Beyond the Information Paradigm: from Prediction to Anticipation

Within theoretical neuroscience, many have by now embraced the view of the brain as a prediction machine which updates its predictions in light of incoming information. Yet, these ‘Predictive Processing’ theories (PP) face big conceptual challenges.

As I've shown previously, by relying on semantic notions like information, representation, prediction, hypothesis-testing etc., they resist integration within the larger causal-mechanistic framework of which they claim to be a part.

The twofold problem is, first, how to make naturalistic sense of semantic content or meaning at the level of individual neurons or neural populations and, second, how the assumed semantic content is supposed to be causally efficacious.

Yet, if we can’t understand the neuroscientific data in terms of upstream information, downstream prediction and resulting prediction errors, how, then, should the neuroscientist interpret the bidirectional neural activity?

Via 3 complementary research objectives (RO1-03), this project is aimed at providing an alternative explanation for the neuroscientific data which is traditionally framed in terms of information processing and, more recently, information prediction.

For RO1, the pivotal move will be to substitute the problematic notion of prediction with an empirically underpinned biological notion of anticipation that does not involve semantic content, and which does fit within the boundaries of the causal-mechanistic framework.

With RO2, this notion of anticipation-without-prediction will be applied to the neuroscientific findings the PP theorist explains in terms of prediction. RO3 will be dedicated to further study anticipation-without-prediction at the microbiological level via lab experiment.

Overall, the project aims to present an alternative to the computationalist view of the brain, which identifies neural activity with information processing. In this sense, the project has paradigm-shifting potential.