Limited Evidence for Probabilistic Cueing Effects on Grating‐Evoked Event‐Related Potentials and Orientation Decoding Performance
ABSTRACT We can rapidly learn recurring patterns that occur within our sensory environments. This knowledge allows us to form expectations about future sensory events. Several influential predictive coding models posit that, when a stimulus matches our expectations, the activity of feature‐selective...
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| Published in: | Psychophysiology Vol. 62; no. 5; pp. e70076 - n/a |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
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United States
Blackwell Publishing Ltd
01.05.2025
John Wiley and Sons Inc |
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| ISSN: | 0048-5772, 1469-8986, 1469-8986, 1540-5958 |
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| Abstract | ABSTRACT
We can rapidly learn recurring patterns that occur within our sensory environments. This knowledge allows us to form expectations about future sensory events. Several influential predictive coding models posit that, when a stimulus matches our expectations, the activity of feature‐selective neurons in the visual cortex will be suppressed relative to when that stimulus is unexpected. However, after accounting for known critical confounds, there is currently scant evidence for these hypothesized effects from studies recording electrophysiological neural activity. To provide a strong test for expectation effects on stimulus‐evoked responses in the visual cortex, we performed a probabilistic cueing experiment while recording electroencephalographic (EEG) data. Participants (n = 48) learned associations between visual cues and subsequently presented gratings. A given cue predicted the appearance of a certain grating orientation with 10%, 25%, 50%, 75%, or 90% validity. We did not observe any stimulus expectancy effects on grating‐evoked event‐related potentials. Multivariate classifiers trained to discriminate between grating orientations performed better when classifying 10% compared to 90% probability gratings. However, classification performance did not substantively differ across any other stimulus expectancy conditions. Our findings provide very limited evidence for modulations of prediction error signaling by probabilistic expectations as specified in contemporary predictive coding models.
Impact Statement
Stimulus expectations are widely assumed to modulate the responsiveness of neurons in the visual system. However, there is currently a lack of clear evidence from electrophysiological studies to support this assumption. Our study provides a strong test of expectation effects on visual evoked responses while controlling for critical confounds. We show that cued probabilistic expectations do not modulate event‐related potentials evoked by visual stimuli, contrary to hypotheses derived from predictive coding models. |
|---|---|
| AbstractList | ABSTRACT
We can rapidly learn recurring patterns that occur within our sensory environments. This knowledge allows us to form expectations about future sensory events. Several influential predictive coding models posit that, when a stimulus matches our expectations, the activity of feature‐selective neurons in the visual cortex will be suppressed relative to when that stimulus is unexpected. However, after accounting for known critical confounds, there is currently scant evidence for these hypothesized effects from studies recording electrophysiological neural activity. To provide a strong test for expectation effects on stimulus‐evoked responses in the visual cortex, we performed a probabilistic cueing experiment while recording electroencephalographic (EEG) data. Participants (n = 48) learned associations between visual cues and subsequently presented gratings. A given cue predicted the appearance of a certain grating orientation with 10%, 25%, 50%, 75%, or 90% validity. We did not observe any stimulus expectancy effects on grating‐evoked event‐related potentials. Multivariate classifiers trained to discriminate between grating orientations performed better when classifying 10% compared to 90% probability gratings. However, classification performance did not substantively differ across any other stimulus expectancy conditions. Our findings provide very limited evidence for modulations of prediction error signaling by probabilistic expectations as specified in contemporary predictive coding models.
Impact Statement
Stimulus expectations are widely assumed to modulate the responsiveness of neurons in the visual system. However, there is currently a lack of clear evidence from electrophysiological studies to support this assumption. Our study provides a strong test of expectation effects on visual evoked responses while controlling for critical confounds. We show that cued probabilistic expectations do not modulate event‐related potentials evoked by visual stimuli, contrary to hypotheses derived from predictive coding models. We can rapidly learn recurring patterns that occur within our sensory environments. This knowledge allows us to form expectations about future sensory events. Several influential predictive coding models posit that, when a stimulus matches our expectations, the activity of feature‐selective neurons in the visual cortex will be suppressed relative to when that stimulus is unexpected. However, after accounting for known critical confounds, there is currently scant evidence for these hypothesized effects from studies recording electrophysiological neural activity. To provide a strong test for expectation effects on stimulus‐evoked responses in the visual cortex, we performed a probabilistic cueing experiment while recording electroencephalographic (EEG) data. Participants (n = 48) learned associations between visual cues and subsequently presented gratings. A given cue predicted the appearance of a certain grating orientation with 10%, 25%, 50%, 75%, or 90% validity. We did not observe any stimulus expectancy effects on grating‐evoked event‐related potentials. Multivariate classifiers trained to discriminate between grating orientations performed better when classifying 10% compared to 90% probability gratings. However, classification performance did not substantively differ across any other stimulus expectancy conditions. Our findings provide very limited evidence for modulations of prediction error signaling by probabilistic expectations as specified in contemporary predictive coding models. We can rapidly learn recurring patterns that occur within our sensory environments. This knowledge allows us to form expectations about future sensory events. Several influential predictive coding models posit that, when a stimulus matches our expectations, the activity of feature‐selective neurons in the visual cortex will be suppressed relative to when that stimulus is unexpected. However, after accounting for known critical confounds, there is currently scant evidence for these hypothesized effects from studies recording electrophysiological neural activity. To provide a strong test for expectation effects on stimulus‐evoked responses in the visual cortex, we performed a probabilistic cueing experiment while recording electroencephalographic (EEG) data. Participants (n = 48) learned associations between visual cues and subsequently presented gratings. A given cue predicted the appearance of a certain grating orientation with 10%, 25%, 50%, 75%, or 90% validity. We did not observe any stimulus expectancy effects on grating‐evoked event‐related potentials. Multivariate classifiers trained to discriminate between grating orientations performed better when classifying 10% compared to 90% probability gratings. However, classification performance did not substantively differ across any other stimulus expectancy conditions. Our findings provide very limited evidence for modulations of prediction error signaling by probabilistic expectations as specified in contemporary predictive coding models. Stimulus expectations are widely assumed to modulate the responsiveness of neurons in the visual system. However, there is currently a lack of clear evidence from electrophysiological studies to support this assumption. Our study provides a strong test of expectation effects on visual evoked responses while controlling for critical confounds. We show that cued probabilistic expectations do not modulate event‐related potentials evoked by visual stimuli, contrary to hypotheses derived from predictive coding models. We can rapidly learn recurring patterns that occur within our sensory environments. This knowledge allows us to form expectations about future sensory events. Several influential predictive coding models posit that, when a stimulus matches our expectations, the activity of feature-selective neurons in the visual cortex will be suppressed relative to when that stimulus is unexpected. However, after accounting for known critical confounds, there is currently scant evidence for these hypothesized effects from studies recording electrophysiological neural activity. To provide a strong test for expectation effects on stimulus-evoked responses in the visual cortex, we performed a probabilistic cueing experiment while recording electroencephalographic (EEG) data. Participants (n = 48) learned associations between visual cues and subsequently presented gratings. A given cue predicted the appearance of a certain grating orientation with 10%, 25%, 50%, 75%, or 90% validity. We did not observe any stimulus expectancy effects on grating-evoked event-related potentials. Multivariate classifiers trained to discriminate between grating orientations performed better when classifying 10% compared to 90% probability gratings. However, classification performance did not substantively differ across any other stimulus expectancy conditions. Our findings provide very limited evidence for modulations of prediction error signaling by probabilistic expectations as specified in contemporary predictive coding models.We can rapidly learn recurring patterns that occur within our sensory environments. This knowledge allows us to form expectations about future sensory events. Several influential predictive coding models posit that, when a stimulus matches our expectations, the activity of feature-selective neurons in the visual cortex will be suppressed relative to when that stimulus is unexpected. However, after accounting for known critical confounds, there is currently scant evidence for these hypothesized effects from studies recording electrophysiological neural activity. To provide a strong test for expectation effects on stimulus-evoked responses in the visual cortex, we performed a probabilistic cueing experiment while recording electroencephalographic (EEG) data. Participants (n = 48) learned associations between visual cues and subsequently presented gratings. A given cue predicted the appearance of a certain grating orientation with 10%, 25%, 50%, 75%, or 90% validity. We did not observe any stimulus expectancy effects on grating-evoked event-related potentials. Multivariate classifiers trained to discriminate between grating orientations performed better when classifying 10% compared to 90% probability gratings. However, classification performance did not substantively differ across any other stimulus expectancy conditions. Our findings provide very limited evidence for modulations of prediction error signaling by probabilistic expectations as specified in contemporary predictive coding models. We can rapidly learn recurring patterns that occur within our sensory environments. This knowledge allows us to form expectations about future sensory events. Several influential predictive coding models posit that, when a stimulus matches our expectations, the activity of feature‐selective neurons in the visual cortex will be suppressed relative to when that stimulus is unexpected. However, after accounting for known critical confounds, there is currently scant evidence for these hypothesized effects from studies recording electrophysiological neural activity. To provide a strong test for expectation effects on stimulus‐evoked responses in the visual cortex, we performed a probabilistic cueing experiment while recording electroencephalographic (EEG) data. Participants ( n = 48) learned associations between visual cues and subsequently presented gratings. A given cue predicted the appearance of a certain grating orientation with 10%, 25%, 50%, 75%, or 90% validity. We did not observe any stimulus expectancy effects on grating‐evoked event‐related potentials. Multivariate classifiers trained to discriminate between grating orientations performed better when classifying 10% compared to 90% probability gratings. However, classification performance did not substantively differ across any other stimulus expectancy conditions. Our findings provide very limited evidence for modulations of prediction error signaling by probabilistic expectations as specified in contemporary predictive coding models. Stimulus expectations are widely assumed to modulate the responsiveness of neurons in the visual system. However, there is currently a lack of clear evidence from electrophysiological studies to support this assumption. Our study provides a strong test of expectation effects on visual evoked responses while controlling for critical confounds. We show that cued probabilistic expectations do not modulate event‐related potentials evoked by visual stimuli, contrary to hypotheses derived from predictive coding models. |
| Author | Kashyap, Máire Ouden, Carla Feuerriegel, Daniel Kikkawa, Morgan |
| AuthorAffiliation | 1 Melbourne School of Psychological Sciences The University of Melbourne Melbourne Victoria Australia |
| AuthorAffiliation_xml | – name: 1 Melbourne School of Psychological Sciences The University of Melbourne Melbourne Victoria Australia |
| Author_xml | – sequence: 1 givenname: Carla surname: Ouden fullname: Ouden, Carla organization: The University of Melbourne – sequence: 2 givenname: Máire surname: Kashyap fullname: Kashyap, Máire organization: The University of Melbourne – sequence: 3 givenname: Morgan surname: Kikkawa fullname: Kikkawa, Morgan organization: The University of Melbourne – sequence: 4 givenname: Daniel orcidid: 0000-0002-0357-1920 surname: Feuerriegel fullname: Feuerriegel, Daniel email: daniel.feuerriegel@unimelb.edu.au organization: The University of Melbourne |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/40391524$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_1162_IMAG_a_152 |
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| Copyright | 2025 The Author(s). published by Wiley Periodicals LLC on behalf of Society for Psychophysiological Research. 2025 The Author(s). Psychophysiology published by Wiley Periodicals LLC on behalf of Society for Psychophysiological Research. 2025. This work is published under Creative Commons Attribution License~https://creativecommons.org/licenses/by/3.0/ (the "License"). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
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| Publisher | Blackwell Publishing Ltd John Wiley and Sons Inc |
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We can rapidly learn recurring patterns that occur within our sensory environments. This knowledge allows us to form expectations about future sensory... We can rapidly learn recurring patterns that occur within our sensory environments. This knowledge allows us to form expectations about future sensory events.... |
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| SubjectTerms | Adult Anticipation, Psychological - physiology Cues EEG Electroencephalography Electrophysiological recording ERP Evoked Potentials - physiology Evoked Potentials, Visual - physiology Expectancy expectation Female Humans Male MVPA Orientation behavior Original Pattern Recognition, Visual - physiology Psychomotor Performance - physiology Somatosensory cortex surprise Visual cortex Visual Cortex - physiology Visual stimuli Young Adult |
| Title | Limited Evidence for Probabilistic Cueing Effects on Grating‐Evoked Event‐Related Potentials and Orientation Decoding Performance |
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