ArticleProceedings of the National Academy of Sciences of the United States of America2017
Lawful relation between perceptual bias and discriminability.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers.
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65 citing papers in PubMed.
- Contrast and pattern adaptation in visual cortex share a common gain control mechanism.Journal of neurophysiology · 2026Article
- Signal-to-Noise Efficiency Explains Inter-Observer Variability in Orientation Discrimination.Vision (Basel, Switzerland) · 2026Article
- Dynamics of working memory drift and information flow across the cortical hierarchy.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Contrast and pattern adaptation in visual cortex share a common gain control mechanism.bioRxiv : the preprint server for biology · 2025Article
- Visual representations in the human brain rely on a reference frame that is in between allocentric and retinocentric coordinates.bioRxiv : the preprint server for biology · 2025Article
- The size-weight illusion and beyond: A new model of perceived weight.PLoS computational biology · 2025Article
- Sequential effects in reaching reveal efficient coding in motor planning.Science advances · 2025Article
- The across-trial accumulation of cardinal illusion in orientation estimation attenuates the significance of serial dependence.Psychological research · 2025Article
- Between repulsion and attraction in serial biases: Replication of Chen and Bae (2024).Journal of vision · 2025Article
- A linear perception-action mapping accounts for response range-dependent biases in heading estimation from optic flow.PLoS computational biology · 2025Article
- The tilt illusion arises from an efficient reallocation of neural coding resources at the contextual boundary.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Article
- Perceptual learning improves discrimination but does not reduce distortions in appearance.PLoS computational biology · 2025Article
- Representational geometry explains puzzling error distributions in behavioral tasks.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Adaptation optimizes sensory encoding for future stimuli.PLoS computational biology · 2025Article
- Weight illusions explained by efficient coding based on correlated natural statistics.Communications psychology · 2024Article
- Sequential Effects in Reaching Reveal Efficient Coding in Motor Planning.bioRxiv : the preprint server for biology · 2024Article
- Sensory-memory interactions via modular structure explain errors in visual working memory.eLife · 2024Article
- A gradual transition toward categorical representations along the visual hierarchy during working memory, but not perception.bioRxiv : the preprint server for biology · 2024Article
- A Bayesian inference model can predict the effects of attention on the serial dependence in heading estimation from optic flow.Journal of vision · 2024Article
5 more citing papers are in PubMed but not listed here.
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2 authors.
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Abstract
Perception of a stimulus can be characterized by two fundamental psychophysical measures: how well the stimulus can be discriminated from similar ones (discrimination threshold) and how strongly the perceived stimulus value deviates on average from the true stimulus value (perceptual bias). We demonstrate that perceptual bias and discriminability, as functions of the stimulus value, follow a surprisingly simple mathematical relation. The relation, which is derived from a theory combining optimal encoding and decoding, is well supported by a wide range of reported psychophysical data including perceptual changes induced by contextual modulation. The large empirical support indicates that the proposed relation may represent a psychophysical law in human perception. Our results imply that the computational processes of sensory encoding and perceptual decoding are matched and optimized based on identical assumptions about the statistical structure of the sensory environment.
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