in five individuals (median angular deviation < 2°). Then, we examine variations in the predictive validity of PEER models across individuals in a subset of data (n = 448) from the Child Mind Institute Healthy Brain Network Biobank, identifying head motion as a primary determinant. Finally, we accurately classify which of the two movies is being watched based on the predicted eye gaze patterns (area under the curve = 0.90 ± 0.02) and map the neural correlates of eye movements derived from PEER. PEER is a freely available and easy-to-use tool for determining eye fixations during naturalistic viewing., (© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Data sharing is increasingly recommended as a means of accelerating science by facilitating collaboration, transparency, and reproducibility. While few oppose data sharing philosophically, a range of barriers deter most researchers from implementing it in practice. To justify the significant effort required for sharing data, funding agencies, institutions, and investigators need clear evidence of benefit. Here, using the International Neuroimaging Data-sharing Initiative, we present a case study that provides direct evidence of the impact of open sharing on brain imaging data use and resulting peer-reviewed publications. We demonstrate that openly shared data can increase the scale of scientific studies conducted by data contributors, and can recruit scientists from a broader range of disciplines. These findings dispel the myth that scientific findings using shared data cannot be published in high-impact journals, suggest the transformative power of data sharing for accelerating science, and underscore the need for implementing data sharing universally.

Complementing long-standing traditions centered on histology, fMRI approaches are rapidly maturing in delineating brain areal organization at the macroscale. The non-human primate (NHP) provides the opportunity to overcome critical barriers in translational research. Here, we establish the data requirements for achieving reproducible and internally valid parcellations in individuals. We demonstrate that functional boundaries serve as a functional fingerprint of the individual animals and can be achieved under anesthesia or awake conditions (rest, naturalistic viewing), though differences between awake and anesthetized states precluded the detection of individual differences across states. Comparison of awake and anesthetized states suggested a more nuanced picture of changes in connectivity for higher-order association areas, as well as visual and motor cortex. These results establish feasibility and data requirements for the generation of reproducible individual-specific parcellations in NHPs, provide insights into the impact of scan state, and motivate efforts toward harmonizing protocols., (Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.)

We discuss the factors that encouraged us to examine the question of whether exercise training has a positive influence on cognitive health of older adults in 2003. At that time there was a substantial literature on exercise and cognition. However, cognitive assessment instruments, exercise protocols (including type of exercise, length, and intensity of exercise programs), and subject-selection criteria differed widely. Our meta-analysis enabled us to examine both the main question under study-exercise effects on cognition-and potential moderators of this effect. Several interesting findings, which are briefly detailed in the present article, were revealed by our analyses. The current article also examines where the literature has gone since our 2003 article.

We extend the notion of an influence or hat matrix to regression with functional responses and scalar predictors. For responses depending linearly on a set of predictors, our definition is shown to reduce to the conventional influence matrix for linear models. The pointwise degrees of freedom, the trace of the pointwise influence matrix, are shown to have an adaptivity property that motivates a two-step bivariate smoother for modeling nonlinear dependence on a single predictor. This procedure adapts to varying complexity of the nonlinear model at different locations along the function, and thereby achieves better performance than competing tensor product smoothers in an analysis of the development of white matter microstructure in the brain., (© 2017, The International Biometric Society.)

Connectomics has enhanced our understanding of neurocognitive development and decline by the integration of network sciences into studies across different stages of the human life span. However, these studies commonly occurred independently, missing the opportunity to test integrated models of the dynamical brain organization across the entire life span. In this review article, we survey empirical findings in life-span connectomics and propose a generative framework for computationally modeling the connectome over the human life span. This framework highlights initial findings that across the life span, the human connectome gradually shifts from an 'anatomically driven' organization to one that is more 'topological'. Finally, we consider recent advances that are promising to provide an integrative and systems perspective of human brain plasticity as well as underscore the pitfalls and challenges., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Alteration in self-perception is a salient feature in major depression. Hyperactivity of anterior cortical midline regions has been implicated in this phenomenon in depressed adults. Here, we extend this work to depressed adolescents during a developmental time when neuronal circuitry underlying the sense of self matures by using task-based functional magnetic resonance imaging (fMRI) and connectivity analyses. Twenty-three depressed adolescents and 18 healthy controls (HC) viewed positive and negative trait words in a scanner and judged whether each word described them ('self' condition) or was a good trait to have ('general' condition). Self-perception scores were based on participants' endorsements of positive and negative traits during the fMRI task. Depressed adolescents exhibited more negative self-perceptions than HC. Both groups activated cortical midline regions in response to self-judgments compared to general-judgments. However, depressed adolescents recruited the posterior cingulate cortex/precuneus more for positive self-judgments. Additionally, local connectivity of the dorsal medial prefrontal cortex was reduced during self-reflection in depressed adolescents. Our findings highlight differences in self-referential processing network function between depressed and healthy adolescents and support the need for further investigation of brain mechanisms associated with the self, as they may be paramount to understanding the etiology and development of major depressive disorder., (Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Transcranial magnetic stimulation (TMS) is a powerful investigational tool for in vivo manipulation of regional or network activity, with a growing number of potential clinical applications. Unfortunately, the vast majority of targeting strategies remain limited by their reliance on non-realistic brain models and assumptions that anatomo-functional relationships are 1:1. Here, we present an integrated framework that combines anatomically realistic finite element models of the human head with resting functional MRI to predict functional networks targeted via TMS at a given coil location and orientation. Using data from the Human Connectome Project, we provide an example implementation focused on dorsolateral prefrontal cortex (DLPFC). Three distinct DLPFC stimulation zones were identified, differing with respect to the network to be affected (default, frontoparietal) and sensitivity to coil orientation. Network profiles generated for DLPFC targets previously published for treating depression revealed substantial variability across studies, highlighting a potentially critical technical issue., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Functional connectomics is one of the most rapidly expanding areas of neuroimaging research. Yet, concerns remain regarding the use of resting-state fMRI (R-fMRI) to characterize inter-individual variation in the functional connectome. In particular, recent findings that "micro" head movements can introduce artifactual inter-individual and group-related differences in R-fMRI metrics have raised concerns. Here, we first build on prior demonstrations of regional variation in the magnitude of framewise displacements associated with a given head movement, by providing a comprehensive voxel-based examination of the impact of motion on the BOLD signal (i.e., motion-BOLD relationships). Positive motion-BOLD relationships were detected in primary and supplementary motor areas, particularly in low motion datasets. Negative motion-BOLD relationships were most prominent in prefrontal regions, and expanded throughout the brain in high motion datasets (e.g., children). Scrubbing of volumes with FD>0.2 effectively removed negative but not positive correlations; these findings suggest that positive relationships may reflect neural origins of motion while negative relationships are likely to originate from motion artifact. We also examined the ability of motion correction strategies to eliminate artifactual differences related to motion among individuals and between groups for a broad array of voxel-wise R-fMRI metrics. Residual relationships between motion and the examined R-fMRI metrics remained for all correction approaches, underscoring the need to covary motion effects at the group-level. Notably, global signal regression reduced relationships between motion and inter-individual differences in correlation-based R-fMRI metrics; Z-standardization (mean-centering and variance normalization) of subject-level maps for R-fMRI metrics prior to group-level analyses demonstrated similar advantages. Finally, our test-retest (TRT) analyses revealed significant motion effects on TRT reliability for R-fMRI metrics. Generally, motion compromised reliability of R-fMRI metrics, with the exception of those based on frequency characteristics - particularly, amplitude of low frequency fluctuations (ALFF). The implications of our findings for decision-making regarding the assessment and correction of motion are discussed, as are insights into potential differences among volume-based metrics of motion., (Copyright © 2013 Elsevier Inc. All rights reserved.)

At macroscopic scales, the human connectome comprises anatomically distinct brain areas, the structural pathways connecting them and their functional interactions. Annotation of phenotypic associations with variation in the connectome and cataloging of neurophenotypes promise to transform our understanding of the human brain. In this Review, we provide a survey of magnetic resonance imaging–based measurements of functional and structural connectivity. We highlight emerging areas of development and inquiry and emphasize the importance of integrating structural and functional perspectives on brain architecture.

The brain's intrinsic functional architecture, revealed in correlated spontaneous activity, appears to constitute a faithful representation of its repertoire of evoked, extrinsic functional interactions. Here, using broad task contrasts to probe evoked patterns of coactivation, we demonstrate tight coupling between the brain's intrinsic and extrinsic functional architectures for default and task-positive regions, but not for subcortical and limbic regions or for primary sensory and motor cortices. While strong correspondence likely reflects persistent or recurrent patterns of evoked coactivation, weak correspondence may exist for regions whose patterns of evoked functional interactions are more adaptive and context dependent. These findings were independent of task. For tight task contrasts (e.g., incongruent vs. congruent trials), evoked patterns of coactivation were unrelated to the intrinsic functional architecture, suggesting that high-level task demands are accommodated by context-specific modulations of functional interactions. We conclude that intrinsic approaches provide only a partial understanding of the brain's functional architecture. Appreciating the full repertoire of dynamic neural responses will continue to require task-based functional magnetic resonance imaging approaches.

Neuroscience is increasingly focusing on developmental factors related to human structural and functional connectivity. Unfortunately, to date, diffusion-based imaging approaches have only contributed modestly to these broad objectives, despite the promise of diffusion-based tractography. Here, we report a novel data-driven approach to detect similarities and differences among white matter tracts with respect to their developmental trajectories, using 64-direction diffusion tensor imaging. Specifically, using a cross-sectional sample comprising 144 healthy individuals (7 to 48 years old), we applied k-means cluster analysis to separate white matter voxels based on their age-related trajectories of fractional anisotropy. Optimal solutions included 5-, 9- and 14-clusters. Our results recapitulate well-established tracts (e.g., internal and external capsule, optic radiations, corpus callosum, cingulum bundle, cerebral peduncles) and subdivisions within tracts (e.g., corpus callosum, internal capsule). For all but one tract identified, age-related trajectories were curvilinear (i.e., inverted 'U-shape'), with age-related increases during childhood and adolescence followed by decreases in middle adulthood. Identification of peaks in the trajectories suggests that age-related losses in fractional anisotropy occur as early as 23 years of age, with mean onset at 30 years of age. Our findings demonstrate that data-driven analytic techniques may be fruitfully applied to extant diffusion tensor imaging datasets in normative and neuropsychiatric samples.

Although it is being successfully implemented for exploration of the genome, discovery science has eluded the functional neuroimaging community. The core challenge remains the development of common paradigms for interrogating the myriad functional systems in the brain without the constraints of a priori hypotheses. Resting-state functional MRI (R-fMRI) constitutes a candidate approach capable of addressing this challenge. Imaging the brain during rest reveals large-amplitude spontaneous low-frequency (<0.1 Hz) fluctuations in the fMRI signal that are temporally correlated across functionally related areas. Referred to as functional connectivity, these correlations yield detailed maps of complex neural systems, collectively constituting an individual's "functional connectome." Reproducibility across datasets and individuals suggests the functional connectome has a common architecture, yet each individual's functional connectome exhibits unique features, with stable, meaningful interindividual differences in connectivity patterns and strengths. Comprehensive mapping of the functional connectome, and its subsequent exploitation to discern genetic influences and brain-behavior relationships, will require multicenter collaborative datasets. Here we initiate this endeavor by gathering R-fMRI data from 1,414 volunteers collected independently at 35 international centers. We demonstrate a universal architecture of positive and negative functional connections, as well as consistent loci of inter-individual variability. Age and sex emerged as significant determinants. These results demonstrate that independent R-fMRI datasets can be aggregated and shared. High-throughput R-fMRI can provide quantitative phenotypes for molecular genetic studies and biomarkers of developmental and pathological processes in the brain. To initiate discovery science of brain function, the 1000 Functional Connectomes Project dataset is freely accessible at www.nitrc.org/projects/fcon&#95;1000/.

Fitness and education may protect against cognitive impairments in aging. They may also counteract age-related structural changes within the brain. Here we analyzed volumetric differences in cerebrospinal fluid and gray and white matter, along with neuropsychological data, in adults differing in age, fitness, and education. Cognitive performance was correlated with fitness and education. Voxel-based morphometry was used for a whole-brain analysis of structural magnetic resonance images. We found age-related losses in gray and white matter in medial-temporal, parietal, and frontal areas. As in previous work, fitness within the old correlated with preserved gray matter in the same areas. In contrast, higher education predicted preserved white matter in inferior frontal areas. These data suggest that fitness and education may both be predictive of preserved cognitive function in aging through separable effects on brain structure.

Older adults' difficulties in performing two tasks concurrently have been well documented (Kramer & Madden, 2008). It has been observed that the age-related differences in dual-task performance are larger when the two tasks require similar motor responses (2001) and that in some conditions older adults also show greater susceptibility than younger adults to input interference (Hein & Schubert, 2004). The authors recently observed that even when the two tasks require motor responses, both older and younger adults can learn to perform a visual discrimination task and an auditory discrimination task faster and more accurately (Bherer et al., 2005). In the present study, the authors extended this finding to a dual-task condition that involves two visual tasks requiring two motor responses. Older and younger adults completed a dual-task training program in which continuous individualized adaptive feedback was provided to enhance performance. The results indicate that, even with similar motor responses and two visual stimuli, both older and younger adults showed substantial gains in performance after training and that the improvement generalized to new task combinations involving new stimuli. These results suggest that dual-task skills can be substantially improved in older adults and that cognitive plasticity in attentional control is still possible in old age.

Laboratory based training studies suggest that older adults can benefit from training in tasks that tap control aspects of attention. This was further explored in the present study in which older and younger adults completed an adaptive and individualized dual-task training program. The testing-the-limits approach was used [Lindenberger, U., & Baltes, P. B. (1995). Testing-the-limits and experimental simulation: Two methods to explicate the role of learning in development. Human Development, 38, 349-360.] in order to gain insight into how attentional control can be improved in older adults. Results indicated substantial improvement in overlapping task performance in both younger and older participants suggesting the availability of cognitive plasticity in both age groups. Improvement was equivalent among age groups in response speed and performance variability but larger in response accuracy for older adults. The results suggest that time-sharing skills can be substantially improved in older adults.

A number of studies have suggested that attentional control skills required to perform 2 tasks concurrently become impaired with age (A. A. Hartley, 1992; J. M. McDowd & R. J. Shaw, 2000). A. A. Hartley (2001) recently observed that the age-related differences in dual-task performance were larger when the 2 tasks required similar motor responses. The present study examined the extent to which age-related deficits in dual-task performance or time sharing--in particular, dual-task performance of 2 discrimination tasks with similar motor requirements--can be moderated by training. The results indicate that, even when the 2 tasks required similar motor responses, both older and younger adults could learn to perform the tasks faster and more accurately. Moreover, the improvement in performance generalized to new task combinations involving new stimuli. Therefore, it appears that training can substantially improve dual-task processing skills in older adults., ((c) 2006 APA)

The present experiment examined the degree to which experience with different stimulus characteristics affects attentional capture, particularly as related to aging. Participants were presented with onset target/color singleton distractor or color singleton target/onset distractor pairs across three experimental sessions. The target/distractor pairs were reversed in the second session such that the target in the first session became the distractor in the second and third sessions. For both young and old adults previous experience with color as a target defining feature influenced oculomotor capture with task-irrelevant color distractors. Experience with sudden onsets had the same effect for younger and older adults, although capture effects were substantially larger for onset than for color distractors. Experience-based capture effects diminished relatively rapidly after target and distractor-defining properties were reversed. The results are discussed in terms of top-down and stimulus-driven effects on age-related differences in attentional control.

We briefly review the extant human and animal literature on the influence of fitness training on brain, cognition and performance. The animal research provides clear support for neurochemical and structural changes in brain with fitness training. The human literature suggests reliable but process specific changes in cognition with fitness training for young and old adults. We describe a research program which examines the influence of aerobic fitness training on the functional activity of the human using event-related functional magnetic resonance imaging, of humans in fitness interventions.

Three studies examined cultural and situational influences on the tendency for people to use their current life satisfaction to predict future life events. On the basis of the self-enhancement literature, it was predicted that either writing about a positive personal experience or reading about another's negative experience would lead European Americans to focus their attention on internal attributes and thus would lead them to use their current life satisfaction in predicting the future. Conversely, on the basis of the self-criticism literature, it was predicted that these same conditions would lead Asian Americans to focus their attention on external factors and, therefore, would decrease their likelihood of using their current life satisfaction to predict the future. Studies 1 and 2 supported these hypotheses. Study 3 showed that these patterns could be obtained by subliminally priming concepts associated with individualism and collectivism.