# Latent State Estimation **Domain:** Signal Processing / Machine Learning / Control **Doc Type:** Technical Concept Node **Maturity:** Established and Evolving **Related:** [[wiki/Observer Stack|Observer Stack]], [[wiki/Inverse Problem|Inverse Problem]], [[wiki/LFADS|LFADS]], [[wiki/Neural Decoding|Neural Decoding]] --- ## Definition **Latent state estimation** infers an unobserved dynamical state from measurements generated by that state. Raw sensor values are treated as indirect evidence rather than the object of interest itself. ## Neural Context Neural population models estimate underlying trajectories, intentions, or computational variables from spikes, field potentials, imaging signals, or hemodynamic measurements. The estimate depends on model assumptions, calibration, sampling, and task context. ## Boundary A useful latent state can support prediction or control without containing every variable required for biological reconstruction or personal continuity.