INVESTIGADORES
PALLAVICINI Carla
congresos y reuniones científicas
Título:
Functional connectivity signatures of classic psychedelics and entactogen psychedelics.
Autor/es:
CARLA PALLAVICINI; FEDERICO ZAMBERLAN; MIRTA VILLARREAL; ROBIN CARHART-HARRIS; DAVID NUTT; ENZO TAGLIAZUCCHI
Lugar:
Buenos Aires
Reunión:
Workshop; XX Giambiagi winter school.; 2018
Institución organizadora:
Departamento de Física, UBA
Resumen:
Classic psychedelics are substances of paramount historical, cultural and scientific relevance. These molecules act primarily as serotonin (5-hydroxytryptamine [5-HT]) receptors agonist, mainly of the 5-HT2A receptor subtype. As a result of their neurochemical action, psychedelics elicit profound transient modifications in the consciousness of the self and the environment. Recently, a number of different studies have revealed the potential therapeutic effect of classic psychedelics (e.g. LSD, psilocybin, and DMT) in the treatment of different neuropsychiatric conditions. Other substances that modulate the level and quality of conscious content that are of potential therapeutic value are entactogen psychedelics (i.e. monoamine transporter substrates, exemplified by 3,4-Methylenedioxymethamphetamine [MDMA]).  Despite variability in the elicited subjective effects, these drugs share as a common motif the induction of a non-ordinary or altered state of consciousness, which may be a relevant component of their therapeutic action. Here we search for the commonalities and divergences between the changes in whole-brain activity elicited by three serotonergic psychedelics (LSD, psilocybin, and DMT, as part of the amazonian conception Ayahuasca), MDMA and a control non-psychedelic drug, the dopaminergic stimulant Modafinil. This multi-centre study comprises data acquired from different scanners which was processed according to an unified standard. Afterwards we computed the functional connectivity between all pairs of 90 neuroanatomical regions and trained a machine learning algorithm (random forest classifier) to classify them from their associated placebo condition. We investigated whether a classifier trained using data from one drug could generalize to reliably detect the changes in brain activity associated with all other drugs, and mapped in anatomical space the network of functional connections associated with the successful generalization. Our results suggest that the shared effects of psychedelics can be quantitatively measured using fMRI, bringing us closer to dissect the varieties of the psychedelic state and their associated neural correlates.