1. Individual Alpha Frequency (IAF)

Each patient’s baseline alpha peak is estimated so frequency bands are individualized rather than based on population norms.

Why this matters:

→ Ensures all session comparisons are anchored to the individual, not averages.

https://www.mdpi.com/2313-7673/10/11/730?utm_

2. Frontal Theta/Alpha Log Ratio

The log transformed ratio of frontal theta and alpha power is computed across the session.

Why this matters:

→ Provides a stable marker of relative cognitive effort and engagement over time.

https://pmc.ncbi.nlm.nih.gov/articles/PMC9149374/?utm_

3. Occipital Alpha Calculated

Relative changes in occipital alpha power are examined across the session.

Why this matters:

→ Helps contextualize shifts in attentional orientation without labeling internal states.

https://www.sciencedirect.com/science/article/abs/pii/S0006899322002189?utm_

4. Z-score Normalization

All spectral features are normalized within the individual using baseline statistics.

Why this matters:

→ Allows session changes to be interpreted as deviations from that person’s typical state.

https://www.researchgate.net/publication/397230750_Mapping_EEG_Metrics_to_Human_Affective_and_Cognitive_Models_An_Interdisciplinary_Scoping_Review_from_a_Cognitive_Neuroscience_Perspective?utm_

5. Theta & Alpha Related studies

https://pmc.ncbi.nlm.nih.gov/articles/PMC9149374/

https://pmc.ncbi.nlm.nih.gov/articles/PMC6614966/