Learning mechanisms in cue reweighting

Harmon, Z., Idemaru, K., & Kapatsinski, V. (2019). Learning mechanisms in cue reweighting. Cognition, 189, 76-88. doi:10.1016/j.cognition.2019.03.011.
Feedback has been shown to be effective in shifting attention across perceptual cues to a phonological contrast in speech perception (Francis, Baldwin & Nusbaum, 2000). However, the learning mechanisms behind this process remain obscure. We compare the predictions of supervised error-driven learning (Rescorla & Wagner, 1972) and reinforcement learning (Sutton & Barto, 1998) using computational simulations. Supervised learning predicts downweighting of an informative cue when the learner receives evidence that it is no longer informative. In contrast, reinforcement learning suggests that a reduction in cue weight requires positive evidence for the informativeness of an alternative cue. Experimental evidence supports the latter prediction, implicating reinforcement learning as the mechanism behind the effect of feedback on cue weighting in speech perception. Native English listeners were exposed to either bimodal or unimodal VOT distributions spanning the unaspirated/aspirated boundary (bear/pear). VOT is the primary cue to initial stop voicing in English. However, lexical feedback in training indicated that VOT was no longer predictive of voicing. Reduction in the weight of VOT was observed only when participants could use an alternative cue, F0, to predict voicing. Frequency distributions had no effect on learning. Overall, the results suggest that attention shifting in learning the phonetic cues to phonological categories is accomplished using simple reinforcement learning principles that also guide the choice of actions in other domains.
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