Biology subjects

Sarasso, S.

Publications and source records attributed to Sarasso, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Inferring structural complexity from dynamical measures

Complexity, commonly defined as the coexistence of integration and differentiation, is a fundamental property of thalamocortical networks and is regarded as a prerequisite for adaptive brain function and consciousness. A variety of metrics have been developed to estimate neural complexity from recorded activity and are increasingly employed in both research and clinical settings. Yet, the extent to which these measures reflect specific architectural features of the underlying circuits remains poorly understood. Here, we used Wilson-Cowan mean-field equations to simulate neural dynamics across networks spanning a broad range of architectures. By systematically rewiring connectivity, we generated graded variations in the structural integration-differentiation balance and assessed a panel of complexity measures derived either from spontaneous activity (observational metrics) or from responses to external perturbations (perturbational metrics). Observational measures exhibited markedly heterogeneous behavior: some were primarily sensitive to network integration, others to differentiation, whereas some showed limited sensitivity to architectural manipulations. In contrast, perturbational measures robustly peaked at intermediate rewiring steps and scaled with small-worldness, consistent with architectures that combine local recurrence and distributed communication. Moreover, perturbational metrics proved robust to common-driver confounds and were highest in a wake-like regime near critical instability, declining as sleep-like dynamics became more widespread across the network. Taken together, these findings map widely used empirical complexity measures onto specific network architectures, reveal dynamical factors that can bias observational estimates, and provide guidance for inferring complexity in systems whose internal organization is inaccessible, unconventional, or only partially known, including brain organoids, non-human nervous systems, and synthetic neural networks.

neuroscience↗

bioRxiv2026

A Whole-Brain Dynamical Framework Linking Resting-State Activity to TMS-Evoked Responses

A major challenge in systems neuroscience is understanding how external perturbations interact with ongoing brain activity. Transcranial magnetic stimulation (TMS), increasingly used in both basic and clinical neuroscience and often combined with electroencephalography (EEG), provides a unique opportunity to probe this interaction. However, how intrinsic dynamics constrain the propagation of TMS-evoked activity remains poorly understood. In particular, effective connectivity (EC)--capturing directed, state-dependent interactions between brain regions--is thought to critically shape perturbational spread, yet remains difficult to estimate at the whole-brain EEG level. Here we introduce an analytically tractable, generative whole-brain model that links spontaneous EEG activity to cortical responses under perturbation. By deriving a closed-form expression for the models cross-spectral density, we directly fit empirical resting-state EEG spectra and infer biophysically interpretable local dynamical parameters without time-domain simulations. We then estimate stimulation-site-specific EC using only a small fraction of the TMS-EEG trials. The resulting model accurately predicts the spatiotemporal structure of TMS-evoked potentials (TEPs) in unseen trials. Moreover, even without subject-specific refitting, group-level EC templates capture canonical site-specific propagation motifs underlying single-subject early TMS responses. Together, our results establish an analytical framework for individualized whole-brain modeling of TMS-EEG with potential applicability to model-based neuromodulation.

neuroscience↗

bioRxiv2026

Temporal fingerprints of TMS-evoked potentials across thalamocortical circuits

BackgroundElectroencephalographic (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. AimTo obtain region-specific properties of frontal, parietal and occipital networks from the time course of TMS-evoked potentials (TEPs). Materials and MethodsWe 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. ResultsOccipital 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. ConclusionsOur 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.

neuroscience↗

bioRxiv2025

Thermodynamics of consciousness: A non-invasive perturbational framework

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.

neuroscience↗

bioRxiv2025

Slow waves generation and propagation in a model of brain lesions

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 seen in patients and identify actionable targets for neuromodulation and rehabilitation.

neuroscience↗

bioRxiv2025

The specific spatiotemporal evolution of TMS-evoked potentials reflects the engagement of cortical circuits

Transcranial Magnetic Stimulation (TMS) evokes electroencephalographic (EEG) responses that can persist for hundreds of milliseconds. While the first 80 ms after the pulse are widely accepted to reflect genuine cortical responses to TMS, 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 targeting the premotor and primary motor cortices in 16 healthy subjects, under conditions designed to optimize 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, lasting up to 300 ms, both at the group and single-subject levels. These differences were absent or marginally detectable 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 genuine EEG responses that reflect 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.

physiology↗

bioRxiv2025

Extracting Reproducible Components from Electroencephalographic Responses to Transcranial Magnetic Stimulation with Group Task-Related Component Analysis

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.

neuroscience↗

bioRxiv2025

Hemispherotomy: a cortical island of sleep-like activity in awake humans

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.

neuroscience↗

bioRxiv2024

Thalamic feedback shapes brain responses evoked by cortical stimulation in mice and humans

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 which contribute to the associated evoked potentials (EPs). Here we find that cortical stimulation generates remarkably similar EPs in humans and mice, with a late component similarly modulated by the subjects behavioral state. We optogenetically dissect the underlying circuit in mice, demonstrating that the late component of these EPs is caused by a thalamic hyperpolarization and rebound. The magnitude of this late component correlates with the bursting frequency and synchronicity of thalamic neurons, modulated by the subjects 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 the cortical stimulation engages cortico-thalamo-cortical circuits highly preserved across different species and stimulation modalities. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/578243v2_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@cae203org.highwire.dtl.DTLVardef@1bc5223org.highwire.dtl.DTLVardef@b48e43org.highwire.dtl.DTLVardef@1e7fe34_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2021

Simultaneous stereo-EEG and high-density scalp EEG recordings to study the effects of intracerebral stimulation parameters

BackgroundCortico-cortical evoked potentials (CCEPs) recorded by stereo-electroencephalography (SEEG) are a valuable clinical tool to investigate brain reactivity and effective connectivity. However, these invasive recordings are spatially sparse since they depend on clinical needs. This sparsity hampers systematic comparisons across-subjects, the detection of the whole-brain spatiotemporal properties of CCEPs, as well as their relationships with classic sensory evoked potentials. ObjectiveTo demonstrate that CCEPs recorded by high-density electroencephalography (hd-EEG) are sensitive to changes in stimulation parameters and compensate for the limitations typical of invasive recordings. MethodsSEEG and hd-EEG activities were simultaneously recorded during SPES in drug-resistant epileptic patients (N=36). Changes in stimulation parameters encompassed physical (pulse intensity and width), geometrical (angle and position with respect to white/grey matter) and topological (stimulated cortical area) properties. Differences were assessed by measuring the overall responses and the amplitude of N1 and N2 components of the CCEPs, and by their spectral profiles. ResultsWhile invasive and non-invasive CCEPs were generally correlated, differences in pulse duration, angle and stimulated cortical area were better captured by hd-EEG. Further, hd-EEG responses to SPES reproduced basic features of responses to transcranial magnetic stimulation and showed a much larger amplitude as compared to typical sensory evoked potentials. ConclusionsThe present results show that macroscale hd-EEG recordings are exquisitely sensitive to variations in SPES parameters, including local changes in physical and geometrical stimulus properties, while providing valuable information about whole-brain dynamics. Moreover, the common reference space across subjects represented by hd-EEG may facilitate the construction of a perturbational atlas of effective connectivity. HighlightsO_LICCEPs recorded with hd-EEG and SEEG are correlated. C_LIO_LIhd-EEG recording is highly sensitive to changes in stimulation parameters. C_LIO_LIhd-EEG responses show higher amplitude responses with respect to non-invasive ones. C_LIO_LISimultaneous recordings provide a fixed observation point across subjects. C_LI

neuroscience↗

bioRxiv2021

The rt-TEP tool: real-time visualization of TMS-evoked potentials to maximize cortical activation and minimize artifacts

BackgroundThe impact of transcranial magnetic stimulation (TMS) on cortical neurons is currently hard to predict based on a priori biophysical and anatomical knowledge alone. This problem can hamper the reliability and reproducibility of protocols aimed at measuring electroencephalographic (EEG) responses to TMS. New MethodWe introduce and release a novel software tool to facilitate and standardize the acquisition of TMS-evoked potentials (TEPs). The tool, rt-TEP (real-time TEP), interfaces with different EEG amplifiers and offers a series of informative visualization modes to assess in real time the immediate impact of TMS on the underlying neuronal circuits. ResultsWe show that rt-TEP can be used to abolish or minimize magnetic and muscle artifacts contaminating the post-stimulus period thus affording a clear visualization and quantification of the amplitude of the early (<50 ms) EEG response after averaging a limited number of trials. This real-time readout can then be used to adjust TMS parameters (e.g. site, orientation, intensity) and experimental settings (e.g. loudness and/or spectral features of the noise masking) to ultimately maximize direct cortical effects over the undesired sensory effects of the coils discharge. Comparison with Existing MethodsThe ensemble of real-time visualization modes of rt-TEP are not implemented in any current commercial software and provide a key readout to titrate TMS parameters beyond the a priori information provided by anatomical models. ConclusionsReal-time optimization of stimulation parameters with rt-TEP can facilitate the acquisition of reliable TEPs with a high signal-to-noise ratio and improve the standardization and reproducibility of data collection across laboratories. HighlightsO_LIrt-TEP provides an immediate EEG readout to assess the quality of TEPs in real time C_LIO_LIrt-TEP interfaces with most commercial EEG systems C_LIO_LIInformative, real time visualization allows maximising the cortical impact of TMS while minimizing artifacts C_LIO_LIrt-TEP facilitates the acquisition of reliable TEPs with a high signal-to-noise ratio C_LI

neuroscience↗

bioRxiv2021

An in-vivo validation of ESI methods with focal sources

Electrical source imaging (ESI) aims at reconstructing the electrical brain activity from measurements of the electric field on the scalp. Even though the localization of single focal sources should be relatively straightforward, different methods provide diverse solutions due to the different underlying assumptions. Furthermore, their input parameter(s) further affects the solution provided by each method, making localization even more challenging. In addition, validations and comparisons are typically performed either on synthetic data or through post-operative outcomes, in both cases with considerable limitations. We use an in-vivo high-density EEG dataset recorded during intracranial single pulse electrical stimulation, in which the true sources are substantially dipolar and their locations are known. We compare ten different ESI methods under multiple choices of input parameters, to assess the accuracy of the best reconstruction, as well as the impact of the parameters on the localization performance. Best reconstructions often fall within 1 cm from the true source, with more accurate methods outperforming less accurate ones by 1 cm, on average. Expectedly, dipolar methods tend to outperform distributed methods. Sensitivity to input parameters varies widely between methods. Depth weighting played no role for three out of six methods implementing it. In terms of regularization parameters, for several distributed methods SNR=1 unexpectedly turned out to be the best choice among the tested ones. Our data show similar levels of accuracy of ESI techniques when applied to "conventional" (32 channels) and dense (64, 128, 256 channels) EEG recordings. Overall findings reinforce the importance that ESI may have in the clinical context, especially when applied to identify the surgical target in potential candidates for epilepsy surgery.

neuroscience↗

bioRxiv2021

TAAC - TMS Adaptable Auditory Control: a universal tool to mask TMS click

BackgroundCoupling transcranial magnetic stimulation with electroencephalography (TMS-EEG) allows recording the EEG response to a direct, non-invasive cortical perturbation. However, obtaining a genuine TMS-evoked EEG potential requires controlling for several confounds, among which a main source is represented by the auditory evoked potentials (AEPs) associated to the TMS discharge noise (TMS click). This contaminating factor can be in principle prevented by playing a masking noise through earphones. New methodHere we release TMS Adaptable Auditory Control (TAAC), a highly flexible, open-source, Matlab(R)-based interface that generates in real-time customized masking noises. TAAC creates noises starting from the stimulator-specific TMS click and tailors them to fit the individual, subject-specific click perception by mixing and manipulating the standard noises in both time and frequency domains. ResultsWe showed that TAAC allows us to provide standard as well as customized noises able to effectively and safely mask the TMS click. Comparison with existing methodsHere, we showcased two customized noises by comparing them to two standard noises previously used in the TMS literature (i.e., a white noise and a noise generated from the stimulator-specific TMS click only). For each, we quantified the Sound Pressure Level (SPL; measured by a Head and Torso Simulator - HATS) required to mask the TMS click in a population of 20 healthy subjects. Both customized noises were effective at safe (according to OSHA and NIOSH safety guidelines), lower SPLs with respect to standard noises. ConclusionsAt odds with previous methods, TAAC allows creating effective and safe masking noises specifically tailored on each TMS device and subject. The combination of TAAC with tools for the real-time visualization of TEPs can help control the influence of auditory confounds also in non-compliant patients. Finally, TAAC is a highly flexible and open-source tool, so it can be further extended to meet different experimental requirements.

neuroscience↗

bioRxiv2021

EEG spectral exponent as a synthetic index for the longitudinal assessment of stroke recovery.

BackgroundQuantitative EEG (qEEG) can capture changes in brain activity that follow a stroke. Accordingly, EEG metrics could be used to monitor patients state and recovery. Although qEEG metrics traditionally focus on oscillatory activity, recent findings highlight the importance of aperiodic (power-law) structure in characterizing pathological brain states. ObjectiveTo assess neurophysiological impairment and recovery from mono-hemispheric stroke by means of the Spectral Exponent (SE), a metric that reflects EEG slowing and quantifies the power-law decay of the EEG Power Spectral Density (PSD). To relate neurophysiological recovery with patients functional outcome. MethodsEighteen patients (n=18) with Middle Cerebral Artery (MCA) ischaemic stroke were retrospectively enrolled for this study. Patients underwent EEG recording in the sub-acute phase (T0) and after 2 months of physical rehabilitation (T1). Sixteen healthy controls (HC; n=16) matched by age and sex were enrolled as a normative group. SE values and narrow-band PSD were estimated for each recording. We compared SE and band-power between patients and HC, and between the affected (AH) and unaffected hemisphere (UH) at T0 and T1 in patients. ResultsAt T0, stroke patients showed significantly more negative SE values than HC (p=0.003), reflecting broad-band EEG slowing. Moreover, SE over the AH was consistently more negative compared to the UH and showed a renormalization at T1 in our patient sample. This SE renormalization significantly correlated with NIHSS improvement (R= 0.63, p=0.005). ConclusionsSE is a reliable readout of the electric changes occurring in the brain after an ischaemic cortical lesion. Moreover, SE holds the promise to be a robust method to assess stroke impairment as well as to monitor and predict functional outcome.

neuroscience↗

bioRxiv2020

Simultaneous human intracerebral stimulation and HD-EEG: ground-truth for source localization methods

Precisely localizing the sources of brain activity as recorded by EEG is a fundamental procedure and a major challenge for both research and clinical practice. Even though many methods and algorithms have been proposed, their relative advantages and limitations are still not well established. Moreover, these methods involve tuning multiple parameters, for which no principled way of selection exists yet. These uncertainties are emphasized due to the lack of ground-truth for their validation and testing. Here we provide the first open dataset that comprises EEG recorded electrical activity originating from precisely known locations inside the brain of living humans. High-density EEG was recorded as single-pulse biphasic currents were delivered at intensities ranging from 0.1 to 5 mA through stereotactically implanted electrodes in diverse brain regions during pre-surgical evaluation of patients with drug-resistant epilepsy. The uses of this dataset range from the estimation of in vivo tissue conductivity to the development, validation and testing of forward and inverse solution methods.

neuroscience↗

bioRxiv2019

Local sleep-like cortical reactivity in the awake brain after focal injury

The functional consequences of brain injury are known to depend on neuronal alterations extending beyond the area of structural damage. Although a lateralized EEG slowing over the injured hemisphere was known since the early days of clinical neurophysiology, its electrophysiological mechanisms were not systematically investigated. In parallel, basic sleep research has thoroughly characterized the neuronal events underlying EEG slow waves in physiological conditions. These EEG events reflect brief interruptions of neuronal firing (OFF-periods) that can occur locally and have prominent consequences on network and behavioral functions. Notably, the EEG slow waves observed following focal brain injury have been never explicitly connected to local sleep-like neuronal events. In previous works, probing cortical circuits with transcranial magnetic stimulation coupled with EEG (TMS/EEG) proved as an effective way to reveal the tendency of cortical circuits to transiently plunge into silent OFF-periods. Here, using this approach, we show that the intact cortex surrounding focal brain injuries engages locally in pathological sleep-like dynamics. Specifically, we employed TMS/EEG in a cohort of thirty conscious awake patients with chronic focal and multifocal brain injuries of various etiologies. TMS systematically evoked prominent slow waves associated with sleep-like OFF-periods in the area surrounding focal cortico-subcortical lesions. These events were associated with a local disruption of signal complexity and were absent when stimulating the contralateral hemisphere. Perilesional sleep-like OFF-periods may represent a valid read-out of the electrophysiological state of discrete cortical circuits following brain injury as well as a potential target of interventions aimed at fostering functional recovery. One Sentence SummaryFocal cortical injuries are associated with local intrusion of sleep-like dynamics over the perilesional areas which disrupt local signal complexity and coexist with typical wakefulness cortical reactivity patterns within the same brain.

neuroscience↗

bioRxiv2018

A fast and general method to empirically estimate the complexity of distributed causal interactions in the brain

BackgroundThe Perturbational Complexity Index (PCI) was recently introduced to assess the capacity of thalamocortical circuits to engage in complex patterns of causal interactions. While showing high accuracy in detecting consciousness in brain injured patients, PCI depends on elaborate experimental setups and offline processing and has restricted applicability to other types of brain signals beyond transcranial magnetic stimulation and high-density EEG (TMS/hd-EEG) recordings. ObjectiveWe aim to address these limitations by introducing PCIST, a fast method for estimating perturbational complexity of any given brain response signal. MethodsPCIST is based on dimensionality reduction and state transitions (ST) quantification of evoked potentials. The index was validated on a large dataset of TMS/hd-EEG recordings obtained from 108 healthy subjects and 108 brain injured patients, and tested on sparse intracranial recordings (SEEG) of 9 patients undergoing intra-cerebral single-pulse electrical stimulation (SPES). ResultsWhen calculated on TMS/hd-EEG potentials, PCIST performed with the same accuracy as the original PCI, while improving on the previous method by being computed in less than a second and requiring a simpler set-up. In SPES/SEEG signals, the index was able to quantify a systematic reduction of intracerebral complexity during sleep, confirming the occurrence of state-dependent changes in the effective connectivity of thalamocortical circuits, as originally assessed through TMS/hd-EEG. ConclusionsPCIST represents a fundamental advancement towards the implementation of a reliable and fast clinical tool for the bedside assessment of consciousness as well as a general measure to explore the neuronal mechanisms of loss/recovery of brain complexity across scales and models.

neuroscience↗

bioRxiv2018

Sleep-like bistability, loss of causality and complexity in the brain of Unresponsive Wakefulness Syndrome patients

Unresponsiveness Wakefulness Syndrome (UWS) patients may retain intact portions of the thalamocortical system that are spontaneously active and responsive to sensory stimuli. In these patients, Transcranial Magnetic Stimulation combined with electroencephalography (TMS/EEG) also reveals preserved cortical reactivity, but in most cases, the residual thalamocortical circuits fail to engage complex causal interactions, as assessed by the perturbational complexity index (PCI). Another condition during which thalamocortical circuits are intact, active and reactive, yet unable to generate complex responses, is physiological non-rapid eye movement (NREM) sleep. The underlying mechanism is bistability: the tendency of cortical neurons to fall into a silent period (OFF-period) upon receiving an input. Here we tested whether a pathological form of bistability may be responsible for loss of brain complexity in UWS patients. Time-frequency decomposition analysis of TMS/EEG responses in UWS patients revealed the occurrence of OFF-periods (detected as a transient suppression of high-frequency oscillations in the EEG) similar to the ones evoked by TMS in the cortex of healthy sleeping subjects. Pathological OFF-periods were detected in any cortical area, significantly impaired local causal interactions (as measured by PLF) and prevented the build-up of global complexity (as measured by PCI) in the brain of UWS patients. Our results draw a first link between neuronal events (OFF-periods) and global brain dynamics (complexity) in UWS patients. To the extent that sleep-like bistability represents the common functional endpoint of loss of complexity, detecting its presence and tracking its evolution over time, may offer a valuable read-out to devise, guide and titrate therapeutic strategies aimed at restoring consciousness.

neuroscience↗