Building on my previous questions regarding thermo-qubit dynamics, intentionality, and intermittency spikes in EEG, I’m now looking into the concept of functional entropy, that is, entropy as a dynamic property of functional organization rather than simply a measure of signal complexity or statistical dispersion.

In the context of theories like the Oscillatory Dynamics Transductive-Bridging Theorem (ODTBT) and Poznanski’s Dynamic Organicity Theory, functional entropy reflects the flux of order and disorder across nested neural structures, and is seen as a key substrate for intentionality, awareness, and transductive reorganization.

Whereas multiscale entropy (MSE) and Lempel-Ziv complexity are frequently applied to EEG and fMRI data, these often measure surface-level signal variation. I’m interested in methods that attempt to capture entropy as it relates to functional transformation, system reorganization, or intentional phase coherence, i.e., entropy in the service of functional differentiation.

Specific questions:

• Are there existing tools or techniques that operationalize functional entropy across neural scales (micro to macro)?
• Has anyone applied entropy-based metrics to study intention, cognitive binding, or nested field coherence?
• What are the limitations of traditional entropy measures in tracking nonlinear transductive shifts or self-referential holon dynamics?

If anyone is working on or aware of methods that bridge thermodynamic principles with neural information flow, I’d be grateful for any insights or references.