References of "Annen, Jitka"
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See detailNeurophysiological Biomarkers of Persistent Post-Concussive Symptoms: A Scoping Reveiw
Mortaheb, Sepehr ULiege; Filippini, Maria Maddalena; Kaux, Jean-François ULiege et al

in Frontiers in Neurology (2021), 12

Background and Objectives: Persistent post-concussive symptoms (PCS) consist of neurologic and psychological complaints persisting after a mild traumatic brain injury (mTBI). It affects up to 50% of mTBI ... [more ▼]

Background and Objectives: Persistent post-concussive symptoms (PCS) consist of neurologic and psychological complaints persisting after a mild traumatic brain injury (mTBI). It affects up to 50% of mTBI patients, may cause long-term disability, and reduce patients’ quality of life. The aim of this review was to examine the possible use of different neuroimaging modalities in PCS. Methods: Articles from Pubmed database were screened to extract studies that investigated the relationship between any neuroimaging features and symptoms of PCS. Descriptive statistics were applied to report the results. Results: A total of 80 out of 939 papers were included in the final review. Ten examined conventional MRI (30% positive finding), 24 examined diffusion weighted imaging (54.17% positive finding), 23 examined functional MRI (82.61% positive finding), nine examined electro(magneto)encephalography (77.78% positive finding), and 14 examined other techniques (71% positive finding). Conclusion: MRI was the most widely used technique, while functional techniques seem to be the most sensitive tools to evaluate PCS. The common functional patterns associated with symptoms of PCS were a decreased anti-correlation between the default mode network and the task positive network and reduced brain activity in specific areas (most often in the prefrontal cortex). Significance: Our findings highlight the importance to use functional approaches which demonstrated a functional alteration in brain connectivity and activity in most studies assessing PCS. [less ▲]

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See detailCircadian and ultradian rhythms depend on the level of consciousness in disorders of consciousness
van der Lande, Glenn ULiege; Sanz, Leandro ULiege; Frasso, Gianluca ULiege et al

Conference (2021, June 01)

Background and aims: Eye opening in patients with disorders of consciousness (DOC) marks the onset of a cyclic pattern with and without arousal. In minimally conscious state (MCS) arousal may be ... [more ▼]

Background and aims: Eye opening in patients with disorders of consciousness (DOC) marks the onset of a cyclic pattern with and without arousal. In minimally conscious state (MCS) arousal may be accompanied with awareness, unlike in unresponsive wakefulness syndrome (UWS). The presence of circadian and/or ultradian rhythmicity in patients with DOC has not been well established. To this end, we analyzed actigraphy data with a method well-suited to account for the variable rhythms within and across days observed in this population. Methods: We collected actigraphy data from 73 subjects (19 controls, 35 MCS, 19 UWS) over seven days and performed analyses using PyActigraphy. Singular Spectrum Analysis, a data-driven technique, was used to decompose the signal into circadian and ultradian rhythms. Next, we will evaluate these results statistically and correlate patients’ clinical diagnoses using the Coma Recovery Scale-Revised with the phase of detected circadian rhythms. Results: Data cleaning resulted in exclusion of one control (5.3%), 10 MCS (28.6%) and nine UWS (45%) subject(s). Our preliminary results show that the strength of circadian and ultradian rhythms in actigraphy data decreases with consciousness from healthy controls to MCS and almost disappearing in UWS (Figure 1).Conclusion: Preservation of circadian/ultradian rhythms seems associated with the level of consciousness. Rhythms appear almost absent in UWS patients, which suggests limited behavioral evidence for a sleep/wake cycle although eye opening is observed. Overall, the use of actigraphy could contribute to clinical assessments in DOC, and although data quality might be suboptimal, acquisition can be repeated easily. [less ▲]

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See detailPreservation of brain activity in unresponsive patients identifies MCS star
Thibaut, Aurore ULiege; Panda, Rajanikant ULiege; Annen, Jitka ULiege et al

in Annals of Neurology (2021), 90(1), 89-100

Objectives: Brain-injured patients who are unresponsive at the bedside (i.e., vegetative state/unresponsive wakefulness syndrome – VS/UWS) may present brain activity similar to patients in minimally ... [more ▼]

Objectives: Brain-injured patients who are unresponsive at the bedside (i.e., vegetative state/unresponsive wakefulness syndrome – VS/UWS) may present brain activity similar to patients in minimally conscious state (MCS). This peculiar condition has been termed “nonbehavioural MCS” or “MCS*”. In the present study we aimed to investigate the proportion and underlying brain characteristics of patients in MCS*. Methods: Brain 18F-fluorodeoxyglucose Positron Emission Tomography (FDG-PET) was acquired on 135 brain-injured patients diagnosed in prolonged VS/UWS (n=48) or MCS (n=87). From an existing database, relative metabolic preservation in the fronto-parietal network (measured with standardized uptake value) was visually inspected by 3 experts. Patients with hypometabolism of the fronto-parietal network were labelled “VS/UWS”, while its (partial) preservation either confirmed the behavioural diagnosis of “MCS” or, in absence of behavioural signs of consciousness, suggested a diagnosis of “MCS*”. Clinical outcome at 1-year follow-up, functional connectivity, grey matter atrophy, and regional brain metabolic patterns were investigated in the three groups (VS/UWS, MCS* and MCS). Results: 67% of behavioural VS/UWS presented a partial preservation of brain metabolism (i.e., MCS*). Compared to VS/UWS patients, MCS* patients demonstrated a better outcome, global functional connectivity and grey matter preservation more compatible with the diagnosis of MCS. MCS* patients presented lower brain metabolism mostly in the posterior regions compared to MCS patients. Interpretation: MCS* is a frequent phenomenon that is associated with better outcome and better brain preservation than the diagnosis of VS/UWS. Complementary exams should be provided to all unresponsive patients before taking medical decisions. [less ▲]

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See detailMapping the functional brain state of a world champion freediver in static dry apnea
Annen, Jitka ULiege; Panda, Rajanikant ULiege; Martial, Charlotte ULiege et al

in Brain Structure and Function (2021), 226

Voluntary apnea showcases extreme human adaptability in trained individuals like professional free divers. We evaluated the psychological and physiological adaptation and the functional cerebral changes ... [more ▼]

Voluntary apnea showcases extreme human adaptability in trained individuals like professional free divers. We evaluated the psychological and physiological adaptation and the functional cerebral changes using electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) to 6.5 min of dry static apnea performed by a world champion free diver. Compared to resting state at baseline, breath holding was characterized by increased EEG power and functional connectivity in the alpha band, along with decreased delta band connectivity. fMRI connectivity was increased within the default mode network (DMN) and visual areas but decreased in pre- and postcentral cortices. While these changes occurred in regions overlapping with cerebral signatures of several meditation practices, they also display some unique features that suggest an altered somatosensory integration. As suggested by self-reports, these findings could reflect the ability of elite free divers to create a state of sensory dissociation when performing prolonged apnea. [less ▲]

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See detailNeural responses to heartbeats detect residual signs of consciousness during resting state in post-comatose patients
Candia-Rivera, Diego; Annen, Jitka ULiege; Gosseries, Olivia ULiege et al

in Journal of Neuroscience (2021)

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See detailDecreased evoked slow-activity after tDCS in disorders of consciousness
Mensen, Armand; BODART, Olivier ULiege; Thibaut, Aurore ULiege et al

in Frontiers in Systems Neuroscience (2020), 14(62),

Due to life-saving medical advances, the diagnosis and treatment of disorders of consciousness (DOC) has become a more commonly occurring clinical issue. One recently developed intervention option has ... [more ▼]

Due to life-saving medical advances, the diagnosis and treatment of disorders of consciousness (DOC) has become a more commonly occurring clinical issue. One recently developed intervention option has been non-invasive transcranial direct current stimulation. This dichotomy of patient responders may be better understood by investigating the mechanism behind the transcranial direct current stimulation (tDCS) intervention. The combination of transcranial magnetic stimulation and electroencephalography (TMS-EEG) has been an important diagnostic tool in DOC patients. We therefore examined the neural response using TMS-EEG both before and after tDCS in seven DOC patients (four diagnosed as in a minimally conscious state and three with unresponsive wakefulness syndrome). tDCS was applied over the dorsolateral prefrontal cortex, while TMS pulses were applied to the premotor cortex. None of the seven patients showed relevant behavioral change after tDCS. We did, however, find that the overall evoked slow activity was reduced following tDCS intervention. We also found a positive correlation between the strength of the slow activity and the amount of high-frequency suppression. However, there was no significant pre-post tDCS difference in high frequencies. In the resting-state EEG, we observed that both the incidence of slow waves and the positive slope of the wave were affected by tDCS. Taken together, these results suggest that the tDCS intervention can reduce the slow-wave activity component of bistability, but this may not directly affect high-frequency activity. We hypothesize that while reduced slow activity may be necessary for the recovery of neural function, especially consciousness, this alone is insufficient. [less ▲]

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See detailIslands of awareness or islands of cortical complexity?
Cecconi, Benedetta; Laureys, Steven ULiege; Annen, Jitka ULiege

in Trends in Neurosciences (2020)

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See detailConsciousness and communication BCIs in severe brain-injured patients
Annen, Jitka ULiege; Laureys, Steven ULiege; Gosseries, Olivia ULiege

in Handbook Brain-Computer Interfacing: Neural Devices for paralysis in neurological practise and beyond (2020)

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See detailAuditory and somatosensory p3 are complementary for the assessment of patients with disorders of consciousness
Annen, Jitka ULiege; Mertel, I.; Xu, R. et al

in Brain Sciences (2020), 10(10), 1-14

The evaluation of the level of consciousness in patients with disorders of consciousness (DOC) is primarily based on behavioural assessments. Patients with unresponsive wakefulness syndrome (UWS) do not ... [more ▼]

The evaluation of the level of consciousness in patients with disorders of consciousness (DOC) is primarily based on behavioural assessments. Patients with unresponsive wakefulness syndrome (UWS) do not show any sign of awareness of their environment, while minimally conscious state (MCS) patients show reproducible but fluctuating signs of awareness. Some patients, although with remaining cognitive abilities, are not able to exhibit overt voluntary responses at the bedside and may be misdiagnosed as UWS. Several studies investigated functional neuroimaging and neurophysiology as an additional tool to evaluate the level of consciousness and to detect covert command following in DOC. Most of these studies are based on auditory stimulation, neglecting patients suffering from decreased or absent hearing abilities. In the present study, we aim to assess the response to a P3-based paradigm in 40 patients with DOC and 12 healthy participants using auditory (AEP) and vibrotactile (VTP) stimulation. To this end, an EEG-based brain-computer interface was used at DOC patient’s bedside. We compared the significance of the P3 performance (i.e., the interpretation of significance of the evoked P3 response) as obtained by ‘direct processing’ (i.e., theoretical-based significance threshold) and ‘offline processing’ (i.e., permutation-based single subject level threshold). We evaluated whether the P3 performances were dependent on clinical variables such as diagnosis (UWS and MCS), aetiology and time since injury. Last we tested the dependency of AEP and VTP performances at the single subject level. Direct processing tends to overestimate P3 performance. We did not find any difference in the presence of a P3 performance according to the level of consciousness (UWS vs. MCS) or the aetiology (traumatic vs. non-traumatic brain injury). The performance achieved at the AEP paradigm was independent from what was achieved at the VTP paradigm, indicating that some patients performed better on the AEP task while others performed better on the VTP task. Our results support the importance of using multimodal approaches in the assessment of DOC patients in order to optimise the evaluation of patient’s abilities. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. [less ▲]

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See detailBrain-computer interfaces for consciousness assessment and communication in severely brain-injured patients
Annen, Jitka ULiege; Laureys, Steven ULiege; Gosseries, Olivia ULiege

in Millán, José del R.; Ramsey, Nick F. (Eds.) Handbook of Clinical Neurology. Volume 168: Brain-Computer Interfaces (2020)

Patients with disorders of consciousness (DOC) suffer from awareness deficits. Comorbidities such as motor disabilities or visual problems hamper clinical assessments, which can lead to misdiagnosis of ... [more ▼]

Patients with disorders of consciousness (DOC) suffer from awareness deficits. Comorbidities such as motor disabilities or visual problems hamper clinical assessments, which can lead to misdiagnosis of the level of consciousness and render the patient unable to communicate. Objective measures of consciousness can reduce the risk of misdiagnosis and could enable patients to communicate by voluntarily modulating their brain activity. This chapter gives an overview of the literature regarding brain-computer interface (BCI) research in DOC patients. Different auditory, visual, and motor imagery paradigms are discussed, alongside their corresponding advantages and disadvantages. At this point, the use of BCIs for DOC patients in clinical applications is still preliminary. However, perspectives on the improvements in BCIs for DOC patients seem positive, and implementation during rehabilitation shows promise. © 2020 Elsevier B.V. [less ▲]

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See detailIslands of Awareness or Cortical Complexity?
Cecconi, Benedetta ULiege; LAUREYS, Steven ULiege; Annen, Jitka ULiege

in Trends in Neurosciences (2020)

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See detailPerturbations in dynamical models of whole-brain activity dissociate between the level and stability of consciousness
Sanz Perl; Pallavicini, Carla; Pérez Ipiña, Ignacio et al

E-print/Working paper (2020)

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See detailAutomated Machine Learning-based diagnosis of impaired consciousness: cross-center and protocol generalization of EEG biomarkers.
Raimondo, Federico ULiege; Engemann, Denis; King, Jean-Remi et al

Conference (2019, September 24)

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See detailDiagnostic accuracy of the CRS-R index in patients with disorders of consciousness
Annen, Jitka ULiege; Filippini, Maria Maddalena; Bonin, Estelle ULiege et al

in Brain Injury (2019), 33(11), 1409-1412

Objective: To obtain a CRS-R index suitable for diagnosis of patients with disorders of consciousness (DOC) and compare it to other CRS-R based scores to evaluate its potential for clinics and research ... [more ▼]

Objective: To obtain a CRS-R index suitable for diagnosis of patients with disorders of consciousness (DOC) and compare it to other CRS-R based scores to evaluate its potential for clinics and research. Design: We evaluated the diagnostic accuracy of several CRS-R-based scores in 124 patients with DOC. ROC analysis of the CRS-R total score, the Rasch-based CRS-R score, CRS-R-MS and the CRS-R index evaluated the diagnostic accuracy for patients with the Unresponsive Wakefulness Syndrome (UWS) and Minimally Conscious State (MCS). Correlations were computed between the CRS-R-MS, CRS-R index, the Rasch-based score and the CRS-R total score. Results: Both the CRS-R-MS and CRS-R index ranged from 0 to 100, with a cut-off of 8.315 that perfectly distinguishes between patients with UWS and MCS. The CRS-R total score and Rasch-based score did not provide a cut-off score for patients with UWS and MCS. The proposed CRS-R index correlated with the CRS-R total score, Rasch-based score and the CRS-R-MS. Conclusion: The CRS-R index is reliable to diagnose patients with UWS and MCS and can be used in compliance with the CRS-R scoring guidelines. The obtained index offers the opportunity to improve the interpretation of clinical assessment and can be used in (longitudinal) research protocols. [less ▲]

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See detailBrain functional network segregation and integration in patients with disorders of consciousness
Panda, Rajanikant ULiege; Annen, Jitka ULiege; Gosseries, Olivia ULiege et al

Conference (2019, June 10)

Introduction: The brain regulates information flow by balancing integration and segregation of networks to facilitate flexible cognition and behavior. However, it is unclear how this mechanism manifests ... [more ▼]

Introduction: The brain regulates information flow by balancing integration and segregation of networks to facilitate flexible cognition and behavior. However, it is unclear how this mechanism manifests during loss of consciousness [1-3]. In this study, we studied brain network segregation and integration using resting state functional magnetic resonance imaging (fMRI) data to assess brain networks in patients with disorders of consciousness. Methods: Fifty-four patients with disorders of consciousness (24 unresponsive wakefulness syndrome (UWS) (M:F=16:8; mean age= 45±13), 30 minimally conscious state (MCS) (M:F=23:7; mean age= 36±14) and 30 age- and gender-matched healthy controls underwent fMRI. The resting-state MRI data were acquired during wakefulness with eyes closed using a 3 Tesla MRI scanner. Additionally a T1-weighted, structural imaging was performed for anatomical coregistration. First, the fMRI data were pre-processed for realignment, co-registration, segmentation, normalization, head motion regressed out and 0.01-0.1Hz band pass filtered. Data were then parcellated in 256 brain regions (ROIs) using Shen functional atlas from [4]. The connectivity matrix was computed using Pearson correlation. Graph theory connectivity was carried out to measure brain network topological properties in terms of network segregation and integration by computing binarized undirected connectivity matrix. Normalized clustering coefficients were computed as measures of network segregation while normalized participation coefficients were computed as measures of network integration [3]. Through integrated nodal graph measures, individual networks (such as default mode, frontoparietal, auditory, salience, subcortical and cerebellum networks) were also computed to study which networks were predominantly affected [3]. To enable comparison of network properties across groups, we used sparsity-based threshold (S) to avoid spurious results. To prevent biases associated with a single threshold, we determined a range of sparsity (0.06 ≤ S ≤ 0.5, with an increment of 0.025), which avoids excess network fragmentation at sparser thresholds. The between group differences for global (i.e., whole brain) and individual networks were computed with unpaired t-test with FDR correction for multiple comparison [5-6]. Finally the network segregation and integration mean values were correlated with Coma Recovery Scale-Revised (CRS-R) modified score [7]. Results: Patients in UWS had decreased participation coefficients (network integration) compared to those in MCS (effect size= -0.44, p<0.0001) and controls (effect size= -0.63, p<0.0001). Patients in MCS had significant decreased participation coefficients compared to controls (effect size= -0.37, p<0.001). On the other hand, patients in UWS had significant increased clustering coefficient (network segregation) compared to those in MCS (effect size= 0.39, p= <0.001) and controls (effect size= 0.63, p<0.0001). Patients in MCS had significant increased clustering coefficients compared to controls (effect size= 0.03, p<0.01). This decreased participation coefficient and increased clustering coefficient were noted predominantly observed in the frontoparietal and subcortical networks. Conclusions: Patients with disorders of consciousness present decreased in network integration and increased in network segregation. Notably, fragmentation of network integration is observed in patients in unaware patients (UWS), which indicates impaired information flow in the brain modules, especially in the frontoparietal and subcortical networks. This introduces a potential measure to classify patients with disorders of consciousness, which could ultimately be used for clinical diagnosis. Reference: 1. Fukushima, M., (2018). Structure–function relationships during segregated and integrated network states of human brain functional connectivity. Brain Structure and Function, 223(3), 1091-1106. 2. Deco, G., (2015). Rethinking segregation and integration: contributions of whole-brain modelling. Nature Reviews Neuroscience, 16(7), 430. 3. Keerativittayayut, R., (2018). Large-scale network integration in the human brain tracks temporal uctuations in memory encoding performance. eLife, 7, e32696. 4. Finn, E. S., (2015). Functional connectome ngerprinting: identifying individuals using patterns of brain connectivity. Nature neuroscience, 18(11), 1664. 5. Holla, B., (2017). Disrupted resting brain graph measures in individuals at high risk for alcoholism. Psychiatry Research: Neuroimaging, 265, 54-64. 6. Chennu, S., (2017). Brain networks predict metabolism, diagnosis and prognosis at the bedside in disorders of consciousness. Brain, 140(8), 2120-2132. 7. Demertzi, A., (2015). Intrinsic functional connectivity differentiates minimally conscious from unresponsive patients. Brain, 138(9), 2619-2631. [less ▲]

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See detail2 EEG-based methods for the diagnosis of disorders of consciousness
Sanz, Leandro ULiege; Wolff, Audrey ULiege; Fecchio, Matteo et al

Poster (2019, May 17)

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