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  • 1
    In: The Journal of Neuroscience, Society for Neuroscience, Vol. 33, No. 41 ( 2013-10-09), p. 16249-16261
    Abstract: Adolescence is characterized by rapid development of executive function. Working memory (WM) is a key element of executive function, but it is not known what brain changes during adolescence allow improved WM performance. Using a fractal n -back fMRI paradigm, we investigated brain responses to WM load in 951 human youths aged 8–22 years. Compared with more limited associations with age, WM performance was robustly associated with both executive network activation and deactivation of the default mode network. Multivariate patterns of brain activation predicted task performance with a high degree of accuracy, and also mediated the observed age-related improvements in WM performance. These results delineate a process of functional maturation of the executive system, and suggest that this process allows for the improvement of cognitive capability seen during adolescence.
    Type of Medium: Online Resource
    ISSN: 0270-6474 , 1529-2401
    Language: English
    Publisher: Society for Neuroscience
    Publication Date: 2013
    detail.hit.zdb_id: 1475274-8
    SSG: 12
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  • 2
    Online Resource
    Online Resource
    Society for Neuroscience ; 2003
    In:  The Journal of Neuroscience Vol. 23, No. 8 ( 2003-04-15), p. 3295-3301
    In: The Journal of Neuroscience, Society for Neuroscience, Vol. 23, No. 8 ( 2003-04-15), p. 3295-3301
    Type of Medium: Online Resource
    ISSN: 0270-6474 , 1529-2401
    Language: English
    Publisher: Society for Neuroscience
    Publication Date: 2003
    detail.hit.zdb_id: 1475274-8
    SSG: 12
    Location Call Number Limitation Availability
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  • 3
    In: The Journal of Neuroscience, Society for Neuroscience, Vol. 40, No. 6 ( 2020-02-05), p. 1265-1275
    Abstract: Adolescence is a time of extensive neural restructuring, leaving one susceptible to atypical development. Although neural maturation in humans can be measured using functional and structural MRI, the subtle patterns associated with the initial stages of abnormal change may be difficult to identify, particularly at an individual level. Brain age prediction models may have utility in assessing brain development in an individualized manner, as deviations between chronological age and predicted brain age could reflect one's divergence from typical development. Here, we built a support vector regression model to summarize high-dimensional neuroimaging as an index of brain age in both sexes. Using structural and functional MRI data from two large pediatric datasets and a third clinical dataset, we produced and validated a two-dimensional neural maturation index (NMI) that characterizes typical brain maturation patterns and identifies those who deviate from this trajectory. Examination of brain signatures associated with NMI scores revealed that elevated scores were related to significantly lower gray matter volume and significantly higher white matter volume, particularly in high-order regions such as the prefrontal cortex. Additionally, those with higher NMI scores exhibited enhanced connectivity in several functional brain networks, including the default mode network. Analysis of data from a sample of male and female patients with schizophrenia revealed an association between advanced NMI scores and schizophrenia diagnosis in participants aged 16–22, confirming the NMI's utility as a marker of atypicality. Altogether, our findings support the NMI as an individualized, interpretable measure by which neural development in adolescence may be assessed. SIGNIFICANCE STATEMENT The substantial neural restructuring that occurs during adolescence increases one's vulnerability to aberration. A brain index that is capable of capturing one's conformance with typical development will allow for individualized assessment and enhance our understanding of typical and atypical development. In this analysis, we produce a neural maturation index (NMI) using support vector regression and a large pediatric sample. This index generalizes across multiple cohorts and shows potential in the identification of clinical groups. We also implement a novel method for examining the developmental trajectory through data-driven analysis. The signatures identified by the NMI reflect key stages of the extensive neural development that occurs during adolescence and support its utility as a metric of typical brain development.
    Type of Medium: Online Resource
    ISSN: 0270-6474 , 1529-2401
    Language: English
    Publisher: Society for Neuroscience
    Publication Date: 2020
    detail.hit.zdb_id: 1475274-8
    SSG: 12
    Location Call Number Limitation Availability
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  • 4
    In: The Journal of Neuroscience, Society for Neuroscience, Vol. 38, No. 10 ( 2018-03-07), p. 2471-2481
    Abstract: Adolescence is characterized by both maturation of brain structure and increased risk of negative outcomes from behaviors associated with impulsive decision-making. One important index of impulsive choice is delay discounting (DD), which measures the tendency to prefer smaller rewards available soon over larger rewards delivered after a delay. However, it remains largely unknown how individual differences in structural brain development may be associated with impulsive choice during adolescence. Leveraging a unique large sample of 427 human youths (208 males and 219 females) imaged as part of the Philadelphia Neurodevelopmental Cohort, we examined associations between delay discounting and cortical thickness within structural covariance networks. These structural networks were derived using non-negative matrix factorization, an advanced multivariate technique for dimensionality reduction, and analyzed using generalized additive models with penalized splines to capture both linear and nonlinear developmental effects. We found that impulsive choice, as measured by greater discounting, was most strongly associated with diminished cortical thickness in structural brain networks that encompassed the ventromedial prefrontal cortex, orbitofrontal cortex, temporal pole, and temporoparietal junction. Furthermore, structural brain networks predicted DD above and beyond cognitive performance. Together, these results suggest that reduced cortical thickness in regions known to be involved in value-based decision-making is a marker of impulsive choice during the critical period of adolescence. SIGNIFICANCE STATEMENT Risky behaviors during adolescence, such as initiation of substance use or reckless driving, are a major source of morbidity and mortality. In this study, we present evidence from a large sample of youths that diminished cortical thickness in specific structural brain networks is associated with impulsive choice. Notably, the strongest association between impulsive choice and brain structure was seen in regions implicated in value-based decision-making; namely, the ventromedial prefrontal and orbitofrontal cortices. Moving forward, such neuroanatomical markers of impulsivity may aid in the development of personalized interventions targeted to reduce risk of negative outcomes resulting from impulsivity during adolescence.
    Type of Medium: Online Resource
    ISSN: 0270-6474 , 1529-2401
    Language: English
    Publisher: Society for Neuroscience
    Publication Date: 2018
    detail.hit.zdb_id: 1475274-8
    SSG: 12
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
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