Biology subjects

Laureys, S.

Publications and source records attributed to Laureys, S..

28 records · Page 2Linked to original sources

bioRxiv2020

Loss of consciousness reduces the stability of brain hubs and the heterogeneity of brain dynamics

Low-level states of consciousness are characterised by disruptions of brain dynamics that sustain arousal and awareness. Yet, how structural, dynamical, local and network brain properties interplay in the different levels of consciousness is unknown. Here, we studied the fMRI brain dynamics from patients that suffered brain injuries leading to a disorder of consciousness and from subjects undergoing propofol-induced anaesthesia. We showed that pathological and pharmacological low-level states of consciousness displayed less recurrent, less diverse, less connected, and more segregated synchronization patterns than conscious states. We interpreted these effects using whole-brain models built on healthy and injured connectomes. We showed that altered dynamics arise from a global reduction of network interactions, together with more homogeneous and more structurally constrained local dynamics. These effects were accentuated using injured connectomes. Notably, these changes lead the hub regions to lose their stability during low-level states of consciousness, thus attenuating the core-periphery structure of brain dynamics.

neuroscience↗

bioRxiv2020

Perturbations in dynamical models of whole-brain activity dissociate between the level and stability of consciousness

Consciousness transiently fades away during deep sleep, more stably under anesthesia, and sometimes permanently due to brain injury. The development of an index to quantify the level of consciousness across these different states is regarded as a key problem both in basic and clinical neuroscience. We argue that this problem is ill-defined since such an index would not exhaust all the relevant information about a given state of consciousness. While the level of consciousness can be taken to describe the actual brain state, a complete characterization should also include its potential behavior against external perturbations. We developed and analyzed whole-brain computational models to show that the stability of conscious states provides information complementary to their similarity to conscious wakefulness. Our work leads to a novel methodological framework to sort out different brain states by their stability and reversibility, and illustrates its usefulness to dissociate between physiological (sleep), pathological (brain-injured patients), and pharmacologically-induced (anesthesia) loss of consciousness.

neuroscience↗

bioRxiv2020

Convolutional neural network MRI segmentation for fast and robust optimization of transcranial electrical current stimulation of the human brain

The segmentation of structural MRI data is an essential step for deriving geometrical information about brain tissues. One important application is in transcranial electrical stimulation (e.g., tDCS), a non-invasive neuromodulatory technique where head modeling is required to determine the electric field (E-field) generated in the cortex to predict and optimize its effects. Here we propose a deep learning-based model (StarNEt) to automatize white matter (WM) and gray matter (GM) segmentation and compare its performance with FreeSurfer, an established tool. Since good definition of sulci and gyri in the cortical surface is an important requirement for E-field calculation, StarNEt is specifically designed to output masks at a higher resolution than that of the original input T1w-MRI. StarNEt uses a residual network as the encoder (ResNet) and a fully convolutional neural network with U-net skip connections as the decoder to segment an MRI slice by slice. Slice vertical location is provided as an extra input. The model was trained on scans from 425 patients in the open-access ADNI+IXI datasets, and using FreeSurfer segmentation as ground truth. Model performance was evaluated using the Dice Coefficient (DC) in a separate subset (N=105) of ADNI+IXI and in two extra testing sets not involved in training. In addition, FreeSurfer and StarNEt were compared to manual segmentations of the MRBrainS18 dataset, also unseen by the model. To study performance in real use cases, first, we created electrical head models derived from the FreeSurfer and StarNEt segmentations and used them for montage optimization with a common target region using a standard algorithm (Stimweaver) and second, we used StarNEt to successfully segment the brains of minimally conscious state (MCS) patients having suffered from brain trauma, a scenario where FreeSurfer typically fails. Our results indicate that StarNEt matches FreeSurfer performance on the trained tasks while reducing computation time from several hours to a few seconds, and with the potential to evolve into an effective technique even when patients present large brain abnormalities.

bioinformatics↗

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↗

bioRxiv2019

Tracking attention in a visual active paradigm for the diagnosis of disorders of consciousness

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSClinical assessment of patients with disorders of consciousness (DOC) relies on the clinicians ability to detect a behavioral response to an instruction (e.g., "squeeze my hand"). However, recent studies have shown that some of these patients can produce volitional brain responses to command while no behavioral response is present. This highlights the importance of developing motor-independent diagnostic tool for this population, complementing standardized behavioral evaluation. We here evaluate the ability of a novel gaze-independent attention-based EEG paradigm to detect volitional attentional processes in patients with disorders of consciousness. MethodsThirty patients with DOC were included in the study: 12 with an unresponsive wakefulness syndrome, 16 in a minimally conscious state (MCS), two who emerged from a MCS. Patients were randomly instructed to either concentrate on a task or rest while brain activity was recorded using EEG during a gaze-independent paradigm. ResultsOne of two EMCS, one of 16 MCS and one of 12 UWS patients showed a response to command using the attention task. Interestingly, this method could detect a brain-based response to command in one MCS patient who did not present a behavioral response to command at the bedside the day of the assessment. ConclusionThis study show that task-related variation of attention during an active task could help to objectively detect response to command in patients with DOC.

neuroscience↗

bioRxiv2019

Functional cortico-subcortical reorganization after complete hemispheric disconnection for intractable epilepsy

Hemispherotomy is a treatment for drug-resistant epilepsy with the whole hemisphere involved in seizure onset. As recovery mechanisms are still debated, we characterize functional reorganization with multimodal MRI in two children operated on the right hemisphere (RH). We found that interhemispheric functional connectivity was abolished in both patients. The healthy left hemispheres (LH) displayed focal hyperperfusion in motor and limbic areas, and preserved network-level organization. The disconnected RHs were hypoperfused despite sustained network-level organization. Functional connectivity was increased in the left thalamo-cortical loop and between the cerebelli. The classification probability of the RH corresponding to a minimally conscious state was smaller than for the LH. We conclude that after hemispherotomy, neurological rehabilitation is sustained by cortical disinhibition and reinforcement of connectivity driven by subcortical structures in the remaining hemisphere. Our results highlight the effect of vascularization on functional connectivity and raise inquiries about the conscious state of the isolated hemisphere.

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

Modulation of the spontaneous hemodynamic response function across levels of consciousness

Functional imaging research has already contributed with several results to the study of neural correlates of consciousness. Apart from task-related activation derived in fMRI, PET based glucose metabolism rate or cerebral blood flow account for a considerable proportion of the study of brain activity under different levels of consciousness. Resting state functional connectivity MRI is playing a crucial role to explore the consciousness related functional integration, successfully complementing PET, another widely used neuroimaging technique. Here, spontaneous hemodynamic response is introduced to characterize resting state brain activity giving information on the local metabolism (neurovascular coupling), and useful to improve the time-resolved activity and connectivity measures based on BOLD fMRI. This voxel-wise measure is then used to investigate the loss of consciousness under Propofol anesthesia and unresponsive wakefulness syndrome. The dysfunction of hemodynamic response in precuneus and posterior cingulate is found to be a common principle underlying loss of consciousness in both conditions. The thalamus appears to be less obviously modulated by Propofol, compared with frontoparietal regions. However, a significant increase in spontaneous thalamic hemodynamic response was found in patients in unresponsive wakefulness syndrome compared with healthy control. Our results ultimately show that anesthesia- or pathology-induced neurovascular coupling could be tracked by modulated spontaneous hemodynamic response derived from resting state fMRI.

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↗

bioRxiv2017

Propofol-Induced Unresponsiveness is Associated with Impaired Feedforward Connectivity in the Cortical Hierarchy

BackgroundImpaired consciousness has been associated with impaired cortical signal propagation following transcranial magnetic stimulation (TMS). Herein we hypothesized that the reduced current propagation under propofol-induced unresponsiveness is associated with changes in both feedforward and feedback connectivity across the cortical hierarchy.\n\nMethodsEight subjects underwent left occipital TMS coupled with high-density electroencephalograph (EEG) recordings during wakefulness and propofol-induced unconsciousness. Spectral analysis was applied to responses recorded from sensors overlying six hierarchical cortical sources involved in visual processing. Dynamic causal modelling (DCM) of evoked and induced source-space responses was used to investigate propofols effects on connectivity between regions.\n\nResultsPropofol produced a wideband reduction in evoked power following TMS in five out of six electrodes. Bayesian Model Selection supported a DCM with hierarchical feedforward and feedback connections to best fit the data. DCM of induced responses revealed that the primary effect of propofol was impaired feedforward responses in cross frequency theta/alpha-gamma coupling and within frequency theta coupling (F contrast, Family Wise Error corrected p<0.05). An exploratory analysis (thresholded at uncorrected p<0.001) also suggested that propofol impaired feedforward and feedback beta band coupling. Posthoc analyses showed impairments in all feedforward connections and one feedback connection from parietal to occipital cortex. DCM of the evoked response potential showed impaired feedforward connectivity between left sided occipital and parietal cortex (T contrast p=0.004, Bonferroni corrected).\n\nConclusionsOur data suggest that propofol-induced loss of consciousness is associated with reduced evoked power and impaired hierarchical feedforward connectivity following occipital TMS.

neuroscience↗