The neural correlates of hierarchical predictions for perceptual decisions
Open accessAbstract
Sensory information is inherently noisy, sparse, and ambiguous. In contrast, visual experience is usually clear, detailed, and stable. Bayesian theories of perception resolve this discrepancy by assuming that prior knowledge about the causes underlying sensory stimulation actively shapes perceptual decisions. The CNS is believed to entertain a generative model aligned to dynamic changes in the hierarchical states of our volatile sensory environment. Here, we used model-based fMRI to study the neural correlates of the dynamic updating of hierarchically structured predictions in male and female human observers. We devised a crossmodal associative learning task with covertly interspersed ambiguous trials in which participants engaged in hierarchical learning based on changing contingencies between auditory cues and visual targets. By inverting a Bayesian model of perceptual inference, we estimated individual hierarchical predictions, which significantly biased perceptual decisions under ambiguity. Although “high-level” predictions about the cue–target contingency correlated with activity in supramodal regions such as orbitofrontal cortex and hippocampus, dynamic “low-level” predictions about the conditional target probabilities were associated with activity in retinotopic visual cortex. Our results suggest that our CNS updates distinct representations of hierarchical predictions that continuously affect perceptual decisions in a dynamically changing environment. SIGNIFICANCE STATEMENTBayesian theories posit that our brain entertains a generative model to provide hierarchical predictions regarding the causes of sensory information. Here, we use behavioral modeling and fMRI to study the neural underpinnings of such hierarchical predictions. We show that “high-level” predictions about the strength of dynamic cue–target contingencies during crossmodal associative learning correlate with activity in orbitofrontal cortex and the hippocampus, whereas “low-level” conditional target probabilities were reflected in retinotopic visual cortex. Our findings empirically corroborate theorizations on the role of hierarchical predictions in visual perception and contribute substantially to a longstanding debate on the link between sensory predictions and orbitofrontal or hippocampal activity. Our work fundamentally advances the mechanistic understanding of perceptual inference in the human brain.
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The metabotropic glutamate agonist pomeglumetad appears to have efficacy in early rather than chronic schizophrenia, suggesting that hyperglutamatergia is more involved around the onset and early phases of illness.
“We note with interest that the metabotropic glutamate agonist pomeglumetad appears to have efficacy in early rather than chronic schizophrenia, suggesting that hyperglutamatergia is more involved around the onset and early phases of illness (99, 100).”
From The Predictive Coding Account of Psychosis (2018) · cites this paper as [100]
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The generalized Hierarchical Gaussian Filter
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- Authors
- Weilnhammer, V. A., Stuke, H., Sterzer, P., & Schmack, K.
- Affiliations
- Charité – Universitätsmedizin Berlin (DE)
- Humboldt-Universität zu Berlin (DE)
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2018-04-30
- Volume
- 38
- Issue
- 21
- Pages
- 5008-5021
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- PMC
- PMC6596123
- OpenAlex
- W2800313572
- Cited by
- 57
- References
- 37
- Citations by year
- 2026: 4 · 2025: 9 · 2024: 5 · 2023: 9 · 2022: 6 · 2021: 9 · 2020: 7 · 2019: 3 · 2018: 5
- FWCI
- 7.85
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Neuroscience (publishedVersion, cc-by-nc-sa)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Deutsche Forschungsgemeinschaft (STE-1430/7-1, 1430/7-1)
- Bundesministerium für Bildung und Forschung (01ZX1404A)
- Berlin Institute of Health
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Multisensory perception and integration
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- hierarchical prediction, Bayesian inference, perceptual decision making, orbitofrontal cortex, hippocampus, retinotopic visual cortex, generative models, ambiguity, sex differences, perceptual inference
- MeSH terms
- Acoustic Stimulation, Adult, Algorithms, Association Learning, Bayes Theorem, Brain Mapping, Cues, Decision Making, Female, Hippocampus, Humans, Magnetic Resonance Imaging, Male, Models, Theoretical, Perception, Photic Stimulation, Visual Cortex, Prefrontal Cortex, Young Adult
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