Theta EEG source localization using LORETA in partial epilepsy patients with and without medication

The applied principles of EEG analysis methods in neuroscience and clinical neurology

Electroencephalography (EEG) is a non-invasive measurement method for brain activity. Due to its safety, high resolution, and hypersensitivity to dynamic changes in brain neural signals, EEG has aroused much interest in scientific research and medical fields. This article reviews the types of EEG signals, multiple EEG signal analysis methods, and the application of relevant methods in the neuroscience field and for diagnosing neurological diseases. First, three types of EEG signals, including time-invariant EEG, accurate event-related EEG, and random event-related EEG, are introduced. Second, five main directions for the methods of EEG analysis, including power spectrum analysis, time-frequency analysis, connectivity analysis, source localization methods, and machine learning methods, are described in the main section, along with different sub-methods and effect evaluations for solving the same problem. Finally, the application scenarios of different EEG analysis methods are emphasized, and the advantages and disadvantages of similar methods are distinguished. This article is expected to assist researchers in selecting suitable EEG analysis methods based on their research objectives, provide references for subsequent research, and summarize current issues and prospects for the future.

Tinnitus and distress: an electroencephalography classification study

There exist no objective markers for tinnitus or tinnitus disorders, which complicates diagnosis and treatments. The combination of EEG with sophisticated classification procedures may reveal biomarkers that can identify tinnitus and accurately differentiate different levels of distress experienced by patients. EEG recordings were obtained from 129 tinnitus patients and 142 healthy controls. Linear support vector machines were used to develop two classifiers: the first differentiated tinnitus patients from controls, while the second differentiated tinnitus patients with low and high distress levels. The classifier for healthy controls and tinnitus patients performed with an average accuracy of 96 and 94% for the training and test sets, respectively. For the distress classifier, these average accuracies were 89 and 84%. Minimal overlap was observed between the features of the two classifiers. EEG-derived features made it possible to accurately differentiate healthy controls and tinnitus patients as well as low and high distress tinnitus patients. The minimal overlap between the features of the two classifiers indicates that the source of distress in tinnitus, which could also be involved in distress related to other conditions, stems from different neuronal mechanisms compared to those causing the tinnitus pathology itself.

Altered functional connectivity in newly diagnosed benign epilepsy with unilateral or bilateral centrotemporal spikes: A multi-frequency MEG study

OBJECTIVE

Rolandic epilepsy (RE) is one of the most common forms of epilepsy syndromes in children. The condition is usually accompanied with either unilateral or bilateral centrotemporal epileptic discharge. Despite the term "benign", many studies have reported that children with benign epilepsy with centrotemporal spikes (BECTS) display a range of pervasive cognitive difficulties. In addition, existing research suggests that unilateral and bilateral centrotemporal spikes may affect cognition through different mechanisms. Consequently, the present study aimed to investigate cognitive impairment and the resting-state network topology of children with benign epilepsy with unilateral centrotemporal spikes (U-BECTS) and with bilateral centrotemporal spikes (B-BECTS).

METHODS

This study recruited 14 children with U-BECTS and 14 with B-BECTS. Thereafter, cognition was assessed in 28 children with BECTS and 14 healthy controls, using the fourth edition of the Wechsler Intelligence Scale (WISC-IV). Additionally, the functional network of the brain was constructed through magnetoencephalography (MEG) to record the resting-state brain magnetic signals of the brain and by computing virtual sensor waveforms at the source level. Moreover, graph theory (GT) analysis was used to assess the properties of the brain network.

RESULTS

Children in the B-BECTS group had an earlier onset of epilepsy compared to those in the U-BECTS category. In addition, both the B-BECTS and U-BECTS groups had lower Full Scale Intelligence Quotient (FSIQ), Verbal Comprehension Index (VCI), and Working Memory Index (WMI) scores, compared to the healthy controls although only children in the B-BECTS category had lower Perceptual Reasoning Index (PRI) scores. The results also showed that both BECTS groups had increased frontal cortex connectivity in specific frequency bands. Notably, children with B-BECTS showed a more disorderly and randomized network in the 1-4-Hz and 80-250-Hz frequency bands. Moreover, GT analysis showed that children with B-BECTS had lower clustering coefficient and characteristic path length in the 80-250-Hz frequency bands and higher connection strength in the 4-8-Hz frequency bands. On the other hand, the U-BECTS group had a higher clustering coefficient in the 8-12-Hz frequency bands, compared to the healthy controls. Correlation analysis revealed that there were negative correlations between network parameters, clinical characteristics, and neuropsychological data in the U-BECTS category.

CONCLUSION

The findings revealed that children with BECTS display a diffuse early cognitive deficit. In addition, resting-state suboptimal network topology may be the mechanism of cognitive impairment in children with BECTS. The study also showed that and children with B-BECTS may be at a higher risk of cognitive impairment.

Resting-State Theta Oscillations and Reward Sensitivity in Risk Taking

Females demonstrate greater risk aversion than males on a variety of tasks, but the underlying neurobiological basis is still unclear. We studied how theta (4–7 Hz) oscillations at rest related to three different measures of risk taking. Thirty-five participants (15 females) completed the Bomb Risk Elicitation Task (BRET), which allowed us to measure risk taking during an economic game. The Domain-Specific Risk-Taking Scale (DOSPERT) was used to measure self-assessed risk attitudes as well as reward and punishment sensitivities. In addition, the Barratt Impulsiveness Scale (BIS11) was included to quantify impulsiveness. To obtain measures of frontal theta asymmetry and frontal theta power, we used magnetoencephalography (MEG) acquired prior to task completion, while participants were at rest. Frontal theta asymmetry correlated with average risk taking during the game but only in the female sample. By contrast, frontal theta power correlated with risk taking as well as with measures of reward and punishment sensitivity in the joint sample. Importantly, we showed that reward sensitivity mediated a correlation between risk taking and the power of theta oscillations localized to the anterior cingulate cortex. In addition, we observed significant sex differences in source- and sensor-space theta power, risk taking during the game, and reward sensitivity. Our findings suggest that sensitivity to rewards, associated with resting-state theta oscillations in the anterior cingulate cortex, is a trait that potentially contributes to sex differences in risk taking.

Power Spectral Differences between Transient Epileptic and Global Amnesia: An eLORETA Quantitative EEG Study

Transient epileptic amnesia (TEA) is a rare epileptic condition, often confused with transient global amnesia (TGA). In a real-life scenario, differential diagnosis between these two conditions can be hard. In this study we use power spectral analysis empowered by exact Low Resolution Brain Electromagnetic Tomography (eLORETA) to evidence the differences between TEA and TGA. Fifteen patients affected by TEA (64.2 ± 5.2 y.o.; 11 female/4 male; 10 left and 5 right temporal epileptic focus) and 15 patients affected by TGA (65.8 ± 7.2 y.o.; 11 females/4 males) were retrospectively identified in our clinical records. All patients recorded EEGs after symptoms offset. EEGs were analyzed with eLORETA to evidence power spectral contrast between the two conditions. We used an inverse problem solution to localize the source of spectral differences. We found a significant increase in beta band power over the affected hemisphere of TEA patients. Significant results corresponded to the uncus and para-hippocampal gyrus, respectively Brodmann’s Areas: 36, 35, 28, 34. We present original evidence of an increase in beta power in the affected hemisphere (AH) of TEA as compared to TGA. These differences involve key areas of the memory network located in the mesial temporal lobe. Spectral asymmetries could be used in the future to recognize cases of amnesia with a high risk of epilepsy.

Co-localization of theta-band activity and hemodynamic responses during face perception: simultaneous electroencephalography and functional near-infrared spectroscopy recordings

Face-specific neural processes in the human brain have been localized to multiple anatomical structures and associated with diverse and dynamic social functions. The question of how various face-related systems and functions may be bound together remains an active area of investigation. We hypothesize that face processing may be associated with specific frequency band oscillations that serve to integrate distributed face processing systems. Using a multimodal imaging approach, including electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), simultaneous signals were acquired during face and object picture viewing. As expected for face processing, hemodynamic activity in the right occipital face area (OFA) increased during face viewing compared to object viewing, and in a subset of participants, the expected N170 EEG response was observed for faces. Based on recently reported associations between the theta band and visual processing, we hypothesized that increased hemodynamic activity in a face processing area would also be associated with greater theta-band activity originating in the same area. Consistent with our hypothesis, theta-band oscillations were also localized to the right OFA for faces, whereas alpha- and beta-band oscillations were not. Together, these findings suggest that theta-band oscillations originating in the OFA may be part of the distributed face-specific processing mechanism.

Identifying neural drivers of benign childhood epilepsy with centrotemporal spikes

Epilepsy is a neurological disorder characterized by abnormal electrical discharges in a group of brain cells. Benign childhood epilepsy, which affect children under the age of 12 years, has been reported to contribute to the cognitive impairment of these children, even in the absence of structural abnormalities. Functional connectivity models have been applied to provide a deeper understanding of the processes that control and regulate interictal activity of benign childhood epilepsy. These studies have shown regions of increased connectivity and activity, particularly at the epileptic zone, which is usually the central region around the sensorimotor cortex, and in the immediate regions surrounding the zone and reduced activity in distant regions, such as the frontal lobe and temporal regions. The present study was designed to identify the neural drivers involved in the initiation and propagation of epileptic activity and the causal relationships between brain regions with increased and decreased connectivity and functional activity. We used three different models to identify neural drivers and casual connectivity with dynamic causal modelling (DCM) of EEG data. All models showed that the central region, the source of the epileptic activity, is the major driver of the brain network during interictal discharges. Other regions include the temporoparietal junction and temporal pole. The central region also had influence on the frontal and contralateral hemisphere, which might explain the cognitive deficits observed in these patients.

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The epileptic source is the major driver of the brain network

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Other drivers include the temporoparietal junction and temporal pole

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Epileptic source had influence on the frontal region which might explain the cognitive deficits

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The right epileptic region drives the left hemisphere during interictal epileptic discharges

Interactions between the anterior cingulate-insula network and the fronto-parietal network during perceptual decision-making

Information processing in the human brain during cognitively demanding goal-directed tasks is thought to involve several large-scale brain networks, including the anterior cingulate-insula network (aCIN) and the fronto-parietal network (FPN). Recent functional MRI (fMRI) studies have provided clues that the aCIN initiates activity changes in the FPN. However, when and how often these networks interact remains largely unknown to date. Here, we systematically examined the oscillatory interactions between the aCIN and the FPN by using the spectral Granger causality analysis of reconstructed brain source signals from the scalp electroencephalography (EEG) recorded from human participants performing a face-house perceptual categorization task. We investigated how the aCIN and the FPN interact, what the temporal sequence of events in these nodes is, and what frequency bands of information flow bind these nodes in networks. We found that beta band (13-30Hz) and gamma (30-100Hz) bands of interactions are involved between the aCIN and the FPN during decision-making tasks. In gamma band, the aCIN initiated the Granger causal control over the FPN in 25-225 ms timeframe. In beta band, the FPN achieved a control over the aCIN in 225-425 ms timeframe. These band-specific time-dependent Granger causal controls of the aCIN and the FPN were retained for behaviorally harder decision-making tasks. These findings of times and frequencies of oscillatory interactions in the aCIN and FPN provide us new insights into the general neural mechanisms for sensory information-guided, goal-directed behaviors, including perceptual decision-making processes.

The salience network dynamics in perceptual decision-making

Recent neuroimaging studies have demonstrated that the network consisting of the right anterior insula (rAI), left anterior insula (lAI) and dorsal anterior cingulate cortex (dACC) is activated in sensory stimulus-guided goal-directed behaviors. This network is often known as the salience network (SN). When and how a sensory signal enters and organizes within SN before reaching the central executive network including the prefrontal cortices is still a mystery. Previous electrophysiological studies focused on individual nodes of SN, either on dACC or rAI, have reports of conflicting findings of the earliest cortical activity within the network. Functional magnetic resonance imaging (fMRI) studies are not able to answer these questions in the time-scales of human sensory perception and decision-making. Here, using clear and noisy face-house image categorization tasks and human scalp electroencephalography (EEG) recordings combined with source reconstruction techniques, we study when and how oscillatory activity organizes SN during a perceptual decision. We uncovered that the beta-band (13-30Hz) oscillations bound SN, became most active around 100ms after the stimulus onset and the rAI acted as a main outflow hub within SN for easier decision making task. The SN activities (Granger causality measures) were negatively correlated with the decision response time (decision difficulty). These findings suggest that the SN activity precedes the executive control in mediating sensory and cognitive processing to arrive at visual perceptual decisions.

EEG Resting State Functional Connectivity Analysis in Children with Benign Epilepsy with Centrotemporal Spikes

In this study, we investigated changes in functional connectivity (FC) of the brain networks in patients with benign epilepsy with centrotemporal spikes (BECTS) compared to healthy controls using high-density EEG data collected under eyes-closed resting state condition. EEG source reconstruction was performed with exact Low Resolution Electromagnetic Tomography (eLORETA). We investigated FC between 84 Brodmann areas using lagged phase synchronization (LPS) in four frequency bands (δ, θ, α, and β). We further computed the network degree, clustering coefficient and efficiency. Compared to controls, patients displayed higher θ and α and lower β LPS values. In these frequency bands, patients were also characterized by less well ordered brain networks exhibiting higher global degrees and efficiencies and lower clustering coefficients. In the β band, patients exhibited reduced functional segregation and integration due to loss of both local and long-distance functional connections. These findings suggest that benign epileptic brain networks might be functionally disrupted due to their altered functional organization especially in the α and β frequency bands.

Electrical source localization by LORETA in patients with epilepsy: Confirmation by postoperative MRI

BACKGROUND

Few studies have been conducted that have compared electrical source localization (ESL) results obtained by analyzing ictal patterns in scalp electroencephalogram (EEG) with the brain areas that are found to be responsible for seizures using other brain imaging techniques. Additionally, adequate studies have not been performed to confirm the accuracy of ESL methods.

MATERIALS AND METHODS

In this study, ESL was conducted using LORETA (Low Resolution Brain Electromagnetic Tomography) in 9 patients with lesions apparent on magnetic resonance imaging (MRI) and in 6 patients who did not exhibit lesions on their MRIs. EEGs of patients who underwent surgery for epilepsy and had follow-ups for at least 1 year after operations were analyzed for ictal spike, rhythmic, paroxysmal fast, and obscured EEG activities. Epileptogenic zones identified in postoperative MRIs were then compared with localizations obtained by LORETA model we employed.

RESULTS

We found that brain areas determined via ESL were in concordance with resected brain areas for 13 of the 15 patients evaluated, and those 13 patients were post-operatively determined as being seizure-free.

CONCLUSION

ESL, which is a noninvasive technique, may contribute to the correct delineation of epileptogenic zones in patients who will eventually undergo surgery to treat epilepsy, (regardless of neuroimaging status). Moreover, ESL may aid in deciding on the number and localization of intracranial electrodes to be used in patients who are candidates for invasive recording.

EEG resting state analysis of cortical sources in patients with benign epilepsy with centrotemporal spikes

Benign epilepsy with centrotemporal spikes (BECTS) is the most common idiopathic childhood epilepsy, which is often associated with developmental disorders in children. In the present study, we analyzed resting state EEG spectral changes in the sensor and source spaces in eight BECTS patients compared with nine age-matched controls. Using high-resolution scalp EEG data, we assessed statistical differences in spatial distributions of EEG power spectra and cortical sources of resting state EEG rhythms in five frequency bands: δ (0.5–3.5 Hz), θ (4–8 Hz), α (8.5–13 Hz), β₁ (13.5–20 Hz) and β₂ (20.5–30 Hz) under the eyes-closed resting state condition. To further investigate the impact of centrotemporal spikes on EEG spectra, we split the EEG data of the patient group into EEG portions with and without spikes. Source localization demonstrated the homogeneity of our population of BECTS patients with a common epileptic zone over the right centrotemporal region. Significant differences in terms of both spectral power and cortical source densities were observed between controls and patients. Patients were characterized by significantly increased relative power in θ, α, β₁ and β₂ bands in the right centrotemporal areas over the spike zone and in the right temporo-parieto-occipital junction. Furthermore, the relative power in all bands significantly decreased in the bilateral frontal and parieto-occipital areas of patients regardless of the presence or absence of spikes in EEG segments. However, the spectral differences between patients and controls were more pronounced in the presence of spikes. This observation emphasized the impact of benign epilepsy on cortical source power, especially in the right centrotemporal regions. Spectral changes in bilateral frontal and parieto-occipital areas may also suggest alterations in the default mode network in BECTS patients.

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BECTS patients exhibited enhanced θ activity over all cortical regions.

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BECTS patients displayed reduced α activity at the occipital regions.

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Patients showed increased power in θ, α, β in right temporo-parieto-occipital pole.

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EEG spectral changes in BECTS patients indicate dysfunction at the epileptic zone.

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EEG spectral changes in BECTS patients may show alteration in default mode network.

Defining regions of interest using cross-frequency coupling in extratemporal lobe epilepsy patients

OBJECTIVE

Clinicians identify seizure onset zones (SOZs) for resection in an attempt to localize the epileptogenic zone (EZ), which is the cortical tissue that is indispensible for seizure generation. An automated system is proposed to objectively localize this EZ by identifying regions of interest (ROIs).

METHODS

Intracranial electroencephalogram recordings were obtained from seven patients presenting with extratemporal lobe epilepsy and the interaction between neuronal rhythms in the form of phase-amplitude coupling was investigated. Modulation of the amplitude of high frequency oscillations (HFOs) by the phase of low frequency oscillations was measured by computing the modulation index (MI). Delta- (0.5-4 Hz) and theta- (4-8 Hz) modulation of HFOs (30-450 Hz) were examined across the channels of a 64-electrode subdural grid. Surrogate analysis was performed and false discovery rates were computed to determine the significance of the modulation observed. Mean MI values were subjected to eigenvalue decomposition (EVD) and channels defining the ROIs were selected based on the components of the eigenvector corresponding to the largest eigenvalue. ROIs were compared to the SOZs identified by two independent neurologists. Global coherence values were also computed.

MAIN RESULTS

MI was found to capture the seizure in time for six of seven patients and identified ROIs in all seven. Patients were found to have a poorer post-surgical outcome when the number of EVD-selected channels that were not resected increased. Moreover, in patients who experienced a seizure-free outcome (i.e., Engel Class I) all EVD-selected channels were found to be within the resected tissue or immediately adjacent to it. In these Engel Class I patients, delta-modulated HFOs were found to identify more of the channels in the resected tissue compared to theta-modulated HFOs. However, for the Engel Class IV patient, the delta-modulated HFOs did not identify any of the channels in the resected tissue suggesting that the resected tissue was not appropriate, which was also suggested by the Engel Class IV outcome. A sensitivity of 75.4% and a false positive rate of 15.6% were achieved using delta-modulated HFOs in an Engel Class I patient.

SIGNIFICANCE

LFO-modulated HFOs can be used to identify ROIs in extratemporal lobe patients. Moreover, delta-modulated HFOs may provide more accurate localization of the EZ. These ROIs may result in better surgical outcomes when used to compliment the SOZs identified by clinicians for resection.

Spectral parameters modulation and source localization of blink-related alpha and low-beta oscillations differentiate minimally conscious state from vegetative state/unresponsive wakefulness syndrome

Recently, the cortical source of blink-related delta oscillations (delta BROs) in resting healthy subjects has been localized in the posterior cingulate cortex/precuneus (PCC/PCu), one of the main core-hubs of the default-mode network. This has been interpreted as the electrophysiological signature of the automatic monitoring of the surrounding environment while subjects are immersed in self-reflecting mental activities. Although delta BROs were directly correlated to the degree of consciousness impairment in patients with disorders of consciousness, they failed to differentiate vegetative state/unresponsive wakefulness syndrome (VS/UWS) from minimally conscious state (MCS). In the present study, we have extended the analysis of BROs to frequency bands other than delta in the attempt to find a biological marker that could support the differential diagnosis between VS/UWS and MCS. Four patients with VS/UWS, 5 patients with MCS, and 12 healthy matched controls (CTRL) underwent standard 19-channels EEG recordings during resting conditions. Three-second-lasting EEG epochs centred on each blink instance were submitted to time-frequency analyses in order to extract the normalized Blink-Related Synchronization/Desynchronization (nBRS/BRD) of three bands of interest (low-alpha, high-alpha and low-beta) in the time-window of 50–550 ms after the blink-peak and to estimate the corresponding cortical sources of electrical activity. VS/UWS nBRS/BRD levels of all three bands were lower than those related to both CTRL and MCS, thus enabling the differential diagnosis between MCS and VS/UWS. Furthermore, MCS showed an intermediate signal intensity on PCC/PCu between CTRL and VS/UWS and a higher signal intensity on the left temporo-parieto-occipital junction and inferior occipito-temporal regions when compared to VS/UWS. This peculiar pattern of activation leads us to hypothesize that resting MCS patients have a bottom-up driven activation of the task positive network and thus are tendentially prone to respond to environmental stimuli, even though in an almost unintentional way.

Cortical source of blink-related delta oscillations and their correlation with levels of consciousness

Recently, blink-related delta oscillations (delta BROs) have been observed in healthy subjects during spontaneous blinking at rest. Delta BROs have been linked with continuous gathering of information from the surrounding environment, which is classically attributed to the precuneus. Furthermore, fMRI studies have shown that precuneal activity is reduced or missing when consciousness is low or absent. We therefore hypothesized that the source of delta BROs in healthy subjects could be located in the precuneus and that delta BROs could be absent or reduced in patients with disorders of consciousness (DOC). To test these hypotheses, electroencephalographic (EEG) activity at rest was recorded in 12 healthy controls and nine patients with DOC (four vegetative states, and five minimally conscious states). Three-second-lasting EEG epochs centred on each blink instance were analyzed in both time- (BROs) and frequency domains (event-related spectral perturbation or ERSP and intertrial coherence or ITC). Cortical sources of the maximum blink-related delta power, corresponding to the positive peak of the delta BROs, were estimated by standardized Low Resolution Electromagnetic Tomography. In control subjects, as expected, the source of delta BROs was located in the precuneus, whereas in DOC patients, delta BROs were not recognizable and no precuneal localization was possible. Furthermore, we observed a direct relationship between spectral indexes and levels of cognitive functioning in all subjects participating in the study. This reinforces the hypothesis that delta BROs reflect neural processes linked with awareness of the self and of the environment.