» Articles » PMID: 31314804

Is There More Room to Improve? The Lifespan Trajectory of Procedural Learning and Its Relationship to the Between- and Within-group Differences in Average Response Times

Overview
Journal PLoS One
Date 2019 Jul 18
PMID 31314804
Citations 22
Authors
Affiliations
Soon will be listed here.
Abstract

Characterizing the developmental trajectories of cognitive functions such as learning, memory and decision making across the lifespan faces fundamental challenges. Cognitive functions typically encompass several processes that can be differentially affected by age. Methodological issues also arise when comparisons are made across age groups that differ in basic performance measures, such as in average response times (RTs). Here we focus on procedural learning-a fundamental cognitive function that underlies the acquisition of cognitive, social, and motor skills-and demonstrate how disentangling subprocesses of learning and controlling for differences in average RTs can reveal different developmental trajectories across the human lifespan. Two hundred-seventy participants aged between 7 and 85 years performed a probabilistic sequence learning task that enabled us to separately measure two processes of procedural learning, namely general skill learning and statistical learning. Using raw RT measures, in between-group comparisons, we found a U-shaped trajectory with children and older adults exhibiting greater general skill learning compared to adolescents and younger adults. However, when we controlled for differences in average RTs (either by using ratio scores or focusing on a subsample of participants with similar average speed), only children (but not older adults) demonstrated superior general skill learning consistently across analyses. Testing the relationship between average RTs and general skill learning within age groups shed light on further age-related differences, suggesting that general skill learning measures are more affected by average speed in some age groups. Consistent with previous studies of learning probabilistic regularities, statistical learning showed a gradual decline across the lifespan, and learning performance seemed to be independent of average speed, regardless of the age group. Overall, our results suggest that children are superior learners in various aspects of procedural learning, including both general skill and statistical learning. Our study also highlights the importance to test, and control for, the effect of average speed on other RT measures of cognitive functions, which can fundamentally affect the interpretation of group differences in developmental, aging and clinical psychology and neuroscience studies.

Citing Articles

Enhancing retrieval capacity of the predictive brain through dorsolateral prefrontal cortex intervention.

Szucs-Bencze L, Vekony T, Pesthy O, Kocsis K, Kincses Z, Szabo N Cereb Cortex. 2025; 35(2).

PMID: 39907213 PMC: 11795508. DOI: 10.1093/cercor/bhaf005.


Children exhibit a developmental advantage in the offline processing of a learned motor sequence.

Van Roy A, Albouy G, Burns R, King B Commun Psychol. 2024; 2(1):30.

PMID: 39242845 PMC: 11332225. DOI: 10.1038/s44271-024-00082-9.


Psychological capacity profiles of different age groups and gender in a national representative sample.

Muschalla B Psych J. 2024; 14(1):142-152.

PMID: 39188054 PMC: 11787875. DOI: 10.1002/pchj.795.


Prefrontal theta-gamma transcranial alternating current stimulation improves non-declarative visuomotor learning in older adults.

Diedrich L, Kolhoff H, Chakalov I, Vekony T, Nemeth D, Antal A Sci Rep. 2024; 14(1):4955.

PMID: 38418511 PMC: 10901881. DOI: 10.1038/s41598-024-55125-2.


Reliability of the serial reaction time task: If at first you don't succeed, try, try, try again.

Oliveira C, Hayiou-Thomas M, Henderson L Q J Exp Psychol (Hove). 2024; 77(11):2256-2282.

PMID: 38311604 PMC: 11529135. DOI: 10.1177/17470218241232347.


References
1.
Perani D, Farsad M, Ballarini T, Lubian F, Malpetti M, Fracchetti A . The impact of bilingualism on brain reserve and metabolic connectivity in Alzheimer's dementia. Proc Natl Acad Sci U S A. 2017; 114(7):1690-1695. PMC: 5320960. DOI: 10.1073/pnas.1610909114. View

2.
HOWARD Jr J, Howard D . Age differences in implicit learning of higher order dependencies in serial patterns. Psychol Aging. 1998; 12(4):634-56. DOI: 10.1037//0882-7974.12.4.634. View

3.
Janacsek K, Nemeth D . Predicting the future: from implicit learning to consolidation. Int J Psychophysiol. 2011; 83(2):213-21. DOI: 10.1016/j.ijpsycho.2011.11.012. View

4.
Bhakuni R, Mutha P . Learning of bimanual motor sequences in normal aging. Front Aging Neurosci. 2015; 7:76. PMC: 4424879. DOI: 10.3389/fnagi.2015.00076. View

5.
Nemeth D, Janacsek K, Csifcsak G, Szvoboda G, Howard Jr J, Howard D . Interference between sentence processing and probabilistic implicit sequence learning. PLoS One. 2011; 6(3):e17577. PMC: 3050904. DOI: 10.1371/journal.pone.0017577. View