Perceptual predictions track subjective, over objective, statistical structure

Over the past two decades, converging evidence from neuroscience and psychology has shown that predictions based on learnt statistical regularities exert a widespread influence on perception, action and cognition. Predictive processes in cognition and the brain are usually modelled as tracking objective event probabilities, deriving predictions and prediction errors from the statistical structure of the environment. However, our subjective models of our environments do not always align with these objective statistics. Currently we know little about how these subjective representations may determine the predictive functions. To separate subjective and objective contributions to prediction, we conducted three studies where cues (actions or tones) predicted visual outcomes (shapes or Gabors) with varying contingencies, and adult participants discriminated these outcomes. Uniquely to our paradigm, participants also reported their experiences of the statistical structure embedded in the task - the subjective probability (Experiment 1; N = 68), expectedness (Experiment 2; N = 35), or surprise (Experiment 3; N = 35) associated with the outcomes. When modelling subjective ratings alongside objective structure, the speed of perceptual decisions was best explained by independent, additive contributions of both. The decision itself was usually only explained by the subjective ratings, with little additional variance explained by objective statistical structure. These findings suggest that subjective experience may play a key, overlooked role in predictive processes, and open a host of interesting questions about the relative objective and subjective contributions to prediction, perception, and learning.