Literature DB >> 8207487

Motor sequence learning: a study with positron emission tomography.

I H Jenkins1, D J Brooks, P D Nixon, R S Frackowiak, R E Passingham.   

Abstract

We have used positron emission tomography to study the functional anatomy of motor sequence learning. Subjects learned sequences of keypresses by trial and error using auditory feedback. They were scanned with eyes closed under three conditions: at rest, while performing a sequence that was practiced before scanning until overlearned, and while learning new sequences at the same rate of performance. Compared with rest, both sequence tasks activated the contralateral sensorimotor cortex to the same extent. Comparing new learning with performance of the prelearned sequence, differences in activation were identified in other areas. (1) Prefrontal cortex was only activated during new sequence learning. (2) Lateral premotor cortex was significantly more activated during new learning, whereas the supplementary motor area was more activated during performance of the prelearned sequence. (3) Activation of parietal association cortex was present during both motor tasks, but was significantly greater during new learning. (4) The putamen was equally activated by both conditions. (5) The cerebellum was activated by both conditions, but the activation was more extensive and greater in degree during new learning. There was an extensive decrease in the activity of prestriate cortex, inferotemporal cortex, and the hippocampus in both active conditions, when compared with rest. These decreases were significantly greater during new learning. We draw three main conclusions. (1) The cerebellum is involved in the process by which motor tasks become automatic, whereas the putamen is equally activated by sequence learning and retrieval, and may play a similar role in both. (2) When subjects learn new sequences of motor actions, prefrontal cortex is activated. This may reflect the need to generate new responses. (3) Reduced activity of areas concerned with visual processing, particularly during new learning, suggests that selective attention may involve depressing the activity of cells in modalities that are not engaged by the task.

Mesh:

Year:  1994        PMID: 8207487      PMCID: PMC6576955     

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  209 in total

1.  Learning-related effects and functional neuroimaging.

Authors:  K M Petersson; C Elfgren; M Ingvar
Journal:  Hum Brain Mapp       Date:  1999       Impact factor: 5.038

2.  Representation of actions in rats: the role of cerebellum in learning spatial performances by observation.

Authors:  M G Leggio; M Molinari; P Neri; A Graziano; L Mandolesi; L Petrosini
Journal:  Proc Natl Acad Sci U S A       Date:  2000-02-29       Impact factor: 11.205

3.  Functional networks in motor sequence learning: abnormal topographies in Parkinson's disease.

Authors:  T Nakamura; M F Ghilardi; M Mentis; V Dhawan; M Fukuda; A Hacking; J R Moeller; C Ghez; D Eidelberg
Journal:  Hum Brain Mapp       Date:  2001-01       Impact factor: 5.038

4.  Functional anatomy of execution, mental simulation, observation, and verb generation of actions: a meta-analysis.

Authors:  J Grèzes; J Decety
Journal:  Hum Brain Mapp       Date:  2001-01       Impact factor: 5.038

5.  Obstacle avoidance during human walking: learning rate and cross-modal transfer.

Authors:  T Erni; V Dietz
Journal:  J Physiol       Date:  2001-07-01       Impact factor: 5.182

6.  Dynamic cortical and subcortical networks in learning and delayed recall of timed motor sequences.

Authors:  Virginia B Penhune; Julien Doyon
Journal:  J Neurosci       Date:  2002-02-15       Impact factor: 6.167

7.  Cluster analysis of activity-time series in motor learning.

Authors:  Daniela Balslev; Finn A Nielsen; Sally A Frutiger; John J Sidtis; Torben B Christiansen; Claus Svarer; Stephen C Strother; David A Rottenberg; Lars K Hansen; Olaf B Paulson; I Law
Journal:  Hum Brain Mapp       Date:  2002-03       Impact factor: 5.038

8.  Cerebellar projections to the prefrontal cortex of the primate.

Authors:  F A Middleton; P L Strick
Journal:  J Neurosci       Date:  2001-01-15       Impact factor: 6.167

9.  Chunking processes in the learning of event sequences: electrophysiological indicators.

Authors:  F Schlaghecken; B Stürmer; M Eimer
Journal:  Mem Cognit       Date:  2000-07

Review 10.  Neural adaptations to resistance training: implications for movement control.

Authors:  T J Carroll; S Riek; R G Carson
Journal:  Sports Med       Date:  2001       Impact factor: 11.136

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