Literature DB >> 12928061

Similar network activated by young and old adults during the acquisition of a motor sequence.

Sander M Daselaar1, Serge A R B Rombouts, Dick J Veltman, Jeroen G W Raaijmakers, Cees Jonker.   

Abstract

In this functional MRI (fMRI) study, we investigated ageing effects on motor skill learning. We applied an adapted version of the serial reaction time (SRT) task to extensive groups of young (N=26) and elderly (N=40) subjects. Since indications have been provided for age-related shrinkage of brain regions assumed to be critical to motor skill learning, we tested the hypothesis that age effects on implicit sequence learning are larger on a neurofunctional level than on a behavioural level. The SRT task consisted of two identical scan sessions, in which subjects had to manually trail an asterisk appearing serially in one of four spatial positions by means of button-pressing. Reliable response time reductions were already found in the first session for both the young and the elderly groups, when comparing a fixed sequence condition to a random sequence, but the learning effect was greater for the young subjects. In the second session, though, both groups showed a similar degree of learning. This indicates that implicit sequence learning is still intact in elderly adults, but that the rate of learning is somewhat slower. Reliable learning-related changes in brain activity were also observed. A similar network of brain regions was recruited by both groups during the fixed compared to the random sequence, involving several regions that have been previously associated with implicit sequence learning, including bilateral parietal, and frontal regions, the supplementary motor area (SMA), cerebellum and the basal ganglia. The direct group comparison did not reveal any differences in brain activity. In addition, we did not observe any significant differences in activity when comparing the different sessions either, neither for the young nor for the elderly subjects. Hence, we did not find indications for an age-related functional reorganisation of neural networks involved in motor sequence learning. In view of earlier reports of pronounced ageing effects on the performance on declarative memory tasks, our finding of age-related sparing of processes that sustain motor skill learning, provides further support for the proposition of different memory systems relying on different brain substrates.

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Year:  2003        PMID: 12928061     DOI: 10.1016/s0197-4580(03)00030-7

Source DB:  PubMed          Journal:  Neurobiol Aging        ISSN: 0197-4580            Impact factor:   4.673


  58 in total

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Authors:  Ilana J Bennett; David J Madden; Chandan J Vaidya; James H Howard; Darlene V Howard
Journal:  Neurobiol Aging       Date:  2010-05-07       Impact factor: 4.673

2.  Implicit learning in children with spelling disability: evidence from artificial grammar learning.

Authors:  Elena Ise; Carolin J Arnoldi; Jürgen Bartling; Gerd Schulte-Körne
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4.  Age differences in implicit learning of probabilistic unstructured sequences.

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5.  Symbolic representations in motor sequence learning.

Authors:  J Bo; S J Peltier; D C Noll; R D Seidler
Journal:  Neuroimage       Date:  2010-08-18       Impact factor: 6.556

6.  The influence of normal human ageing on automatic movements.

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Journal:  J Physiol       Date:  2004-10-28       Impact factor: 5.182

Review 7.  Memory systems do not divide on consciousness: Reinterpreting memory in terms of activation and binding.

Authors:  Lynne M Reder; Heekyeong Park; Paul D Kieffaber
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8.  Age-related dedifferentiation of learning systems: an fMRI study of implicit and explicit learning.

Authors:  Nancy A Dennis; Roberto Cabeza
Journal:  Neurobiol Aging       Date:  2010-05-14       Impact factor: 4.673

Review 9.  Perturbations of neural circuitry in aging, mild cognitive impairment, and Alzheimer's disease.

Authors:  Stephanie L Leal; Michael A Yassa
Journal:  Ageing Res Rev       Date:  2013-02-04       Impact factor: 10.895

10.  Multimodal connectivity of motor learning-related dorsal premotor cortex.

Authors:  Robert M Hardwick; Elise Lesage; Claudia R Eickhoff; Mareike Clos; Peter Fox; Simon B Eickhoff
Journal:  Neuroimage       Date:  2015-08-15       Impact factor: 6.556

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