Abstract Background Electroencephalographic (EEG) potentials evoked by transcranial magnetic stimulation (TMS) offer a direct window into cortical dynamics. Yet, a systematic exploration of their morphological features, analogous to sensory-evoked potentials, is lacking, especially for stimulation outside the motor cortex. Aim To obtain region-specific properties of frontal, parietal and occipital networks from the time course of TMS-evoked potentials (TEPs). Materials and Methods We implemented and applied an automatic procedure to compute peak-to-peak amplitude, peak latency, and inter-peak interval of TEPs recorded from 40 neurotypical subjects stimulated over left occipital (n=25), parietal (n=25), and frontal (n=25) cortices. Results Occipital TEPs showed the largest peak-to-peak amplitude and longest latency of the first waveform component, independently of stimulation intensity and consistent with the recruitment of a large patch of densely interconnected neurons. Concerning later components, both latency and inter-peak interval systematically decreased along the posterior-to-anterior axis, reflecting progressively faster recurrent dynamics from the alpha-dominated occipital circuitry to the tightly coupled loops between frontal cortex and subcortical structures. Parietal TEPs showed intermediate amplitude and latency measures, consistent with the heterogeneous cytoarchitectonic and connectional organization of the superior parietal cortex. Conclusions Our findings suggest that TEP morphology is shaped by the distinct properties of the stimulated networks, with early amplitude reflecting the extent of local recruitment and later temporal features tracking the rhythm of recurrent activity. This work offers a mechanistically grounded and practically accessible approach, also released as a Python-based tool, that allows to characterize cortical reactivity across different brain-states and populations.

The simulation of whole-brain dynamics should reproduce realistic spontaneous and evoked neural activity across different scales, including emergent rhythms, spatio-temporal activation patterns, and macroscale complexity. Once a mathematical model is selected, its configuration must be determined by properly setting its parameters. A critical preliminary step in this process is defining an appropriate set of observables to guide the selection of model configurations (parameter tuning), laying the groundwork for quantitative calibration of accurate whole-brain models. Here, we address this challenge by presenting a framework that integrates two complementary tools: The Virtual Brain (TVB) platform for simulating whole-brain dynamics, and the Collaborative Brain Wave Analysis Pipeline (Cobrawap) for analyzing simulation outputs using a set of standardized metrics. We apply this framework to a 998-node human connectome, using two configurations of the Larter-Breakspear neural mass model: one with the TVB default parameters, the other tuned using Cobrawap. The results reveal that the tuned configuration exhibits several biologically relevant features, absent in the default model for both spontaneous and evoked dynamics. In response to external perturbations, the tuned model generates non-stereotyped, complex spatio-temporal activity, as measured by the perturbational complexity index. In spontaneous activity, it exhibits robust alpha-band oscillations, infra-slow rhythms, scale-free characteristics, greater spatio-temporal heterogeneity, and asymmetric functional connectivity. This work demonstrates how combining TVB and Cobrawap can guide parameter tuning and lays the groundwork for data-driven calibration and validation of accurate whole-brain models.

Slow waves (SWs), the hallmark of non-rapid eye movement (NREM) sleep, reflect the periodic occurrence of transient silent periods in cortical neurons (Down states). During NREM, SWs and Down states physiologically disrupt large-scale network interactions. Since early EEG studies, SWs have also been observed in awake patients after brain injury. Emerging evidence indicates that these intrusions of sleep-like activity interfere with ongoing network activity and contribute to motor and cognitive deficits; yet, the mechanisms governing the generation and spread of post-lesional SWs remain unclear. Here, we extend a neural mass model of EEG to capture transitions between wake-like and sleep-like dynamics and embed it in connectome-based networks with virtual lesions. This model supports that local disfacilitation, topology-dependent propagation, and synchrony-dependent amplification throughout the connectome are sufficient to produce post-lesional SWs. These mechanisms reproduce the spatial gradients of post-lesional SWs previously reported in patient studies, and identify actionable targets for neuromodulation and rehabilitation.

The quest for reliable and objective measures of consciousness is critical in basic and clinical neuroscience. Across species, the perturbational complexity index (PCI) has emerged as a robust empirical marker by directly perturbing the brain, yet its relationship to broader physical principles remains unclear. Here, we address this gap by introducing a non-invasive framework based on generative whole-brain models of non-equilibrium brain dynamics. Using these models, we identify violations of the fluctuation-dissipation theorem (FDT) in humans and rodents across wakefulness, anesthesia, and disorders of consciousness (DoC). Mirroring PCI, FDT violations decrease in unresponsive DoC and anesthesia compared with conscious conditions. These findings reveal a robust empirical link between PCI and non-equilibrium dynamics in spontaneous brain signals, suggesting that non-equilibrium dynamics capture an important aspect of perturbational complexity. Overall, this framework opens non-invasive, model-based avenues for understanding consciousness and supports efforts to assess its loss and recovery in health and disease.

Transcranial magnetic stimulation (TMS) is a non-invasive technique to stimulate the brain, while electroencephalography (EEG) is a non-invasive technique to record its electrical activity. Their combined use (TMS-EEG) has been established only relatively recently, after successful development of TMS-compatible EEG amplifiers. TMS-EEG offers the unparalleled opportunity to directly perturb the brain with TMS and simultaneously record its response with EEG. This allows inferences on causal input-output relationships, therefore going critically beyond purely observational techniques, such as resting-state EEG or functional MRI, in the study of brain dynamics. This consensus review updates the work of Tremblay and coworkers [Clin Neurophysiol 2019; 130: 802-844]. Since then, substantial advances have been made in understanding contamination of TMS-EEG signals by physiological and non-physiological artifacts, as well as in developing strategies to avoid or control them. In parallel, new insights have emerged regarding the physiological mechanisms underlying TMS-EEG responses and their diagnostic and prognostic utility in a broad range of psychiatric and neurological disorders. As such, TMS-EEG is rapidly shaping a dynamic new field in clinical neurophysiology and neuroscience. This review provides a critical and comprehensive synthesis of current knowledge, including practical guidance for implementing TMS-EEG in the clinical setting.

Transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) is a powerful technique for investigating human cortical circuits. However, characterizing TMS-evoked potentials (TEPs) at the group level typically relies on grand averaging across stimulus repetitions (trials) and subjects-an approach that assumes a level of spatial and temporal consistency that is often lacking in TEPs. Here, we introduce an adaptation of Group Task-Related Component Analysis (gTRCA), a novel multivariate signal decomposition method, to automatically extract TEP components that are maximally reproducible across both trials and subjects. Following the validation of a new permutation-based statistical test for gTRCA using simulated data, the method was applied to two independent TMS-EEG datasets, in which stimulation was targeted to the primary motor cortex (M1) in cohorts of 16 and 22 healthy participants. We found that gTRCA reliably identified TEP components that were reproducible at the group level. Notably, the main gTRCA component captured the key spatial, temporal, and spectral features of motor TEPs, remained robust despite reduced number of stimuli and participants, and was consistent across different recordings. These findings demonstrate that gTRCA affords a more reliable characterization of TEPs at the group level, thereby facilitating the translation of TMS-EEG research into clinical practice.

Hemispherotomy is a neurosurgical procedure for treating refractory epilepsy, which entails disconnecting a significant portion of the cortex, potentially encompassing an entire hemisphere, from its cortical and subcortical connections. While this intervention prevents the spread of seizures, it raises important questions. Given the complete isolation from sensory-motor pathways, it remains unclear whether the disconnected cortex retains any form of inaccessible awareness. More broadly, the activity patterns that large portions of the deafferented cortex can sustain in awake humans remain poorly understood. We address these questions by exploring for the first time the electrophysiological state of the isolated cortex before and after surgery in ten awake pediatric patients. Post-surgery, the isolated cortex exhibited prominent slow oscillations (<2 Hz) and a broad-band shift in power spectral density from high to low frequencies. This resulted in a marked decrease of the spectral exponent, a validated consciousness marker, indicating broad-band slowing characteristic of unconscious states. When compared with a reference pediatric sample across the sleep-wake cycle, the spectral exponent of the contralateral cortex aligned with wakefulness, whereas that of the isolated cortex was consistent with deep NREM sleep. However, spindles did not emerge in the isolated cortex due to the lack of subcortical inputs, constituting a fundamental difference from physiological sleep. These findings demonstrate a unihemispheric sleep-like state during wakefulness, challenging the possibility that hemispherotomy might lead to inaccessible "islands of awareness." Moreover, the persistence of sleep-like patterns years after disconnection provides unique insights into the electrophysiological effects of disconnections in the human brain. ### Competing Interest Statement I have read the journal's policy and the authors of this manuscript have the following competing interests: M.M. is co-founder and shareholder of Intrinsic Powers, Inc., a spin-off of the University of Milan Si.Sa. is advisor of the same company. The remaining co-authors have no conflicts of interest to declare.

Transcranial Magnetic Stimulation (TMS) evokes electroencephalographic (EEG) responses that can last hundreds of milliseconds. Yet only the first 80 ms after the pulse are widely accepted to reflect genuine cortical responses to TMS, while later components have mainly been attributed to the effects of sensory co-stimulations. Here we reappraise this view by investigating the target-specificity of the spatiotemporal evolution of TMS-evoked potentials (TEPs). To this end, we compared TEPs elicited by TMS targeting the premotor and primary motor cortices in healthy subjects, under conditions designed to optimize the TMS effectiveness on the cortex while minimizing peripheral confounds. As a counterfactual, we conducted the same comparison on the EEG responses evoked by realistic sham TMS and high-intensity somatosensory scalp stimulation. We found that EEG responses to motor and premotor TMS can exhibit distinct spatiotemporal evolutions up to 300 ms both at the group and single-subject levels. These differences were absent or marginally present in both realistic sham TMS and high-intensity somatosensory scalp stimulation. Our findings suggest that, when effectiveness is optimized and peripheral confounds are controlled, TMS elicits specific long-lasting EEG responses that reflect genuine responses to the initial engagement of specific cortical targets. These results challenge previous assumptions and highlight how TMS-EEG can be reliably used to assess large-scale properties within corticothalamic networks. ### Competing Interest Statement MM is a co-founder and shareholder of Intrinsic Powers, a spin-off of the University of Milan. MR, SC, SS, are advisors and shareholders of Intrinsic Powers. SR is the Chief Medical Officer of Manava Plus. These affiliations in no way affect the content of this article. The other authors report no competing interests or personal relationships that could have appeared to influence the work reported in this paper. Massachusetts General Hospital, https://ror.org/002pd6e78, Transformative Scholar Award in Brain Health European Research Council, 101071900 Tiny Blue Dot Foundation, https://ror.org/01a4es322

Chronic migraine (CM) is a highly disabling condition, affecting about 2% of the global population. Non-pharmacological treatments can be optimal for their non-invasive nature. This prospective, randomized, double-blind, controlled trial aimed to test the efficacy of therapeutic neuroscience education (TNE) in CM. Early response biomarkers were also evaluated. A total of 80 CM patients were consecutively enrolled and randomly allocated to TNE or a general education program. Treatment effectiveness was evaluated at baseline (T1) and 2 months after the end of treatment (T4). We collected the responses to disability and comorbidity questionnaires at the start (T1) and end of treatment (T3, 10 weeks after start). Early response biomarkers were evaluated at screening (T0) and mid-way through the process (T2, 5 weeks after start). We expected that TNE would provide a greater benefit than the general education program, which served as the primary outcome of this study. We also expected that a change in clinical and neurophysiological measures could potentially occur, reflecting plasticity-induced reorganization and predicting clinical response. This is the first study selectively exploring the effect of TNE as a standalone treatment for CM. A new, effective treatment regime without interactions with other medication could be of great interest as an addition to migraine therapeutic strategies.

The quest for reliable and objective measures of consciousness is critical in basic and clinical neuroscience. Across species, the Perturbational Complexity Index (PCI) has emerged as a robust empirical marker by directly perturbing the brain, yet its underlying principles of physics are not fully understood. Here, we bridge this gap by introducing a non-invasive framework based on generative whole-brain models of non-equilibrium brain dynamics. Using these models, we identified violations of the Fluctuation-Dissipation Theorem (FDT) in humans and rodents across wakefulness, anesthesia, and disorders of consciousness. Mirroring the patterns observed with PCI, we found decreased FDT violations in unresponsive disorders of consciousness and anesthesia compared to conscious conditions. This reveals a close link between PCI and non-equilibrium dynamics in spontaneous brain signals, grounding PCI in fundamental principles of physics. Overall, this framework offers new complementary, non-invasive, model-based avenues for understanding the nature of consciousness and for developing objective tools to assess its loss and recovery in health and disease. It also provides a principled foundation for discovering novel strategies to restore consciousness. ### Competing Interest Statement Marcello Massimini is a co-founder and shareholder of Intrinsic Powers, a spin-off of the University of Milan. Simone Sarasso is advisor of Intrinsic Powers. This affiliation in no way affects the content of this article. CONICET external scholarship

Hemispherotomy is a neurosurgical procedure for treating refractory epilepsy, which entails disconnecting a significant portion of the cortex, potentially encompassing an entire hemisphere, from its cortical and subcortical connections. While this intervention prevents the spread of seizures, it raises important questions. Given the complete isolation from sensory-motor pathways, it remains unclear whether the disconnected cortex retains any form of inaccessible awareness. More broadly, the activity patterns that large portions of the deafferented cortex can sustain in awake humans remain poorly understood. We address these questions by exploring for the first time the electroencephalographic (EEG) state of the isolated cortex during wakefulness before and after surgery in 10 pediatric patients, focusing on non-epileptic background activity. Post-surgery, the isolated cortex exhibited prominent slow oscillations (<2 Hz) and a steeper broad-band spectral decay, reflecting a redistribution of power toward lower frequencies. This broad-band EEG slowing resulted in a marked decrease of the spectral exponent, a validated consciousness marker, reaching values characteristic of deep anesthesia and the vegetative state. When compared with a reference pediatric sample across the sleep-wake cycle, the spectral exponent of the contralateral cortex aligned with wakefulness, whereas that of the isolated cortex was consistent with deep NREM sleep. The findings of prominent slow oscillations and broad-band slowing provisionally support inferences of absent or reduced awareness in the isolated cortex. Moreover, the persistence of unihemispheric sleep-like patterns years after surgery provides unique insights into the long-term electrophysiological effects of cortical disconnections in the human brain.

Distilling the neural correlates of consciousness (NCCs) in humans is challenging due to limitations in the spatiotemporal resolution of recording techniques and confounds related to pre- and post-perceptual processes. In this study, we leveraged the detailed insights provided by human intracortical recordings to elucidate how somatosensory responses to simple tactile stimuli vary across different stimulus intensities and reporting conditions. Among the various spatiotemporal components of somatosensory processing, we observed tonic responses in posterior perisylvian regions that exhibited all the key characteristics of somatosensory NCCs. These responses remained invariant regardless of reporting, displayed an all-or-nothing pattern at the verge of the sensory threshold, and showed the most pronounced divergence between perceived and non-perceived stimuli. Overall, our findings indicate that conscious perception of simple tactile stimuli depends on higher-order somatosensory regions and that sustained neural dynamics in these areas may serve as an organizational principle of somatosensory awareness.

OBJECTIVE:Recent studies indicate that brain injuries often lead to the occurrence of sleep-like slow waves in perilesional cortical areas. These slow waves may disrupt local cortico-cortical interactions and contribute to behavioral impairments but are, in principle, reversible. This study employs Transcranial Magnetic Stimulation (TMS) combined with Electroencephalography (EEG) to monitor changes in perilesional slow waves and local cortical interactions examining their relation to changes in stroke severity. METHODS:Twelve patients with post-acute/chronic unilateral ischemic cortical stroke participated in a longitudinal study with two assessment points. Each assessment included a neurological evaluation using the National Institutes of Health Stroke Scale (NIHSS) and TMS-EEG recordings targeting perilesional cortical areas. Neurophysiological parameters, such as slow wave amplitude (SWa), high-frequency power (HFp) suppression, and the Perturbational Complexity Index-state transition (PCIst), were extracted from the perilesional EEG responses to TMS to quantify local sleep-like slow waves andcortical interactions. RESULTS:We observed a perilesional reduction in sleep-like slow waves and a restoration of local cortical interactions. Notably, these changes significantly correlated with patients' clinical evolution as assessed by the NIHSS score. CONCLUSIONS:These findings highlight the potential of TMS-EEG as an objective tool for tracking neurological evolution post-stroke. SIGNIFICANCE:Targeting sleep-like cortical dynamics may be relevant for devising post-stroke rehabilitation strategies.

Cortical stimulation with single pulses is a common technique in clinical practice and research. However, we still do not understand the extent to which it engages subcortical circuits that may contribute to the associated evoked potentials (EPs). Here we show that cortical stimulation generates remarkably similar EPs in humans and mice, with a late component similarly modulated by the state of the targeted cortico-thalamic network. We then optogenetically dissect the underlying circuit in mice, demonstrating that the EPs late component is caused by a thalamic hyperpolarization and rebound. The magnitude of this late component correlates with bursting frequency and synchronicity of thalamic neurons, modulated by the subject's behavioral state. A simulation of the thalamo-cortical circuit highlights that both intrinsic thalamic currents as well as cortical and thalamic GABAergic neurons contribute to this response profile. We conclude that single pulse cortical stimulation engages cortico-thalamo-cortical circuits largely preserved across different species and stimulation modalities.