Distribution of Spatial Complexity of EEG in Idiopathic Generalized Epilepsy and Its Change After Chronic Valproate Therapy

Dragon boat exercise reshapes the temporal-spatial dynamics of the brain

Although exercise training has been shown to enhance neurological function, there is a shortage of research on how exercise training affects the temporal-spatial synchronization properties of functional networks, which are crucial to the neurological system. This study recruited 23 professional and 24 amateur dragon boat racers to perform simulated paddling on ergometers while recording EEG. The spatiotemporal dynamics of the brain were analyzed using microstates and omega complexity. Temporal dynamics results showed that microstate D, which is associated with attentional networks, appeared significantly altered, with significantly higher duration, occurrence, and coverage in the professional group than in the amateur group. The transition probabilities of microstate D exhibited a similar pattern. The spatial dynamics results showed the professional group had lower brain complexity than the amateur group, with a significant decrease in omega complexity in the α (8-12 Hz) and β (13-30 Hz) bands. Dragon boat training may strengthen the attentive network and reduce the complexity of the brain. This study provides evidence that dragon boat exercise improves the efficiency of the cerebral functional networks on a spatiotemporal scale.

Altered resting-state brain oscillation and the associated cognitive impairments in late-life depression with different depressive severity: An EEG power spectrum and functional connectivity study

OBJECTIVE

Cognitive impairments are prevalent in late-life depression (LLD). However, it remains unclear whether there are concurrent brain oscillation alterations in resting condition across varying level of depression severity. This cross-sectional study aims to investigate the characteristics of altered resting-state oscillations, including power spectrum and functional connectivity, and their association with the cognitive impairments in LLD with different depression severity.

METHODS

A total of 65 patients with LLD and 40 elder participants without depression were recruited. Global cognition and subtle cognitive domains were evaluated. A five-minute resting-state electroencephalography (EEG) was conducted under eyes-closed conditions. Measurements included the ln-transformed absolute power for power spectrum analysis and the weighted phase lag index (wPLI) for functional connectivity analysis.

RESULTS

Attentional and executive dysfunction were exhibited in Moderate-Severe LLD group. Enhanced posterior upper gamma power was observed in both LLD groups. Additionally, enhanced parietal and fronto-parietal/occipital theta connectivity were observed in Moderate-Severe LLD group, which were associated with the attentional impairment.

LIMITATIONS

Limitations include a small sample size, concomitant medication use, and a relatively higher proportion of females.

CONCLUSIONS

Current study observed aberrant brain activity patterns in LLD across different levels of depression severity, which were linked to cognitive impairments. The altered posterior brain oscillations may be trait marker of LLD. Moreover, cognitive impairments and associated connectivity alterations were exhibited in moderate-severe group, which may be a state-like marker of moderate-to severe LLD. The study deepens understanding of cognitive impairments with the associated oscillation changes, carrying implications for neuromodulation targets in LLD.

Sleep Spindle Characteristics and Relationship with Memory Ability in Patients with Obstructive Sleep Apnea-Hypopnea Syndrome

Obstructive sleep apnea syndrome (OSAS) causes intermittent hypoxia and sleep disruption in the brain, resulting in cognitive dysfunction, but its pathogenesis is unclear. The sleep spindle wave is a transient neural event involved in sleep memory consolidation and synaptic plasticity. This study aimed to investigate the characteristics of sleep spindle activity and its relationship with memory ability in patients with OSAS. A total of 119 patients, who were divided into the OSAS group (n = 59, AHI ≥ 15) and control group (n = 60, AHI < 15) according to the Apnea Hypopnea Index (AHI), were enrolled and underwent polysomnography. Power spectral density (PSD) and omega complexity were used to analyze the characteristics of single and different brain regions of sleep spindles. Memory-related cognitive functions were assessed in all subjects, including logical memory, digit ordering, pattern recognition, spatial recognition and spatial working memory. The spindle PSD of the OSAS group was significantly slower than the control group, regardless of the slow, fast, or total spindle. The complexity of the spindles in the prefrontal and central region decreased significantly, whereas it increased in the occipital region. Sleep spindle PSD was positively correlated with logical memory and working memory. Spindle complexity was positively correlated with immediate logical and visual memory in the prefrontal region and positively correlated with immediate/delayed logical and working memory in the central region. In contrast, spindle complexity in the occipital region negatively correlated with delayed logical memory. Spindle hyperconnectivity in the prefrontal and central regions underlies declines in logical, visual and working memory and weak connections in the occipital spindles underlie the decline in delayed logical memory.

EEG-Driven Prediction Model of Oxcarbazepine Treatment Outcomes in Patients With Newly-Diagnosed Focal Epilepsy

Objective: Antiseizure medicine (ASM) is the first choice for patients with epilepsy. The choice of ASM is determined by the type of epilepsy or epileptic syndrome, which may not be suitable for certain patients. This initial choice of a particular drug affects the long-term prognosis of patients, so it is critical to select the appropriate ASMs based on the individual characteristics of a patient at the early stage of the disease. The purpose of this study is to develop a personalized prediction model to predict the probability of achieving seizure control in patients with focal epilepsy, which will help in providing a more precise initial medication to patients.

Methods: Based on response to oxcarbazepine (OXC), enrolled patients were divided into two groups: seizure-free (52 patients), not seizure-free (NSF) (22 patients). We created models to predict patients' response to OXC monotherapy by combining Electroencephalogram (EEG) complexities and 15 clinical features. The prediction models were gradient boosting decision tree-Kolmogorov complexity (GBDT-KC) and gradient boosting decision tree-Lempel-Ziv complexity (GBDT-LZC). We also constructed two additional prediction models, support vector machine-Kolmogorov complexity (SVM-KC) and SVM-LZC, and these two models were compared with the GBDT models. The performance of the models was evaluated by calculating the accuracy, precision, recall, F1-score, sensitivity, specificity, and area under the curve (AUC) of these models.

Results: The mean accuracy, precision, recall, F1-score, sensitivity, specificity, AUC of GBDT-LZC model after five-fold cross-validation were 81%, 84%, 91%, 87%, 91%, 64%, 81%, respectively. The average accuracy, precision, recall, F1-score, sensitivity, specificity, AUC of GBDT-KC model with five-fold cross-validation were 82%, 84%, 92%, 88%, 83%, 92%, 83%, respectively. We used the rank of absolute weights to separately calculate the features that have the most significant impact on the classification of the two models.

Conclusion: (1) The GBDT-KC model has the potential to be used in the clinic to predict seizure-free with OXC monotherapy. (2). Electroencephalogram complexity, especially Kolmogorov complexity (KC) may be a potential biomarker in predicting the treatment efficacy of OXC in newly diagnosed patients with focal epilepsy.

Action Video Gaming Experience Related to Altered Resting-State EEG Temporal and Spatial Complexity

Action video gaming (AVG) places sustained cognitive load on various behavioral systems, thus offering new insights into learning-related neural plasticity. This study aims to determine whether AVG experience is associated with resting-state electroencephalogram (rs-EEG) temporal and spatial complexity, and if so, whether this effect is observable across AVG subgenres. Two AVG games - League of Legends (LOL) and Player Unknown's Battle Grounds (PUBG) that represent two major AVG subgenres - were examined. We compared rs-EEG microstate and omega complexity between LOL experts and non-experts (Experiment 1) and between PUBG experts and non-experts (Experiment 2). We found that the experts and non-experts had different rs-EEG activities in both experiments, thus revealing the adaptive effect of AVG experience on brain development. Furthermore, we also found certain subgenre-specific complexity changes, supporting the recent proposal that AVG should be categorized based on the gaming mechanics of a specific game rather than a generic genre designation.

Novel analysis of fNIRS acquired dynamic hemoglobin concentrations: application in young children with autism spectrum disorder

A novel analysis of the spatial complexity of functional connectivity (SCFC) was proposed to investigate the spatial complexity of multiple dynamic functional connectivity series in an fNIRS study, using an approach combining principal component analysis and normalized entropy. The analysis was designed to describe the complex spatial features of phase synchrony based dynamic functional connectivity (dFC), which are unexplained in traditional approaches. The feasibility and validity of this method were verified in a sample of young patients with autism spectrum disorders (ASD). Our results showed that there were information exchange deficits in the right prefrontal cortex (PFC) of children with ASD, with markedly higher interregion SCFCs between the right PFC and other brain regions than those of normal controls. Furthermore, the global SCFC was significantly higher in young patients with ASD, along with considerably higher intraregion SCFCs in the prefrontal and temporal lobes which represents more diverse information exchange in these areas. The study suggests a novel method to analyze the fNIRS required dynamic hemoglobin concentrations by using concepts of SCFC. Moreover, the clinical results extend our understanding of ASD pathology, suggesting the crucial role of the right PFC during the information exchange process.

Normalized spatial complexity analysis of neural signals

The spatial complexity of neural signals, which was traditionally quantified by omega complexity, varies inversely with the global functional connectivity level across distinct region-of-interests, thus provides a novel approach in functional connectivity analysis. However, the measures in omega complexity are sensitive to the number of neural time-series. Here, normalized spatial complexity was suggested to overcome the above limitation, and was verified by the functional near-infrared spectroscopy (fNIRS) data from a previous published autism spectrum disorder (ASD) research. By this new method, several conclusions consistent with traditional approaches on the pathological mechanisms of ASD were found, i.e., the prefrontal cortex made a major contribution to the hypo-connectivity of young children with ASD. Moreover, some novel findings were also detected (e.g., significantly higher normalized regional spatial complexities of bilateral prefrontal cortices and the variability of normalized local complexity differential of right temporal lobe, and the regional differences of measures in normalized regional spatial complexity), which could not be successfully detected via traditional approaches. These results confirmed the value of this novel approach, and extended the methodology system of functional connectivity. This novel technique could be applied to the neural signal of other neuroimaging techniques and other neurological and cognitive conditions.

The influence of vertical disparity gradient and cue conflict on EEG omega complexity in Panum's limiting case

Using behavioral measures and ERP technique, researchers discovered at least two factors could influence the final perception of depth in Panum's limiting case, which are the vertical disparity gradient and the degree of cue conflict between two- and three-dimensional shapes. Although certain event-related potential components have been proved to be sensitive to the different levels of these two factors, some methodological limitations existed in this technique. In this study, we proposed that the omega complexity of EEG signal may serve as an important supplement of the traditional event-related potential technique. We found that the trials with lower vertical gradient disparity have lower omega complexity (i.e., higher global functional connectivity) of the occipital region, especially that of the right-occipital hemisphere. Moreover, for occipital omega complexity, the trials with low-cue conflict have significantly larger omega complexity than those with medium- and high-cue conflict. It is also found that the electrodes located in the middle line of the occipital region (i.e., POz and Oz) are more crucial to the impact of different levels of cue conflict on omega complexity than the other electrodes located in the left- and right-occipital hemispheres. These evidences demonstrated that the EEG omega complexity could reflect distinct neural activities evoked by Panum's limiting case configurations, with different levels of vertical disparity gradient and cue conflict. Besides, the influence of vertical disparity gradient and cue conflict on omega complexity may be regional dependent. NEW & NOTEWORTHY The EEG omega complexity could reflect distinct neural activities evoked by Panum's limiting case configurations with different levels of vertical disparity gradient and cue conflict. The influence of vertical disparity gradient and cue conflict on omega complexity is regional dependent. The omega complexity of EEG signal can serve as an important supplement of the traditional ERP technique.

The relationship between ERP components and EEG spatial complexity in a visual Go/Nogo task

The ERP components and variations of spatial complexity or functional connectivity are two distinct dimensions of neurophysiological events in the visual Go/Nogo task. Extensive studies have been conducted on these two distinct dimensions; however, no study has investigated whether these two neurophysiological events are linked to each other in the visual Go/Nogo task. The relationship between spatial complexity of electroencephalographic (EEG) data, quantified by the measure omega complexity, and event-related potential (ERP) components in a visual Go/Nogo task was studied. We found that with the increase of spatial complexity level, the latencies of N1 and N2 component were shortened and the amplitudes of N1, N2, and P3 components were decreased. The anterior Go/Nogo N2 effect and the Go/Nogo P3 effect were also found to be decreased with the increase of EEG spatial complexity. In addition, the reaction times in high spatial complexity trials were significantly shorter than those of medium and low spatial complexity trials when the time interval used to estimate the EEG spatial complexity was extended to 0∼1,000 ms after stimulus onset. These results suggest that high spatial complexity may be associated with faster cognitive processing and smaller postsynaptic potentials that occur simultaneously in large numbers of cortical pyramidal cells of certain brain regions. The EEG spatial complexity is closely related with demands of certain cognitive processes and the neural processing efficiency of human brain.

NEW & NOTEWORTHY

The reaction times, the latencies/amplitudes of event-related potential (ERP) components, the Go/Nogo N2 effect, and the Go/Nogo P3 effect are linked to the electroencephalographic (EEG) spatial complexity level. The EEG spatial complexity is closely related to demands of certain cognitive processes and could reflect the neural processing efficiency of human brain. Obtaining the single-trial ERP features through single-trial spatial complexity may be a more efficient approach than traditional methods.

Inferring spatiotemporal network patterns from intracranial EEG data

OBJECTIVE

The characterization of spatial network dynamics is desirable for a better understanding of seizure physiology. The goal of this work is to develop a computational method for identifying transient spatial patterns from intracranial electroencephalographic (iEEG) data.

METHODS

Starting with bivariate synchrony measures, such as phase correlation, a two-step clustering procedure is used to identify statistically significant spatial network patterns, whose temporal evolution can be inferred. We refer to this as the composite synchrony profile (CSP) method.

RESULTS

The CSP method was verified with simulated data and evaluated using ictal and interictal recordings from three patients with intractable epilepsy. Application of the CSP method to these clinical iEEG datasets revealed a set of distinct CSPs with topographies consistent with medial temporal/limbic and superior parietal/medial frontal networks thought to be involved in the seizure generation process.

CONCLUSIONS

By combining relatively straightforward multivariate signal processing techniques, such as phase synchrony, with clustering and statistical hypothesis testing, the methods we describe may prove useful for network definition and identification.

SIGNIFICANCE

The network patterns we observe using the CSP method cannot be inferred from direct visual inspection of the raw time series data, nor are they apparent in voltage-based topographic map sequences.

Valproate decreases EEG synchronization in a use-dependent manner in idiopathic generalized epilepsy

INTRODUCTION

In order to explore the mechanism of action of valproate (VPA) in idiopathic generalized epilepsy (IGE), the effect of VPA on cortical EEG activity was investigated.

HYPOTHESIS

VPA decreases EEG synchronization in the delta and theta frequency bands in a use-dependent manner in IGE patients.

METHODS

First setting: EEG records of 17 untreated IGE patients (NAE group) were analyzed and compared to those of 15 healthy controls (NC group). Second setting: EEG recorded in the untreated condition (NAE) was compared to the EEG recorded in the treated condition (VPA) of the patient group. Technique and analysis: 2 min of eyes-closed, waking EEG background activity (without epileptiform potentials and artifacts) were analyzed. Absolute power (AP) and mean frequency (MF) were computed for 19 electrodes and four frequency bands (delta=1.5-3.5 Hz, theta=3.5-7.5 Hz, alpha=7.5-12.5 Hz, beta=12.5-25.0 Hz). Log-transformed data entered further analysis. Group differences were computed by means of parametric statistics including correction for multiple comparisons. The VPA-related changes (APvpa-APnae) were correlated with the degree of the baseline abnormality (APnae) and the daily dose/serum levels of VPA.

MAIN RESULTS

Statistically significant (p<0.05, corrected) changes in the first setting: diffuse delta, theta, alpha AP increase, mainly right hemispheric beta AP increase was found in the NAE group, as compared to the NC group. Second setting: VPA decreased delta and theta AP. Strong correlation was demonstrated between the degree of the initial AP abnormality and the VPA-related AP decrease. AP decrease did not correlate with the daily dose and the serum level of the drug.

CONCLUSION

The hypothesis that VPA decreased EEG synchronization in the delta and theta frequency bands in a use-dependent manner was supported. The findings contribute to the understanding of the action of VPA at the network level.

Valproate selectively reduces EEG activity in anterior parts of the cortex in patients with idiopathic generalized epilepsy

PURPOSE

To localize the cortical area where the anticonvulsive drug valproate (VPA) exerts its effect in patients with idiopathic generalized epilepsy (IGE).

METHODS

In a prior study we investigated 15 IGE patients in the untreated condition and compared their low resolution electromagnetic tomography (LORETA) results to a normal control group. The investigation of these patients was continued in the present study. All the 15 patients were treated with VPA and were followed by the authors. EEG was recorded after 3 months of VPA treatment in the seizure-free patients. A total of 2min of 19-channels, common reference-recorded, waking-relaxed background activity (without paroxysmal and other, non-stationary elements) was analyzed. "Activity" (current density, amper/meters squared) was given in four frequency bands (delta, theta, alpha, beta). Band-related group differences between the present LORETA results (treated condition) and the prior LORETA results (untreated condition) were computed for all the 2394 voxels by t-tests for interdependent datasets. The statistically significant (p<0.01, uncorrected) differences of activity were projected to real cortical anatomy using the Talairach Brain Atlas.

RESULTS

Statistically significant differences between the untreated and treated condition emerged in the delta and theta bands. VPA decreased delta and theta activity in the entire frontal cortex, insula, anterior temporal cortex and hippocampus, and in the anterior part of the parietal cortex.

CONCLUSIONS

VPA decreased activity in parts of the cortex that display ictogenic properties and contribute to seizure generation in IGE. Furthermore, the anatomical distribution of the drug effect exactly corresponded to the VPA-related accumulation of neuroprotective proteins reported in experimental papers.

On the meaning and interpretation of global descriptors of brain electrical activity. Including a reply to X. Pei et al

Global descriptors of the brain's electrical activity, Sigma, Phi, and Omega, provide a comprehensive characterisation of brain functional states. Recently, Pei et al. [Pei, X., Zheng, C., Zhang, A., Duan, F., Bin, G., 2005. Discussion on "Towards a quantitative characterisation of functional states of the brain: from the nonlinear methodology to the global linear description" by J. Wackermann. Int. J. Psychophysiol. 56, 201-207] discussed the effects of signal power on the global measure of spatial complexity, Omega, and suggested a modification consisting in epoch-wise and channel-wise normalisation of input data to unit power. In the present paper, the basic principles of the global approach are reviewed, and the issues of Pei et al.'s approach are assessed. The original and the modified measures of spatial complexity are compared in two case studies. Numerical simulation shows that both methods veridically estimate small numbers of signal sources, but systematically underestimate as the number increases; the modified method yields a minor relative improvement. A study on real EEG data shows that the two measures sensibly differ only where artefactual inhomogeneities in channel variances affect the data; a combined procedure, consisting in record-wise equalisation of channel variances before Omega calculations, is suggested as the optimal strategy. Differences between the original objectives of the global methodology and the proposed modifications are pointed out and critically discussed.

Characteristic Distribution of Interictal Brain Electrical Activity in Idiopathic Generalized Epilepsy

PURPOSE

To demonstrate the anatomic localization of the cortical sources of the interictal EEG activity in human idiopathic generalized epilepsy (IGE).

METHODS

Multiple cortical and hippocampal sources of the interictal spontaneous EEG activity were investigated by low-resolution electromagnetic tomography in 15 untreated IGE patients and in 15 healthy controls. EEG activity (current density) in four frequency bands (delta: 1.5-3.5 Hz, theta: 3.5-7.5 Hz, alpha: 7.5-12.5 Hz, beta: 12.5-25.0 Hz) was computed for 2,397 voxels. Voxel-by-voxel group comparison was done between the patient and the control group. Voxels with p < 0.01 differences (between the two groups) were correlated with cortical anatomy.

RESULTS

Areas of significantly increased or decreased activity were characterized by their anatomical extension and the frequency bands involved. Five areas of bilaterally increased activity were found: rostral part of the prefrontal cortex (delta, theta); posterior part of the insula (delta); hippocampus and mediobasal temporal cortex (all frequency bands); medial parietooccipital cortex (theta, alpha, beta); dorsal and polar parts of the occipital cortex (alpha). Bilaterally decreased delta, theta, alpha activity was found in the majority of the frontal and anterior parietal cortex on the lateral surface, and in parts of the medial surface of the hemispheres. The area of decreased beta activity was less extensive. The right lateral and laterobasal temporal cortex showed decreased delta, theta, alpha, and beta activity, while its left counterpart only showed decreased delta and alpha activity in a limited part of this area.

CONCLUSIONS

(1) Pathological interictal EEG activity is not evenly distributed across the cortex in IGE. The prefrontal area of increased activity corresponds to the area that is essential in the buildup of the ictal spike-wave paroxysms (absence seizures). The existence of the posterior "center of gravity" of increased EEG activity in IGE was confirmed. The frontal area of decreased activity might be related to the cognitive deficit described in IGE patients. (2) Increased activity in a lot of ontogenetically older areas (including the hippocampi) and decreased activity in the majority of the isocortex is a peculiar pattern that argues for a developmental hypothesis for IGE.