Learning During Processing: Word Learning Doesn't Wait for Word Recognition to Finish

Abstract

Previous research on associative learning has uncovered detailed aspects of the process, including what types of things are learned, how they are learned, and where in the brain such learning occurs. However, perceptual processes, such as stimulus recognition and identification, take time to unfold. Previous studies of learning have not addressed when, during the course of these dynamic recognition processes, learned representations are formed and updated. If learned representations are formed and updated while recognition is ongoing, the result of learning may incorporate spurious, partial information. For example, during word recognition, words take time to be identified, and competing words are often active in parallel. If learning proceeds before this competition resolves, representations may be influenced by the preliminary activations present at the time of learning. In three experiments using word learning as a model domain, we provide evidence that learning reflects the ongoing dynamics of auditory and visual processing during a learning event. These results show that learning can occur before stimulus recognition processes are complete; learning does not wait for ongoing perceptual processing to complete.

Keywords: Associative learning; Lexical access; Processing dynamics; Temporal processes; Word learning.

Figure 1

Examples of visual stimuli used in the experiments (images in the experiment were in color).

Figure 2

Proportion of correct responses during interim testing trials for Experiment 1. A) Onset competitor trials. B) Offset competitor trials.

Figure 3

Raw proportion of looks to the target items in Experiment 1. A) Onset competitor trials. B) Offset competitor trials.

Figure 4

Raw proportion of looks to competitor and unrelated (UR) items in Experiment 1. Unrelated items reflect the mean of looks to the two unrelated items in the display. A) Onset-competitor trials. B) Offset-competitor trials.

Fig. 5

Competitor effects in Experiment 1. Looks to the competitor are compared to the mean of looks to the two unrelated items. A) Log odds ratio of looks for onset competitors across time. B) Log odds ratio of looks to the offset competitors divided by looks to the unrelated objects across time. C) Mean log odds ratio during analysis window (500–1500 ms) by competitor type and timing condition. Error bars are the standard error of the mean.

Figure 6

Proportion of correct responses during the interim testing trials across blocks of training. A) Onset competitor items. B) Offset competitor items.

Figure 7

Raw proportion of looks to the target object across time, comparing participants from the synchronous condition of Experiment 1 to participants in Experiment 2. A) Onset competitor trials. B) Offset competitor trials.

Figure 8

Log odds ratios of competitor effects in Experiment 2. A) Log odds ratio for onset competitor trials across time. B) Log odds ratio for offset competitor trials across time. C) Mean log odds ratio during analysis window by competitor type and timing condition. Error bars are the standard error of the mean.

Figure 9

Proportion of correct responses during the interim testing trials, comparing participants in the synchronous condition of Experiment 1 to participants in Experiment 3. A) Onset competitor trials. B) Offset competitor trials.

Figure 10

Raw proportion of looks to the target object across time, comparing participants in the synchronous condition of Experiment 1 to participants in Experiment 3. A) Onset competitor trials. B) Offset competitor trials.

Figure 11

Log odds ratios of competitor effects for Experiment 3. A) Log odds ratio for onset competitor trials across time. B) Log odd ratio for offset competitor trials across time. C) Mean log odd ratios during analysis window by competitor type and timing condition. Error bars signify the standard error of the mean.

Figure 12

Log odds ratios of competitor effects for different learner groups (LL: Low learners; HL: High learners). Error bars signify the standard error of the mean.