Psychedelic substances have shown promise in treating an array of clinical conditions. Here, an overview of mechanisms of action making them powerful therapeutic tools is provided, as explored through neuropharmacological, behavioural and neural network lenses. Functional connectivity analyses are identified as fundamental tools to understand how psychedelic-induced brain alterations mediate beneficial long-term outcomes. The present study offers a paradigm shift from a static to dynamic conceptualization of brain connectivity. Aiming to uncover how alterations in complex spatiotemporal dynamics of the acute psychedelic experience compare to normal waking consciousness, Harmonic Decomposition of Space-Time (HADES) is applied to three rs-fMRI placebo-controlled datasets of DMT-, LSD- and psilocybin-induced states. HADES defines frequency-specific functional harmonic brain patterns (FH) by eigen-decomposing the graph Laplacian of the dense functional connectome. The cortical connectivity gradients of psychedelic-induced signals were described in spatial terms through measures of time-averaged absolute and relative power of the first 11 computed FHs projected onto individual recordings, and temporally through measures of their fractional occupancy and life times across the timeseries. Results support notions of modular disintegration and desegregation proposed by the RElaxed Brain Under pSychedelics (REBUS) and the anarchic brain model. In fact, findings suggest a flattening of neural landscapes, increased global signals and decreased segregations between uni- and trans-modal networks. Furthermore, functional segregations within the visual cortex were reduced throughout the timeseries. Results are discussed in relation to neural changes observed in psychedelic states compared to depression. Finally, strengths and limitations of HADES for interpretations of spatiotemporal brain dynamics are considered.
Psychedelic substances have shown promise in treating an array of clinical conditions. Here, an overview of mechanisms of action making them powerful therapeutic tools is provided, as explored through neuropharmacological, behavioural and neural network lenses. Functional connectivity analyses are identified as fundamental tools to understand how psychedelic-induced brain alterations mediate beneficial long-term outcomes. The present study offers a paradigm shift from a static to dynamic conceptualization of brain connectivity. Aiming to uncover how alterations in complex spatiotemporal dynamics of the acute psychedelic experience compare to normal waking consciousness, Harmonic Decomposition of Space-Time (HADES) is applied to three rs-fMRI placebo-controlled datasets of DMT-, LSD- and psilocybin-induced states. HADES defines frequency-specific functional harmonic brain patterns (FH) by eigen-decomposing the graph Laplacian of the dense functional connectome. The cortical connectivity gradients of psychedelic-induced signals were described in spatial terms through measures of time-averaged absolute and relative power of the first 11 computed FHs projected onto individual recordings, and temporally through measures of their fractional occupancy and life times across the timeseries. Results support notions of modular disintegration and desegregation proposed by the RElaxed Brain Under pSychedelics (REBUS) and the anarchic brain model. In fact, findings suggest a flattening of neural landscapes, increased global signals and decreased segregations between uni- and trans-modal networks. Furthermore, functional segregations within the visual cortex were reduced throughout the timeseries. Results are discussed in relation to neural changes observed in psychedelic states compared to depression. Finally, strengths and limitations of HADES for interpretations of spatiotemporal brain dynamics are considered.
DMT, Psilocybin and LSD: insights on psychedelic-induced dynamic brain states using Harmonic Decomposition of Space-Time (HADES)
SERRA, ELISA
2021/2022
Abstract
Psychedelic substances have shown promise in treating an array of clinical conditions. Here, an overview of mechanisms of action making them powerful therapeutic tools is provided, as explored through neuropharmacological, behavioural and neural network lenses. Functional connectivity analyses are identified as fundamental tools to understand how psychedelic-induced brain alterations mediate beneficial long-term outcomes. The present study offers a paradigm shift from a static to dynamic conceptualization of brain connectivity. Aiming to uncover how alterations in complex spatiotemporal dynamics of the acute psychedelic experience compare to normal waking consciousness, Harmonic Decomposition of Space-Time (HADES) is applied to three rs-fMRI placebo-controlled datasets of DMT-, LSD- and psilocybin-induced states. HADES defines frequency-specific functional harmonic brain patterns (FH) by eigen-decomposing the graph Laplacian of the dense functional connectome. The cortical connectivity gradients of psychedelic-induced signals were described in spatial terms through measures of time-averaged absolute and relative power of the first 11 computed FHs projected onto individual recordings, and temporally through measures of their fractional occupancy and life times across the timeseries. Results support notions of modular disintegration and desegregation proposed by the RElaxed Brain Under pSychedelics (REBUS) and the anarchic brain model. In fact, findings suggest a flattening of neural landscapes, increased global signals and decreased segregations between uni- and trans-modal networks. Furthermore, functional segregations within the visual cortex were reduced throughout the timeseries. Results are discussed in relation to neural changes observed in psychedelic states compared to depression. Finally, strengths and limitations of HADES for interpretations of spatiotemporal brain dynamics are considered.File | Dimensione | Formato | |
---|---|---|---|
Elisa Serra Final Dissertation.pdf
accesso riservato
Dimensione
3.04 MB
Formato
Adobe PDF
|
3.04 MB | Adobe PDF |
The text of this website © Università degli studi di Padova. Full Text are published under a non-exclusive license. Metadata are under a CC0 License
https://hdl.handle.net/20.500.12608/36622