The influence of learning history on anterograde interference

Classically interpreted as a competition between opposite memories (A vs B), anterograde interference (AI) also emerges in the absence of competing memories (A vs A), suggesting that mechanisms other than those involved in memory competition contribute to AI. To investigate this, we tested the hypothesis that extending motor practice would enhance a first memory, but come at the cost of reduced learning capabilities when subsequently exposed to a second learning session of the same task. Based on converging biological evidence, AI was expected to depend upon the degree of extended practice of the initial exposure. During a first Session, four conditions were carried out where participants (n = 24) adapted to a gradually introduced −20° visual deviation while the extent of the initial exposure was manipulated by varying the duration or type of the performance asymptote. Specifically, the performance asymptote at −20° was either Short (40 trials), Moderate (160 trials), Long (320 trials), or absent due to continuously changing perturbations around the mean of −20° (Jagged; 160 trials). After a 2-min interval, participants re-adapted to the same (-20°) visual deviation, which was meant to probe the effect of extended practice in the first Session on the learning capabilities of a second identical memory (A vs A). The results first confirmed that the duration of exposure in the first Session enhanced immediate aftereffects in the Moderate, Long, and Jagged conditions as compared to the Short condition, suggesting that extended practice enhanced retention of the first memory. When comparing the second Session to the first one, results revealed a different pattern of re-adaptation depending on the duration of initial exposure: in the Short condition, there was evidence for facilitated re-adaptation and similar aftereffects. However, in the Moderate, Long and Jagged conditions, re-adaptation was similar and aftereffects were impaired, suggestive of AI. This suggests that extended practice initially enhances memory formation, but comes at the cost of reduced subsequent learning capabilities. One possibility is that AI occurs because extended practice induces the emergence of network-specific homeostatic constraints, which limit subsequent neuroplastic and learning capabilities in the same neural network.