References of "Soddu, Andrea"
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See detailMultifaceted Brain Networks Reconfiguration in Disorders of Consciousness Uncovered by Co-Activation Patterns
Di Perri, Carol ULiege; Amico, Enrico; Heine, Lizette ULiege et al

in Human Brain Mapping (in press)

Introduction: Given that recent research has shown that functional connectivity is not a static phenomenon, we aim to investigate the dynamic properties of the default mode network’s (DMN) connectivity in ... [more ▼]

Introduction: Given that recent research has shown that functional connectivity is not a static phenomenon, we aim to investigate the dynamic properties of the default mode network’s (DMN) connectivity in patients with disorders of consciousness. Methods: Resting-state fMRI volumes of a convenience sample of 17 patients in unresponsive wakefulness syndrome (UWS) and controls were reduced to a spatiotemporal point process by selecting critical time points in the posterior cingulate cortex (PCC). Spatial clustering was performed on the extracted PCC time frames to obtain 8 different co-activation patterns (CAPs). We investigated spatial connectivity patterns positively and negatively correlated with PCC using both CAPs and standard stationary method. We calculated CAPs occurrences and the total number of frames. Results: Compared to controls, patients showed (i) decreased within-network positive correlations and between-network negative correlations, (ii) emergence of “pathological” within-network negative correlations and between-network positive correlations (better defined with CAPs), and (iii) “pathological” increases in within-network positive correlations and between-network negative correlations (only detectable using CAPs). Patients showed decreased occurrence of DMN-like CAPs (1–2) compared to controls. No between-group differences were observed in the total number of frames Conclusion: CAPs reveal at a more fine-grained level the multifaceted spatial connectivity reconfiguration following the DMN disruption in UWS patients, which is more complex than previously thought and suggests alternative anatomical substrates for consciousness. BOLD fluctuations do not seem to differ between patients and controls, suggesting that BOLD response represents an intrinsic feature of the signal, and therefore that spatial configuration is more important for consciousness than BOLD activation itself. [less ▲]

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See detailA method for independent component graph analysis of resting-state fMRI. Brain and Behavior 2017, in press
Ribeiro de Paula, Demetrius; Ziegler, Erik; Abeyasinghe, P et al

in Brain and Behavior (in press)

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See detailDisorders of consciousness: new advances in neuroimaging techniques
Soddu, Andrea ULiege; Bruno, Marie-Aurélie ULiege; VANHAUDENHUYSE, Audrey ULiege et al

in Zanotti, Bruno (Ed.) Vegetative State (in press)

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See detailSleep, Coma, Vegetative and Minimally 4 Conscious States
Di Perri, Carol ULiege; Cavaliere, Carlo; Bodart, Olivier ULiege et al

in Sleep Disorders Medicine (2017)

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See detailSedation of Patients With Disorders of Consciousness During Neuroimaging: Effects on Resting State Functional Brain Connectivity.
KIRSCH, Murielle ULiege; Guldenmund, Pieter; Bahri, Mohamed Ali ULiege et al

in Anesthesia and Analgesia (2017), 124(2),

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See detailFunctional Connectivity Substrates for tDCS Response in Minimally Conscious State Patients
Cavaliere, Carlo ULiege; Aiello, Marco; Di Perri, Carol ULiege et al

in Frontiers in Cellular Neuroscience (2016)

Transcranial direct current stimulation (tDCS) is a non-invasive technique recently employed in disorders of consciousness, and determining a transitory recovery of signs of consciousness in almost half ... [more ▼]

Transcranial direct current stimulation (tDCS) is a non-invasive technique recently employed in disorders of consciousness, and determining a transitory recovery of signs of consciousness in almost half of minimally conscious state (MCS) patients. Although the rising evidences about its possible role in the treatment of many neurological and psychiatric conditions exist, no evidences exist about brain functional connectivity substrates underlying tDCS response. We retrospectively evaluated resting state functional Magnetic Resonance Imaging (fMRI) of 16 sub-acute and chronic MCS patients (6 tDCS responders) who successively received a single left dorsolateral prefrontal cortex (DLPFC) tDCS in a double-blind randomized cross-over trial. A seed-based approach for regions of left extrinsic control network (ECN) and default-mode network (DMN) was performed. tDCS responders showed an increased left intra-network connectivity for regions co-activated with left DLPFC, and significantly with left inferior frontal gyrus. Non-responders (NR) MCS patients showed an increased connectivity between left DLPFC and midline cortical structures, including anterior cingulate cortex and precuneus. Our findings suggest that a prior high connectivity with regions belonging to ECN can facilitate transitory recovery of consciousness in a subgroup of MCS patients that underwent tDCS treatment. Therefore, resting state-fMRI could be very valuable in detecting the neuronal conditions necessary for tDCS to improve behavior in MCS. [less ▲]

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See detailResting-state Network-specific Breakdown of Functional Connectivity during Ketamine Alteration of Consciousness in Volunteers
BONHOMME, Vincent ULiege; VANHAUDENHUYSE, Audrey ULiege; Demertzi, Athina ULiege et al

in Anesthesiology (2016), 125(5), 873-878

Background: Consciousness-altering anesthetic agents disturb connectivity between brain regions composing the resting-state consciousness networks (RSNs). The default mode network (DMn), executive control ... [more ▼]

Background: Consciousness-altering anesthetic agents disturb connectivity between brain regions composing the resting-state consciousness networks (RSNs). The default mode network (DMn), executive control network, salience network (SALn), auditory network, sensorimotor network (SMn), and visual network sustain mentation. Ketamine modifies consciousness differently from other agents, producing psychedelic dreaming and no apparent interaction with the environment. The authors used functional magnetic resonance imaging to explore ketamine-induced changes in RSNs connectivity. Methods: Fourteen healthy volunteers received stepwise intravenous infusions of ketamine up to loss of responsiveness. Because of agitation, data from six subjects were excluded from analysis. RSNs connectivity was compared between absence of ketamine (wake state [W1]), light ketamine sedation, and ketamine-induced unresponsiveness (deep sedation [S2]). Results: Increasing the depth of ketamine sedation from W1 to S2 altered DMn and SALn connectivity and suppressed the anticorrelated activity between DMn and other brain regions. During S2, DMn connectivity, particularly between the medial prefrontal cortex and the remaining network (effect size β [95% CI]: W1 = 0.20 [0.18 to 0.22]; S2 = 0.07 [0.04 to 0.09]), and DMn anticorrelated activity (e.g., right sensory cortex: W1 = −0.07 [−0.09 to −0.04]; S2 = 0.04 [0.01 to 0.06]) were broken down. SALn connectivity was nonuniformly suppressed (e.g., left parietal operculum: W1 = 0.08 [0.06 to 0.09]; S2 = 0.05 [0.02 to 0.07]). Executive control networks, auditory network, SMn, and visual network were minimally affected. Conclusions: Ketamine induces specific changes in connectivity within and between RSNs. Breakdown of frontoparietal DMn connectivity and DMn anticorrelation and sensory and SMn connectivity preservation are common to ketamine and propofol-induced alterations of consciousness. [less ▲]

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See detailCorrelation between resting state fMRI total neuronal activity and PET metabolism in healthy controls and patients with disorders of consciousness
Soddu, Andrea ULiege; Gomez, Francisco; Heine, Lizette ULiege et al

in Brain and Behavior (2016), 6(1), 1-15

Introduction: The mildly invasive 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) is a well-established imaging technique to measure ‘resting state’ cerebral metabolism. This technique made ... [more ▼]

Introduction: The mildly invasive 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) is a well-established imaging technique to measure ‘resting state’ cerebral metabolism. This technique made it possible to assess changes in metabolic activity in clinical applications, such as the study of severe brain injury and disorders of consciousness. Objective: We assessed the possi- bility of creating functional MRI activity maps, which could estimate the rela- tive levels of activity in FDG-PET cerebral metabolic maps. If no metabolic absolute measures can be extracted, our approach may still be of clinical use in centers without access to FDG-PET. It also overcomes the problem of recogniz- ing individual networks of independent component selection in functional mag- netic resonance imaging (fMRI) resting state analysis. Methods: We extracted resting state fMRI functional connectivity maps using independent component analysis and combined only components of neuronal origin. To assess neu- ronality of components a classification based on support vector machine (SVM) was used. We compared the generated maps with the FDG-PET maps in 16 healthy controls, 11 vegetative state/unresponsive wakefulness syndrome patients and four locked-in patients. Results: The results show a significant similarity with q = 0.75  0.05 for healthy controls and q = 0.58  0.09 for vegetative state/unresponsive wakefulness syndrome patients between the FDG- PET and the fMRI based maps. FDG-PET, fMRI neuronal maps, and the conjunction analysis show decreases in frontoparietal and medial regions in vegetative patients with respect to controls. Subsequent analysis in locked-in syndrome patients produced also consistent maps with healthy controls. Conclusions: The constructed resting state fMRI functional connectivity map points toward the possibility for fMRI resting state to estimate relative levels of activity in a metabolic map. [less ▲]

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See detailNeural correlates of consciousness in patients who have emerged from a minimally conscious state: A cross-sectional multimodal imaging study
Di Perri, Carol ULiege; Bahri, Mohamed Ali ULiege; Amico, Enrico ULiege et al

in Lancet Neurology (2016), 15

Background Between pathologically impaired consciousness and normal consciousness exists a scarcely researched transition zone, referred to as emergence from minimally conscious state, in which patients ... [more ▼]

Background Between pathologically impaired consciousness and normal consciousness exists a scarcely researched transition zone, referred to as emergence from minimally conscious state, in which patients regain the capacity for functional communication, object use, or both. We investigated neural correlates of consciousness in these patients compared with patients with disorders of consciousness and healthy controls, by multimodal imaging. Methods In this cross-sectional, multimodal imaging study, patients with unresponsive wakefulness syndrome, patients in a minimally conscious state, and patients who had emerged from a minimally conscious state, diagnosed with the Coma Recovery Scale–Revised, were recruited from the neurology department of the Centre Hospitalier Universitaire de Liège, Belgium. Key exclusion criteria were neuroimaging examination in an acute state, sedation or anaesthesia during scanning, large focal brain damage, motion parameters of more than 3 mm in translation and 3° in rotation, and suboptimal segmentation and normalisation. We acquired resting state functional and structural MRI data and ¹⁸F-fl uorodeoxyglucose (FDG) PET data; we used seed-based functional MRI (fMRI) analysis to investigate positive default mode network connectivity (within-network correlations) and negative default mode network connectivity (between-network anticorrelations). We correlated FDG-PET brain metabolism with fMRI connectivity. We used voxel- based morphometry to test the eff ect of anatomical deformations on functional connectivity. Findings We recruited a convenience sample of 58 patients (21 [36%] with unresponsive wakefulness syndrome, 24 [41%] in a minimally conscious state, and 13 [22%] who had emerged from a minimally conscious state) and 35 healthy controls between Oct 1, 2009, and Oct 31, 2014. We detected consciousness-level-dependent increases (from unresponsive wakefulness syndrome, minimally conscious state, emergence from minimally conscious state, to healthy controls) for positive and negative default mode network connectivity, brain metabolism, and grey matter volume (p<0·05 false discovery rate corrected for multiple comparisons). Positive default mode network connectivity diff ered between patients and controls but not among patient groups (F test p<0·0001). Negative default mode network connectivity was only detected in healthy controls and in those who had emerged from a minimally conscious state; patients with unresponsive wakefulness syndrome or in a minimally conscious state showed pathological between-network positive connectivity (hyperconnectivity; F test p<0·0001). Brain metabolism correlated with positive default mode network connectivity (Spearman’s r=0·50 [95% CI 0·26 to 0·61]; p<0·0001) and negative default mode network connectivity (Spearman’s r=–0·52 [–0·35 to –0·67); p<0·0001). Grey matter volume did not diff er between the studied groups (F test p=0·06). Interpretation Partial preservation of between-network anticorrelations, which are seemingly of neuronal origin and cannot be solely explained by morphological deformations, characterise patients who have emerged from a minimally conscious state. Conversely, patients with disorders of consciousness show pathological between-network correlations. Apart from a deeper understanding of the neural correlates of consciousness, these fi ndings have clinical implications and might be particularly relevant for outcome prediction and could inspire new therapeutic options. [less ▲]

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See detailCerebral functional connectivity periodically (de)synchronizes with anatomical constraints
Liegeois, Raphaël ULiege; Ziegler, Erik; Bahri, Mohamed Ali ULiege et al

in Brain Structure and Function (2015)

This paper studies the link between resting-state functional connectivity (FC), measured by the correlations of the fMRI BOLD time courses, and structural connectivity (SC), estimated through fiber ... [more ▼]

This paper studies the link between resting-state functional connectivity (FC), measured by the correlations of the fMRI BOLD time courses, and structural connectivity (SC), estimated through fiber tractography. Instead of a static analysis based on the correlation between SC and the FC averaged over the entire fMRI time series, we propose a dynamic analysis, based on the time evolution of the correlation between SC and a suitably windowed FC. Assessing the statistical significance of the time series against random phase permutations, our data show a pronounced peak of significance for time window widths around 20-30 TR (40-60 sec). Using the appropriate window width, we show that FC patterns oscillate between phases of high modularity, primarily shaped by anatomy, and phases of low modularity, primarily shaped by inter-network connectivity. Building upon recent results in dynamic FC, this emphasizes the potential role of SC as a transitory architecture between different highly connected resting state FC patterns. Finally, we show that networks implied in consciousness-related processes, such as the default mode network (DMN), contribute more to these brain-level fluctuations compared to other networks, such as the motor or somatosensory networks. This suggests that the fluctuations between FC and SC are capturing mind-wandering effects. [less ▲]

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See detailThalamic volume as a biomarker for Disorders Of Consciousness. Progress in Biomedical Optics and Imaging
Rubeaux, M; Mahalingam, J; Gomez, F et al

in Proceedings of SPIE (2015)

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See detailImaging correlation in non-communicating patients
Heine, Lizette ULiege; Di Perri, Carol ULiege; Soddu, Andrea ULiege et al

in Rossetti, A.O; Laureys, Steven (Eds.) Clinical Neurophysiology in Disorders of Consciousness-Brain Function Monitoring in the ICU and beyond (2015)

The diagnosis and medical management of patients with acute or chronic disorders of consciousness (DOC) are challenging. Motor-independent functional neuroimaging technologies are increasingly employed to ... [more ▼]

The diagnosis and medical management of patients with acute or chronic disorders of consciousness (DOC) are challenging. Motor-independent functional neuroimaging technologies are increasingly employed to study covert cognitive processes in the absence of behavioural reports. Studies with functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) performed in this patient population have utilized active, passive and restingstate paradigms. Active paradigms refer to mental imagery tasks that measure wilful modulation of brain signal in specific brain areas, aiming to detect command-following. Passive paradigms are used to measure brain responses to external sensory stimulation (e.g. auditory, somatosensory and visual). Alternatively, in resting-state paradigms, spontaneous brain function is assessed while subjects receive no external stimulation and are instructed to let their mind wander. Independently from each other, these methods have shown differences between healthy controls and patients, as well as among patients with DOC. However, these techniques cannot yet be used in clinical settings before robust information at the single-subject level will be provided: it is expected that multimodal research will improve the single-patient diagnosis, shed light on the prognostic biomarkers, and eventually promote the medical management of patients with consciousness alterations. [less ▲]

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See detailPrincipal-component analysis of particle motion
Chen, Hui Yao; Liegeois, Raphaël ULiege; de Bruyn, John et al

in Physical Review. E : Statistical, Nonlinear, and Soft Matter Physics (2015)

We demonstrate the application of principal-component analysis (PCA) to the analysis of particle motion data in the form of a time series of images. PCA has the ability to resolve and isolate ... [more ▼]

We demonstrate the application of principal-component analysis (PCA) to the analysis of particle motion data in the form of a time series of images. PCA has the ability to resolve and isolate spatiotemporal patterns in the data. Using simulated data, we show that this translates into the ability to separate individual frequency components of the particle motion. We also show that PCA can be used to extract the fluid viscosity from images of particles undergoing Brownian motion. PCA thus provides an efficient alternative to more traditional particle-tracking methods for the analysis of microrheological data. [less ▲]

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See detailAn independent SSVEP-based brain-computer interface in locked-in-syndrome
Lesenfants, Damien ULiege; Habbal, Dina; Lugo et al

in Journal of Neural Engineering (2014)

OBJECTIVE: Steady-state visually evoked potential (SSVEP)-based brain-computer interfaces (BCIs) allow healthy subjects to communicate. However, their dependence on gaze control prevents their use with ... [more ▼]

OBJECTIVE: Steady-state visually evoked potential (SSVEP)-based brain-computer interfaces (BCIs) allow healthy subjects to communicate. However, their dependence on gaze control prevents their use with severely disabled patients. Gaze-independent SSVEP-BCIs have been designed but have shown a drop in accuracy and have not been tested in brain-injured patients. In the present paper, we propose a novel independent SSVEP-BCI based on covert attention with an improved classification rate. We study the influence of feature extraction algorithms and the number of harmonics. Finally, we test online communication on healthy volunteers and patients with locked-in syndrome (LIS). APPROACH: Twenty-four healthy subjects and six LIS patients participated in this study. An independent covert two-class SSVEP paradigm was used with a newly developed portable light emitting diode-based 'interlaced squares' stimulation pattern. MAIN RESULTS: Mean offline and online accuracies on healthy subjects were respectively 85 ± 2% and 74 ± 13%, with eight out of twelve subjects succeeding to communicate efficiently with 80 ± 9% accuracy. Two out of six LIS patients reached an offline accuracy above the chance level, illustrating a response to a command. One out of four LIS patients could communicate online. SIGNIFICANCE: We have demonstrated the feasibility of online communication with a covert SSVEP paradigm that is truly independent of all neuromuscular functions. The potential clinical use of the presented BCI system as a diagnostic (i.e., detecting command-following) and communication tool for severely brain-injured patients will need to be further explored. [less ▲]

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See detailDiagnostic precision of PET imaging and functional MRI in disorders of consciousness: a clinical validation study
Stender, Johan; Gosseries, Olivia ULiege; Bruno, Marie-Aurélie ULiege et al

in Lancet Neurology (2014), 384(9942), 514-522

Background: Bedside clinical examinations can have high rates of misdiagnosis of unresponsive wakefulness syndrome (vegetative state) or minimally conscious state. The diagnostic and prognostic usefulness ... [more ▼]

Background: Bedside clinical examinations can have high rates of misdiagnosis of unresponsive wakefulness syndrome (vegetative state) or minimally conscious state. The diagnostic and prognostic usefulness of neuroimaging-based approaches has not been established in a clinical setting. We did a validation study of two neuroimaging-based diagnostic methods: PET imaging and functional MRI (fMRI). Methods: For this clinical validation study, we included patients referred to the University Hospital of Liège, Belgium, between January, 2008, and June, 2012, who were diagnosed by our unit with unresponsive wakefulness syndrome, locked-in syndrome, or minimally conscious state with traumatic or non-traumatic causes. We did repeated standardised clinical assessments with the Coma Recovery Scale—Revised (CRS—R), cerebral 18F-fluorodeoxyglucose (FDG) PET, and fMRI during mental activation tasks. We calculated the diagnostic accuracy of both imaging methods with CRS—R diagnosis as reference. We assessed outcome after 12 months with the Glasgow Outcome Scale—Extended. Findings: We included 41 patients with unresponsive wakefulness syndrome, four with locked-in syndrome, and 81 in a minimally conscious state (48=traumatic, 78=non-traumatic; 110=chronic, 16=subacute). 18F-FDG PET had high sensitivity for identification of patients in a minimally conscious state (93%, 95% CI 85—98) and high congruence (85%, 77—90) with behavioural CRS—R scores. The active fMRI method was less sensitive at diagnosis of a minimally conscious state (45%, 30—61) and had lower overall congruence with behavioural scores (63%, 51—73) than PET imaging. 18F-FDG PET correctly predicted outcome in 75 of 102 patients (74%, 64—81), and fMRI in 36 of 65 patients (56%, 43—67). 13 of 42 (32%) of the behaviourally unresponsive patients (ie, diagnosed as unresponsive with CRS—R) showed brain activity compatible with (minimal) consciousness (ie, activity associated with consciousness, but diminished compared with fully conscious individuals) on at least one neuroimaging test; 69% of these (9 of 13) patients subsequently recovered consciousness. Interpretation: Cerebral 18F-FDG PET could be used to complement bedside examinations and predict long-term recovery of patients with unresponsive wakefulness syndrome. Active fMRI might also be useful for differential diagnosis, but seems to be less accurate. Funding: The Belgian National Funds for Scientific Research (FNRS), Fonds Léon Fredericq, the European Commission, the James McDonnell Foundation, the Mind Science Foundation, the French Speaking Community Concerted Research Action, the University of Copenhagen, and the University of Liège. [less ▲]

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See detailMeasuring consciousness in coma and related states
Di Perri, Carol; Thibaut, Aurore ULiege; Soddu, Andrea ULiege et al

in World Journal of Radiology (2014), 6(8), 589-597

Consciousness is a prismatic and ambiguous concept that still eludes any universal definition. Severe acquired brain injuries resulting in a disorder of consciousness (DOC) provide a model from which ... [more ▼]

Consciousness is a prismatic and ambiguous concept that still eludes any universal definition. Severe acquired brain injuries resulting in a disorder of consciousness (DOC) provide a model from which insights into consciousness can be drawn. A number of recent studies highlight the difficulty in making a diagnosis in patients with DOC based only on behavioral assessments. Here we aim to provide an overview of how neuroimaging techniques can help assess patients with DOC. Such techniques are expected to facilitate a more accurate understanding of brain function in states of unconsciousness and to improve the evaluation of the patient’s cognitive abilities by providing both diagnostic and prognostic indicators. [less ▲]

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