Extended Data Fig. 7: Semantic embedding prediction performance by LFP power band.
From: Plasticity and language in the anaesthetized human hippocampus
Each panel recreates the analysis of Fig. 4c, showing the average correlation between true power and predicted power of a linear model regressing LFP power in the given band vs. the semantic embedding of each word, computed separately for each channel and grouped by patient. Colours indicate distributions for 4 different patients. For all bands, the RMSE of a linear model significantly outperformed models trained on shuffled data, though with reduced prediction performance relative to single units (p < 0.05; delta: mean R = 0.029, 46% of channels were significant; theta: mean R = 0.054, 75.8% significant channels; alpha: mean R = 0.039, 73.7% significant channels; beta: mean R = 0.067, 76.4% significant channels; low gamma: mean R = 0.052, 76.3% significant channels; gamma: mean R = 0.021, 39.3% significant channels).
