Prior probability and feature predictability interactively bias perceptual decisions
Anticipating a forthcoming sensory experience facilitates perception for expected stimuli but also hinders perception for less likely alternatives. Recent neuroimaging studies suggest that expectation biases arise from feature-level predictions that enhance early sensory representations and facilita...
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| Vydáno v: | Neuropsychologia Ročník 61; s. 210 - 221 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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Kidlington
Elsevier Ltd
01.08.2014
Elsevier |
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| ISSN: | 0028-3932, 1873-3514, 1873-3514 |
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| Abstract | Anticipating a forthcoming sensory experience facilitates perception for expected stimuli but also hinders perception for less likely alternatives. Recent neuroimaging studies suggest that expectation biases arise from feature-level predictions that enhance early sensory representations and facilitate evidence accumulation for contextually probable stimuli while suppressing alternatives. Reasonably then, the extent to which prior knowledge biases subsequent sensory processing should depend on the precision of expectations at the feature level as well as the degree to which expected features match those of an observed stimulus. In the present study we investigated how these two sources of uncertainty modulated pre- and post-stimulus bias mechanisms in the drift-diffusion model during a probabilistic face/house discrimination task. We tested several plausible models of choice bias, concluding that predictive cues led to a bias in both the starting-point and rate of evidence accumulation favoring the more probable stimulus category. We further tested the hypotheses that prior bias in the starting-point was conditional on the feature-level uncertainty of category expectations and that dynamic bias in the drift-rate was modulated by the match between expected and observed stimulus features. Starting-point estimates suggested that subjects formed a constant prior bias in favor of the face category, which exhibits less feature-level variability, that was strengthened or weakened by trial-wise predictive cues. Furthermore, we found that the gain on face/house evidence was increased for stimuli with less ambiguous features and that this relationship was enhanced by valid category expectations. These findings offer new evidence that bridges psychological models of decision-making with recent predictive coding theories of perception.
•Competing diffusion models were fit to probabilistic face/house decisions.•Probabilistic cues biased the starting-point and drift-rate of face/house decisions.•Stimulus discriminability decreased RT when consistent with expected category.•Expectations and stimulus discriminability interactively modulated evidence gain. |
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| AbstractList | Anticipating a forthcoming sensory experience facilitates perception for expected stimuli but also hinders perception for less likely alternatives. Recent neuroimaging studies suggest that expectation biases arise from feature-level predictions that enhance early sensory representations and facilitate evidence accumulation for contextually probable stimuli while suppressing alternatives. Reasonably then, the extent to which prior knowledge biases subsequent sensory processing should depend on the precision of expectations at the feature level as well as the degree to which expected features match those of an observed stimulus. In the present study we investigated how these two sources of uncertainty modulated pre- and post-stimulus bias mechanisms in the drift-diffusion model during a probabilistic face/house discrimination task. We tested several plausible models of choice bias, concluding that predictive cues led to a bias in both the starting-point and rate of evidence accumulation favoring the more probable stimulus category. We further tested the hypotheses that prior bias in the starting-point was conditional on the feature-level uncertainty of category expectations and that dynamic bias in the drift-rate was modulated by the match between expected and observed stimulus features. Starting-point estimates suggested that subjects formed a constant prior bias in favor of the face category, which exhibits less feature-level variability, that was strengthened or weakened by trial-wise predictive cues. Furthermore, we found that the gain on face/house evidence was increased for stimuli with less ambiguous features and that this relationship was enhanced by valid category expectations. These findings offer new evidence that bridges psychological models of decision-making with recent predictive coding theories of perception.Anticipating a forthcoming sensory experience facilitates perception for expected stimuli but also hinders perception for less likely alternatives. Recent neuroimaging studies suggest that expectation biases arise from feature-level predictions that enhance early sensory representations and facilitate evidence accumulation for contextually probable stimuli while suppressing alternatives. Reasonably then, the extent to which prior knowledge biases subsequent sensory processing should depend on the precision of expectations at the feature level as well as the degree to which expected features match those of an observed stimulus. In the present study we investigated how these two sources of uncertainty modulated pre- and post-stimulus bias mechanisms in the drift-diffusion model during a probabilistic face/house discrimination task. We tested several plausible models of choice bias, concluding that predictive cues led to a bias in both the starting-point and rate of evidence accumulation favoring the more probable stimulus category. We further tested the hypotheses that prior bias in the starting-point was conditional on the feature-level uncertainty of category expectations and that dynamic bias in the drift-rate was modulated by the match between expected and observed stimulus features. Starting-point estimates suggested that subjects formed a constant prior bias in favor of the face category, which exhibits less feature-level variability, that was strengthened or weakened by trial-wise predictive cues. Furthermore, we found that the gain on face/house evidence was increased for stimuli with less ambiguous features and that this relationship was enhanced by valid category expectations. These findings offer new evidence that bridges psychological models of decision-making with recent predictive coding theories of perception. Anticipating a forthcoming sensory experience facilitates perception for expected stimuli but also hinders perception for less likely alternatives. Recent neuroimaging studies suggest that expectation biases arise from feature-level predictions that enhance early sensory representations and facilitate evidence accumulation for contextually probable stimuli while suppressing alternatives. Reasonably then, the extent to which prior knowledge biases subsequent sensory processing should depend on the precision of expectations at the feature level as well as the degree to which expected features match those of an observed stimulus. In the present study we investigated how these two sources of uncertainty modulated pre- and post-stimulus bias mechanisms in the drift-diffusion model during a probabilistic face/house discrimination task. We tested several plausible models of choice bias, concluding that predictive cues led to a bias in both the starting-point and rate of evidence accumulation favoring the more probable stimulus category. We further tested the hypotheses that prior bias in the starting-point was conditional on the feature-level uncertainty of category expectations and that dynamic bias in the drift-rate was modulated by the match between expected and observed stimulus features. Starting-point estimates suggested that subjects formed a constant prior bias in favor of the face category, which exhibits less feature-level variability, that was strengthened or weakened by trial-wise predictive cues. Furthermore, we found that the gain on face/house evidence was increased for stimuli with less ambiguous features and that this relationship was enhanced by valid category expectations. These findings offer new evidence that bridges psychological models of decision-making with recent predictive coding theories of perception. •Competing diffusion models were fit to probabilistic face/house decisions.•Probabilistic cues biased the starting-point and drift-rate of face/house decisions.•Stimulus discriminability decreased RT when consistent with expected category.•Expectations and stimulus discriminability interactively modulated evidence gain. Anticipating a forthcoming sensory experience facilitates perception for expected stimuli but also hinders perception for less likely alternatives. Recent neuroimaging studies suggest that expectation biases arise from feature-level predictions that enhance early sensory representations and facilitate evidence accumulation for contextually probable stimuli while suppressing alternatives. Reasonably then, the extent to which prior knowledge biases subsequent sensory processing should depend on the precision of expectations at the feature level as well as the degree to which expected features match those of an observed stimulus. In the present study we investigated how these two sources of uncertainty modulated pre- and post-stimulus bias mechanisms in the drift-diffusion model during a probabilistic face/house discrimination task. We tested several plausible models of choice bias, concluding that predictive cues led to a bias in both the starting-point and rate of evidence accumulation favoring the more probable stimulus category. We further tested the hypotheses that prior bias in the starting-point was conditional on the feature-level uncertainty of category expectations and that dynamic bias in the drift-rate was modulated by the match between expected and observed stimulus features. Starting-point estimates suggested that subjects formed a constant prior bias in favor of the face category, which exhibits less feature-level variability, that was strengthened or weakened by trial-wise predictive cues. Furthermore, we found that the gain on face/house evidence was increased for stimuli with less ambiguous features and that this relationship was enhanced by valid category expectations. These findings offer new evidence that bridges psychological models of decision-making with recent predictive coding theories of perception. |
| Author | Wheeler, Mark E. Tremel, Joshua J. Dunovan, Kyle E. |
| AuthorAffiliation | 3 Center for the Neural Basis of Cognition, University of Pittsburgh, PA, USA 4 Center for Neuroscience, University of Pittsburgh, PA, USA 1 Department of Psychology, University of Pittsburgh, PA, USA 2 Learning Research and Development Center, University of Pittsburgh, PA, USA 5 School of Psychology, Georgia Institute of Technology, GA, USA |
| AuthorAffiliation_xml | – name: 1 Department of Psychology, University of Pittsburgh, PA, USA – name: 4 Center for Neuroscience, University of Pittsburgh, PA, USA – name: 2 Learning Research and Development Center, University of Pittsburgh, PA, USA – name: 5 School of Psychology, Georgia Institute of Technology, GA, USA – name: 3 Center for the Neural Basis of Cognition, University of Pittsburgh, PA, USA |
| Author_xml | – sequence: 1 givenname: Kyle E. surname: Dunovan fullname: Dunovan, Kyle E. email: ked64@pitt.edu organization: Department of Psychology, University of Pittsburgh, PA, USA – sequence: 2 givenname: Joshua J. surname: Tremel fullname: Tremel, Joshua J. organization: Department of Psychology, University of Pittsburgh, PA, USA – sequence: 3 givenname: Mark E. surname: Wheeler fullname: Wheeler, Mark E. organization: Department of Psychology, University of Pittsburgh, PA, USA |
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| Keywords | Predictive coding Expectation Drift-diffusion model Perceptual decision-making Human Decision making Prediction Cognition Prior probability Experimental study Coding Vision Perception Mathematical model Cognitive bias |
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| SubjectTerms | Adult Anticipation, Psychological Biological and medical sciences Cues Decision Making Discrimination, Psychological Drift-diffusion model Expectation Face Female Fundamental and applied biological sciences. Psychology Humans Male Models, Psychological Neuropsychological Tests Perception Perceptual decision-making Photic Stimulation - methods Predictive coding Probability Psychology. Psychoanalysis. Psychiatry Psychology. Psychophysiology Reaction Time Vision Visual Perception Young Adult |
| Title | Prior probability and feature predictability interactively bias perceptual decisions |
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