LSD Relaxes Structural Constraints on Brain Dynamics and Default Mode Decoupling Tracks Ego Dissolution
Subramani, V.; Pascarella, A.; Brunel, J.; Harel, Y.; Muthukumaraswamy, S. D.; Carhart-Harris, R.; Jerbi, K.; Lioi, G.; Farrugia, N.
Show abstract
Psychedelics profoundly alter conscious experience, yet how they reshape the relationship between brain anatomy and function remains unclear. In particular, it is unknown whether psychedelic states reflect a global disruption of structure-function organization or a frequency- and network-specific reconfiguration of neural dynamics relative to the structural connectome. Here we address this question using source-localized magnetoencephalography mapped onto connectome harmonics to quantify structure-function coupling in humans under lysergic acid diethylamide (LSD) and placebo. LSD induces a robust decoupling of low-frequency (theta, alpha and beta) activity from anatomical constraints, indicating a global loosening of structure-aligned large-scale dynamics. In contrast, high-frequency gamma activity shows selective reorganization rather than uniform disruption. Greater gamma-band decoupling within core default-mode network regions predicts the intensity of ego dissolution across individuals, demonstrating that while LSD broadly alters large-scale dynamics, subjective loss of self is specifically linked to frequency-selective reorganization of the default-mode network. Functional decoding reveals that LSD does not produce indiscriminate disintegration but instead drives system-specific rebalancing, with preferential decoupling of visual and attentional systems and strengthened coupling within auditory networks. Together, these findings provide electrophysiological evidence that psychedelic states emerge from a frequency-dependent relaxation of structural constraints on brain activity and identify default-mode reorganization as a neural correlate of ego dissolution. These results offer a mechanistic framework for understanding how LSD may exert therapeutic effects by transiently relaxing rigid structural constraints and enhancing dynamical flexibility within networks involved in self-related processing.
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