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Helmut Laufs

12 papers in the library · 1,359 citations · publishing 2013-2022

Papers

Increased Global Functional Connectivity Correlates with LSD-Induced Ego Dissolution.

Curr Biol April 13, 2016 Enzo Tagliazucchi, Leor Roseman, Mendel Kaelen et al. 531 citations

LSD, a potent serotonin-receptor agonist, increases global functional connectivity in the human brain, particularly in high-level association cortices and the thalamus, as shown by fMRI. These effects overlap with serotonin 2A receptor densities and correlate with subjective reports of ego dissolution. The drug also enhances communication between normally distinct brain networks, reducing the brain's modular and rich-club organization. This is the first modern human imaging study of LSD's acute effects on brain connectivity, demonstrating that LSD selectively expands global connectivity and blurs perceptual boundaries between self and environment.

Breakdown of long-range temporal dependence in default mode and attention networks during deep sleep

Proceedings of the National Academy of Sciences September 3, 2013 Enzo Tagliazucchi, Frederic von Wegner, Astrid Morzelewski et al. 278 citations

A conscious brain integrates information across segregated functional modules and also maintains long-term memory in its neural activity. This study examined temporal memory in blood oxygen level-dependent signals across the human nonrapid eye movement sleep cycle. Temporal dependence gradually decreased from wakefulness to deep nonrapid eye movement sleep, particularly in default mode and attention networks. Although spatial organization of spontaneous fluctuations remained nontrivial even during deep sleep, temporal complexity decreased in specific brain regions. These findings suggest that long-range temporal dependence may be a characteristic of the spontaneous conscious mentation that occurs during wakeful rest.

Large-scale signatures of unconsciousness are consistent with a departure from critical dynamics

Journal of The Royal Society Interface January 1, 2016 Enzo Tagliazucchi, Dante R. Chialvo, Michael Siniatchkin et al. 210 citations

Loss of consciousness from propofol sedation reduces long-range temporal correlations in frontothalamic brain activity and weakens the link between functional connectivity and anatomical structure. A model based on phase transitions in complex systems reproduces these patterns and also explains the cortex's reduced sensitivity to external stimuli during unconsciousness. The findings suggest that these neural changes are universal across different causes of unconsciousness.

Nonequilibrium brain dynamics as a signature of consciousness

Physical review. E July 28, 2021 Yonatan Sanz Perl, Hernan Bocaccio, Carla Pallavicini et al. 82 citations

Conscious wakefulness is characterized by brain dynamics far from thermodynamic equilibrium, while states of reduced consciousness—such as deep sleep and anesthesia induced by propofol, ketamine, or ketamine plus medetomidine—operate closer to equilibrium. This conclusion comes from analyzing electrocorticography data from nonhuman primates and functional magnetic resonance imaging data from humans. Entropy production and the curl of probability flux in phase space reliably distinguished conscious from unconscious states. The findings establish nonequilibrium macroscopic brain dynamics as a robust signature of consciousness and offer a statistical mechanics framework for studying cognition and awareness.

Modeling regional changes in dynamic stability during sleep and wakefulness

NeuroImage April 11, 2020 Ignacio Pérez Ipiña, Patricio Donnelly Kehoe, Morten L. Kringelbach et al. 81 citations

A semi-empirical model combining fMRI data, structural connectivity, and anatomically-informed priors shows that brain states during the wake-sleep cycle are better described by multiple dimensions rather than a single continuum. The best fit used priors based on functionally coherent networks, dividing the cortex into regions with opposite dynamics: frontoparietal regions approached a noise-driven bifurcation from fixed-point dynamics, while sensorimotor regions approached a bifurcation from oscillatory dynamics. Sleep onset involved subcortical deactivation with low correlation, reversed in deeper stages. Periodic forcing simulating external perturbations identified key regions for wakefulness recovery. The model characterizes sleep as having diminished perceptual gating but latent capacity for rapid arousal.

Unifying turbulent dynamics framework distinguishes different brain states

Communications Biology June 29, 2022 Anira Escrichs, Yonatan Sanz Perl, Carme Uribe et al. 67 citations

Different brain states—resting, meditating, deep sleep, and disorders of consciousness after coma—are underpinned by distinct spatiotemporal dynamics that can be characterized using turbulence theory. Non-conscious states tend to be more synchronous, while conscious states are more asynchronous, but the work goes beyond this simple dichotomy. A model-free analysis of human neuroimaging data applied Kuramoto's turbulence framework with coupled oscillators and measured information cascades across spatial scales. A complementary model-based approach used exhaustive computer simulations of whole-brain models fitted to those measures to study information encoding. The framework shows that turbulence theory provides excellent tools for describing and differentiating between brain states.

Signature of consciousness in brain-wide synchronization patterns of monkey and human fMRI signals

NeuroImage November 1, 2020 Gerald J. Hahn, Gorka Zamora‐lópez, Lynn Uhrig et al. 55 citations

Brain-wide signal levels can reliably distinguish sleep and anesthesia from the awake state in human and monkey fMRI resting state data. A whole-brain computational model reproduces changes in global synchronization, functional connectivity, structure-function relationship, integration, and segregation across vigilance states. The awake brain operates near a Hopf bifurcation, which coincides with globally correlated fMRI signals. Simulated lesions of connectivity hubs in the posterior brain and subcortical nuclei disrupt the model's awake state, matching predictions from graph-theoretical analyses of structural data.

Sleep Neuroimaging and Models of Consciousness

Frontiers in Psychology January 1, 2013 Enzo Tagliazucchi, Marion Behrens, Helmut Laufs 42 citations

Deep sleep, marked by reduced sensory activity and loss of conscious awareness, offers a natural setting for testing theories of consciousness. This review examines recent fMRI studies of spontaneous brain activity during sleep, linking findings to the global workspace theory, information integration theory, and the dynamical core hypothesis. The authors highlight a shift from studying evoked responses to resting-state activity and emphasize the need for dynamic analysis of functional interactions over time. They also stress the importance of experimentally verifying reduced or absent conscious content during the deepest sleep stages.

Unconsciousness reconfigures modular brain network dynamics

Chaos An Interdisciplinary Journal of Nonlinear Science September 1, 2021 Sofía Morena del Pozo, Helmut Laufs, Vincent Bonhomme et al. 13 citations

Consciousness is linked to brain regions that synchronize transiently in ways that are both integrated and differentiated. Using dynamic brain networks from fMRI data collected during deep sleep and propofol anesthesia, this study found that unconsciousness reduced the size and flexibility of the largest spatiotemporal module, identified as the dynamic core. These results support the dynamic core hypothesis of consciousness.

Low-dimensional organization of global brain states of reduced consciousness

bioRxiv Preprint Server September 28, 2022 Yonatan Sanz Perl, Carla Pallavicini, Juan Piccinini et al. preprint

Brain states are often described on a single scale from full consciousness to unconsciousness, but this ignores the complex, high-dimensional nature of brain activity. By combining whole-brain modeling, data augmentation, and deep learning, researchers mapped states of consciousness into a low-dimensional space where distances reflect similarities between states. They found an orderly trajectory from wakefulness to brain-injured patients, with coordinates related to functional modularity and structure-function coupling, both increasing as consciousness is lost. Model perturbations provided a geometric interpretation of state stability and reversibility. The work suggests conscious awareness depends on functional patterns encoded as a low-dimensional trajectory within the vast space of brain configurations.

Non-equilibrium brain dynamics as a signature of consciousness

arXiv Preprint Archive December 19, 2020 Yonatan Sanz Perl, Hernan Bocaccio, Ignacio Perez-Ipina et al.

Consciousness depends on brain activity that is far from thermodynamic equilibrium. Analyzing electrocorticography data from non-human primates during sleep and various anesthetics, and fMRI data from humans during deep sleep and propofol anesthesia, all states of reduced consciousness showed dynamics closer to equilibrium than conscious wakefulness. This was measured by entropy production and the curl of probability flux in phase space. Non-equilibrium macroscopic brain dynamics therefore serve as a robust signature of consciousness, offering a statistical mechanics approach to studying cognition and awareness.

Perturbations in dynamical models of whole-brain activity dissociate between the level and stability of consciousness

bioRxiv Preprint Server July 2, 2020 Yonatan Sanz Perl, Carla Pallavicini, Ignacio Pérez Ipiña et al. preprint

The level of consciousness—how conscious someone is—is often measured by how similar their brain activity is to normal wakefulness. However, this approach misses important information about how stable that state is. Using computer models of the whole brain, the authors show that the stability of a conscious state—how easily it can be disrupted—provides additional, complementary information. They propose a new framework that sorts brain states by both their similarity to wakefulness and their stability, which helps distinguish between different types of unconsciousness: natural sleep, anesthesia, and brain injury. This framework offers a more complete way to characterize and differentiate states of consciousness.