Inter and intra-individual variability of Information-theoretic and spectral EEG measures during autobiographical memory reconstruction

Characterizing neural dynamics during autobiographical memory (AM) reconstruction is key to understanding how personal experiences are retrieved from distributed representations. We first identified an alpha-beta (9–21 Hz) spectral marker associated with AM reconstruction and then investigated whether this signature reflects stable individual characteristics or trial-specific neural dynamics by comparing it with information-theoretic measures. We recorded EEG activity from 33 participants during AM reconstruction. Using an intraclass correlation coefficient (ICC) framework with subject-level bootstrapping, we quantified the relative contribution of between- and within-subject variance for alpha-beta power, Shannon entropy (H) and Statistical Complexity (C). Preliminary analyses indicate that alpha-beta power is predominantly characterized by within-subject variance, suggesting that this signature of AM reconstruction is dependent on the specific episode being reconstructed. In contrast, H and C show higher between-subject ICC, indicating greater stability across episodes and stronger individual-level signatures. Building on this distinction, we will examine whether inter-individual differences in H and C relate to cognitive and affective profiles (working memory, processing speed, executive control and mood), while testing whether trial-level fluctuations in alpha-beta power relate to episodic phenomenology, including access latency, retrieval difficulty and amount of details