What does the retina know about natural scenes?
Neural Computation
Neural Computation
Perception as Bayesian inference
Perception as Bayesian inference
Statistically efficient estimation using population coding
Neural Computation
Probabilistic interpretation of population codes
Neural Computation
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Population coding and decoding in a neural field: a computational study
Neural Computation
Population Coding with Correlation and an Unfaithful Model
Neural Computation
Spatial transformations in the parietal cortex using basis functions
Journal of Cognitive Neuroscience
Bayesian computation in recurrent neural circuits
Neural Computation
Difficulty of Singularity in Population Coding
Neural Computation
Computing with Continuous Attractors: Stability and Online Aspects
Neural Computation
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Population coding is a simplified model of distributed information processing in the brain. This study investigates the performance and implementation of a sequential Bayesian decoding (SBD) paradigm in the framework of population coding. In the first step of decoding, when no prior knowledge is available, maximum likelihood inference is used; the result forms the prior knowledge of stimulus for the second step of decoding. Estimates are propagated sequentially to apply maximum a posteriori (MAP) decoding in which prior knowledge for any step is taken from estimates from the previous step. Not only do we analyze the performance of SBD, obtaining the optimal form of prior knowledge that achieves the best estimation result, but we also investigate its possible biological realization, in the sense that all operations are performed by the dynamics of a recurrent network. In order to achieve MAP, a crucial point is to identify a mechanism that propagates prior knowledge. We find that this could be achieved by short-term adaptation of network weights according to the Hebbian learning rule. Simulation results on both constant and time-varying stimulus support the analysis.