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Hanna M. Tolle

4 papers in the library · 43 citations · publishing 2022-2024

Papers

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Shared functional connectome fingerprints following ritualistic ayahuasca intake.

Neuroimage 2024 Pablo Mallaroni, Natasha L. Mason, Lilian Kloft et al. 17 citations

The knowledge that brain functional connectomes are unique and reliable has enabled behaviourally relevant inferences at a subject level. However, whether such "fingerprints" persist under altered states of consciousness is unknown. Ayahuasca is a potent serotonergic psychedelic which produces a widespread dysregulation of functional connectivity. Used communally in religious ceremonies, its...

The unique neural signature of your trip: Functional connectome fingerprints of subjective psilocybin experience

Network Neuroscience November 1, 2023 Juan Carlos Farah, Pablo Mallaroni, Enrico Amico et al. 21 citations

Abstract The emerging neuroscientific frontier of brain fingerprinting has recently established that human functional connectomes (FCs) exhibit fingerprint-like idiosyncratic features, which map onto heterogeneously distributed behavioral traits. Here, we harness brain-fingerprinting tools to extract FC features that predict subjective drug experience induced by the psychedelic psilocybin....

Ritualistic use of ayahuasca enhances a shared functional connectome identity with others

bioRxiv (Cold Spring Harbor Laboratory) October 11, 2022 Pablo Mallaroni, Natasha L. Mason, Lilian Kloft et al. 4 citations preprint

Abstract The knowledge that brain functional connectomes are both unique and reliable has enabled behaviourally relevant inferences at a subject level. However, it is unknown whether such “fingerprints” persist under altered states of consciousness. Ayahuasca is a potent serotonergic psychedelic which elicits a widespread dysregulation of functional connectivity. Used communally in religious...

Accurate and Interpretable Prediction of Antidepressant Treatment Response from Receptor-informed Neuroimaging

bioRxiv (Cold Spring Harbor Laboratory) Hanna M. Tolle, Andrea I. Luppi, Timothy Lawn et al. 1 citation preprint

Conventional antidepressants show moderate efficacy in treating major depressive disorder. Psychedelic-assisted therapy holds promise, yet individual responses vary, underscoring the need for predictive tools to guide treatment selection. Here, we present graphTRIP (graph-based Treatment Response Interpretability and Prediction) – a geometric deep learning architecture that enables three...