Cortex; a journal devoted to the study of the nervous system and behavior
September 1, 2021
Santiago Alcaide, Jacobo Sitt, Tomoyasu Horikawa et al.
13 citations
Waking up from early sleep involves a two-stage brain process. First, subcortical and sensorimotor structures activate before most cortical regions, followed by rapid whole-brain activation, with frontal regions engaging slightly later. A second, slower stage may then occur, where cortical regions activate before subcortical structures and the cerebellum. This pattern suggests subcortical structures play a key role in initiating and maintaining conscious states.
PNAS nexus
December 1, 2024
Emilia Fló, Laouen Belloli, Álvaro Cabana et al.
10 citations
Directing attention toward the body's internal signals (interoception) versus external sounds (exteroception) produces distinct brain activity patterns. Exteroceptive attention flattened overall brain wave power, while interoceptive attention reduced brain signal complexity, increased frontal connectivity and theta oscillations, and modulated the heartbeat-evoked potential (HEP). Classifiers using HEP features correctly identified the attentional state in 17 of 20 healthy participants; power spectral density features classified all 20. In five brain-injured patients, one with unresponsive wakefulness syndrome and one with locked-in syndrome showed willful modulation of the HEP, suggesting they could follow commands. These findings highlight how attention shapes sensory processing and may aid diagnosis in 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.
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.
bioRxiv Preprint Server
April 22, 2026
Nicolás Bruno, Federico Cavanna, Federico Zamberlan et al.
preprint
Spontaneous thoughts make up most of everyday inner experience, but studying them is difficult because traditional methods disrupt the natural flow of thinking or introduce motor artifacts. An alternative approach combined delayed verbal retrospective free reports with automated ratings from large language models. Twenty-two participants performed an eyes-closed free-thinking task, and their reports were evaluated on ten dimensions by four LLMs and human raters. Machine-learning models trained on EEG features achieved above-chance accuracy for predicting emotional valence. LLMs showed higher inter-rater agreement than humans, supporting their use for scalable annotation and suggesting that affective dimensions of spontaneous thoughts can be decoded from brain activity.
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.
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.