online-generalised-predictive-coding

name	online-generalised-predictive-coding
description	Online Generalised Predictive Coding via Dynamic Expectation Maximisation (ODEM) for biologically plausible online learning. Activation: predictive coding, online learning, DEM, dynamic expectation maximisation, active inference.

Online Generalised Predictive Coding

Online Dynamic Expectation Maximisation (ODEM) — biologically plausible framework for online predictive coding and parameter estimation.

Metadata

• Source: arXiv:2605.04242
• Authors: Mehran H. Z. Bazargani, Szymon Urbas, Adeel Razi, Thomas Brendan Murphy, Karl Friston
• Published: 2026-05-07
• Categories: stat.ML, cs.LG, q-bio.NC

Core Methodology

Online DEM (ODEM)

• Extends Generalised Predictive Coding to online/sequential setting
• Simultaneous state and parameter estimation via variational inference
• Biologically plausible update rules compatible with neural implementation
• Handles non-stationary environments with adaptive learning rates

Technical Framework

1. Generalised coordinates of motion for temporal derivatives
2. Variational free energy minimisation online
3. Expectation step: update posterior over hidden states
4. Maximisation step: update model parameters
5. Recursive updates with forgetting factor for non-stationarity

Applications

• Online brain state tracking
• Adaptive neural decoding
• Real-time fMRI/EEG analysis
• Active inference agents

Pitfalls

• Requires careful tuning of learning rates
• Convergence guarantees depend on model complexity
• Computational cost scales with model dimensionality

Related Skills

• free-energy-moe-routing
• autopoiesis-self-evolving-systems
• brain-digital-twins-execution-semantics-v3