@article{pmid41072637,

title = {Altered electrophysiological meta-state dynamics in disorders of consciousness},

author = {Pablo Núñez and Prejaas Tewarie and Víctor Rodríguez-González and Naji L N Alnagger and Glenn J M van der Lande and Marie M Vitello and Paolo Cardone and Aurore Thibaut and Laouen Belloli and Steven Laureys and Jacobo D Sitt and Jitka Annen and Olivia Gosseries},

doi = {10.1016/j.neuroimage.2025.121519},

issn = {1095-9572},

year  = {2025},

date = {2025-12-01},

journal = {Neuroimage},

volume = {323},

pages = {121519},

abstract = {BACKGROUND: This multi-centric study aimed to explore differences in brain activity patterns in patients with disorders of consciousness (DoC), including unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS).nnMETHODS: Using high-density electroencephalographic (EEG) recordings from 368 DoC patients, 39 who emerged from MCS (eMCS), and 73 healthy controls, we examined instantaneous functional connectivity-based meta-states acting as attractors in a dynamical system, extracted by means of community detection algorithms and recurrence analysis. We analyzed data from two patient cohorts and included resting-state and auditory processing tasks in four frequency bands (delta, theta, alpha, beta) and from three perspectives, namely: (i) discrete activation of dominant states, (ii) a dynamical system composed of attractor states and (iii) the correlation and anticorrelation patterns of the active states.nnRESULTS: Findings revealed that while the overall structure of brain connectivity remained stable after injury, patients with DoC and those who emerged showed notable differences in the speed and consistency of how their brain states activated. Specifically, in higher frequencies, UWS patients exhibited faster, and less stable dynamics, shorter dwell times and decreased meta-state anticorrelation compared to those in MCS and eMCS. Moreover, a four-way combined learning classification analysis showed that the measures were able to distinguish the UWS and MCS subgroups.nnSIGNIFICANCE: These brain state dynamics could serve as valuable markers for assessing states of consciousness. Our results highlight the potential of using high-temporal resolution dynamic brain activity patterns to improve the understanding of altered consciousness and their application to clinical settings.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41218082,

title = {Individual trajectories for recovery of neocortical activity in disorders of consciousness},

author = {Prejaas K B Tewarie and Romesh Abeysuriya and Rajanikant Panda and Pablo Nùñez and Marie M Vitello and Glenn van der Lande and Olivia Gosseries and Aurore Thibaut and Steven Laureys and Gustavo Deco and Jitka Annen},

doi = {10.1371/journal.pcbi.1013659},

issn = {1553-7358},

year  = {2025},

date = {2025-11-01},

journal = {PLoS Comput Biol},

volume = {21},

number = {11},

pages = {e1013659},

abstract = {The evolution from disturbed brain activity to physiological brain rhythms can precede recovery in patients with disorders of consciousness (DoC). Accordingly, intriguing questions arise: What are the pathophysiological factors associated to disrupted brain rhythms in patients with DoC, and are there potential pathways for individual patients with DoC to return to normal brain rhythms? We addressed these questions at the individual subject level using biophysical simulations based on electroencephalography (EEG). The main findings are that unconscious patients exhibit a loss of excitatory corticothalamic synaptic strength. Synaptic plasticity in this excitatory corticothalamic circuitry facilitates the return of physiological brain rhythms, characterized by the reappearance of spectral peaks and flattening of the aperiodic (1/f) component of the power spectrum, in the selection of patients with DoC, particularly in those who are minimally conscious. The extent to which this occurred was correlated with cerebral glucose uptake. The current findings emphasize the importance of excitatory thalamocortical activity in reestablishing normal brain rhythms after brain injury and show that biophysical modelling of the corticothalamic circuitry could help select patients who might be potentially receptive to treatment and undergo plasticity.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41261994,

title = {A Virtual Clinical Trial of Psychedelics to Treat Patients With Disorders of Consciousness},

author = {Naji L N Alnagger and Paolo Cardone and Charlotte Martial and Yonatan Sanz Perl and Iván Mindlin and Jacobo D Sitt and Leor Roseman and Robin Carhart-Harris and David Nutt and Pablo Mallaroni and Natasha Mason and Johannes G Ramaekers and Vincent Bonhomme and Steven Laureys and Gustavo Deco and Olivia Gosseries and Pablo Núñez and Jitka Annen},

doi = {10.1002/advs.202511780},

issn = {2198-3844},

year  = {2025},

date = {2025-11-01},

journal = {Adv Sci (Weinh)},

pages = {e11780},

abstract = {Disorders of consciousness (DoC), including unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS), have limited treatment options and are characterized by low complexity of brain activity. Recent research suggests that psychedelic drugs, which enhance the complexity of brain activity, could offer promising therapies. Here, individualized whole-brain computational models are developed for patients with DoC, optimized with empirical functional magnetic resonance imaging data and diffusion-weighted imaging data, upon which the administration of lysergic acid diethylamide (LSD) and psilocybin is simulated. An in silico perturbation protocol is applied to assess brain dynamics, first distinguishing between different states of consciousness, including DoC, anesthesia, and the psychedelic state. Then, brain dynamics are assessed before and after a simulation of psychedelic drugs on patients with DoC. Findings indicated that the simulation of LSD and psilocybin shifted the brain activity of patients with DoC closer to criticality (the point at a phase transition between order and chaos), with a greater effect in patients in the MCS. In patients with UWS, the treatment response correlated with structural connectivity, while in patients in the MCS, it aligned with baseline functional connectivity. These results offer a computational foundation for using psychedelics in DoC treatment and highlight the potential future role of computational modeling in drug discovery and personalized medicine.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41285808,

title = {A shared central thalamus mechanism underlying diverse recoveries in disorders of consciousness},

author = {Haoran Zhang and Qianqian Ge and Xiao Liu and Yuanyuan Dang and Long Xu and Yutong Zhuang and Si Wu and Steven Laureys and Jianghong He and Shan Yu},

doi = {10.1038/s41467-025-65360-4},

issn = {2041-1723},

year  = {2025},

date = {2025-11-01},

journal = {Nat Commun},

volume = {16},

number = {1},

pages = {10400},

abstract = {Disorders of consciousness (DoC) encompass a range of states characterized by prolonged altered awareness due to heterogeneous brain damage and are associated with highly diverse prognoses. However, the neural mechanisms underlying such diverse recoveries in DoC remain unclear. To address this issue, we analyzed direct recordings from the central thalamus (CeTh), a key hub in arousal regulation, in a series of 23 DoC patients receiving deep brain stimulation treatment (CeTh-DBS). We identified a core set of electrophysiological features of the CeTh, particularly those of the theta rhythm. These features could account for individual recovery outcomes across highly varied etiologies (trauma, brainstem hemorrhage, and anoxia), and across clinical baselines and patient ages. CeTh activities also identified two subgroups of patients with recovery potential, including those with poor initial clinical manifestations but who eventually exhibited functional recovery. A biophysical model further revealed the neurodynamics of the theta rhythm in the CeTh across different brain states correlating with varying consciousness levels. These findings uncover a shared CeTh mechanism underlying diverse recoveries in DoC.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40857706,

title = {The Stuck Brain: Constrained Connectivity and Temporal Rigidity in Tinnitus},

author = {Marie Detroz and Steven Laureys and Audrey Maudoux},

doi = {10.1177/21580014251374571},

issn = {2158-0022},

year  = {2025},

date = {2025-09-01},

journal = {Brain Connect},

volume = {15},

number = {7},

pages = {278--279},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40253244,

title = {Characterization of responders to transcranial direct current stimulation in disorders of consciousness: A retrospective study of 8 clinical trials},

author = {Alice Barra and Rodrigo Huerta-Gutierrez and Jitka Annen and Geraldine Martens and Steven Laureys and Roberto Llorens and Tobias Kurth and Aurore Thibaut},

doi = {10.1016/j.neurot.2025.e00587},

issn = {1878-7479},

year  = {2025},

date = {2025-07-01},

journal = {Neurotherapeutics},

volume = {22},

number = {4},

pages = {e00587},

abstract = {The treatment for patients with disorders of consciousness challenges researchers and clinicians. The stimulation of the left dorsolateral prefrontal cortex with transcranial direct current stimulation (tDCS) may enhance behavioral responsiveness of a subset of patients in a minimally conscious state, while having limited effects in unresponsive patients. However, heterogeneity in responses raises questions about the effectiveness of tDCS. Our objective was to explore the characteristics of responders to tDCS based on previously published RCTs and investigate the heterogeneity of treatment effect to better direct future tDCS studies towards patient profiles that appear to be more responsive to the treatment. We explored clinical and demographical differences between responders (i.e., recovery of a new sign of consciousness after active stimulation) and non-responder and the predictors of treatment response with a LASSO logistic regression. We included 131 patients (44 women, 61 traumatic brain injury, 90 minimally conscious, mean age 46.13 years [SD ​= ​16], median time since injury 12.84 months [IQR: 5.25-35.10]) of which 33 responded to tDCS. While 32 ​% of minimally conscious patients responded to tDCS (95%CI 0.24, 0.43), 10 ​% (95%CI 0.04, 0.25) of those unresponsive responded. The regression model, using diagnosis at baseline, Coma Recovery Scale-Revised Index at baseline, age, sex and time since injury correctly discriminated between tDCS responders and non-responders (area under the curve of 0.77). Our findings suggest that patients in minimally conscious state, with a better cognitive profile and longer TSI respond better to tDCS, making them better candidates for the treatment.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40736881,

title = {Characterizing consciousness states: EEG microstate dynamics in patients with disorders of consciousness during naturalistic movie-viewing},

author = {Xiyuan Lei and Anqi Wang and Kexu Zhang and Siyang Liu and Ying Zhao and Steven Laureys and Shanbao Tong and Haibo Di and Nantu Hu and Xiaoli Guo},

doi = {10.1007/s11517-025-03415-w},

issn = {1741-0444},

year  = {2025},

date = {2025-07-01},

journal = {Med Biol Eng Comput},

abstract = {Consciousness assessment in disorders of consciousness (DoC) patients remains clinically challenging. Dynamic brain activities responsive to sensory stimulations have been suggested to contain consciousness-related information. However, primary sensory processing can occur unconsciously, necessitating evaluation of residual higher-order cognitive functions for effective assessment. In this study, we introduced a movie-viewing paradigm incorporating a scrambled version to control for primary sensory processing and applied electroencephalography (EEG) microstate analysis to capture higher-order neural dynamics. By comparing 23 DoC patients with 23 healthy individuals and 12 conscious brain-injured patients, we found significant abnormalities in microstate D in DoC patients. Healthy individuals and conscious brain-injured patients showed enhanced D-related parameters during intact movie-viewing compared to the scrambled condition. Conversely, DoC patients displayed a significant decrease in Duration, Coverage, Occurrence, and Transition Probabilities of microstate D during intact movie-viewing. Additionally, K-nearest neighbors classifier showed that the differences in microstate features between the intact and scrambled movie-viewing yielded the best classification outcome (AUC = 0.83), in which microstate D parameters serve as the most important features. Our results suggested that EEG microstates during naturalistic movie-viewing, especially microstate D, have the potential to serve as a novel, objective indicator for characterizing and diagnosing the state of consciousness.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40434895,

title = {Revisiting the Multilayer Network Framework for Electrophysiological Networks},

author = {Prejaas K B Tewarie and Steven Laureys and Rikkert Hindriks},

doi = {10.1089/brain.2025.0010},

issn = {2158-0022},

year  = {2025},

date = {2025-06-01},

journal = {Brain Connect},

volume = {15},

number = {5},

pages = {189--194},

abstract = { The multilayer network framework has emerged as an innovative approach for analyzing electrophysiological networks, providing insights into complex neuronal interactions by integrating connectivity across different frequency bands in electroencephalography (EEG) and magnetoencephalography (MEG) data.  Traditionally, multilayer networks have treated canonical frequency bands (e.g., delta, theta, alpha, beta, gamma) as distinct layers. Recent findings could raise potential concerns regarding this approach, emphasizing the need to incorporate the distinction between periodic (oscillatory) and aperiodic (broadband) signal components.  Aperiodic signals may reflect excitation-inhibition balance and scale-free dynamics, while periodic signals capture oscillatory rhythms, both contributing uniquely to brain network interactions. A multilayer network framework in the current context could be applicable in the case of genuine coupling between these components, termed "aperiodic-to-periodic coupling." This necessitates novel connectivity metrics and analytical methods that can handle broadband data. Furthermore, challenges remain in decomposing these components in the time domain and developing robust metrics for broadband connectivity that account for signal leakage.  Addressing these issues will enhance multilayer frameworks, enabling better insights into brain network integrity, cognitive dysfunction, and neurological conditions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}