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Sensory neurons: 'predictive coding' or 'coding for predictions'?


The notion of sensory prediction has a long history in theories of neural coding. For example, the influential 'predictive coding' hypothesis posits that to spare resources, rather than encoding all sensory inputs, neurons encode a prediction error, equal to the difference between their received and expected sensory inputs. An alternative, recent, idea is that sensory neurons instead 'code for predictions', by preferentially encoding sensory signals that are informative about the future while discarding other, non-predictive, signals.

Despite decades of research on predictive coding, many questions remain unanswered. For example, are sensory predictions important in determining what is encoded (i.e. do neurons selectively encode 'predictive' stimuli?). In addition, do sensory predictions play a role in determining how sensory signals are encoded (e.g. do neurons encode a 'prediction error' signal?). Finally, how, and over what timescales, do sensory circuits adjust their predictions based on experience and changes in the environment?

This workshop will bring together a broad group of theoretical and experimental researchers to discuss and debate the role of sensory predictions in neural coding. It will aim to build bridges between current theories of sensory prediction, clarifying what they have in common, and when they are opposed. Further, it will address how these different theories are supported by experiments. It is hoped that the resulting discussion will stimulate new ideas about how to test these theories, to uncover how sensory predictions are used by the brain to shape neural coding.