Andrea I. Luppi

This study examines brain dynamics and structural connectivity in individuals with heavy alcohol use using multimodal imaging and finds reduced brain complexity and increased control energy.

This study shows that general anaesthesia reduces the uniqueness of human brain connectivity both between individuals and across species.

This paper uses Bayesian methods to analyze heart rate dynamics during psychedelic experiences, finding increased entropy and variability linked to subjective and neural effects.

The paper investigates how consciousness states affect brain structure-function organisation using anaesthesia and deep brain stimulation in non-human primates.

The paper evaluates 576 functional connectomics pipelines to identify those that minimize spurious discrepancies and motion confounds while being sensitive to inter-subject and experimental effects.

This paper introduces CSER, a new complexity estimator for neural signals that overcomes limitations of LZ by providing spectral decomposition and higher temporal resolution, revealing gamma band dominance and early entropy changes in consciousness states.

The paper investigates how brain network structure, neuromodulation, and disease influence transitions between cognitive activation patterns using multimodal neuroimaging data.

This study quantifies neural emergence in brain injury patients using functional MRI and shows reduced emergent dynamics correlate with structural connectome disruptions.

The paper identifies harmonic patterns of structure-function dependence in the human connectome that correlate with different states of consciousness.

This paper shows that LSD and psilocybin reduce brain control energy and increase entropy by flattening the brain's energy landscape, using network control theory and PET data.

The paper examines dynamic brain state transitions in Parkinson's disease patients with visual hallucinations, finding altered temporal dynamics and links to neurotransmitter systems.

This study maps how pharmacological drugs alter brain function by linking neurotransmitter receptor distribution with drug-induced changes in functional MRI connectivity.

The paper evaluates phase-based dynamic functional connectivity metrics in resting-state fMRI to identify reliable and interpretable measures of brain dynamics and their relationships.

The paper introduces an information decomposition framework to identify synergistic and redundant neural interactions, showing synergistic activity underlies human complex cognition and evolutionary brain expansion.

The paper introduces FastDMF, a computationally efficient implementation of the Dynamic Mean Field model, enabling simulations of whole-brain dynamics with significantly faster performance and reduced memory usage.

This study investigates how small world topology dynamics scale with decreasing levels of awareness, finding that subcortical areas show higher predictive power for awareness levels.

This study evaluates how different data-processing pipelines affect the reproducibility of brain network topologies across repeated scans, identifying reliable pipeline combinations.

This study identifies common neural mechanisms underlying anaesthesia and disorders of consciousness by simulating brain dynamics with a whole-brain model incorporating GABA receptor density and structural connectomes.

The paper shows that inhibitory plasticity rules shape receptive fields by modulating the correlation between excitatory and inhibitory inputs, allowing context-dependent changes in neuronal responses.

The paper investigates algorithmic and process complexity measures in functional MRI data from propofol sedation, showing they correlate with sedation levels and support a complexity-based hypothesis of consciousness.