scholarly journals Age-related Differences in Processing Speed in Preschool Children

2015 ◽  
Vol 9 (1) ◽  
pp. 23-31 ◽  
Author(s):  
Sergey Kiselev
2016 ◽  
Vol 6 (1-2) ◽  
pp. 119-146 ◽  
Author(s):  
Henrike K. Blumenfeld ◽  
Scott R. Schroeder ◽  
Susan C. Bobb ◽  
Max R. Freeman ◽  
Viorica Marian

Abstract Recent research suggests that bilingual experience reconfigures linguistic and nonlinguistic cognitive processes. We examined the relationship between linguistic competition resolution and nonlinguistic cognitive control in younger and older adults who were either bilingual or monolingual. Participants heard words in English and identified the referent among four pictures while eye-movements were recorded. Target pictures (e.g., cab) appeared with a phonological competitor picture (e.g., cat) and two filler pictures. After each eye-tracking trial, priming probes assessed residual activation and inhibition of target and competitor words. When accounting for processing speed, results revealed that age-related changes in activation and inhibition are smaller in bilinguals than in monolinguals. Moreover, younger and older bilinguals, but not monolinguals, recruited similar inhibition mechanisms during word identification and during a nonlinguistic Stroop task. Results suggest that, during lexical access, bilinguals show more consistent competition resolution and recruitment of cognitive control across the lifespan than monolinguals.


1998 ◽  
Vol 69 (5) ◽  
pp. 393-400 ◽  
Author(s):  
Yasuyuki Gondo ◽  
Osamu Ishihara ◽  
Katsuharu Nakazato ◽  
Yoshiko Shimonaka ◽  
Leonard W. Poon

2019 ◽  
Vol 8 (1) ◽  
pp. 1 ◽  
Author(s):  
Anna-Lena Schubert ◽  
Dirk Hagemann ◽  
Christoph Löffler ◽  
Gidon T. Frischkorn

Several studies have demonstrated that individual differences in processing speed fully mediate the association between age and intelligence, whereas the association between processing speed and intelligence cannot be explained by age differences. Because measures of processing speed reflect a plethora of cognitive and motivational processes, it cannot be determined which specific processes give rise to this mediation effect. This makes it hard to decide whether these processes should be conceived of as a cause or an indicator of cognitive aging. In the present study, we addressed this question by using a neurocognitive psychometrics approach to decompose the association between age differences and fluid intelligence. Reanalyzing data from two previously published datasets containing 223 participants between 18 and 61 years, we investigated whether individual differences in diffusion model parameters and in ERP latencies associated with higher-order attentional processing explained the association between age differences and fluid intelligence. We demonstrate that individual differences in the speed of non-decisional processes such as encoding, response preparation, and response execution, and individual differences in latencies of ERP components associated with higher-order cognitive processes explained the negative association between age differences and fluid intelligence. Because both parameters jointly accounted for the association between age differences and fluid intelligence, age-related differences in both parameters may reflect age-related differences in anterior brain regions associated with response planning that are prone to be affected by age-related changes. Conversely, age differences did not account for the association between processing speed and fluid intelligence. Our results suggest that the relationship between age differences and fluid intelligence is multifactorially determined.


2019 ◽  
Vol 17 (3) ◽  
pp. 415-431
Author(s):  
Yu-Jung Tsai ◽  
Chung-Ju Huang ◽  
Chiao-Ling Hung ◽  
Shih-Chun Kao ◽  
Chi-Fang Lin ◽  
...  

2004 ◽  
Vol 10 (4) ◽  
pp. 489-503 ◽  
Author(s):  
NAOMI CHAYTOR ◽  
MAUREEN SCHMITTER-EDGECOMBE

Age-related declines in working memory performance have been associated with deficits in inhibition, strategy use, processing speed, and monitoring. In the current study, cross-sectional and longitudinal methodologies were used to investigate the relative contribution of these components to age-related changes in working memory. In Experiment 1, a sample of 140 younger and 140 older adults completed an abstract design version of the Self-Ordered Pointing Task modeled after Shimamura and Jurica (1994). Experiment 1 revealed that only processing speed and monitoring explained age differences in SOPT performance. Participants in Experiment 2 were 53 older adults who returned 4 years after the initial testing and 53 young adults. A task that assessed the ability to generate and monitor an internal series of responses as compared to an externally imposed series of responses was also administered. Experiment 2 replicated the key findings from Experiment 1 and provided some further evidence for age-related internal monitoring difficulties. Furthermore, the exploratory longitudinal analysis revealed that older age and lower intellectual abilities tended to be associated with poorer performance on the SOPT at Time 2. (JINS, 2004, 10, 489–503.)


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