References of "Mortaheb, Sepehr"
     in
Bookmark and Share    
Full Text
Peer Reviewed
See detailNeurophysiological effects and behavioral outcomes after tPCS and tDCS in a patient in minimally conscious state
Barra, Alice ULiege; Mortaheb, Sepehr ULiege; Carrière, Manon ULiege et al

Conference (2019, March 15)

Introduction: Non-invasive brain stimulation (NIBS)(1-4) is a promising path in the search for treatments of patients with disorders of consciousness (DOC). Transcranial pulsed-current stimulation (tPCS ... [more ▼]

Introduction: Non-invasive brain stimulation (NIBS)(1-4) is a promising path in the search for treatments of patients with disorders of consciousness (DOC). Transcranial pulsed-current stimulation (tPCS) has been used to modulate cortical and subcortical neural connectivity within 6-10Hz(5). It was successfully employed to enhance motor and cognitive functions in healthy volunteers (6) and it is theoretically able to reach deeper brain structures(7) . On the other hand, transcranial direct-current stimulation (tDCS) over left dorsolateral prefrontal cortex (DLPFC) has shown to improve cognitive functions in DOC patients as measured by the Coma Recovery Scale-Revised (CRS-R) in about 50% of patients in minimally conscious state (MCS) (8,9). These are preliminary results of an ongoing study that aim to investigate the effects of tPCS and tDCS on one patient with DOC. Methods: This was a randomized double-blind sham-controlled clinical trial on a patient with DOC. The Subject received 3 sessions of stimulation: active tPCS sham tDCS, sham tPCS with active tDCS, and sham tPCS with sham tDCS. Before and after each session we evaluated the patient with the CRS-R and recorded 10 minutes of resting EEG. The stimulation target for tPCS was the bimastoid line with a random frequency of 6-10Hz (2mA peak to peak), whereas the target for tDCS was the left DLPFC with 2mA of intensity. EEG data were pre-processed and the power of signal was calculated for each frequency band: Delta (0-4 Hz), Theta (4-8 Hz), Alpha (8-12 Hz) and Beta (12-25 Hz). A non-parametric corrected cluster permutation test(10) was used to statistically compare the power maps before and after each session. Electrode clusters with p-value below 0.01 were considered as significantly different. Results and Discussion: An increase of Alpha and Beta power and decrease of Theta and Delta power was observed after anodal tDCS together with an increase of behavioural responsiveness as measured by the CRS-R score. After active tPCS, a significant increase was observed in Theta power consistently with the frequency of the stimulation (6-10Hz). However, this increase did not result in any measurable behavioural improvement maybe due to insufficient number of sessions or inadequate frequency of stimulation. Nevertheless, it could be relevant to mention that the patient’s caregivers noticed longer periods of wakefullness and higher arousal after tPCS. Therefore, it may be hypothesized that the CRS-R was not sensitive enough to capture these behavioural changes. Conclusion: In conclusion, here tDCS and tPCS induced distinct neurophysiological and clinical effects. So far, tDCS seems to be confirmed as a promising tool to improve behavioural responsiveness of patients with DOC. On the other hand, tPCS should be explored in larger cohorts to understand if this type of stimulation can reach similar results as the ones observed for tDCS. [less ▲]

Detailed reference viewed: 69 (2 ULiège)
Full Text
See detailPupil diameter and Behavioral Responsiveness in Disorders of Consciousness
Mortaheb, Sepehr ULiege; Bonin, Estelle ULiege; Laureys, Steven ULiege et al

Poster (2019, March 15)

The clinical diagnosis of consciousness is mainly based on bedside observation of the patient's responses using standardized neurobehavioral scales. By definition, it is common to observe vigilance ... [more ▼]

The clinical diagnosis of consciousness is mainly based on bedside observation of the patient's responses using standardized neurobehavioral scales. By definition, it is common to observe vigilance fluctuation in patients in minimally conscious state (MCS) who would show reproducible but fluctuating signs of consciousness [1]. As the probability to detect voluntary responses depends on the patient's level of vigilance at the time of assessment, multiple assessments are needed in order to detect signs of consciousness and avoid misdiagnosis [2]. If this fluctuation is known in disorders of consciousness (DOC), it remains poorly understood and characterized. In this study, we investigated the relationship between pupil diameter (suggested as an objective physiological measure of alertness level in healthy subjects [3-6]) and behavioral responsiveness in DOC patients. To this end, five patients with chronic DOC (1 unresponsive wakefulness syndrome [UWS; ie, reflexive responses], 2 MCS- [ie, signs of consciousness but no signs of language preservation, 2 MCS+ [ie, signs of language preservation]; 3 males; age=47±15.16 (median ± SD), median TSI=284 days) were enrolled. For each patient, four behavioral assessments were performed in a single day using the Coma Recovery Scale-Revised. Before each assessment, pupil response was recorded for 10 minuttients (MCS-) was excluded from the analysis due to eye closure during whole recording period. Pupil diameter was recorded using Phasya Drowsimeter R100 glasses (eye images acquired at 120 Hz with a high-speed camera integrated into the glasses). Eye closure periods were marked manually. Several parameters were investigated: eye opening percentage (EOP), as well as median, variance, entropy, and Lempel-Ziv complexity of the pupil diameter. We here provide preliminary descriptive results for this small sample. We observed lower EOP and median pupil diameter when the patients were unresponsive (i.e., diagnosis of UWS) vs. when they were responsive at bedside (i.e., MCS; median EOP=74.78% vs 99.6%, median pupil diameter=21 vs 28). Variance did not show any specific pattern; however, complexity measures of entropy and Lempel-Ziv were also lower in the UWS (median entropy=9.83 vs 10.58 and median Lempel-Ziv complexity=121 vs 328). Median pupil diameter also seemed to be more sensitive to behavioural changes across different assessments. These preliminary data suggest that higher responsiveness is related to higher median and complexity of the pupillometry signal and eye opening percentage at rest, supporting that pupillometry markers could be used as potential predictor of behavioral responsiveness in DOC patients. [less ▲]

Detailed reference viewed: 42 (6 ULiège)
Full Text
Peer Reviewed
See detailDecreased integration of EEG source-space networks in disorders of consciousness
Rizkallah, Jennifer; Annen, Jitka ULiege; Modolo, Julien et al

in NeuroImage: Clinical (2019), 23

Increasing evidence links disorders of consciousness (DOC) with disruptions in functional connectivity between distant brain areas. However, to which extent the balance of brain network segregation and ... [more ▼]

Increasing evidence links disorders of consciousness (DOC) with disruptions in functional connectivity between distant brain areas. However, to which extent the balance of brain network segregation and integration is modified in DOC patients remains unclear. Using high-density electroencephalography (EEG), the objective of our study was to characterize the local and global topological changes of DOC patients' functional brain networks. Resting state high-density-EEG data were collected and analyzed from 82 participants: 61 DOC patients recovering from coma with various levels of consciousness (EMCS (n=6), MCS+ (n=29), MCS- (n=17) and UWS (n=9)), and 21 healthy subjects (i.e., controls). Functional brain networks in five different EEG frequency bands and the broadband signal were estimated using an EEG connectivity approach at the source level. Graph theory-based analyses were used to evaluate their relationship with decreasing levels of consciousness as well as group differences between healthy volunteers and DOC patient groups. Results showed that networks in DOC patients are characterized by impaired global information processing (network integration) and increased local information processing (network segregation) as compared to controls. The large-scale functional brain networks had integration decreasing with lower level of consciousness. [less ▲]

Detailed reference viewed: 24 (1 ULiège)
Full Text
Peer Reviewed
See detailA New Binarization Method for High Accuracy Handwritten Digit Recognition of Slabs in Steel Companies
Nasiri, Sanaz; Amirfattahi, Rassoul; Sadeghi, Mohammad Taghi et al

in 2017 10th Iranian Conference on Machine Vision and Image Processing (MVIP) (2017, November)

Handwritten digit recognition plays a crucial role in various automatic systems and industries nowadays. In steel companies, the code digits written on slab forehead should be recognized with high ... [more ▼]

Handwritten digit recognition plays a crucial role in various automatic systems and industries nowadays. In steel companies, the code digits written on slab forehead should be recognized with high accuracy because these codes are used for determination of suitable thickness of steel slabs in rolling procedure. Because of special artifacts exist in these kinds of images such as color sagging, faint colors, and color separation, most of the common digit recognition algorithms have low accuracy in recognition of code digits. In this paper, a new two stage algorithm is proposed in order to reach high accuracy in determination of the handwritten codes written on slabs forehead and are corrupted by color sagging, faint colors and color separation. Applying our proposed algorithm on a dataset of images of slabs in Isfahan Steel Company shows that accuracy of the algorithm is 89.12% which is much higher than common and recently proposed algorithms. [less ▲]

Detailed reference viewed: 13 (0 ULiège)
Full Text
Peer Reviewed
See detailImprovement of Flexible Design Matrix in Sparse Bayesian Learning for Multi Task fMRI Data Analysis
Shahin, Safoura; Shayegh, Farzaneh; Mortaheb, Sepehr ULiege et al

in 2016 23rd Iranian Conference on Biomedical Engineering and 2016 1st International Iranian Conference on Biomedical Engineering (ICBME) (2016, November)

Detecting the active regions of the brain during cognitive functions is one of the important problems in cognitive neuroscience and disorder diagnosis. One of the promising approaches to solve this ... [more ▼]

Detecting the active regions of the brain during cognitive functions is one of the important problems in cognitive neuroscience and disorder diagnosis. One of the promising approaches to solve this problem is to use General Linear Model (GLM) in functional Magnetic Resonance Imaging (fMRI) data. The main difficulty of the GLM method is to determine a flexible design matrix to model mentioned problem appropriately. In this paper, an approach to the critical construction of a flexible design matrix for precise detection of active regions of the brain, according to response in synthetic fMRI data based on GLM is presented. Should the design matrix is accurate, the next detection algorithm can extract a correct response from a very low signal to noise ratio (SNR); therefore, the presented design matrix is flexible to eschew over fitting and capture unfamiliar slow drifts. Using a sparse Bayesian learning method, some specific regressors are selected for flexible design matrix. Results show clearly prominent performance of suggested algorithm rather than conventional t-test methods and other conventional Bayesian analysis of fMRI data. [less ▲]

Detailed reference viewed: 17 (1 ULiège)
Full Text
Peer Reviewed
See detailWavelet Based Single Trial Event Related Potential Extraction in Very Low SNR Conditions
Mortaheb, Sepehr ULiege; Rostami, Farzad; Shahin, Safoura et al

in 2016 6th International Conference on Computer and Knowledge Engineering (ICCKE) (2016, October)

Event Related Potentials (ERPs) are generated in ongoing brain electrical activity due to visual, auditory, or sensory stimuli. These signals have very low SNR and are contaminated by background EEG ... [more ▼]

Event Related Potentials (ERPs) are generated in ongoing brain electrical activity due to visual, auditory, or sensory stimuli. These signals have very low SNR and are contaminated by background EEG. Extraction of single trial ERPs from background EEG is a challenging task due to overlapping nature of the frequency bands of ERP and EEG signals and much higher power of EEG than ERPs. In this paper we proposed a method based on wavelet transform and adaptive noise cancelers in order to extract single trial ERPs from background EEG in very low SNR conditions. Simulation results show the superiority of the proposed algorithm over the existing methods. In addition, performance of the algorithm is justified under different noise models namely White Gaussian Noise, Auto Regressive, and Real EEG signals [less ▲]

Detailed reference viewed: 14 (2 ULiège)