Noninvasive cortical stimulation enhances motor skill acquisition over multiple days through an effect on consolidation

Abstract

Motor skills can take weeks to months to acquire and can diminish over time in the absence of continued practice. Thus, strategies that enhance skill acquisition or retention are of great scientific and practical interest. Here we investigated the effect of noninvasive cortical stimulation on the extended time course of learning a novel and challenging motor skill task. A skill measure was chosen to reflect shifts in the task's speed-accuracy tradeoff function (SAF), which prevented us from falsely interpreting variations in position along an unchanged SAF as a change in skill. Subjects practiced over 5 consecutive days while receiving transcranial direct current stimulation (tDCS) over the primary motor cortex (M1). Using the skill measure, we assessed the impact of anodal (relative to sham) tDCS on both within-day (online) and between-day (offline) effects and on the rate of forgetting during a 3-month follow-up (long-term retention). There was greater total (online plus offline) skill acquisition with anodal tDCS compared to sham, which was mediated through a selective enhancement of offline effects. Anodal tDCS did not change the rate of forgetting relative to sham across the 3-month follow-up period, and consequently the skill measure remained greater with anodal tDCS at 3 months. This prolonged enhancement may hold promise for the rehabilitation of brain injury. Furthermore, these findings support the existence of a consolidation mechanism, susceptible to anodal tDCS, which contributes to offline effects but not to online effects or long-term retention.

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.

Sequential visual isometric pinch task. To control an on-screen cursor movement, subjects pinched a force transducer with thumb and index finger. The aim was to navigate the cursor quickly and accurately between a HOME position and 5 gates by alternating the pinch force exerted onto the transducer (see SI Methods for details). The practiced sequence was Home-1-Home-2-Home-3-Home-4-Home-5. Movement time (from movement onset to stopping at gate 5) and error rate (proportion of trials with at least 1 under- or overshooting movement) were used to determine a skill measure.

Fig. 2.

(A) Target region for cortical stimulation. Left M1 was determined by TMS targeting the optimal scalp position to elicit motor evoked potentials (MEPs) (inset) of the right first dorsal interosseus muscle. Neuronavigation revealed the precentral gyrus as the cortical target for tDCS. The anode/cathode was placed according to this landmark and the second electrode was placed on the right supraorbital area. (B) Study design. Subjects participated in 5 training and 5 follow-up sessions. During training of the SVIPT, 20 min of sham or anodal tDCS was applied to M1 in a double blind fashion. In the follow-ups, subjects performed 40 trials. Fam, familiarization with the experimental setting.

Fig. 3.

Speed–accuracy tradeoff function. Speed–accuracy tradeoff function data (black diamonds, pretraining initial data set; black triangles, posttraining initial data set; unfilled squares, posttraining validation data set) and the corresponding nonlinear least squares fits of Eq. 1 (SI Methods) (gray lines, initial data set fits; black line, validation data set fit). Data were obtained from 12 naïve subjects for the initial data set and 6 subjects per posttraining data set. The SAF is derived from the movement time (abscissa) and the error rate per block (ordinate).

Fig. 4.

The learning curve for the sham (white diamonds) and anodal (gray squares) tDCS groups for the 30 training blocks over 5 days. Each block depicts the group mean of the averaged number of trials (40 in blocks 1 and 6; 30 in blocks 2–5). The dotted lines represent breaks between consecutive days. Both groups started with comparable skills at the beginning of day 1, but by day 5 the anodal tDCS group had acquired more skills than the sham tDCS group.

Fig. 5.

Online and offline effects. Online (within-day) and offline (between-day) effects and total learning (online + offline) in the sham tDCS (white bars) and anodal tDCS (gray bars) groups are shown. Note that the significantly greater total learning in the anodal tDCS group (last gray bar) was predominantly driven by significantly greater offline effects compared to sham tDCS, in the absence of differences in online effects. Data show mean (bars) ± SEM. *, P < 0.05; **, P < 0.01.

Fig. 6.

Retention of skill. Skill at D5 and at follow-up sessions on D8, D15 ± 1, D29 ± 2, D57 ± 2, and D85 ± 2 is shown. Skill in the anodal tDCS group (gray squares) remained superior to the sham tDCS group (white diamonds) at all times, including D85. Small inset: retention, the time-weighed slope measure, calculated within single subjects over the follow-up period, did not differ between the sham (white bar) and anodal (gray bar) tDCS groups. Data show mean ± SEM. *, P < 0.01.