Dynamics of neuronal activity during mental training
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1
CNRS and Université de la Méditerranée, INCM, UMR 619, France
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2
Université Mohamed V, LIMIARF, Morocco
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3
Institut des Sciences Cognitives, Laboratoire Langage, Cerveau et Cognition, France
Although there is converging experimental and clinical evidence suggesting that mental training with motor imagery can improve motor performance, it is unclear to what extent humans can learn movements through mental training despite the lack of sensory feedback from the body and the environment. In a recent study, we showed that mental rehearsal combined with physical practice leads to similar (or even better) performance than physical practice alone (Allami et al., 2008). Here, we investigate the changes in brain activity underlying improvement of performance during mental rehearsal. The scalp electroencephalogram (EEG) was recorded from two groups of subjects. In the first group (GEx) subjects physically performed a grasping task for 240 trials. In the second group (GIm), the subjects mentally rehearsed the same task for 180 trials (75% of 240) and then executed it physically for 60 trials (25%). Amplitudes and latencies of event-related potentials (ERPs) were compared across the two groups and across learning. Interestingly, learning in both groups was accompanied by similar cerebral changes over the sensorimotor region of the brain (fronto-central electrodes), that lead to comparable patterns of EEG activity at the end of learning. To analyse the dynamics of changes during learning, we further processed the EEG signals on a trial-by-trial basis using a 5th order linear predictive model. Under the assumption that EEG signal is a non stationary stochastic process, which means that its statistical properties (means, correlation) may change in time, the model considered is time dependant. For this reason, the model feature (coefficients) extraction was performed adaptively in such a way to enable the detection of any changes in the statistics that may occur in the signal while maintaining high speed of convergence. These changes, reflected as abrupt jumps in the curve representing the model coefficients’ behaviour versus time followed, could be related to neuronal behaviour change. On the basis of this technique, for each trial, we estimated the time of occurrence of the first significant jump (TJ). Preliminary results showed that, in both the GEx group and the GIm group, the TJ parameter maintains in average a value of 385 msec during the training phase, diminishes rapidly during the 10 following trials before converging towards a value of 185 msec during the physical practice. Examination of the TJ curves obtained for these two groups revealed that they differ both in terms of leaning phase duration (much longer in GIm), and as TJ decreases, the slope is higher in the GIm group (twice the slope in GEx). This suggests that mental learning is slow, but increases the learning speed through physical experience.
Acknowledgment: This work was supported by the GDRI Neuro
References
1. Allami N, Paulignan Y, Brovelli A and Boussaoud D (2008). Visuo-motor learning with combination of different rates of motor imagery and physical practice. EXPERIMENTAL BRAIN RESEARCH, 184:105-113.
Conference:
2nd NEUROMED Workshop, Fez, Morocco, 10 Jun - 12 Jun, 2010.
Presentation Type:
Oral Presentation
Topic:
Oral Session 4: Technological developments for neurosciences
Citation:
Allami
N,
Regragui
F,
Hamzaoui
E,
Brovelli
A,
Paulignan
Y and
Boussaoud
D
(2010). Dynamics of neuronal activity during mental training.
Front. Neurosci.
Conference Abstract:
2nd NEUROMED Workshop.
doi: 10.3389/conf.fnins.2010.12.00037
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Received:
04 Jun 2010;
Published Online:
04 Jun 2010.
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Correspondence:
Fakhita Regragui, Université Mohamed V, LIMIARF, Rabat Agdal, Morocco, fakhitaregragui@yahoo.fr