Objective:

Explore the development of a valid SEEG sleep-staging system anchored to surface EEG; compare SEEG-derived labels to scalp staging and characterize stage transitions (dwell times, sequences); and define micro-stages within macro-stages to support a simple, clinically usable framework.

Background:

Conventional sleep-staging in polysomnography relies on scalp EEG, but no validated system exists for SEEG, limiting the reliability of state-association of interictal epileptiform discharge, seizures, and network dynamics. Mapping scalp-defined macro-stages (Wake, N1, N2, N3 & REM) onto simultaneous SEEG may reveal intracranial signatures and micro-stages (e.g., spindle-rich or K-complex–dominant N2, slow-oscillation–dominant N3, phasic vs tonic REM), enabling reliable identification of sleep stages in cases with exclusive SEEG monitoring.

Design/Methods:

We systematically searched PubMed, EMBASE, and Cochrane and screened references (PRISMA). Macro-stages were assigned per American Academy of Sleep Medicine (AASM) on scalp EEG and projected onto SEEG within subjects. We extracted classic graphoelements (vertex waves, spindles, K-complexes, slow waves, sawtooth/REM activity) and compared topography, morphology, timing, and transition dynamics (onset/offset latencies).

Results:

Surface EEG reliably marked macro-architecture (alpha attenuation; N2 spindles/K-complexes; N3 slow waves; REM features). SEEG provided micro-architectural resolution, often showing earlier local onset of N2 spindles and K-complexes, focal N3 slow oscillations, and phasic REM activity within hippocampal, thalamic, and limbic contacts before—or without—clear scalp correlates. Across macro-stage transitions (e.g., N2→N3, NREM↔REM), SEEG highlighted local-to-global propagation and cortical–subcortical coupling. Intracranial features differentiated micro-stages within macro-stages.

Conclusions:

SEEG complements scalp staging by resolving micro-architecture and exposing earlier, deeper generators of sleep graphoelements and transitions. A surface-anchored, SEEG-refined approach lays the groundwork for a practical SEEG sleep-staging framework, including for SEEG-only recordings.