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Jitka Annen

Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium.

13 papers in the library · 233 citations · publishing 2016-2025

Papers

Quantifying arousal and awareness in altered states of consciousness using interpretable deep learning

Nature Communications February 25, 2022 Minji Lee, Leandro Sanz, Alice Barra et al. 120 citations

A deep-learning-based explainable consciousness indicator (ECI) uses EEG responses to transcranial magnetic stimulation and resting-state EEG to separately quantify arousal and awareness. Tested during sleep (n=6), general anesthesia (n=16), and severe brain injury (n=34), ECI distinguishes states such as ketamine-induced anesthesia and rapid eye movement sleep, which combine low arousal with high awareness. Parietal brain regions are most relevant for these measurements. The indicator offers a way to disentangle the two components of consciousness across physiological, pharmacological, and pathological conditions.

A systematic analysis of distressing near-death experience accounts

Memory June 12, 2019 Héléna Cassol, Charlotte Martial, Jitka Annen et al. 60 citations

Near-death experiences (NDEs) are typically positive, but about 14% of 123 NDE accounts were distressing. These distressing NDEs included inverse, hellish, or void types, with inverse and hellish each appearing 8 times and void once. A higher proportion of suicide survivors reported distressing NDEs compared to classical ones. Memories of distressing NDEs were as phenomenologically detailed as those of classical NDEs. The findings suggest distressing NDEs require careful attention to help experiencers integrate them into their identity.

Changes in high-order interaction measures of synergy and redundancy during non-ordinary states of consciousness induced by meditation, hypnosis, and auto-induced cognitive trance.

NeuroImage June 1, 2024 Pradeep Kumar G, Rajanikant Panda, Kanishka Sharma et al. 20 citations

High-order interactions between brain regions, measured as synergistic and redundant information, change differently across three non-ordinary states of consciousness. During Rajyoga meditation, synergy increased across the whole brain in delta and theta brainwave bands, while redundancy decreased in frontal, central, and posterior electrodes in delta and beta bands. During hypnosis, synergy decreased in mid-frontal, temporal, and mid-centro-parietal electrodes in the delta band, and in left frontal and right parietal electrodes in the beta2 band. During auto-induced cognitive trance, synergy decreased in delta and theta bands in left-frontal, right-frontocentral, and posterior electrodes, and at the whole brain level in the alpha band. Redundancy changes during hypnosis and auto-induced cognitive trance were not significant. Subjective reports of absorption, dissociation, and mystical experience did not correlate with the high-order measures.

Mapping the functional brain state of a world champion freediver in static dry apnea

Brain Structure and Function January 1, 2021 Jitka Annen, Rajanikant Panda, Charlotte Martial et al. 15 citations

A world champion free diver's brain activity and connectivity shift markedly during a 6.5-minute breath-hold. EEG shows increased alpha wave power and connectivity, with decreased delta band connectivity. fMRI reveals heightened connectivity within the default mode network and visual areas, but reduced connectivity in sensorimotor cortices. These changes overlap with some meditation-related brain signatures but also include unique features suggesting altered somatosensory integration. Self-reports indicate that elite free divers may achieve a state of sensory dissociation during prolonged apnea, reflecting their ability to adapt psychologically and physiologically to extreme breath-holding.

Phenomenology of auto-induced cognitive trance using text mining: a prospective and exploratory group study.

Neuroscience of consciousness January 1, 2024 Audrey Vanhaudenhuyse, Marie-Carmen Castillo, Charlotte Martial et al. 7 citations

Auto-induced cognitive trance (AICT) produces richer and more distinct subjective experiences than ordinary rest, auditory stimulation, or imagination. In 27 trained participants, free recalls of experiences were longer during AICT than in other conditions. Text mining identified four distinct classes of discourse, with AICT forming its own class clearly separate from ordinary conscious states. Nine content categories emerged, including nature, animals, body modifications, and difficulty describing thoughts. AICT was specifically characterized by reports of nature, animals, body modifications, and difficulty describing thoughts. These findings indicate that AICT generates a unique and richer phenomenology compared to other conscious states.

Characterization of responders to transcranial direct current stimulation in disorders of consciousness: A retrospective study of 8 clinical trials.

Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics April 18, 2025 Alice Barra, Rodrigo Huerta-Gutierrez, Jitka Annen et al. 3 citations

A subset of patients in a minimally conscious state show improved behavioral responsiveness after transcranial direct current stimulation (tDCS) of the left dorsolateral prefrontal cortex, while those who are unresponsive show limited benefit. Among 131 patients, 32% of minimally conscious patients responded to tDCS, compared to 10% of unresponsive patients. A regression model using baseline diagnosis, Coma Recovery Scale-Revised Index, age, sex, and time since injury correctly identified responders 77% of the time. Patients in a minimally conscious state with better cognitive profiles and longer time since injury appear to respond better to tDCS, suggesting they are better candidates for this treatment.

A virtual clinical trial of psychedelics to treat patients with disorders of consciousness

bioRxiv (Cold Spring Harbor Laboratory) August 19, 2024 Naji Alnagger, Paolo Cardone, Charlotte Martial et al. 3 citations preprint

Disorders of consciousness, such as unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS), have few treatments. Using whole-brain computational models built from individual patients' fMRI and diffusion-weighted imaging data, this virtual clinical trial simulated the effects of LSD and psilocybin. The psychedelics shifted the brains of patients with disorders of consciousness closer to a critical dynamical state, with a larger effect in MCS patients. In UWS patients, the treatment response depended on structural connectivity, whereas in MCS patients it aligned with baseline functional connectivity. These results provide a computational foundation for considering psychedelics in treating disorders of consciousness and highlight the role of computational modeling in drug discovery and personalized medicine.

A Virtual Clinical Trial of Psychedelics to Treat Patients With Disorders of Consciousness

Advanced Science November 20, 2025 Paolo Cardone, Charlotte Martial, Yonatan Sanz Perl et al. 2 citations

Simulated administration of LSD and psilocybin in computational models of patients with disorders of consciousness (DoC), including unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS), shifted brain activity closer to criticality—the phase transition between order and chaos. The effect was greater in MCS patients. In UWS patients, the treatment response correlated with structural connectivity, while in MCS patients it aligned with baseline functional connectivity. These results provide a computational foundation for using psychedelics in DoC treatment and highlight the potential role of computational modeling in drug discovery and personalized medicine.

Personalized stimulation therapies for disorders of consciousness: a computational approach to inducing healthy-like brain activity based on neural field theory.

Journal of neural engineering June 10, 2025 Daniel Polyakov, P A Robinson, Eli J Müller et al. 2 citations

A computational method uses a simplified brain model fitted to a patient's EEG power spectrum to design personalized electrical stimulation signals. In computer simulations, these signals induce healthy-like brain activity patterns in models of people with disorders of consciousness. When the model's parameters were near a stability boundary, stimulation caused a lasting change in activity beyond the stimulation period. The approach may activate plasticity mechanisms during long-term treatment, potentially leading to sustained improvements. Further clinical adjustments and validation are needed, but the method holds promise for improving therapeutic outcomes in disorders of consciousness and may extend to other neurological conditions.

Exploring Mystical-Type Experiences Through Auto-Induced Cognitive Trance.

The International journal of clinical and experimental hypnosis January 1, 2025 Aminata Bicego, Naji Alnagger, Etzel Cardeña et al. 1 citation

Auto-induced cognitive trance (AICT) can produce mystical-type experiences in healthy individuals, with 29% of participants reporting such experiences during AICT compared to none during a rest condition. The study examined twenty-seven people who could self-induce AICT, measuring their religious and spiritual practices and paranormal beliefs beforehand. Participants completed five conditions including rest, imagination, and AICT with or without auditory stimulation. The intensity of the AICT experience and features resembling near-death experiences were linked to mystical-type experiences only during AICT. This is the first demonstration that AICT, a technique distinct from hypnosis or meditation, can induce mystical-type experiences outside life-threatening situations.

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.

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.

Mapping the functional connectome traits of levels of consciousness

arXiv Preprint Archive May 10, 2016 Enrico Amico, Daniele Marinazzo, Carol DiPerri et al.

A new data-driven method, connICA, extracts independent functional connectivity patterns (FC-traits) from brain scans of patients with disorders of consciousness after severe brain damage. Three main FC-traits emerged. The first relates to sedation, overall pathology, and level of arousal. The second reflects disconnection of visual and sensory-motor networks, time since injury, and ability to communicate. The third involves fronto-parietal and default-mode networks and interhemispheric interaction, associated with self-awareness and awareness of surroundings. Each trait represents a distinct functional process linked to degradation of conscious states, clarifying which neural subcircuits are disrupted in severe brain injury.