bioRxiv
December 17, 2024
Dian Lyu, Ram Adapa, Robin Carhart-Harris et al.
preprint
The default mode network (DMN) and frontoparietal control network (FPCN), typically anticorrelated at rest in healthy brains, show continuous rather than absolute anatomical boundaries in the posterior precuneus. Connectivity differences along the dorsal-ventral axis follow linear slopes, forming functional gradients that exist only within each network's territory. These gradients flatten in altered states of consciousness (ASC), with the gradient magnitude similarly impaired across different ASC types, while spatial entropy differs between psychedelic and sedative states. The findings suggest the DMN and FPCN, though appearing distinct, may originate from a single integrated mechanism, and the loss of functional differentiation between them characterizes altered conscious states.
bioRxiv Preprint Server
October 20, 2024
Peter Coppola, Adrian M. Owen, David K. Menon et al.
preprint
A new method captures the brain dynamics unique to each person's subjective experience. Using fMRI while people listened to a story awake and under different levels of anaesthesia, the approach tracks moment-to-moment changes in functional connectivity without assuming common brain states across individuals. The default mode network's dynamics were more dissimilar between conscious participants, reflecting personal engagement with the story. In contrast, the auditory and posterior dorsal attention networks showed higher similarity across conscious individuals, supporting more generalizable experiences. Conscious brain dynamics were more complex for individual-specific patterns but less complex for shared patterns.
bioRxiv Preprint Server
April 12, 2021
Peter Coppola, Lennart R.b. Spindler, Andrea I. Luppi et al.
preprint
The diversity of brain dynamics within small-world network topology, measured as sample entropy (dSW-E), consistently predicts levels of awareness across sedation and disorders of consciousness, even after accounting for underlying functional connectivity dynamics. Both subcortical and cortical areas show predictive value, but subcortical regions exhibit higher and more robust effect sizes. The dynamic reorganization of the functional information architecture, especially in the subcortex, emerges with awareness and offers explanatory power beyond the complexity of dynamic functional connectivity alone.
bioRxiv Preprint Server
June 12, 2026
Dante Sebastián Galván Rial, Gabriel A. Della Bella, Lorina Naci et al.
preprint
States of consciousness can be ordered along a single dimension defined by the entropy of spontaneous neural activity, as proposed by the Entropic Brain Theory. Applying the same analytical pipeline to pharmacological (psychedelics, modafinil, propofol anaesthesia) and clinical (schizophrenia) fMRI datasets, the temporal irregularity of brain network topology was quantified. Propofol anaesthesia occupied the low-entropy end; psychedelic states and schizophrenia occupied the high end. This ordering tracks combined modulations of the level and content of consciousness, from reduced awareness under anaesthesia to heightened arousal and expanded experience under psychedelics and disorganised processing in schizophrenia. The result was not reducible to fluctuations in mean functional connectivity and was supported by convergent reorganisation of higher-order association cortex.
bioRxiv Preprint Server
June 7, 2026
Andrea I. Luppi, Dragana Manasova, Justine Y. Hansen et al.
preprint
Functional connectivity in the awake human brain is shaped primarily by cognitive co-activation—the tendency of brain regions to work together during mental tasks—more than by structural or molecular constraints. This predominance is systematically lost across five datasets involving pharmacological and pathological perturbations of consciousness (chronic disorders of consciousness; anesthesia with sevoflurane, propofol, or ketamine), when cognition is disconnected from the environment or abolished. During such states, the predictors of functional architecture shift away from cognitive co-activation and toward anatomical and molecular constraints.
Brain Communications
January 1, 2026
Dorottya Szocs, Dian Lyu, Andrea I. Luppi et al.
The pulvinar nucleus of the thalamus shows the strongest functional connectivity change with loss of consciousness under anesthesia in healthy volunteers, while the ventral-latero-ventral nucleus shows the strongest change in patients with disorders of consciousness. These nuclei exhibit distinct connectivity patterns with higher-order brain networks such as the default mode and executive control networks. In patients, the neural connectivity biomarker mirrored behavioral changes, suggesting potential clinical relevance for targeted deep brain stimulation therapy.
Neuroimage
February 11, 2023
Andrea I. Luppi, Pedro A. M. Mediano, Fernando E. Rosas et al.
High-level brain functions are thought to arise from coordinated activity across neural systems, but this has been hard to test empirically. Using a framework called Integrated Information Decomposition, which quantifies emergence in dynamical systems, the authors analyzed functional MRI data and found that emergent and hierarchical neural dynamics are significantly reduced in chronically unresponsive patients with severe brain injury. Emergence capacity was positively correlated with hierarchical organization in brain activity. Combining network control theory and whole-brain modeling, the authors show that reduced emergent and hierarchical dynamics in these patients can be explained by disruptions in the structural connectome. The results suggest that chronic unresponsiveness after severe brain injury may stem from structural damage to neural infrastructure needed for emergent brain dynamics.
Communications Biology
November 3, 2022
Peter Coppola, Judith Allanson, Lorina Naci et al.
Consciousness is associated with short-term brain connectivity transitions that are less predictable, quicker, but on average more constant than those in unconscious states. By combining modern consciousness theories with phenomenology and dynamical systems theory, the authors created an individual-specific landscape of brain connectivity dynamics as a proxy for the stream of consciousness. They found that temporally-specific connectivity states are less easily describable by network patterns distant in time, suggesting a richer space of possible states. The cortex, cerebellum, and subcortex all display consciousness-relevant dynamics.
Communications Biology
September 8, 2022
Angeliki Zarkali, Andrea I. Luppi, Emmanuel A. Stamatakis et al.
People with Parkinson's disease who experience hallucinations spend more time in a brain state where regions are functionally segregated from one another and make fewer transitions between brain states. The shift from an integrated to a segregated state requires less energy in those who hallucinate, making that state potentially preferable. The regional energy needed for this transition correlates with neurotransmitter density and gene expression for serotoninergic, GABAergic, noradrenergic, and cholinergic receptors, but not dopaminergic receptors. The findings suggest that neurochemistry and brain structure together shape the dynamic brain states that underlie hallucinations.
Dian Lu, Adapa Ram, Robin Carhart-Harris et al.
The posterior precuneus, a key hub of the default mode network, sits at the boundary with the frontoparietal control network. Using a spatial-derivative approach across five pharmacological datasets including psychedelic and anaesthetic states, the authors show that measuring how functional connectivity changes along the precuneus's dorsal–ventral axis reveals the organization of these networks with greater anatomical specificity than connectivity alone. This functional gradient is systematically altered by consciousness level: its overall magnitude diminishes across all altered states of consciousness, while its spatial entropy increases under psychedelics but decreases under sedation. The findings suggest the precuneus embeds a continuous, anatomically constrained transition between large-scale networks sensitive to global brain-state dynamics.