Yonatan Sanz Perl

This study shows serotonergic psychedelics like LSD and DMT delay resting state neurovascular coupling, affecting hemodynamic delays and functional connectivity in brain regions with serotonin receptors.

This study links receptor profiles and cortical excitability to acute and long-term stroke outcomes using patient-specific whole-brain models.

This study introduces vorticity-based metrics to analyze brain dynamics during DMT experiences, finding increased rotational organization and spatial heterogeneity associated with subjective intensity changes.

This study shows that brain dynamics change with the duration of oral contraceptive use, with prolonged use linked to restricted local synchronization and enhanced cross-scale information flow.

This study examines brain dynamics during unusual bodily experiences and out-of-body experiences, finding reduced neural hierarchy and increased EEG complexity.

This paper introduces a non-invasive framework linking consciousness measures to non-equilibrium thermodynamics by analyzing FDT violations in humans and rodents across different states of consciousness.

This paper introduces a homeostatic inhibitory plasticity rule into a biophysical model to study how local adaptive processes influence global brain dynamics.

This study compares how psilocybin and escitalopram affect brain reconfiguration in MDD patients using whole-brain models and perturbation analysis.

This study compares brain responses to psilocybin and escitalopram in depression using the Fluctuation-Dissipation Theorem, finding distinct non-equilibrium dynamics and responder differentiation.

This study shows that cognitive co-activation dominates fMRI synchrony in the awake brain but is replaced by anatomical and molecular constraints during consciousness perturbations.

This paper investigates how and when brain stimulation drives state transitions by analyzing subject-specific whole-brain models of neural dynamics.

The paper uses computational whole-brain models to show that perilesional excitability predicts long-term motor recovery after stroke, but not acute impairment.

This paper introduces a whole-brain model of turbulent vortices to understand cognition by analyzing neuroimaging data and showing its ability to distinguish cognitive states and tasks.

The paper introduces FDTest, a method to detect memory effects in brain dynamics by violating the Fluctuation-Dissipation Theorem, showing stronger memory in wakefulness than sleep.

This study uses a thermodynamics-inspired framework to model brain dynamics across menstrual cycle phases, finding that model-based biomarkers outperform hormonal and traditional connectivity measures in phase prediction.

This study uses computational models to simulate psychedelic treatments for disorders of consciousness, finding they shift brains closer to criticality, with varying effects based on patient state.

The Turbulent Brain toolbox applies turbulence physics to analyze brain activity dynamics, showing reduced information transmission during movie watching compared to resting state.

The paper uses a whole-brain model of an anesthetized macaque to simulate and restore consciousness through thalamic stimulation, showing how brain states transition during loss and recovery of consciousness.

This study investigates the reconfiguration of brain hierarchy in schizophrenia using resting-state fMRI and finds increased hierarchical organization linked to clinical symptoms and diagnostic separation.

This study investigates quantum-like dynamics in the human brain using coupled oscillators and finds that the QL regime provides the best whole-brain model fit to neuroimaging data with lower energy consumption.

This paper identifies disrupted hierarchical organization in disorders of consciousness using fluctuation-dissipation theorem deviations from fMRI data.

The paper uses whole-brain modeling to analyze brain dynamics during advanced meditation states, finding increased functional integration and near-critical dynamics in later states associated with minimal phenomenal experience.

This study analyzes EEG microstate dynamics in disorders of consciousness to identify differences in brain activity patterns between patients and healthy controls.

This study develops a personalized fMRI analysis pipeline for disorders of consciousness, identifying connectivity and local parameters as biomarkers for diagnosis and prognosis.

Inception simulates long-term recovery in Disorders of Consciousness using whole-brain models and fMRI data, showing improved patient classification and potential for capturing pharmacological effects.

This paper applies whole-brain models to study state transitions in depression following psilocybin and escitalopram treatments, showing differential effects on susceptibility and drivability to healthier states.

The paper examines how dimensionality reduction techniques preserve synergistic interactions in brain dynamics using resting-state fMRI data from 100 healthy participants.

This paper quantifies the energy cost of non-equilibrium brain computation using a new framework, showing the human brain is more energy-efficient than other mammals and cognitive tasks vary in their energy demands.

The paper investigates how non-equilibrium dynamics in the brain relate to complexity in response to stimuli, finding reduced asymmetry and irreversibility in states of reduced consciousness.

The paper introduces a whole-brain model called NEMO that uses neurotransmitter maps to simulate brain dynamics and shows it correlates with behavioral performance and intelligence.