Verbal fluency (VF) is a heterogeneous cognitive function that requires executive as well as lang... more Verbal fluency (VF) is a heterogeneous cognitive function that requires executive as well as language abilities. The purpose of this study was to elucidate the specificity of the resting state MEG correlates of the executive and language components. To this end, we administered a VF test, another verbal test (Vocabulary), and another executive test (Trail Making Test), and we recorded 5-min eyes-open resting-state MEG data in 28 healthy participants. We used source-reconstructed spectral power estimates to compute correlation/anticorrelation MEG clusters with the performance at each test, as well as with the advantage in performance between tests, across individuals using cluster-level statistics in the standard frequency bands. By obtaining conjunction clusters between verbal fluency scores and factor loading obtained for verbal fluency and each of the two other tests, we showed a core of slow clusters (delta to beta) localized in the right hemisphere, in adjacent parts of the prem...
How do we choose a particular action among equally valid alternatives? Nonhuman primate findings ... more How do we choose a particular action among equally valid alternatives? Nonhuman primate findings have shown that decision-making implicates modulations in unit firing rates and local field potentials (LFPs) across frontal and parietal cortices. Yet the electrophysiological brain mechanisms that underlie free choice in humans remain ill defined. Here, we address this question using rare intracerebral electroencephalography (EEG) recordings in surgical epilepsy patients performing a delayed oculomotor decision task. We find that the temporal dynamics of high-gamma (HG, 60–140 Hz) neural activity in distinct frontal and parietal brain areas robustly discriminate free choice from instructed saccade planning at the level of single trials. Classification analysis was applied to the LFP signals to isolate decision-related activity from sensory and motor planning processes. Compared with instructed saccades, free-choice trials exhibited delayed and longer-lasting HG activity during the dela...
Shifting attention to a thought: electroencephalographic dynamics during a modified word generati... more Shifting attention to a thought: electroencephalographic dynamics during a modified word generation task. Diego Cosmelli Escuela de Psicolog´ia, Pontificia Universidad Cat´olica de Chile Centro Interdiciplinario de Neurociencias, Pontificia Universidad Cat´olica de Chile Cristobal Moenne Programa de Doctorado en Ciencias de la Ingenier´ia, Pontificia Universidad Cat´olica de Chile Hern´ an Labb´ e Escuela de Psicolog´ia, Pontificia Universidad Cat´olica de Chile Karim Jerbi Brain Dynamics and Cognition Lab, INSERM U821, Lyon, France. Vladimir L´ opez Escuela de Psicolog´ia, Pontificia Universidad Cat´olica de Chile Centro Interdiciplinario de Neurociencias, Pontificia Universidad Cat´olica de Chile Francisco Aboitiz Laboratorio de Neurociencia Cognitiva, Departamento de Psiquiatr´ia, Escuela de Medicina, Pontificia Universidad Cat´ olica de Chile. Centro Interdiciplinario de Neurociencias, Pontificia Universidad Cat´olica de Chile Abstract: What happens if you are asked to come up w...
SummaryFreely choosing an action between alternatives activates a widely distributed decision cir... more SummaryFreely choosing an action between alternatives activates a widely distributed decision circuit in the brain. Primate studies suggest that oculomotor decision processes are encoded by high-frequency components of local field potentials (LFPs) recorded in frontal and parietal areas. To what extent these LFP observations extend to oculomotor decision-making in humans is unknown. Here, we address this question using intracerebral EEG recordings from 778 sites across six surgical epilepsy patients. Free saccade choices were associated with sustained high gamma (60-140 Hz) activity during the delay period in prefrontal and parietal areas. Importantly, employing single-trial signal classification to contrast free, instructed and control trials, we were able to isolate decision-related activity from sensory and motor processes. Our findings provide the first direct electrophysiological evidence in humans for the role of high gamma activity in parietal and prefrontal areas in the intr...
Recent years have witnessed a massive push towards reproducible research in neuroscience. Unfortu... more Recent years have witnessed a massive push towards reproducible research in neuroscience. Unfortunately, this endeavor is often challenged by the large diversity of tools used, project-specific custom code and the difficulty to track all user-defined parameters. NeuroPycon is an open-source multi-modal brain data analysis toolkit which provides Python-based template pipelines for advanced multi-processing of MEG, EEG, functional and anatomical MRI data, with a focus on connectivity and graph theoretical analyses. Importantly, it provides shareable parameter files to facilitate replication of all analysis steps. NeuroPycon is based on the NiPype framework which facilitates data analyses by wrapping many commonly-used neuroimaging software tools into a common Python environment. In other words, rather than being a brain imaging software with is own implementation of standard algorithms for brain signal processing, NeuroPycon seamlessly integrates existing packages (coded in python, Ma...
For the assessment of functional interactions between distinct brain regions there is a great var... more For the assessment of functional interactions between distinct brain regions there is a great variety of mathematical techniques, with well-known properties, relative merits and shortcomings; however, the methods that deal specifically with task-based fluctuations in interareal coupling are scarce, and their relative performance is unclear. In the present article, we compare two approaches used in the estimation of correlation changes between the envelope amplitudes of narrowband brain activity obtained from magnetoencephalography (MEG) recordings. One approach is an implementation of semipartial canonical correlation analysis (SP-CCA), which is formally equivalent to the psychophysiological interactions technique successfully applied to functional magnetic resonance data. The other approach, which has been used in recent electrophysiology studies, consists of simply computing linear correlation coefficients of signals from two experimental conditions and taking their differences. W...
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology, Sep 1, 2017
Neuroimaging studies provide evidence of disturbed resting-state brain networks in Schizophrenia ... more Neuroimaging studies provide evidence of disturbed resting-state brain networks in Schizophrenia (SZ). However, untangling the neuronal mechanisms that subserve these baseline alterations requires measurement of their electrophysiological underpinnings. This systematic review specifically investigates the contributions of resting-state Magnetoencephalography (MEG) in elucidating abnormal neural organization in SZ patients. A systematic literature review of resting-state MEG studies in SZ was conducted. This literature is discussed in relation to findings from resting-state fMRI and EEG, as well as to task-based MEG research in SZ population. Importantly, methodological limitations are considered and recommendations to overcome current limitations are proposed. Resting-state MEG literature in SZ points towards altered local and long-range oscillatory network dynamics in various frequency bands. Critical methodological challenges with respect to experiment design, and data collection ...
High dream recallers (HR) show a larger brain reactivity to auditory stimuli during wakefulness a... more High dream recallers (HR) show a larger brain reactivity to auditory stimuli during wakefulness and sleep as compared to low dream recallers (LR) and also more intra-sleep wakefulness (ISW), but no other modification of the sleep macrostructure. To further understand the possible causal link between brain responses, ISW and dream recall, we investigated the sleep microstructure of HR and LR, and tested whether the amplitude of auditory evoked potentials (AEPs) was predictive of arousing reactions during sleep. Participants (18 HR, 18 LR) were presented with sounds during a whole night of sleep in the lab and polysomnographic data were recorded. Sleep microstructure (arousals, rapid eye movements (REMs), muscle twitches (MTs), spindles, KCs) was assessed using visual, semi-automatic and automatic validated methods. AEPs to arousing (awakenings or arousals) and non-arousing stimuli were subsequently computed. No between-group difference in the microstructure of sleep was found. In N2 ...
International journal of developmental neuroscience : the official journal of the International Society for Developmental Neuroscience, 2017
Fragile X Syndrome (FXS) is a neurodevelopmental genetic disorder associated with cognitive and b... more Fragile X Syndrome (FXS) is a neurodevelopmental genetic disorder associated with cognitive and behavioural deficits. In particular, neuronal habituation processes have been shown to be altered in FXS patients. Yet, while such deficits have been primarily explored using auditory stimuli, less is known in the visual modality. Here, we investigated the putative alteration of repetition suppression using faces in FXS patients compared to controls that had the same age distribution. Electroencephalographic (EEG) signals were acquired while participants were presented with 18 different faces, each repeated ten times successively. The repetition suppression effect was probed by comparing the brain responses to the first and second presentation, based on task-evoked event-related potentials (ERP) as well as on task-induced oscillatory activity. We found different patterns of habituation for controls and patients both in ERP and oscillatory power. While the N170 was not affected by face rep...
Despite numerous important contributions, the investigation of brain connectivity with magnetoenc... more Despite numerous important contributions, the investigation of brain connectivity with magnetoencephalography (MEG) still faces multiple challenges. One critical aspect of source-level connectivity, largely overlooked in the literature, is the putative effect of the choice of the inverse method on the subsequent cortico-cortical coupling analysis. We set out to investigate the impact of three inverse methods on source coherence detection using simulated MEG data. To this end, thousands of randomly located pairs of sources were created. Several parameters were manipulated, including inter- and intra-source correlation strength, source size and spatial configuration. The simulated pairs of sources were then used to generate sensor-level MEG measurements at varying signal-to-noise ratios (SNR). Next, the source level power and coherence maps were calculated using three methods (a) L2-Minimum-Norm Estimate (MNE), (b) Linearly Constrained Minimum Variance (LCMV) beamforming, and (c) Dyna...
Previous research suggests visual short-term memory (VSTM) capacity and mathematical abilities ar... more Previous research suggests visual short-term memory (VSTM) capacity and mathematical abilities are significantly related. Moreover, both processes activate similar brain regions within the parietal cortex, in particular, the intraparietal sulcus; however, it is still unclear whether the neuronal underpinnings of VSTM directly correlate with mathematical operation and reasoning abilities. The main objective was to investigate the association between parieto-occipital brain activity during the retention period of a VSTM task and performance in mathematics. The authors measured mathematical abilities and VSTM capacity as well as brain activity during memory maintenance using magnetoencephalography (MEG) in 19 healthy adult participants. Event-related magnetic fields (ERFs) were computed on the MEG data. Linear regressions were used to estimate the strength of the relation between VSTM related brain activity and mathematical abilities. The amplitude of parieto-occipital cerebral activity during the retention of visual information was related to performance in 2 standardized mathematical tasks: mathematical reasoning and calculation fluency. The findings show that brain activity during retention period of a VSTM task is associated with mathematical abilities. Contributions of VSTM processes to numerical cognition should be considered in cognitive interventions. (PsycINFO Database Record
Sleep spindles and K-complexes are among the most prominent micro-events observed in electroencep... more Sleep spindles and K-complexes are among the most prominent micro-events observed in electroencephalographic (EEG) recordings during sleep. These EEG microstructures are thought to be hallmarks of sleep-related cognitive processes. Although tedious and time-consuming, their identification and quantification is important for sleep studies in both healthy subjects and patients with sleep disorders. Therefore, procedures for automatic detection of spindles and K-complexes could provide valuable assistance to researchers and clinicians in the field. Recently, we proposed a framework for joint spindle and K-complex detection (Lajnef et al., 2015a) based on a Tunable Q-factor Wavelet Transform (TQWT; Selesnick, 2011a) and morphological component analysis (MCA). Using a wide range of performance metrics, the present article provides critical validation and benchmarking of the proposed approach by applying it to open-access EEG data from the Montreal Archive of Sleep Studies (MASS; O'Re...
2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), 2015
We present a method for the study of condition-based variations of functional connectivity in the... more We present a method for the study of condition-based variations of functional connectivity in the brain with MEG data. The method is an implementation, for multivariate inputs, of the concept of psychophysiological interactions (PPI). We obtain spectral representations of estimates of brain activity, and use the signal power at specific frequency bands as inputs to our PPI model. PPI can be formulated as a multivariate linear model, which allows us to compute statistics measuring the amount of coupling change. The resulting PPI maps can be thresholded for significance controlling the familywise error rate. These thresholds are directly applicable to tests to identify the frequency bands that cause a significant effect, which are modifications of the original PPI model. Applying our method to simulations and to data from a MEG visuomotor study, we demonstrate that it is able to accurately detect modulations in interaction across space as well as the frequency bands that contribute to these modulations.
International Image Processing, Applications and Systems Conference, 2014
ABSTRACT Discrete High Frequency Oscillations (HFOs) in the range of 80–500 Hz have recently rece... more ABSTRACT Discrete High Frequency Oscillations (HFOs) in the range of 80–500 Hz have recently received attention as a promising reliable biomarkers for epileptic activity, both in scalp EEG as well as in intracranial recordings. HFOs are often characterized by variable durations (10–100 ms) and rates of occurrence (17.5 ± 9.5 / min). The total duration of HFOs is extremely small compared to the entire length of the EEG signals to be analyzed which, in the case of intracerebral recordings, are generally acquired over several days and sometimes up to weeks. As a result, visual marking of HFOs events associated with large amounts of EEG data is extremely tedious, inevitably subjective and requires a great deal of mental concentration. Therefore, automatic detection of HFOs can be very useful to propel the clinical use of HFOs as biomarkers of epileptogenic tissue and is crucial when conducting large-scale investigations of HFO activity. As a first step towards robust and reliable automatic detection, we propose in this paper a new method for HFOs detection based on Decision Tree analysis. The performance and added value of the proposed method are evaluated by comparing it with five other previously proposed methods. The HFO detection performances were tested in terms of sensitivity, False Discovery Rate (FDR) and Area Under the ROC Curve (AUC). Our results demonstrate that the decision-tree approach yields low false detection (FDR=8.62 %) but that, in its current implementation, it is not highly sensitive to HFO events (sensitivity=66.96 %). Nevertheless some advantages of the method are discussed and paths for further improvements are outlined.
Imaging neural generators from MEG magnetic fields is often considered as a compromise between co... more Imaging neural generators from MEG magnetic fields is often considered as a compromise between computationally-reasonable methodology that usually yields poor spatial resolution on the one hand, and more sophisticated approaches on the other hand, potentially leading to intractable computational costs. We approach the problem of obtaining well-resolved source images with unexcessive computation load with a multiresolution image model selection (MiMS) technique. The building blocks of the MiMS source model are parcels of the cortical surface which can be designed at multiple spatial resolutions with the combination of anatomical and functional priors. Computation charge is reduced owing to 1) compact parametric models of the activation of extended brain parcels using current multipole expansions and 2) the optimization of the generalized cross-validation error on image models, which is closed-form for the broad class of linear estimators of neural currents. Model selection can be com...
We describe the use of truncated multipolar expansions for producing dynamic images of cortical n... more We describe the use of truncated multipolar expansions for producing dynamic images of cortical neural activation from measurements of the magnetoencephalogram. We use a signal-subspace method to find the locations of a set of multipolar sources, each of which represents a region of activity in the cerebral cortex. Our method builds up an estimate of the sources in a recursive
Verbal fluency (VF) is a heterogeneous cognitive function that requires executive as well as lang... more Verbal fluency (VF) is a heterogeneous cognitive function that requires executive as well as language abilities. The purpose of this study was to elucidate the specificity of the resting state MEG correlates of the executive and language components. To this end, we administered a VF test, another verbal test (Vocabulary), and another executive test (Trail Making Test), and we recorded 5-min eyes-open resting-state MEG data in 28 healthy participants. We used source-reconstructed spectral power estimates to compute correlation/anticorrelation MEG clusters with the performance at each test, as well as with the advantage in performance between tests, across individuals using cluster-level statistics in the standard frequency bands. By obtaining conjunction clusters between verbal fluency scores and factor loading obtained for verbal fluency and each of the two other tests, we showed a core of slow clusters (delta to beta) localized in the right hemisphere, in adjacent parts of the prem...
How do we choose a particular action among equally valid alternatives? Nonhuman primate findings ... more How do we choose a particular action among equally valid alternatives? Nonhuman primate findings have shown that decision-making implicates modulations in unit firing rates and local field potentials (LFPs) across frontal and parietal cortices. Yet the electrophysiological brain mechanisms that underlie free choice in humans remain ill defined. Here, we address this question using rare intracerebral electroencephalography (EEG) recordings in surgical epilepsy patients performing a delayed oculomotor decision task. We find that the temporal dynamics of high-gamma (HG, 60–140 Hz) neural activity in distinct frontal and parietal brain areas robustly discriminate free choice from instructed saccade planning at the level of single trials. Classification analysis was applied to the LFP signals to isolate decision-related activity from sensory and motor planning processes. Compared with instructed saccades, free-choice trials exhibited delayed and longer-lasting HG activity during the dela...
Shifting attention to a thought: electroencephalographic dynamics during a modified word generati... more Shifting attention to a thought: electroencephalographic dynamics during a modified word generation task. Diego Cosmelli Escuela de Psicolog´ia, Pontificia Universidad Cat´olica de Chile Centro Interdiciplinario de Neurociencias, Pontificia Universidad Cat´olica de Chile Cristobal Moenne Programa de Doctorado en Ciencias de la Ingenier´ia, Pontificia Universidad Cat´olica de Chile Hern´ an Labb´ e Escuela de Psicolog´ia, Pontificia Universidad Cat´olica de Chile Karim Jerbi Brain Dynamics and Cognition Lab, INSERM U821, Lyon, France. Vladimir L´ opez Escuela de Psicolog´ia, Pontificia Universidad Cat´olica de Chile Centro Interdiciplinario de Neurociencias, Pontificia Universidad Cat´olica de Chile Francisco Aboitiz Laboratorio de Neurociencia Cognitiva, Departamento de Psiquiatr´ia, Escuela de Medicina, Pontificia Universidad Cat´ olica de Chile. Centro Interdiciplinario de Neurociencias, Pontificia Universidad Cat´olica de Chile Abstract: What happens if you are asked to come up w...
SummaryFreely choosing an action between alternatives activates a widely distributed decision cir... more SummaryFreely choosing an action between alternatives activates a widely distributed decision circuit in the brain. Primate studies suggest that oculomotor decision processes are encoded by high-frequency components of local field potentials (LFPs) recorded in frontal and parietal areas. To what extent these LFP observations extend to oculomotor decision-making in humans is unknown. Here, we address this question using intracerebral EEG recordings from 778 sites across six surgical epilepsy patients. Free saccade choices were associated with sustained high gamma (60-140 Hz) activity during the delay period in prefrontal and parietal areas. Importantly, employing single-trial signal classification to contrast free, instructed and control trials, we were able to isolate decision-related activity from sensory and motor processes. Our findings provide the first direct electrophysiological evidence in humans for the role of high gamma activity in parietal and prefrontal areas in the intr...
Recent years have witnessed a massive push towards reproducible research in neuroscience. Unfortu... more Recent years have witnessed a massive push towards reproducible research in neuroscience. Unfortunately, this endeavor is often challenged by the large diversity of tools used, project-specific custom code and the difficulty to track all user-defined parameters. NeuroPycon is an open-source multi-modal brain data analysis toolkit which provides Python-based template pipelines for advanced multi-processing of MEG, EEG, functional and anatomical MRI data, with a focus on connectivity and graph theoretical analyses. Importantly, it provides shareable parameter files to facilitate replication of all analysis steps. NeuroPycon is based on the NiPype framework which facilitates data analyses by wrapping many commonly-used neuroimaging software tools into a common Python environment. In other words, rather than being a brain imaging software with is own implementation of standard algorithms for brain signal processing, NeuroPycon seamlessly integrates existing packages (coded in python, Ma...
For the assessment of functional interactions between distinct brain regions there is a great var... more For the assessment of functional interactions between distinct brain regions there is a great variety of mathematical techniques, with well-known properties, relative merits and shortcomings; however, the methods that deal specifically with task-based fluctuations in interareal coupling are scarce, and their relative performance is unclear. In the present article, we compare two approaches used in the estimation of correlation changes between the envelope amplitudes of narrowband brain activity obtained from magnetoencephalography (MEG) recordings. One approach is an implementation of semipartial canonical correlation analysis (SP-CCA), which is formally equivalent to the psychophysiological interactions technique successfully applied to functional magnetic resonance data. The other approach, which has been used in recent electrophysiology studies, consists of simply computing linear correlation coefficients of signals from two experimental conditions and taking their differences. W...
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology, Sep 1, 2017
Neuroimaging studies provide evidence of disturbed resting-state brain networks in Schizophrenia ... more Neuroimaging studies provide evidence of disturbed resting-state brain networks in Schizophrenia (SZ). However, untangling the neuronal mechanisms that subserve these baseline alterations requires measurement of their electrophysiological underpinnings. This systematic review specifically investigates the contributions of resting-state Magnetoencephalography (MEG) in elucidating abnormal neural organization in SZ patients. A systematic literature review of resting-state MEG studies in SZ was conducted. This literature is discussed in relation to findings from resting-state fMRI and EEG, as well as to task-based MEG research in SZ population. Importantly, methodological limitations are considered and recommendations to overcome current limitations are proposed. Resting-state MEG literature in SZ points towards altered local and long-range oscillatory network dynamics in various frequency bands. Critical methodological challenges with respect to experiment design, and data collection ...
High dream recallers (HR) show a larger brain reactivity to auditory stimuli during wakefulness a... more High dream recallers (HR) show a larger brain reactivity to auditory stimuli during wakefulness and sleep as compared to low dream recallers (LR) and also more intra-sleep wakefulness (ISW), but no other modification of the sleep macrostructure. To further understand the possible causal link between brain responses, ISW and dream recall, we investigated the sleep microstructure of HR and LR, and tested whether the amplitude of auditory evoked potentials (AEPs) was predictive of arousing reactions during sleep. Participants (18 HR, 18 LR) were presented with sounds during a whole night of sleep in the lab and polysomnographic data were recorded. Sleep microstructure (arousals, rapid eye movements (REMs), muscle twitches (MTs), spindles, KCs) was assessed using visual, semi-automatic and automatic validated methods. AEPs to arousing (awakenings or arousals) and non-arousing stimuli were subsequently computed. No between-group difference in the microstructure of sleep was found. In N2 ...
International journal of developmental neuroscience : the official journal of the International Society for Developmental Neuroscience, 2017
Fragile X Syndrome (FXS) is a neurodevelopmental genetic disorder associated with cognitive and b... more Fragile X Syndrome (FXS) is a neurodevelopmental genetic disorder associated with cognitive and behavioural deficits. In particular, neuronal habituation processes have been shown to be altered in FXS patients. Yet, while such deficits have been primarily explored using auditory stimuli, less is known in the visual modality. Here, we investigated the putative alteration of repetition suppression using faces in FXS patients compared to controls that had the same age distribution. Electroencephalographic (EEG) signals were acquired while participants were presented with 18 different faces, each repeated ten times successively. The repetition suppression effect was probed by comparing the brain responses to the first and second presentation, based on task-evoked event-related potentials (ERP) as well as on task-induced oscillatory activity. We found different patterns of habituation for controls and patients both in ERP and oscillatory power. While the N170 was not affected by face rep...
Despite numerous important contributions, the investigation of brain connectivity with magnetoenc... more Despite numerous important contributions, the investigation of brain connectivity with magnetoencephalography (MEG) still faces multiple challenges. One critical aspect of source-level connectivity, largely overlooked in the literature, is the putative effect of the choice of the inverse method on the subsequent cortico-cortical coupling analysis. We set out to investigate the impact of three inverse methods on source coherence detection using simulated MEG data. To this end, thousands of randomly located pairs of sources were created. Several parameters were manipulated, including inter- and intra-source correlation strength, source size and spatial configuration. The simulated pairs of sources were then used to generate sensor-level MEG measurements at varying signal-to-noise ratios (SNR). Next, the source level power and coherence maps were calculated using three methods (a) L2-Minimum-Norm Estimate (MNE), (b) Linearly Constrained Minimum Variance (LCMV) beamforming, and (c) Dyna...
Previous research suggests visual short-term memory (VSTM) capacity and mathematical abilities ar... more Previous research suggests visual short-term memory (VSTM) capacity and mathematical abilities are significantly related. Moreover, both processes activate similar brain regions within the parietal cortex, in particular, the intraparietal sulcus; however, it is still unclear whether the neuronal underpinnings of VSTM directly correlate with mathematical operation and reasoning abilities. The main objective was to investigate the association between parieto-occipital brain activity during the retention period of a VSTM task and performance in mathematics. The authors measured mathematical abilities and VSTM capacity as well as brain activity during memory maintenance using magnetoencephalography (MEG) in 19 healthy adult participants. Event-related magnetic fields (ERFs) were computed on the MEG data. Linear regressions were used to estimate the strength of the relation between VSTM related brain activity and mathematical abilities. The amplitude of parieto-occipital cerebral activity during the retention of visual information was related to performance in 2 standardized mathematical tasks: mathematical reasoning and calculation fluency. The findings show that brain activity during retention period of a VSTM task is associated with mathematical abilities. Contributions of VSTM processes to numerical cognition should be considered in cognitive interventions. (PsycINFO Database Record
Sleep spindles and K-complexes are among the most prominent micro-events observed in electroencep... more Sleep spindles and K-complexes are among the most prominent micro-events observed in electroencephalographic (EEG) recordings during sleep. These EEG microstructures are thought to be hallmarks of sleep-related cognitive processes. Although tedious and time-consuming, their identification and quantification is important for sleep studies in both healthy subjects and patients with sleep disorders. Therefore, procedures for automatic detection of spindles and K-complexes could provide valuable assistance to researchers and clinicians in the field. Recently, we proposed a framework for joint spindle and K-complex detection (Lajnef et al., 2015a) based on a Tunable Q-factor Wavelet Transform (TQWT; Selesnick, 2011a) and morphological component analysis (MCA). Using a wide range of performance metrics, the present article provides critical validation and benchmarking of the proposed approach by applying it to open-access EEG data from the Montreal Archive of Sleep Studies (MASS; O'Re...
2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), 2015
We present a method for the study of condition-based variations of functional connectivity in the... more We present a method for the study of condition-based variations of functional connectivity in the brain with MEG data. The method is an implementation, for multivariate inputs, of the concept of psychophysiological interactions (PPI). We obtain spectral representations of estimates of brain activity, and use the signal power at specific frequency bands as inputs to our PPI model. PPI can be formulated as a multivariate linear model, which allows us to compute statistics measuring the amount of coupling change. The resulting PPI maps can be thresholded for significance controlling the familywise error rate. These thresholds are directly applicable to tests to identify the frequency bands that cause a significant effect, which are modifications of the original PPI model. Applying our method to simulations and to data from a MEG visuomotor study, we demonstrate that it is able to accurately detect modulations in interaction across space as well as the frequency bands that contribute to these modulations.
International Image Processing, Applications and Systems Conference, 2014
ABSTRACT Discrete High Frequency Oscillations (HFOs) in the range of 80–500 Hz have recently rece... more ABSTRACT Discrete High Frequency Oscillations (HFOs) in the range of 80–500 Hz have recently received attention as a promising reliable biomarkers for epileptic activity, both in scalp EEG as well as in intracranial recordings. HFOs are often characterized by variable durations (10–100 ms) and rates of occurrence (17.5 ± 9.5 / min). The total duration of HFOs is extremely small compared to the entire length of the EEG signals to be analyzed which, in the case of intracerebral recordings, are generally acquired over several days and sometimes up to weeks. As a result, visual marking of HFOs events associated with large amounts of EEG data is extremely tedious, inevitably subjective and requires a great deal of mental concentration. Therefore, automatic detection of HFOs can be very useful to propel the clinical use of HFOs as biomarkers of epileptogenic tissue and is crucial when conducting large-scale investigations of HFO activity. As a first step towards robust and reliable automatic detection, we propose in this paper a new method for HFOs detection based on Decision Tree analysis. The performance and added value of the proposed method are evaluated by comparing it with five other previously proposed methods. The HFO detection performances were tested in terms of sensitivity, False Discovery Rate (FDR) and Area Under the ROC Curve (AUC). Our results demonstrate that the decision-tree approach yields low false detection (FDR=8.62 %) but that, in its current implementation, it is not highly sensitive to HFO events (sensitivity=66.96 %). Nevertheless some advantages of the method are discussed and paths for further improvements are outlined.
Imaging neural generators from MEG magnetic fields is often considered as a compromise between co... more Imaging neural generators from MEG magnetic fields is often considered as a compromise between computationally-reasonable methodology that usually yields poor spatial resolution on the one hand, and more sophisticated approaches on the other hand, potentially leading to intractable computational costs. We approach the problem of obtaining well-resolved source images with unexcessive computation load with a multiresolution image model selection (MiMS) technique. The building blocks of the MiMS source model are parcels of the cortical surface which can be designed at multiple spatial resolutions with the combination of anatomical and functional priors. Computation charge is reduced owing to 1) compact parametric models of the activation of extended brain parcels using current multipole expansions and 2) the optimization of the generalized cross-validation error on image models, which is closed-form for the broad class of linear estimators of neural currents. Model selection can be com...
We describe the use of truncated multipolar expansions for producing dynamic images of cortical n... more We describe the use of truncated multipolar expansions for producing dynamic images of cortical neural activation from measurements of the magnetoencephalogram. We use a signal-subspace method to find the locations of a set of multipolar sources, each of which represents a region of activity in the cerebral cortex. Our method builds up an estimate of the sources in a recursive
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Papers by Karim Jerbi