question
active
question:can-process-theories-implementing-bayesian-models-be-derived-and-shown-to-explain-empirical-neuronal-phenomenaCan process theories implementing Bayesian models be derived and shown to explain empirical neuronal phenomena?
Motivating question: bridging normative Bayesian theory and testable neuroscience predictions.
Source paper
extracted_from(2017) · Karl Friston · Thomas FitzGerald · Francesco Rigoli · Philipp Schwartenbeck +1
Related by similarity (8)
cosine ≥ 0.65 · no typed edgeEntities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.
- Process theories can be derived from variational principles in a straightforward manner with biological plausibility.hypothesis0.827Paper's core methodological hypothesis: gap between normative and process-level theories can be bridged.
- Open question about inter-agent communication beyond model-space assumption
- The core process theory hypothesis set up in the paper.
- Forward-looking claim suggesting the methodological framework is relevant for future AI systems beyond current LLMs.
- Acknowledges that the model's additional descriptions of its experience are unverified.
- Empirical gap explicitly acknowledged; experiments reportedly in progress at time of writing
- Alexander's methodological justification for using the Guasare simulation studies.
- Overall assessment from Discussion.