PLoS computational biology
June 6, 2025
Wiep Stikvoort, Eider Pérez-Ordoyo, Iván Mindlin et al.
3 citations
A person's level of consciousness can be assessed by how the brain reacts to stimulation, but this study shows that the brain's unperturbed activity already contains that information. Using personalized whole-brain models fitted to resting-state fMRI data from people in altered states of consciousness (deep sleep, disorders of consciousness), the researchers measured the brain's out-of-equilibrium dynamics—specifically, the asymmetry of effective connections and time irreversibility. They found that states with lower arousal or awareness had less asymmetric connectivity, less irreversibility, and lower complexity in simulated responses compared to controls. The asymmetry in connections drives the nonequilibrium state and, in turn, the differences in complexity.
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 (Cold Spring Harbor Laboratory)
July 1, 2026
Fernando Lehue, Iván Mindlin, Carlos Coronel-Oliveros et al.
Disorders of consciousness are linked to large-scale changes in brain dynamics, but the structural factors behind these changes are unclear. Using a whole-brain computational model constrained by diffusion MRI-derived connectivity, the authors show that a node's integration within the structural connectome, measured by a spectral integration metric, strongly predicts its impact on global brain dynamics. Lesions to highly integrative hubs, especially in posterior medial regions like the precuneus and posterior cingulate cortex, drive the system toward low-complexity dynamical regimes resembling disorders of consciousness. Increasing excitability in these regions restores healthy-like dynamics in silico. Perturbations to weakly integrated regions have limited global effects, explaining why damage to specific hubs disproportionately disrupts conscious brain activity.
bioRxiv (Cold Spring Harbor Laboratory)
January 13, 2026
Iván Mindlin, Carlos Coronel-Oliveros, Jacobo Sitt et al.
A biologically grounded inhibitory homeostatic plasticity rule embedded into the Dynamic Mean Field (DMF) model creates a Homeostatic Dynamic Mean Field (HDMF) model that dynamically tunes local excitation-inhibition balance. The HDMF reproduces statistical observables of brain activity as well as the original DMF, can sustain neuromodulatory perturbations without overhead computations, and generates unprecedented sleep-like slow-wave activity that can coexist with wake-like asynchronous dynamics, permitting modeling of dissociated states of consciousness such as parasomnias. A single homeostatic rule broadens the stability and expressiveness of the DMF, providing a unified platform for studying how local adaptive processes shape the diverse global dynamics of the human brain.