Dimensional training attenuates overshadowing
Description
Prior experience with elemental or configural discriminations shapes how agents learn subsequent information: prior training that encourages elemental processing promotes competition between events, while prior configural training tends to attenuate competition. We sought to assess whether configural and elemental pretraining modulated subsequent overshadowing when using two separable dimensions (i.e., colors and symbols) in a predictive learning task. Furthermore, we used post-test questionnaires asking whether participants used either only one or both dimensions during training, and assessed if this modulated the magnitude of overshadowing. Across three experiments, prior experience with a configural discrimination (i.e., biconditional discrimination) did not modulate the magnitude of overshadowing compared to control groups. However, attended dimensions were less prone to overshadowing (Experiments 1 and 2), and Experiment 3 revealed that prior elemental training making one dimension relevant attenuated subsequent overshadowing of that dimension. Hence, preferred or trained dimensions are less prone to be overshadowed. Results are discussed in light of attentional and configural theories of associative learning.
External URI
Subjects
- Paired-association learning
- Learning
- Training
- overshadowing, pretraining, elemental, configural, intradimensional
- Biological Sciences::Psychology::Cognitive & affective psychology::Psychology of memory & learning
- B Philosophy. Psychology. Religion::BF Psychology
Divisions
- University of Nottingham, UK Campus::Faculty of Science::School of Psychology
Deposit date
2022-11-25Data type
Behavioural results of predictive learning experiments. During training, participants need to predict whether an outcome will occur on the basis of signals by answering yes or no. During test, participants give a predictive rating for each signal, indication (from 0 to 100) whether the outcome will occur in the presence of the signal.Contributors
- Alcalá, José A
- Prados, Jose
Funders
- Economic & Social Research Council
Grant number
- ES/R011494/2
Data collection method
Online data collection. Participants were recruited through Prolific.Resource languages
- en