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Andrea I Luppi

Montreal Neurological Institute, Montreal, ON, Canada.

7 papers in the library · 494 citations · publishing 2021-2025

Papers

LSD alters dynamic integration and segregation in the human brain.

NeuroImage February 15, 2021 Andrea I Luppi, Robin L Carhart-Harris, Leor Roseman et al. 186 citations

LSD alters brain network dynamics non-uniformly over time, making globally segregated connectivity states more complex and weakening the link between functional and anatomical connectivity. The drug reduces functional connectivity in the anterior medial prefrontal cortex specifically during states of high segregation. Ego dissolution was predicted by increased small-world organization during a state of high global integration. These temporally-specific effects reveal a more nuanced picture of psychedelic-induced changes in brain connectivity and complexity than previously reported.

Receptor-informed network control theory links LSD and psilocybin to a flattening of the brain's control energy landscape.

Nature communications October 3, 2022 S Parker Singleton, Andrea I Luppi, Robin L Carhart-Harris et al. 156 citations

Psychedelics like LSD and psilocybin temporarily alter subjective experience by acting on serotonin 2a (5-HT2a) receptors, increasing the diversity (entropy) of brain activity. This increase may arise from a flattening of the brain's control energy landscape. Using fMRI data, the authors show that these compounds reduce the control energy needed for transitions between brain states compared to placebo. Across individuals, lower control energy correlates with more frequent state transitions and higher entropy. Incorporating PET data on 5-HT2a receptor distribution under non-drug conditions, the analysis links these receptors to reduced control energy. The findings demonstrate that receptor-informed network control theory can model how neuropharmacological manipulation affects brain dynamics.

Distributed harmonic patterns of structure-function dependence orchestrate human consciousness.

Communications biology January 28, 2023 Andrea I Luppi, Jakub Vohryzek, Morten L Kringelbach et al. 98 citations

Consciousness depends on how tightly brain function follows the brain's physical wiring. Using MRI scans, researchers measured structure-function coupling across spatial scales in people who were unconscious from anesthesia or brain injury and in people under psychedelics (LSD or ketamine). During loss of consciousness, function more closely tracked the brain's structural connections, a signature that could distinguish behaviorally similar brain-injured patients and detect covert consciousness. In contrast, psychedelics decoupled function from structure, and this decoupling correlated with physiological and subjective scores. The findings suggest that connectome harmonic decomposition reveals how neuromodulation and network architecture jointly shape consciousness.

Local orchestration of distributed functional patterns supporting loss and restoration of consciousness in the primate brain.

Nature communications March 11, 2024 Andrea I Luppi, Lynn Uhrig, Jordy Tasserie et al. 43 citations

Loss of consciousness under anesthesia increasingly constrains brain activity to follow the brain's physical structure, collapsing hierarchical cortical organization across scales. This effect was observed with three different anesthetics—propofol, sevoflurane, and ketamine—and was reversed by electrically stimulating the central thalamus, which also restored behavioral signs of arousal. Stimulating the ventral lateral thalamus did not produce these effects, showing specificity. The findings identify distributed brain signatures of consciousness that are orchestrated by particular thalamic nuclei.

Network control energy reductions under DMT relate to serotonin receptors, signal diversity, and subjective experience.

Communications biology April 18, 2025 S Parker Singleton, Christopher Timmermann, Andrea I Luppi et al. 7 citations

After DMT injection, the brain requires less control energy to transition between states compared to placebo, indicating a more flexible and less constrained brain dynamic. These energy changes track with EEG signal diversity and subjective intensity of the drug experience. The regional pattern of DMT's effects aligns with serotonin 2a receptor density, and a model using receptor distribution and pharmacokinetics can predict the drug's impact on brain energy trajectories.

Connectome harmonic decomposition tracks the presence of disconnected consciousness during ketamine-induced unresponsiveness.

British journal of anaesthesia April 1, 2025 Milan Van Maldegem, Jakub Vohryzek, Selen Atasoy et al. 3 citations

Ketamine, at anesthetic doses, produces a state where people are unresponsive yet often report vivid inner experiences, separating conscious awareness from behavioral responsiveness. Using connectome harmonic decomposition on fMRI data, researchers found that brain signals during ketamine-induced unresponsiveness show increased fine-grained spatial patterns, indicating higher neural granularity. This harmonic signature aligned with those of LSD-induced and ketamine-induced psychedelic states, but misaligned with signatures from unconscious individuals due to propofol sedation or brain injury. The method can track changes in conscious awareness even when behavior is absent, offering a tool for consciousness and anesthesia research.

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

A geometric deep learning model called graphTRIP predicts post-treatment depression severity from pretreatment clinical and brain imaging data. Trained on a clinical trial comparing psilocybin and escitalopram, it achieves strong predictive accuracy (r = 0.75) and generalizes to an independent dataset. The model links better outcomes to reduced functional coupling within serotonin systems and broader serotonergic integration with sensory-motor networks. Causal analysis shows a group-level advantage of psilocybin over escitalopram but identifies individuals with specific stress-related neuromodulatory profiles who may benefit more from escitalopram, advancing precision medicine and biomarker discovery in depression.