Literature DB >> 24773417

Within-individual variability in neurocognitive performance: age- and sex-related differences in children and youths from ages 8 to 21.

David R Roalf1, Raquel E Gur1, Kosha Ruparel1, Monica E Calkins1, Theodore D Satterthwaite1, Warren B Bilker2, Hakon Hakonarson3, Lauren Julius Harris4, Ruben C Gur1.   

Abstract

OBJECTIVE: The transition from childhood to adulthood is characterized by improved motor and cognitive performance in many domains. Developmental studies focus on average performance in single domains but ignore consistency of performance across domains. Within-individual variability (WIV) provides an index of that evenness and is a potential marker of development.
METHOD: We gave a computerized battery of 14 neurocognitive tests to 9138 youths ages 8-21 from the Philadelphia Neurodevelopmental Cohort.
RESULTS: As expected, performance improved with age, with both accuracy and speed peaking in adulthood. WIV, however, showed a U-shaped course: highest in childhood, declining yearly into mid-adolescence, and increasing again into adulthood. Young females outperformed and were less variable than males, but by early adulthood male performance matched that of females despite being more variable.
CONCLUSION: We conclude that WIV declines from childhood to adolescence as developmental lags are overcome, and then increases into adulthood reflecting the emergence of cognitive specializations related to skill-honing and brain maturation.

Entities:  

Mesh:

Year:  2014        PMID: 24773417      PMCID: PMC4175525          DOI: 10.1037/neu0000067

Source DB:  PubMed          Journal:  Neuropsychology        ISSN: 0894-4105            Impact factor:   3.295


  45 in total

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2.  Maturation of cognitive processes from late childhood to adulthood.

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Review 5.  Gender differences across age in motor performance a meta-analysis.

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7.  Staying on the job: the frontal lobes control individual performance variability.

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9.  Cognitive sex differences are not magnified as a function of age, sex hormones, or puberty development during early adolescence.

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Authors:  Dominika Dykiert; Geoff Der; John M Starr; Ian J Deary
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  36 in total

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2.  Control-group feature normalization for multivariate pattern analysis of structural MRI data using the support vector machine.

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3.  Emotion recognition deficits as predictors of transition in individuals at clinical high risk for schizophrenia: a neurodevelopmental perspective.

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4.  The Philadelphia Neurodevelopmental Cohort: A publicly available resource for the study of normal and abnormal brain development in youth.

Authors:  Theodore D Satterthwaite; John J Connolly; Kosha Ruparel; Monica E Calkins; Chad Jackson; Mark A Elliott; David R Roalf; Ryan Hopson; Karthik Prabhakaran; Meckenzie Behr; Haijun Qiu; Frank D Mentch; Rosetta Chiavacci; Patrick M A Sleiman; Ruben C Gur; Hakon Hakonarson; Raquel E Gur
Journal:  Neuroimage       Date:  2015-03-31       Impact factor: 6.556

5.  Allometric Analysis Detects Brain Size-Independent Effects of Sex and Sex Chromosome Complement on Human Cerebellar Organization.

Authors:  Catherine Mankiw; Min Tae M Park; P K Reardon; Ari M Fish; Liv S Clasen; Deanna Greenstein; Jay N Giedd; Jonathan D Blumenthal; Jason P Lerch; M Mallar Chakravarty; Armin Raznahan
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6.  Sex differences in spatial accuracy relate to the neural activation of antagonistic muscles in young adults.

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Review 7.  Sex differences in brain and behavior in adolescence: Findings from the Philadelphia Neurodevelopmental Cohort.

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8.  White matter microstructural deficits in 22q11.2 deletion syndrome.

Authors:  David R Roalf; J Eric Schmitt; Simon N Vandekar; Theodore D Satterthwaite; Russell T Shinohara; Kosha Ruparel; Mark A Elliott; Karthik Prabhakaran; Donna M McDonald-McGinn; Elaine H Zackai; Ruben C Gur; Beverly S Emanuel; Raquel E Gur
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9.  Within-Individual Variability: An Index for Subtle Change in Neurocognition in Mild Cognitive Impairment.

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10.  Neurodevelopmental Genomic Strategies in the Study of the Psychosis Spectrum.

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