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tDCS-induced alterations in GABA concentration within primary motor cortex predict motor learning and motor memory: a 7 T magnetic resonance spectroscopy study.

Kim S, Stephenson MC, Morris PG, Jackson SR - Neuroimage (2014)

Bottom Line: Note that adaptation to a robot-induced force field has long been considered to be a form of model-based learning that is closely associated with the computation and 'supervised' learning of internal 'forward' models within the cerebellum.This effect was specific to GABA, localised to the left motor cortex, and was polarity specific insofar as it was not observed following either cathodal or sham stimulation.Importantly, we show that the magnitude of tDCS-induced alterations in GABA concentration within motor cortex predicts individual differences in both motor learning and motor memory on the robotic force adaptation and de-adaptation task.

View Article: PubMed Central - PubMed

Affiliation: Brain and Body Centre, School of Psychology, University of Nottingham, UK.

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a. A graphical representation of the display used within the force adaptation task (left) and an illustration of the measurement of the perpendicular error from a straight line. b. Example trajectory of the first bin and the last bin (bin size = 8 trials, blue: force trials; red: catch trials). Note that, whereas force trials decrease in error with practice, errors during catch trials increase. c. Binned results of the force adaptation task of the adaptation phase (top: force trials; bottom: catch trials) and the de-adaptation phase for each group (solid line: force field; dashed line:  field). Groups 1, 2, and 3 each subsequently went on to receive anodal, cathodal, or sham tDCS in the following MRS session.
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f0010: a. A graphical representation of the display used within the force adaptation task (left) and an illustration of the measurement of the perpendicular error from a straight line. b. Example trajectory of the first bin and the last bin (bin size = 8 trials, blue: force trials; red: catch trials). Note that, whereas force trials decrease in error with practice, errors during catch trials increase. c. Binned results of the force adaptation task of the adaptation phase (top: force trials; bottom: catch trials) and the de-adaptation phase for each group (solid line: force field; dashed line: field). Groups 1, 2, and 3 each subsequently went on to receive anodal, cathodal, or sham tDCS in the following MRS session.

Mentions: Participants were seated throughout and held the handle of the vBot during the task. Each trial started with an auditory warning that was followed immediately by the presentation of a target stimulus that could appear at one of eight radially arrayed positions (i.e. 45°, 90°, … 360°), each 12 cm from the central starting position (see Fig. 2a). The location of the target was pseudo-randomised such that, within each set of eight consecutive trials, each target location was presented only once. Participants were instructed to perform the task using rapid aiming movements towards the target. In particular, they were required to execute their movements so as to pass through the target position rather than stop at the target. Hand movement trajectories were recorded for a period of 3 s from the onset of each trial, after which the robot automatically returned the handle back to the central starting position. The perpendicular movement error was measured at 10 points that were equally distant (i.e., 10%, 20%, 30%, etc.) from the starting point to the target (see Fig. 2b). Negative error values indicate that the error was made in the direction opposite to the external force created by the robot. Each new trial commenced one second after the handle had returned to the starting position. If the peak velocity of the movement was greater than 80 cm/s or slower than 50 cm/s, a warning message of “too fast” or “too slow” was shown on the screen at the end of each trial.


tDCS-induced alterations in GABA concentration within primary motor cortex predict motor learning and motor memory: a 7 T magnetic resonance spectroscopy study.

Kim S, Stephenson MC, Morris PG, Jackson SR - Neuroimage (2014)

a. A graphical representation of the display used within the force adaptation task (left) and an illustration of the measurement of the perpendicular error from a straight line. b. Example trajectory of the first bin and the last bin (bin size = 8 trials, blue: force trials; red: catch trials). Note that, whereas force trials decrease in error with practice, errors during catch trials increase. c. Binned results of the force adaptation task of the adaptation phase (top: force trials; bottom: catch trials) and the de-adaptation phase for each group (solid line: force field; dashed line:  field). Groups 1, 2, and 3 each subsequently went on to receive anodal, cathodal, or sham tDCS in the following MRS session.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4121086&req=5

f0010: a. A graphical representation of the display used within the force adaptation task (left) and an illustration of the measurement of the perpendicular error from a straight line. b. Example trajectory of the first bin and the last bin (bin size = 8 trials, blue: force trials; red: catch trials). Note that, whereas force trials decrease in error with practice, errors during catch trials increase. c. Binned results of the force adaptation task of the adaptation phase (top: force trials; bottom: catch trials) and the de-adaptation phase for each group (solid line: force field; dashed line: field). Groups 1, 2, and 3 each subsequently went on to receive anodal, cathodal, or sham tDCS in the following MRS session.
Mentions: Participants were seated throughout and held the handle of the vBot during the task. Each trial started with an auditory warning that was followed immediately by the presentation of a target stimulus that could appear at one of eight radially arrayed positions (i.e. 45°, 90°, … 360°), each 12 cm from the central starting position (see Fig. 2a). The location of the target was pseudo-randomised such that, within each set of eight consecutive trials, each target location was presented only once. Participants were instructed to perform the task using rapid aiming movements towards the target. In particular, they were required to execute their movements so as to pass through the target position rather than stop at the target. Hand movement trajectories were recorded for a period of 3 s from the onset of each trial, after which the robot automatically returned the handle back to the central starting position. The perpendicular movement error was measured at 10 points that were equally distant (i.e., 10%, 20%, 30%, etc.) from the starting point to the target (see Fig. 2b). Negative error values indicate that the error was made in the direction opposite to the external force created by the robot. Each new trial commenced one second after the handle had returned to the starting position. If the peak velocity of the movement was greater than 80 cm/s or slower than 50 cm/s, a warning message of “too fast” or “too slow” was shown on the screen at the end of each trial.

Bottom Line: Note that adaptation to a robot-induced force field has long been considered to be a form of model-based learning that is closely associated with the computation and 'supervised' learning of internal 'forward' models within the cerebellum.This effect was specific to GABA, localised to the left motor cortex, and was polarity specific insofar as it was not observed following either cathodal or sham stimulation.Importantly, we show that the magnitude of tDCS-induced alterations in GABA concentration within motor cortex predicts individual differences in both motor learning and motor memory on the robotic force adaptation and de-adaptation task.

View Article: PubMed Central - PubMed

Affiliation: Brain and Body Centre, School of Psychology, University of Nottingham, UK.

Show MeSH
Related in: MedlinePlus