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The ultrafast spatiotemporal dynamics of large-scale neural networks can be examined using resting-state electroencephalography (EEG) microstates, representing transient periods of synchronized neural activity that evolve dynamically over time. In adults, four canonical microstates have been shown to explain most topographic variance in resting-state EEG. Their temporal structures are age-, sex- and state-dependent, and are susceptible to pathological brain states. However, no studies have assessed the spatial and temporal properties of EEG microstates exclusively during early childhood, a critical period of rapid brain development. Here we sought to investigate EEG microstates recorded with high-density EEG in a large sample of 103, 4–8-year-old children. Using data-driven k -means cluster analysis, we show that the four canonical microstates reported in adult populations already exist in early childhood. Using multiple linear regressions, we demonstrate that the temporal dynamics of two microstates are associated with age and sex. Source localization suggests that attention- and cognitive control-related networks govern the topographies of the age- and sex-dependent microstates. These novel findings provide unique insights into functional brain development in children captured with EEG microstates. • Resting-state EEG microstates are stable periods of scalp potential topographies. • They reflect the activity of large-scale neural networks at the millisecond-level. • Age and sex relate to the temporal dynamics of two microstates during early childhood. • Their sources represent attention- and cognitive control-related networks. • Microstates provide unique insights into brain development during early childhood. [ABSTRACT FROM AUTHOR]

Abstract: There is growing evidence that the visual processing of human body stimuli is particular and distinct from that of other objects. This is due to implicit knowledge of anatomical and biomechanical constraints of the human body. The question arises whether body stimuli in which biomechanical constraints are violated are processed in the same way as realistic bodies. This study investigated the neural mechanisms of anatomically plausible and implausible body stimuli. Event-related potentials (ERP) were recorded in healthy participants during mental rotation of body parts. Subjects were shown pictures of body parts or whole bodies in which one element (finger, arm) could be anatomically accurate or inaccurate (e.g., left forearm attached to right upper arm). Furthermore, the body parts were rotated in 7 different orientations, from 0° to 180° in 30° increments, resulting in some possible and some impossible positions of the body parts. Analysis of the 123-channel ERPs was carried out by determining the successive segments of stable map topographies and comparing them between conditions. A particular segment appeared in the case of anatomically impossible postures at 190–230 ms followed by a segment reflecting mental rotation at 310–380 ms. Anatomically implausible positions are thus detected at a very early stage, before mental rotation occurs. Source estimations derived from the topographic data indicated that left occipital, bilateral frontal and two medial areas were activated in the case of impossible postures, whereas left parietal regions were strongly activated during mental rotation. This result contrasts with mental rotation of objects, which is considered to be a right parietal process. [Copyright &y& Elsevier]

Objective: Electroencephalography (EEG) is an important tool for studying the temporal dynamics of the human brain''s large-scale neuronal circuits. However, most EEG applications fail to capitalize on all of the data''s available information, particularly that concerning the location of active sources in the brain. Localizing the sources of a given scalp measurement is only achieved by solving the so-called inverse problem. By introducing reasonable a priori constraints, the inverse problem can be solved and the most probable sources in the brain at every moment in time can be accurately localized.Methods and Results: Here, we review the different EEG source localization procedures applied during the last two decades. Additionally, we detail the importance of those procedures preceding and following source estimation that are intimately linked to a successful, reliable result. We discuss (1) the number and positioning of electrodes, (2) the varieties of inverse solution models and algorithms, (3) the integration of EEG source estimations with MRI data, (4) the integration of time and frequency in source imaging, and (5) the statistical analysis of inverse solution results.Conclusions and Significance: We show that modern EEG source imaging simultaneously details the temporal and spatial dimensions of brain activity, making it an important and affordable tool to study the properties of cerebral, neural networks in cognitive and clinical neurosciences. [Copyright &y& Elsevier]

Numerous behavioral studies have highlighted the contribution of visual perceptual deficits to the nonverbal cognitive profile of individuals with 22q11.2 deletion syndrome. However, the neurobiological processes underlying these widespread behavioral alterations are yet to be fully understood. Thus, in this paper, we investigated the role of neural oscillations toward visuoperceptual deficits to elucidate the neurobiology of sensory impairments in deletion carriers. We acquired 125 high-density electroencephalography recordings during a visual grating task in a group of 62 deletion carriers and 63 control subjects. Stimulus-elicited oscillatory responses were analyzed with 1) time-frequency analysis using wavelets decomposition at sensor and source level, 2) intertrial phase coherence, and 3) Granger causality connectivity in source space. Additional analyses examined the development of neural oscillations across age bins. Deletion carriers had decreased theta-band (4–8 Hz) and gamma-band (58–68 Hz) spectral power compared with control subjects in response to the visual stimuli, with an absence of age-related increase of theta- and gamma-band responses. Moreover, adult deletion carriers had decreased gamma- and theta-band responses but increased alpha/beta desynchronization (10–25 Hz) that correlated with behavioral performance. Granger causality estimates reflected an increased frontal-occipital connectivity in the beta range (22–40 Hz). Deletion carriers exhibited decreased theta- and gamma-band responses to visual stimuli, while alpha/beta desynchronization was preserved. Overall, the lack of age-related changes in deletion carriers implicates developmental impairments in circuit mechanisms underlying neural oscillations. The dissociation between the maturation of theta/gamma- and alpha/beta-band responses may indicate a selective impairment in supragranular cortical layers, leading to compensatory top-down connectivity. [ABSTRACT FROM AUTHOR]

Electroencephalography (EEG) is a powerful method of studying the electrophysiology of the brain with high temporal resolution. Several analytical approaches to extract information from the EEG signal have been proposed. One method, termed microstate analysis , considers the multichannel EEG recording as a series of quasi-stable “microstates” that are each characterized by a unique topography of electric potentials over the entire channel array. Because this technique simultaneously considers signals recorded from all areas of the cortex, it is capable of assessing the function of large-scale brain networks whose disruption is associated with several neuropsychiatric disorders. In this review, we first introduce the method of EEG microstate analysis. We then review studies that have discovered significant changes in the resting-state microstate series in a variety of neuropsychiatric disorders and behavioral states. We discuss the potential utility of this method in detecting neurophysiological impairments in disease and monitoring neurophysiological changes in response to an intervention. Finally, we discuss how the resting-state microstate series may reflect rapid switching among neural networks while the brain is at rest, which could represent activity of resting-state networks described by other neuroimaging modalities. We conclude by commenting on the current and future status of microstate analysis, and suggest that EEG microstates represent a promising neurophysiological tool for understanding and assessing brain network dynamics on a millisecond timescale in health and disease. [ABSTRACT FROM AUTHOR]

• Spatial accuracy of 6 linear distributed inverse solutions for interictal high-density EEG source localisation was evaluated. • Low-Resolution Electromagnetic Tomography and Local Autoregressive Average best localised both patients' and simulated sources. • These two algorithms' superiority over newer inverse solutions was due to their relative robustness towards noise. To compare the spatial accuracy of 6 linear distributed inverse solutions for EEG source localisation of interictal epileptic discharges: Minimum Norm, Weighted Minimum Norm, Low-Resolution Electromagnetic Tomography (LORETA), Local Autoregressive Average (LAURA), Standardised LORETA, and Exact LORETA. Spatial accuracy was assessed clinically by retrospectively comparing the maximum source of averaged interictal discharges to the resected brain area in 30 patients with successful epilepsy surgery, based on 204-channel EEG. Additionally, localisation errors of the inverse solutions were assessed in computer simulations, with different levels of noise added to the signal in both sensor space and source space. In the clinical evaluations, the source maximum was located inside the resected brain area in 50–57% of patients when using LORETA or LAURA, while all other inverse solutions performed significantly worse (17–30%; corrected p < 0.01). In the simulation studies, when noise levels exceeded 10%, LORETA and LAURA had substantially smaller localisation errors than the other inverse solutions. LORETA and LAURA provided the highest spatial accuracy both in clinical and simulated data, alongside with a comparably high robustness towards noise. Among the different linear inverse solution algorithms tested, LORETA and LAURA might be preferred for interictal EEG source localisation. [ABSTRACT FROM AUTHOR]

Abstract: In order to investigate electroencephalographic (EEG) biomarkers of auditory processing for schizophrenia, we studied a group with a well known high-risk profile: patients with 22q11.2 deletion syndrome (22q11 DS) have a 30% risk of developing schizophrenia during adulthood. We performed high-density EEG source imaging to measure auditory gating of the P50 component of the evoked potential and middle to late latency auditory processing in 21 participants with the 22q11.2 deletion and 17 age-matched healthy controls. While we found no indication of altered P50 suppression in 22q11 DS, we observed marked differences for the first N1 component with increased amplitudes on central electrodes, corresponding to increased activations in dorsal anterior cingulate and medial frontal cortex. We also found a left lateralized reduction of activation of primary and secondary auditory cortex during the second N1 (120ms) and the P2 component in 22q11 DS. Our results show that sensory gating and activations until 50ms were preserved in 22q11 DS, while impairments appear at latencies that correspond to higher order auditory processing. While the increased activation of cingulate and medial frontal cortex could reflect developmental changes in 22q11 DS, the reduced activity seen in left auditory cortex might serve as a biomarker for the development of schizophrenia, if confirmed by longitudinal research protocols. [Copyright &y& Elsevier]

Abstract: Neuroimaging studies typically compare experimental conditions using average brain responses, thereby overlooking the stimulus-related information conveyed by distributed spatio-temporal patterns of single-trial responses. Here, we take advantage of this rich information at a single-trial level to decode stimulus-related signals in two event-related potential (ERP) studies. Our method models the statistical distribution of the voltage topographies with a Gaussian Mixture Model (GMM), which reduces the dataset to a number of representative voltage topographies. The degree of presence of these topographies across trials at specific latencies is then used to classify experimental conditions. We tested the algorithm using a cross-validation procedure in two independent EEG datasets. In the first ERP study, we classified left- versus right-hemifield checkerboard stimuli for upper and lower visual hemifields. In a second ERP study, when functional differences cannot be assumed, we classified initial versus repeated presentations of visual objects. With minimal a priori information, the GMM model provides neurophysiologically interpretable features – vis à vis voltage topographies – as well as dynamic information about brain function. This method can in principle be applied to any ERP dataset testing the functional relevance of specific time periods for stimulus processing, the predictability of subject''s behavior and cognitive states, and the discrimination between healthy and clinical populations. [Copyright &y& Elsevier]

Abstract: Objective: To test the accuracy of EEG source imaging in epilepsy patients with large cerebral lesions. It is hypothesized that lesions are most likely to change conductivity properties and to significantly impair the accuracy of electromagnetic source imaging (ESI) based on the EEG. This has, however, not been tested in patients’ EEG. Methods: Fourteen patients with focal epilepsy and large cerebral lesions underwent high-resolution (128–256 channels) interictal EEG recordings. Thirteen patients were operated, leading to seizure freedom in 12. The spike sources were localized with a distributed linear inverse solution (LAURA) and compared to the post-operative MRI or the results of other invasive or non-invasive exams. Results: In 12 patients ESI indicated the maximum source of the epileptic activity to be located within the epileptogenic zone (85%). One of the remaining cases was not seizure free after surgery. According to the ESI result, however, the focus was incompletely removed. Conclusion: High resolution ESI constrained to the individual anatomy identifies the epileptogenic focus in patients with volume relevant brain lesions with excellent accuracy, comparable to that of other non-invasive methods. Significance: Our results are of particular clinical importance, as they show that ESI can be extended to patients with large inhomogeneous lesions. [Copyright &y& Elsevier]

Objective: In patients with drug-resistant epilepsy who are candidate for surgery, non-invasive functional imaging methods are helpful in guiding surgical resections. Our main aim was to determine localisation precision of the epileptogenic focus with electric source imaging (ESI) and to compare it to other well-established imaging tools. Methods: One hundred fifty-two pharmaco-resistant epileptic patients with more than 1year post-operative follow-up were included. Sensitivity (defined as % of seizure free patients with focus localization within the resected zone) and specificity (defined as % of patients with focus localization outside the operated area) of different techniques was assessed: ESI, magnetic resonance imaging (MRI), positron emission tomography (PET) and single-photon emission-computed tomography (SPECT). Results: A total of 43 patients underwent all examinations. High-resolution ESI (>64 electrodes) using individual MRI as a head model rendered the highest sensitivity (80%) and, principally, specificity rate (88%), followed by MRI (71.4% and 50%), PET (62.9% and 37.5%) and SPECT (54.3% but a higher specificity as compared to MRI and PET of 62.5%). The sensitivity of ESI was high in both temporal and extratemporal lobe epilepsy (91% and 75%, resp). The chance to become seizure-free if the focus source maximum is resected is 97%. Conclusion: From a clinical point of view, ESI is a very attractive non-invasive technique with a high localization yield which provides superior temporal resolution in the millisecond range, as compared to methods based on changes in metabolic or vascular correlates of neural activity. From a practical perspective, this type of examination does not require sedation, it can be performed at patient’s bedside and it is suitable in the pediatric population and cognitively impaired patients. [ABSTRACT FROM AUTHOR]