Abstract
Categorical judgments can systematically bias the perceptual interpretation of stimulus features. However, it remained unclear whether categorical judgments directly modify working memory representations or, alternatively, generate these biases via an inference process down-stream from working memory. To address this question we ran two novel psychophysical experiments in which human subjects had to reverse their categorical judgments about a stimulus feature, if incorrect, before providing an estimate of the feature. If categorical judgments indeed directly altered sensory representations in working memory, subjects’ estimates should reflect some aspects of their initial (incorrect) categorical judgment in those trials. We found no traces of the initial categorical judgment. Rather, subjects seemed to be able to flexibly switch their categorical judgment if needed and use the correct corresponding categorical prior to properly perform feature inference. A cross-validated model comparison also revealed that feedback may lead to selective memory recall such that only memory samples that are consistent with the categorical judgment are accepted for the inference process. Our results suggest that categorical judgments do not modify sensory information in working memory but rather act as top-down expectations in the subsequent sensory recall and inference process.
Highlights
Human visual perception is biased by the statistical regularities in the sensory input
Using a detailed computational model comparison, we show that these biases do not reflect distortions in the memory representation of the evidence but rather result from a biased interpretation of the evidence during memory recall
Our results are important as they suggest that consistency biases are malleable, even reversible, which has implications for our understanding of economic and cognitive decision-making processes and even society at large
Summary
Human visual perception is biased by the statistical regularities in the sensory input. A general theory proposes that these bias patterns emerge because inference is intrinsically a top-down process where low-level feature estimates are conditioned on the observer’s preceding, (explicit or implicit) high-level categorical judgment [10, 16, 20,21,22]. Embodying this theory, a “self-consistent” Bayesian observer model [21] has performed remarkably well in quantitatively capturing the rich and diverse perceptual behavior of individual human subjects in these tasks [10]. The model assumes that a categorical judgment acts as a subjective prior that conditions the inference process of the stimulus feature
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