Simple visual features, such as orientation, are thought to be represented in the spiking of visual neurons using population codes. I show that optimal decoding of such activity predicts characteristic deviations from the normal distribution of errors at low gains. Examining human perception of orientation stimuli, I show that these predicted deviations are present at near-threshold levels of contrast. The findings may provide a neural-level explanation for the appearance of a threshold in perceptual awareness whereby stimuli are categorized as seen or unseen. As well as varying in error magnitude, perceptual judgments differ in certainty about what was observed. I demonstrate that variations in the total spiking activity of a neural population can account for the empirical relationship between subjective confidence and precision. These results establish population coding and decoding as the neural basis of perception and perceptual confidence.
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