Adaptive coding for dynamic sensory inference
| Autor: | Wiktor Mlynarski, Ann M Hermundstad |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
neural dynamics Computer science efficient coding Bayesian inference Action Potentials Inference adaptation perception computer.software_genre Bayes' theorem 0302 clinical medicine Biology (General) media_common Neurons 0303 health sciences General Neuroscience normative theories General Medicine Adaptation Physiological Medicine Research Article Sensory Receptor Cells QH301-705.5 Science media_common.quotation_subject Models Neurological Fidelity Sensory system Stimulus (physiology) Machine learning General Biochemistry Genetics and Molecular Biology 03 medical and health sciences Encoding (memory) None Humans 030304 developmental biology General Immunology and Microbiology Quantitative Biology::Neurons and Cognition business.industry Bayes Theorem Pattern recognition 030104 developmental biology Adaptive coding Artificial intelligence business computer 030217 neurology & neurosurgery Neuroscience |
| Zdroj: | eLife eLife, Vol 7 (2018) |
| DOI: | 10.1101/189506 |
| Popis: | Behavior relies on the ability of sensory systems to infer properties of the environment from incoming stimuli. The accuracy of inference depends on the fidelity with which behaviorally-relevant properties of stimuli are encoded in neural responses. High-fidelity encodings can be metabolically costly, but low-fidelity encodings can cause errors in inference. Here, we discuss general principles that underlie the tradeoff between encoding cost and inference error. We then derive adaptive encoding schemes that dynamically navigate this tradeoff. These optimal encodings tend to increase the fidelity of the neural representation following a change in the stimulus distribution, and reduce fidelity for stimuli that originate from a known distribution. We predict dynamical signatures of such encoding schemes and demonstrate how known phenomena, such as burst coding and firing rate adaptation, can be understood as hallmarks of optimal coding for accurate inference. |
| Databáze: | OpenAIRE |
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