A simple approach to ignoring irrelevant variables by population decoding based on multisensory neurons
Open accessAbstract
Sensory input reflects events that occur in the environment, but multiple events may be confounded in sensory signals. For example, under many natural viewing conditions, retinal image motion reflects some combination of self-motion and movement of objects in the world. To estimate one stimulus event and ignore others, the brain can perform marginalization operations, but the neural bases of these operations are poorly understood. Using computational modeling, we examine how multisensory signals may be processed to estimate the direction of self-motion (i.e., heading) and to marginalize out effects of object motion. Multisensory neurons represent heading based on both visual and vestibular inputs and come in two basic types: “congruent” and “opposite” cells. Congruent cells have matched heading tuning for visual and vestibular cues and have been linked to perceptual benefits of cue integration during heading discrimination. Opposite cells have mismatched visual and vestibular heading preferences and are ill-suited for cue integration. We show that decoding a mixed population of congruent and opposite cells substantially reduces errors in heading estimation caused by object motion. In addition, we present a general formulation of an optimal linear decoding scheme that approximates marginalization and can be implemented biologically by simple reinforcement learning mechanisms. We also show that neural response correlations induced by task-irrelevant variables may greatly exceed intrinsic noise correlations. Overall, our findings suggest a general computational strategy by which neurons with mismatched tuning for two different sensory cues may be decoded to perform marginalization operations that dissociate possible causes of sensory inputs.
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Previous theoretical modeling work indicated that opposite neurons in macaque MSTd may be involved in segregating sensory cues.
“Previous theoretical modeling work has indicated that opposite neurons in macaque MSTd may be involved in segregating sensory cues (22, 32, 33).”
From How multisensory neurons solve causal inference. (2021) · cites this paper as [32]
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空間知覚：物体の運動知覚に関与する視覚- 前庭情報統合の神経基盤
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- Authors
- Kim, H. R., Pitkow, X., Angelaki, D. E., & DeAngelis, G. C.
- Affiliations
- University of Rochester (US)
- Baylor College of Medicine (US)
- Corresponding author
- DeAngelis, Gregory C.
- Venue
- Journal of Neurophysiology
- Publisher
- American Physiological Society
- Published
- 2016-09-01
- Volume
- 116
- Issue
- 3
- Pages
- 1449-1467
- ISSN
- 0022-3077 (ISSN-L)
- 1522-1598
- PMC
- PMC5040375
- OpenAlex
- W2474958196
- Cited by
- 32
- References
- 70
- Citations by year
- 2026: 1 · 2025: 1 · 2023: 1 · 2022: 3 · 2021: 4 · 2020: 5 · 2019: 5 · 2018: 4 · 2017: 7 · 2016: 1
- FWCI
- 8.07
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Neurophysiology (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- HHS | NIH | National Eye Institute (NEI) (EY016178, EY013644, EY001319)
- HHS | NIH | National Institute on Deafness and Other Communication Disorders (NIDCD) (T32DC009974)
- Robert and Janice McNair Foundation
- 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 › Neurology › Vestibular and auditory disorders
- Keywords
- multisensory neurons, population decoding, marginalization, heading estimation, self-motion, visual-vestibular integration, reinforcement learning, noise correlation
- MeSH terms
- Animals, Attention, Discrimination, Psychological, Models, Neurological, Motion Perception, Neurons, Orientation, Proprioception, Reinforcement, Psychology, Space Perception, Likelihood Functions, Linear Models, Optic Flow
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