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A Rosetta Stone hypothesis for neurophenomenology: mathematical predictions from predictive processing
Lancelot Da Costa1,2,3, Anil K Seth4,5,6, Karl Friston1,3
1VERSES AI Research Lab, 2121 Avenue of the Stars, 8th Floor, Los Angeles, CA 90016, United States.
Neuroscience of Consciousness
|July 22, 2026
Summary
This study proposes a "Rosetta Stone" hypothesis linking subjective experience (phenomenology) to brain activity using predictive processing. It suggests beliefs bridge first-person experience and third-person measurements in consciousness science.
Area of Science:
- Cognitive Science
- Neuroscience
- Philosophy of Mind
Background:
- Consciousness science struggles to connect subjective experience with objective measurements.
- Neurophenomenology seeks to bridge this gap but lacks mathematical tools.
- Predictive processing offers a framework for understanding brain function.
Purpose of the Study:
- To develop a mathematical framework for neurophenomenology.
- To propose a "Rosetta Stone" hypothesis based on predictive processing.
- To connect phenomenology, beliefs, and neural dynamics.
Main Methods:
- Formulating a hypothesis where beliefs act as a central hub.
- Deriving mathematical predictions based on the assumption that phenomenology is a function of beliefs.
- Reviewing the link between beliefs and neural dynamics.
Main Results:
- Predictions derived for subjective similarity judgments, cognitive metabolic cost, subjective cognitive effort, and time perception.
- A generative passage for neurophenomenology is outlined, focusing on beliefs and neural dynamics.
- The connection between beliefs and behavior is noted as well-documented.
Conclusions:
- Testing the derived predictions will validate the link between beliefs and phenomenology.
- The study advances the neurophenomenology research program by providing a mathematical approach.
- This work offers a potential method for integrating subjective and objective data in consciousness studies.
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