Neural Mechanisms of the Contextual Interference Effect and Parameter Similarity on Motor Learning in Older Adults: An EEG Study

Abstract

The purpose of this study was to investigate the neural mechanisms of the contextual interference effect (CIE) and parameter similarity on motor learning in older adults. Sixty older adults (mean age, 67.68 ± 3.95 years) were randomly assigned to one of six experimental groups: blocked-similar, algorithm-similar, random-similar, blocked-dissimilar, algorithm-dissimilar, and random-dissimilar. Algorithm practice was a hybrid practice schedule (a combination of blocked, serial, and random practice) that switching between practice schedules were based on error trial number, ≤33%. The sequential motor task was used to record the absolute timing for the absolute timing goals (ATGs). In similar conditions, the participants' performance was near ATGs (1,350, 1,500, 1,650 ms) and in dissimilar conditions, they performed far ATGs (1,050, 1,500, 1,950 ms) with the same spatial sequence for all groups. EEG signals were continuously collected during the acquisition phase and delayed retention. Data were analyzed in different bands (alpha and beta) and scalp locations (frontal: Fp1, Fp2, F3, F4; central: C3, C4; and parietal: P3, P4) with repeated measures on the last factor. The analyses were included motor preparation and intertrial interval (motor evaluation) periods in the first six blocks and the last six blocks, respectively. The results of behavioral data indicated that algorithm practice resulted in medium error related to classic blocked and random practice during the acquisition, however, algorithm practice outperformed the classic blocked and random practice in the delayed retention test. The results of EEG data demonstrated that algorithm practice, due to optimal activity in the frontal lobe (medium alpha and beta activation at prefrontal), resulted in increased activity of sensorimotor areas (high alpha activation at C3 and P4) in older adults. Also, EEG data showed that similar conditions could affect the intertrial interval period (medium alpha and beta activation in frontal in the last six-block), while the dissimilar conditions could affect the motor preparation period (medium alpha and beta activation in frontal in the first six-block). In conclusion, algorithm practice can enhance motor learning and optimize the efficiency of brain activity, resulting in the achievement of a desirable goal in older adults.

Keywords: EEG; contextual interference effect; motor learning; older adults; optimal error; parameter similarity.

Figure 1

Sequential timing device (A), and procedure of experiment in progress (B).

Figure 2

Procedure of one trial.

Figure 3

The paradigm of the experimental groups in the acquisition phase and delayed retention. Note that algorithm practice was a combination of blocked, serial, and random practice that forward and/or not backward switching between stages was based on error rate (number of error trial ≤33% in each block based on error range of the ATGs, ±5%).

Figure 4

Computer algorithm and how to change the stages in the algorithm practice schedule. Follow the arrows in regards to Yes/No.

Figure 5

Means and standard deviations of the total error of the groups in (A) different phases and (B) the first and last six blocks (for a direct comparison with EEG data).

Figure 6

Means and standard deviations power of the groups in (A) alpha band and (B) beta band in different scalp locations at the acquisition phase.

Figure 7

Means and standard deviations power of the groups for (A) alpha band and (B) beta band in different scalp locations in the delayed retention test.

Figure 8

Proposed Contextual Interference Model (CIM).