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Background: Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for disabling fluctuations in motor symptoms in Parkinson's disease (PD) patients. However, iterative exploration of all individual contact points (four in each STN) by the clinician for optimal clinical effects may take months., Objective: In this proof of concept study we explored whether magnetoencephalography (MEG) has the potential to noninvasively measure the effects of changing the active contact point of STN-DBS on spectral power and functional connectivity in PD patients, with the ultimate aim to aid in the process of selecting the optimal contact point, and perhaps reduce the time to achieve optimal stimulation settings., Methods: The study included 30 PD patients who had undergone bilateral DBS of the STN. MEG was recorded during stimulation of each of the eight contact points separately (four on each side). Each stimulation position was projected on a vector running through the longitudinal axis of the STN, leading to one scalar value indicating a more dorsolateral or ventromedial contact point position. Using linear mixed models, the stimulation positions were correlated with band-specific absolute spectral power and functional connectivity of i) the motor cortex ipsilateral tot the stimulated side, ii) the whole brain., Results: At group level, more dorsolateral stimulation was associated with lower low-beta absolute band power in the ipsilateral motor cortex (p = .019). More ventromedial stimulation was associated with higher whole-brain absolute delta (p = .001) and theta (p = .005) power, as well as higher whole-brain theta band functional connectivity (p = .040). At the level of the individual patient, switching the active contact point caused significant changes in spectral power, but the results were highly variable., Conclusions: We demonstrate for the first time that stimulation of the dorsolateral (motor) STN in PD patients is associated with lower low-beta power values in the motor cortex. Furthermore, our group-level data show that the location of the active contact point correlates with whole-brain brain activity and connectivity. As results in individual patients were quite variable, it remains unclear if MEG is useful in the selection of the optimal DBS contact point., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: RDB received unrestricted research grants from Medtronic paid to the institution. PRS is a consultant on educational activities for Medtronic, Boston Scientific and Elekta. All other authors report no declarations of interest., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Accurate identification of the underlying cause(s) of cognitive decline and dementia is challenging due to significant symptomatic overlap between subtypes. This study presents a multi-class classification framework for subjects with subjective cognitive decline, mild cognitive impairment, Alzheimer's disease, dementia with Lewy bodies, fronto-temporal dementia and cognitive decline due to psychiatric illness, trained on source-localized resting-state magnetoencephalography data. Diagnostic profiles, describing probability estimates for each of the 6 diagnoses, were assigned to individual subjects. A balanced accuracy rate of 41% and multi-class area under the curve value of 0.75 were obtained for 6-class classification. Classification primarily depended on posterior relative delta, theta and beta power and amplitude-based functional connectivity in the beta and gamma frequency band. Dementia with Lewy bodies (sensitivity: 100%, precision: 20%) and Alzheimer's disease subjects (sensitivity: 51%, precision: 90%) could be classified most accurately. Fronto-temporal dementia subjects (sensitivity: 11%, precision: 3%) were most frequently misclassified. Magnetoencephalography biomarkers hold promise to increase diagnostic accuracy in a noninvasive manner. Diagnostic profiles could provide an intuitive tool to clinicians and may facilitate implementation of the classifier in the memory clinic., (Copyright © 2021. Published by Elsevier Inc.)

The objective of this study was to examine if patterns of resting-state brain activity and functional connectivity in cortical and subcortical regions in patients with early symptomatic amyotrophic lateral sclerosis (ALS) resemble those of behavioural variant frontotemporal dementia (bvFTD). In a cross-sectional design, eyes-closed resting-state magnetoencephalography (MEG) data of 34 ALS patients, 18 bvFTD patients and 18 age- and gender-matched healthy controls (HCs) were projected to source-space using an atlas-based beamformer. Group differences in peak frequency, band-specific oscillatory activity and functional connectivity (corrected amplitude envelope correlation) in 78 cortical regions and 12 subcortical regions were determined. False discovery rate was used to correct for multiple comparisons. BvFTD patients, as compared to ALS and HCs, showed lower relative beta power in parietal, occipital, temporal and nearly all subcortical regions. Compared to HCs, patients with ALS and patients with bvFTD had a higher delta (0.5-4 Hz) and gamma (30-48 Hz) band resting-state functional connectivity in a high number of overlapping regions in the frontal lobe and in limbic and subcortical regions. Higher delta band connectivity was widespread in the bvFTD patients compared to HCs. ALS showed a more widespread higher gamma band functional connectivity compared to bvFTD. In conclusion, MEG in early symptomatic ALS patients shows resting-state functional connectivity changes in frontal, limbic and subcortical regions that overlap considerably with bvFTD. The findings show the potential of MEG to detect brain changes in early symptomatic phases of ALS and contribute to our understanding of the disease spectrum, with ALS and bvFTD at the two extreme ends., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Objective: We aimed to test the hypothesis that computational features of the first several minutes of EEG recording can be used to estimate the risk for development of acute seizures in comatose critically-ill children., Methods: In a prospective cohort of 118 comatose children, we computed features of the first five minutes of artifact-free EEG recording (spectral power, inter-regional synchronization and cross-frequency coupling) and tested if these features could help identify the 25 children who went on to develop acute symptomatic seizures during the subsequent 48 hours of cEEG monitoring., Results: Children who developed acute seizures demonstrated higher average spectral power, particularly in the theta frequency range, and distinct patterns of inter-regional connectivity, characterized by greater connectivity at delta and theta frequencies, but weaker connectivity at beta and low gamma frequencies. Subgroup analyses among the 97 children with the same baseline EEG background pattern (generalized slowing) yielded qualitatively and quantitatively similar results., Conclusions: These computational features could be applied to baseline EEG recordings to identify critically-ill children at high risk for acute symptomatic seizures., Significance: If confirmed in independent prospective cohorts, these features would merit incorporation into a decision support system in order to optimize diagnostic and therapeutic management of seizures among comatose children., (Copyright © 2021 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

Background: Notwithstanding the large improvement in motor function in Parkinson's disease (PD) patients treated with deep brain stimulation (DBS), apathy may increase. Postoperative apathy cannot always be related to a dose reduction of dopaminergic medication and stimulation itself may play a role., Objective: We studied whether apathy in DBS-treated PD patients could be a stimulation effect., Methods: In 26 PD patients we acquired apathy scores before and >6 months after DBS of the subthalamic nucleus (STN). Magnetoencephalography recordings (ON and OFF stimulation) were performed ≥6 months after DBS placement. Change in apathy severity was correlated with (i) improvement in motor function and dose reduction of dopaminergic medication, (ii) stimulation location (merged MRI and CT-scans) and (iii) stimulation-related changes in functional connectivity of brain regions that have an alleged role in apathy., Results: Average apathy severity significantly increased after DBS (p < 0.001) and the number of patients considered apathetic increased from two to nine. Change in apathy severity did not correlate with improvement in motor function or dose reduction of dopaminergic medication. For the left hemisphere, increase in apathy was associated with a more dorsolateral stimulation location (p = 0.010). The increase in apathy severity correlated with a decrease in alpha1 functional connectivity of the dorsolateral prefrontal cortex (p = 0.006), but not with changes of the medial orbitofrontal or the anterior cingulate cortex., Conclusions: The present observations suggest that apathy after STN-DBS is not necessarily related to dose reductions of dopaminergic medication, but may be an effect of the stimulation itself. This highlights the importance of determining optimal DBS settings based on both motor and non-motor symptoms., Competing Interests: Declarations of competing interest RDB received unrestricted research grants from Medtronic. PRS is consultant on educational activities for Medtronic, Boston Scientific and Elekta. All other authors report no declarations of interest., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Patients with posterior cortical atrophy (PCA-AD) show more severe visuospatial and perceptual deficits than those with typical AD (tAD). The aim of this study was to investigate whether functional alterations measured by electroencephalography can help understand the mechanisms that explain this clinical heterogeneity. 21-channel electroencephalography recordings of 29 patients with PCA-AD were compared with 29 patients with tAD and 29 controls matched for age, gender, and disease severity. Patients with PCA-AD and tAD both showed a global decrease in fast and increase in slow oscillatory activity compared with controls. This pattern was, however, more profound in patients with PCA-AD which was driven by more extensive slowing of the posterior regions. Alpha band functional connectivity showed a similar decrease in PCA-AD and tAD. Compared with controls, a less integrated network topology was observed in PCA-AD, with a decrease of posterior and an increase of frontal hubness. In PCA-AD, decreased right parietal peak frequency correlated with worse performance on visual tasks. Regional vulnerability of the posterior network might explain the atypical pattern of neurodegeneration in PCA-AD., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Prematurely born children are at higher risk for long-term adverse motor and cognitive outcomes. The aim of this paper was to compare quantitative measures derived from electroencephalography (EEG) between extremely (EP) and very prematurely (VP) born children at 9-10 years of age. Fifty-five children born <32 weeks' of gestation underwent EEG at 9-10 years of age and were assessed for motor development and cognitive outcome. Relative frequency power and functional connectivity, as measured by the Phase Lag Index (PLI), were calculated for all frequency bands. Per subject, power spectrum and functional connectivity results were averaged over all channels and pairwise PLI values to explore differences in global frequency power and functional connectivity between EP and VP children. Brain networks were constructed for the upper alpha frequency band using the Minimum Spanning Tree method and were compared between EP and VP children. In addition, the relationships between upper alpha quantitative EEG results and cognitive and motor outcomes were investigated. Relative power and functional connectivity were significantly higher in VP than EP children in the upper alpha frequency band, and VP children had more integrated networks. A strong positive correlation was found between relative upper alpha power and motor outcome whilst controlling for gestational age, age during EEG recording, and gender (ρ = 0.493, p = 0.004). These results suggest that 9-10 years after birth, the effects of the degree of prematurity can be observed in terms of alterations in functional brain activity and that motor deficits are associated with decreases in relative upper alpha power., Competing Interests: Declaration of competing interest CPS is founder and consultant at Neurophyxia BV. She holds several patents and stocks of Neurophyxia BV. None of this work has a relationship with the current manuscript., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

Objective: In the autosomal dominant, multisystem, chronic progressive disease myotonic dystrophy type 1 (DM1), cognitive deficits may originate from disrupted functional brain networks. We aimed to use network analysis of resting-state electro-encephalography (EEG) recordings of patients with DM1 and matched unaffected controls to investigate changes in network organization in large-scale functional brain networks and correlations with cognitive deficits., Methods: In this cross-sectional study, 28 adult patients with genetically confirmed DM1 and 26 age-, sex- and education-matched unaffected controls underwent resting-state EEG and neuropsychological assessment. We calculated the Phase Lag Index (PLI) to determine EEG frequency-dependent functional connectivity between brain regions. Functional brain networks were characterized by applying concepts from graph theory and compared between-groups. Network topology was evaluated using the minimum spanning tree (MST). We evaluated correlations between network metrics and neuropsychological tests that showed statistically significant between-group differences., Results: Functional connectivity estimated as whole-brain median PLI for DM1 patients versus healthy controls was higher in theta band (0.141 [0.050] versus 0.125 [0.018], p = 0.029), and lower in the upper alpha band (0.154 [0.048] versus 0.182 [0.073], p = 0.038), respectively. Functional MST-constructed networks in DM1 patients were significantly dissimilar from healthy controls in the delta, (p = 0.009); theta, (p = 0.009); lower alpha, (p = 0.036); and upper alpha, (p = 0.008) bands. In evaluation of local MST network measures, trends toward networks with higher global integration in the theta band and lower global integration in the upper alpha band were observed. Compared to unaffected controls, DM1 patients performed worse on tests of attention, motor function, executive function and visuospatial memory. Visuospatial memory correlated with the global median PLI in the upper alpha band; the Stroop interference test correlated with betweenness centrality in this band., Conclusion: This study supports the hypothesis that brain changes in DM1 give rise to disrupted functional network organization, as modelled with EEG-based networks. Further study may help unravel the relations with clinical brain-related DM1 symptoms., Significance: EEG network analysis has potential to help understand brain related DM1 phenotypes., Funding: This work was supported by the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 305697 (OPTIMISTIC) and the Marigold Foundation., Competing Interests: Declaration of Competing Interest The authors have no competing interests., (Copyright © 2020 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an established symptomatic treatment in Parkinson's disease, yet its mechanism of action is not fully understood. Locally in the STN, stimulation lowers beta band power, in parallel with symptom relief. Therefore, beta band oscillations are sometimes referred to as "anti-kinetic". However, in recent studies functional interactions have been observed beyond the STN, which we hypothesized to reflect clinical effects of DBS. Resting-state, whole-brain magnetoencephalography (MEG) recordings and assessments on motor function were obtained in 18 Parkinson's disease patients with bilateral STN-DBS, on and off stimulation. For each brain region, we estimated source-space spectral power and functional connectivity with the rest of the brain. Stimulation led to an increase in average peak frequency and a suppression of absolute band power (delta to low-beta band) in the sensorimotor cortices. Significant changes (decreases and increases) in low-beta band functional connectivity were observed upon stimulation. Improvement in bradykinesia/rigidity was significantly related to increases in alpha2 and low-beta band functional connectivity (of sensorimotor regions, the cortex as a whole, and subcortical regions). By contrast, tremor improvement did not correlate with changes in functional connectivity. Our results highlight the distributed effects of DBS on the resting-state brain and suggest that DBS-related improvements in rigidity and bradykinesia, but not tremor, may be mediated by an increase in alpha2 and low-beta functional connectivity. Beyond the local effects of DBS in and around the STN, functional connectivity changes in these frequency bands might therefore be considered as "pro-kinetic"., Competing Interests: Declaration of Competing Interests The authors report no competing interests., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Objective: In Parkinson's Disease (PD), measures of non-dopaminergic systems involvement may reflect disease severity and therefore contribute to patient-selection for Deep Brain Stimulation (DBS). There is currently no determinant for non-dopaminergic disease severity. In this exploratory study, we investigated whether quantitative EEG reflects non-dopaminergic disease severity in PD., Methods: Sixty-three consecutive PD patients screened for DBS were included (mean age 62.4 ± 7.2 years, 32% females). Relative spectral powers and the Phase-Lag-Index (PLI) reflecting functional connectivity were analysed on routine EEGs. Non-dopaminergic disease severity was quantified using the SENS-PD score and its subdomains; motor-severity was quantified using the MDS-UPDRS III., Results: The SENS-PD composite score correlated with a spectral ratio ((δ + θ)/(α1 + α2 + β) powers) (global spectral ratio Pearson's r = 0.4, 95% Confidence Interval (95%CI) 0.1-0.6), and PLI in the α2 band (10-13 Hz) (r = -0.3, 95%CI -0.5 to -0.1). These correlations seem driven by the subdomains cognition and psychotic symptoms. MDS-UPDRS III was not significantly correlated with EEG parameters., Conclusions: EEG slowing and reduced functional connectivity in the α2 band were associated with non-dopaminergic disease severity in PD., Significance: The described EEG parameters may have complementary utility as determinants of non-dopaminergic involvement in PD., (Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

We studied neurophysiological indicators of hallucinations in Alzheimer's disease patients with hallucinations (ADhall+), and compared them with nonhallucinating AD (ADhall-) and dementia with Lewy bodies (DLBhall+) patients. Thirty-six matched ADhall+ and 108 ADhall- and 29 DLBhall+ patients were selected from the Amsterdam Dementia Cohort. Electroencephalography (EEG) spectral and functional connectivity (FC) analyses (phase lag index) were performed. Quantitative and visual EEG measures were combined in a random forest algorithm to determine which EEG-based variable(s) play a role in hallucinations. ADhall+ patients showed lower peak frequency (7.26 vs. 7.94 Hz, p < 0.01), α2-and β-power, and α2-FC but higher δ-power compared to ADhall-. ADhall+ showed lower δ-power, higher β-power, and α1-FC than DLBhall+ but did not differ in peak frequency (7.26 vs. 6.95 Hz), θ- or α-power. ADhall+ patients could be differentiated from ADhall- and DLBhall+ with a weighted accuracy of 71% with α1-power and 100% with β-FC, the 2 most differentiating features. In sum, EEG slowing and decrease in α1-and β-band activity form potential neurophysiological indicators of underlying cholinergic deficiency in ADhall+ and DLBhall+., (Copyright © 2018 Elsevier Inc. All rights reserved.)

In some patients with medically refractory epilepsy, EEG with intracerebrally placed electrodes (stereo-electroencephalography, SEEG) is needed to locate the seizure onset zone (SOZ) for successful epilepsy surgery. SEEG has limitations and entails risk of complications because of its invasive character. Non-invasive magnetoencephalography virtual electrodes (MEG-VEs) may overcome SEEG limitations and optimize electrode placement making SOZ localization safer. Our purpose was to assess whether interictal activity measured by MEG-VEs and SEEG at identical anatomical locations were comparable, and whether MEG-VEs activity properties could determine the location of a later resected brain area (RA) as an approximation of the SOZ. We analyzed data from nine patients who underwent MEG and SEEG evaluation, and surgery for medically refractory epilepsy. MEG activity was retrospectively reconstructed using beamforming to obtain VEs at the anatomical locations corresponding to those of SEEG electrodes. Spectral, functional connectivity and functional network properties were obtained for both, MEG-VEs and SEEG time series, and their correlation and reliability were established. Based on these properties, the approximation of the SOZ was characterized by the differences between RA and non-RA (NRA). We found significant positive correlation and reliability between MEG-VEs and SEEG spectral measures (particularly in delta [0.5-4 Hz], alpha2 [10-13 Hz], and beta [13-30 Hz] bands) and broadband functional connectivity. Both modalities showed significantly slower activity and a tendency towards increased broadband functional connectivity in the RA compared to the NRA. Our findings show that spectral and functional connectivity properties of non-invasively obtained MEG-VEs match those of invasive SEEG recordings, and can characterize the SOZ. This suggests that MEG-VEs might be used for optimal SEEG planning and fewer depth electrode implantations, making the localization of the SOZ safer and more successful.

We studied whether electroencephalography (EEG)-derived measures of brain oscillatory activity are related to clinical progression in nondemented, amyloid positive subjects. We included 205 nondemented amyloid positive subjects (63 subjective cognitive decline [SCD]; 142 mild cognitive impairment [MCI]) with a baseline resting-state EEG data and ≥1-year follow-up. Peak frequency and relative power of 4 frequency bands were calculated. Relationships between normalized EEG measures and time to clinical progression (conversion from SCD to MCI/dementia or from MCI to dementia) were analyzed using Cox proportional hazard models. One hundred eight (53%) subjects clinically progressed after 2.1 (IQR 1.3-3.0) years. In the total sample, none of the EEG spectral measures were significant predictors. Stratified for baseline diagnosis, we found that in SCD patients higher delta and theta power (HR [95% CI] = 1.7 [1.0-2.7] resp. 2.3 [1.2-4.4]), and lower alpha power and peak frequency (HR [95% CI] = 0.5 [0.3-1.0] resp. 0.6 [0.4-1.0]) were associated with clinical progression over time. In amyloid positive subjects with normal cognition, slowing of oscillatory brain activity is related to clinical progression., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Objective: The pathophysiological mechanisms underlying Parkinson's disease (PD)-related cognitive decline and conversion to PD dementia are poorly understood. In the healthy human brain, stable patterns of posterior-to-anterior cortical information flow have recently been demonstrated in the higher frequency bands using magnetoencephalography (MEG). In this study we estimated PD-related changes in information flow patterns, as well as the contribution of subcortical regions., Methods: Resting-state MEG recordings were acquired in moderately advanced PD patients (n=34; mean Hoehn and Yahr-stage 2.5) and healthy controls (n=12). MEG signals were projected to both cortical and subcortical brain regions, following which we estimated the balance between incoming and outgoing information flow per region., Results: In PD patients, compared to controls, preferential beta band information outflow was significantly higher for the basal ganglia and frontotemporal cortical regions, and significantly lower for parieto-occipital regions. In addition, in patients, low preferential information outflow from occipital regions correlated with poor global cognitive performance., Conclusion: In the PD brain, a shift in balance towards more anterior-to-posterior beta band information flow takes place and is associated with poorer cognitive performance., Significance: Our results indicate that a reversal of the physiological posterior-to-anterior information flow may be an important mechanism in PD-related cognitive decline., (Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

Objective: To gain insight in the underlying mechanism of reduced levels of consciousness due to hypoactive delirium versus recovery from anesthesia, we studied functional connectivity and network topology using electroencephalography (EEG)., Methods: EEG recordings were performed in age and sex-matched patients with hypoactive delirium (n=18), patients recovering from anesthesia (n=20), and non-delirious control patients (n=20), all after cardiac surgery. Functional and directed connectivity were studied with phase lag index and directed phase transfer entropy. Network topology was characterized using the minimum spanning tree (MST). A random forest classifier was calculated based on all measures to obtain discriminative ability between the three groups., Results: Non-delirious control subjects showed a back-to-front information flow, which was lost during hypoactive delirium (p=0.01) and recovery from anesthesia (p<0.01). The recovery from anesthesia group had more integrated network in the delta band compared to non-delirious controls. In contrast, hypoactive delirium showed a less integrated network in the alpha band. High accuracy for discrimination between hypoactive delirious patients and controls (86%) and recovery from anesthesia and controls (95%) were found. Accuracy for discrimination between hypoactive delirium and recovery from anesthesia was 73%., Conclusion: Loss of functional and directed connectivity were observed in both hypoactive delirium and recovery from anesthesia, which might be related to the reduced level of consciousness in both states. These states could be distinguished in topology, which was a less integrated network during hypoactive delirium., Significance: Functional and directed connectivity are similarly disturbed during a reduced level of consciousness due to hypoactive delirium and sedatives, however topology was differently affected., (Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

Objective: Previous studies have associated network hubs and epileptiform activity, such as spikes and high frequency oscillations (HFOs), with the epileptogenic zone. The epileptogenic zone is approximated by the area that generates interictal epileptiform activity: the irritative zone. Our aim was to determine the relation between network hubs and the irritative zone., Methods: Interictal resting-state MEG recordings of 12 patients with refractory epilepsy were analysed. Beamformer-based virtual electrodes were calculated at 70 locations around the epileptic spikes (irritative zone) and in the contralateral hemisphere. Spikes and HFOs were marked in all virtual electrodes. A minimum spanning tree network was generated based on functional connectivity (phase lag index; PLI) between all virtual electrodes to calculate the betweenness centrality, an indicator of hub status of network nodes., Results: Betweenness centrality was low, and PLI was high, in virtual electrodes close to the centre of the irritative zone, and in virtual electrodes with many spikes and HFOs., Conclusion: Node centrality increases with distance from brain areas with spikes and HFOs, consistent with the idea that the irritative zone is a functionally isolated part of the epileptic network during the interictal state., Significance: A new hypothesis about a pathological hub located remotely from the irritative zone and seizure onset zone opens new ways for surgery when epileptogenic areas and eloquent cortex coincide., (Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.)

Objective: It remains unclear to what extent brain networks are altered at an early stage of epilepsy, which may be important to improve our understanding on the course of network alterations and their association with recurrent seizures and cognitive deficits., Methods: 89 Drug-naïve children with newly diagnosed focal or generalized epilepsies and 179 controls were included. Brain networks were based on interictal electroencephalography recordings obtained at first consultation. Conventional network metrics and minimum spanning tree (MST) metrics were computed to characterize topological network differences, such integration and segregation and a hub measures (betweenness centrality)., Results: Network alterations between groups were only identified by MST metrics and most pronounced in the delta band, in which a loss of network integration and a significant lower betweenness centrality was found in children with focal epilepsies compared to healthy controls (p<0.01). A reversed group difference was found in the upper alpha band. The network topology in generalized epilepsies was relatively spared., Conclusions: Interictal network alterations - only identifiable with the MST method - are already present at an early stage of focal epilepsy., Significance: We argue that these alterations are subtle at the early stage and aggravate later as a result of persisting seizures., (Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.)

Directed information flow between brain regions might be disrupted in dementia with Lewy bodies (DLB) and relate to the clinical syndrome of DLB. To investigate this hypothesis, resting-state electroencephalography recordings were obtained in patients with probable DLB and Alzheimer's disease (AD), and controls (N = 66 per group, matched for age and gender). Phase transfer entropy was used to measure directed connectivity in the groups for the theta, alpha, and beta frequency band. A posterior-to-anterior phase transfer entropy gradient, with occipital channels driving the frontal channels, was found in controls in all frequency bands. This posterior-to-anterior gradient was largely lost in DLB in the alpha band (p < 0.05). In the beta band, posterior brain regions were less driving in information flow in AD than in DLB and controls. In conclusion, the common posterior-to-anterior pattern of directed connectivity in controls is disturbed in DLB patients in the alpha band, and in AD patients in the beta band. Disrupted alpha band-directed connectivity may underlie the clinical syndrome of DLB and differentiate between DLB and AD., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Objectives: The presence of intracranial lesions or epilepsy may lead to functional reorganization and hemispheric lateralization. We applied a clinical magnetoencephalography (MEG) protocol for the localization of the contralateral and ipsilateral S1 and M1 of the foot and hand in patients with non-lesional epilepsy, stroke, developmental brain injury, traumatic brain injury and brain tumors. We investigated whether differences in activation patterns could be related to underlying pathology., Methods: Using dipole fitting, we localized the sources underlying sensory and motor evoked magnetic fields (SEFs and MEFs) of both hands and feet following unilateral stimulation of the median nerve (MN) and posterior tibial nerve (PTN) in 325 consecutive patients. The primary motor cortex was localized using beamforming following a self-paced repetitive motor task for each hand and foot., Results: The success rate for motor and sensory localization for the feet was significantly lower than for the hands (motor&#95;hand 94.6% versus motor&#95;feet 81.8%, p < 0.001; sensory&#95;hand 95.3% versus sensory&#95;feet 76.0%, p < 0.001). MN and PTN stimulation activated 86.6% in the contralateral S1, with ipsilateral activation < 0.5%. Motor cortex activation localized contralaterally in 76.1% (5.2% ipsilateral, 7.6% bilateral and 11.1% failures) of all motor MEG recordings. The ipsilateral motor responses were found in 43 (14%) out of 308 patients with motor recordings (range: 8.3-50%, depending on the underlying pathology), and had a higher occurrence in the foot than in the hand (motor&#95;foot 44.8% versus motor&#95;hand 29.6%, p = 0.031). Ipsilateral motor responses tended to be more frequent in patients with a history of stroke, traumatic brain injury (TBI) or developmental brain lesions (p = 0.063)., Conclusions: MEG localization of sensorimotor cortex activation was more successful for the hand compared to the foot. In patients with neural lesions, there were signs of brain reorganization as measured by more frequent ipsilateral motor cortical activation of the foot in addition to the traditional sensory and motor activation patterns in the contralateral hemisphere. The presence of ipsilateral neural reorganization, especially around the foot motor area, suggests that careful mapping of the hand and foot in both contralateral and ipsilateral hemispheres prior to surgery might minimize postoperative deficits.

The objective of this study was to quantitatively assess the relationship between apolipoprotein (APOE) genotype and electroencephalographic oscillatory brain dynamics in Alzheimer's disease (AD) patients and control subjects and its regional distribution. We obtained resting-state electroencephalographs of 320 AD patients and 246 control subjects, categorized into APOE ε4 carriers and noncarriers. Peak frequency and relative power in 4 different frequency bands were calculated. We tested the associations between APOE genotype and relative power in 4 brain regions. Peak frequency was comparable in APOE ε4 carrying and noncarrying control subjects, but lower in APOE ε4 noncarrying AD patients. In control subjects, APOE ε4 carriers had a different regional distribution of alpha power than noncarriers. We found no APOE effect in beta, delta, and theta bands. In AD, APOE ε4 noncarriers had lower alpha and higher delta power than carriers. This difference was most pronounced in the parieto-occipital region. In the theta band, APOE ε4 noncarriers had a different regional distribution of power compared with carriers. In conclusion, the most pronounced effect of genotype was seen in AD patients, and APOE ε4 noncarriers showed slower activity, especially in parieto-occipital regions., (Copyright © 2013 Elsevier Inc. All rights reserved.)

The interrelationships between pathological processes and emerging clinical phenotypes in Alzheimer's disease (AD) are important yet complicated to study, because the brain is a complex network where local disruptions can have widespread effects. Recently, properties in brain networks obtained with neuroimaging techniques have been studied in AD with tools from graph theory. However, the interpretation of graph alterations remains unclear, because the definition of connectivity depends on the imaging modality used. Here we examined which graph properties have been consistently reported to be disturbed in AD studies, using a heuristically defined "graph space" to investigate which theoretical models can best explain graph alterations in AD. Findings from structural and functional graphs point to a loss of highly connected areas in AD. However, studies showed considerable variability in reported group differences of most graph properties. This suggests that brain graphs might not be isometric, which complicates the interpretation of graph measurements. We highlight confounding factors such as differences in graph construction methods and provide recommendations for future research., (Copyright © 2013 Elsevier Inc. All rights reserved.)

The assessment of resting-state functional connectivity has become an important tool in studying brain disease mechanisms. Here we use magnetoencephalography to longitudinally evaluate functional connectivity changes in relation to clinical measures of disease progression in Parkinson's disease (PD). Using a source-space based approach with detailed anatomical mapping, functional connectivity was assessed for temporal, prefrontal and high order sensory association areas known to show neuropathological changes in early clinical disease stages. At baseline, early stage, untreated PD patients (n = 12) had lower parahippocampal and temporal delta band connectivity and higher temporal alpha1 band connectivity compared to controls. Longitudinal analyses over a 4-year period in a larger patient group (n = 43) revealed decreases in alpha1 and alpha2 band connectivity for multiple seed regions that were associated with motor or cognitive deterioration. In the earliest clinical stages of PD, delta and alpha1 band resting-state functional connectivity is altered in temporal cortical regions. With disease progression, a reversal of the initial changes in alpha1 and additional decreases in alpha2 band connectivity evolving in a more widespread cortical pattern. These changes in functional connectivity appear to reflect clinically relevant phenomena and therefore hold promise as a marker of disease progression, with potential predictive value for clinical outcome.

The pathophysiological mechanisms of Parkinson's disease (PD)-related dementia (PDD) are still poorly understood. Previous studies using electroencephalography (EEG) and magnetoencephalography (MEG) have demonstrated widespread slowing of oscillatory brain activity as a neurophysiological characteristic of PD-related dementia. Here, we use MEG to longitudinally study early changes in oscillatory brain activity in initially nondemented PD patients that may be associated with cognitive decline. Using a longitudinal design, resting-state MEG recordings were performed twice at an approximate 4-year interval in 14 healthy controls and 49 PD patients. Changes in peak frequency and in relative spectral power for 10 brain regions were analyzed in relation to clinical measures of cognitive and motor function. In contrast to healthy controls, PD patients showed a slowing of the dominant peak frequency. Furthermore, analysis per frequency band revealed an increase in theta power over time, along with decreases in alpha1 and alpha2 power. In PD patients, decreasing cognitive performance was associated with increases in delta and theta power, as well as decreases in alpha1, alpha2, and gamma power, whereas increasing motor impairment was associated with a theta power increase only. The present longitudinal study revealed widespread progressive slowing of oscillatory brain activity in initially nondemented PD patients, independent of aging effects. The slowing of oscillatory brain activity strongly correlated with cognitive decline and therefore holds promise as an early marker for the development of dementia in PD., (Copyright © 2013 Elsevier Inc. All rights reserved.)

The human brain is a complex network of interconnected brain regions. In adulthood, the brain's network was recently found to be under genetic influence. However, the extent to which genes influence the functional brain network early in development is not yet known. We report on the heritability of functional brain efficiency during early brain development. Using a twin design, young children underwent resting-state functional magnetic resonance imaging brain scans (N=86 from 21MZ and 22DZ twin-pairs, age=12 years). Functional connectivity, defined as the temporal dependency of neuronal activation patterns of anatomically separated brain regions, was explored using graph theory and its heritability was examined using structural equation modeling. Our findings suggest that 'global efficiency of communication' among brain regions is under genetic control (h² lambda=42%), irrespectively of the total number of brain connections (connectivity density). In addition, no influence of genes or common environment to local clustering (gamma) was found, suggesting a less pronounced effect of genes on local information segregation. Thus our findings suggest that a set of genes is shaping the underlying architecture of functional brain communication during development., (Copyright © 2012 Elsevier B.V. and ECNP. All rights reserved.)

The brain is the characteristic of a complex structure. By representing brain function, measured with EEG, MEG, and fMRI, as an abstract network, methods for the study of complex systems can be applied. These network studies have revealed insights in the complex, yet organized, architecture that is evidently present in brain function. We will discuss some technical aspects of formation and assessment of the functional brain networks. Moreover, the results that have been reported in this respect in the last years, in healthy brains as well as in functional brain networks of subjects with a neurological or psychiatrical disease, will be reviewed., (Copyright © 2012 Elsevier B.V. and ECNP. All rights reserved.)

The objective of this study was to examine the differences in oscillatory brain dynamics in Alzheimer's disease (AD) according to age at onset using quantitative electroencephalography (EEG). We examined resting state electroencephalograms of 320 probable AD patients and 246 controls, both categorized into a young (≤ 65 years) and old (> 65 years) group. Relative power in 4 different frequency bands was calculated. The effect of age on global and regional relative power was examined. Globally, young AD patients showed lower alpha- and higher delta-power than old AD patients. Regional analysis showed that these differences were most pronounced in the parieto-occipital region. Young AD patients had lower beta- and higher theta-power than old patients in all but the temporal regions. In controls, there was no age effect on global relative power in any frequency band. Young AD patients present with more severe slowing of spontaneous oscillatory activity than old AD patients, which is most pronounced in the posterior brain areas. This finding supports the hypothesis that early onset AD presents with a distinct endophenotype., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Background: Chronic insomnia is a poorly understood disorder. Risk factors for developing chronic insomnia are largely unknown, yet disturbances in brain indexes of arousal seem to accompany the disorder. We here investigate whether insomnia patients and control participants differ with respect to brain responses to direct stimulation, i.e., cortical excitability. Transcranial magnetic stimulation (TMS) offers a method to directly investigate the excitability level of the human cerebral cortex in psychiatric and neurological disease., Methods: We investigated cortical excitability in 16 insomnia patients and 14 carefully matched control participants using absolute and relative amplitudes of motor evoked potentials in response to single- and paired-pulse stimulation using TMS., Results: Nonmedicated insomnia patients showed, first, an exaggerated absolute response to both suprathreshold single- and paired-pulse stimulation compared with control participants and second, a reduced relative response to paired-pulse stimulation at long interpulse intervals (i.e., a reduced intracortical facilitation). The abnormal excitability persisted despite sleep therapy that effectively improved sleep quality as well as behavioral and neuroimaging indexes of brain function., Conclusions: The results suggest that a subtly disturbed intracortical excitability characterizes patients with chronic insomnia: a relatively reduced intracortical facilitation in the context of a globally increased absolute excitability. The findings do not resemble TMS findings after sleep deprivation or in sleep apnea and thus seem specific to insomnia. They may offer diagnostic value and implications for assessment of risk to develop this common and disabling disorder., (Copyright © 2010 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Objective: We examined the relation between Apolipoprotein E epsilon4 allele (ApoE epsilon4) genotype and functional connectivity measured by Electroencephalography (EEG) in patients with Alzheimer's disease (AD) and patients with subjective complaints (SC)., Methods: We included 43 patients with AD (age (SD)=74.2 (4.0), m/f=22/21; 30 of ApoE epsilon4 carriers) and 21 patients with SC (age (SD)=73.2 (5.2), m/f=13/8; 7 ApoE epsilon4 carriers) for this study. Resting state EEGs were recorded in all subjects. Synchronisation likelihood (SL) between local cortical areas was compared in the alpha and beta band according to ApoE epsilon4 status and diagnosis., Results: ApoE epsilon4 carriers had higher SL values in lower and upper alpha band, in both diagnostic groups. In upper alpha band and beta band AD patients had lower SL than patients with SC, was irrespective of ApoE status., Conclusion: The effects of AD and ApoE epsilon4 on functional connectivity are opposite and independent., Significance: The observed increase in SL in both AD and patients with SC carrying ApoE epsilon4 suggests a strong genetic impact of ApoE epsilon4 on brain function.

Objective: To analyze the functional connectivity patterns of the different EEG bands during wakefulness and sleep (different sleep stages and cyclic alternating pattern (CAP) conditions), using concepts derived from Graph Theory., Methods: We evaluated spatial patterns of EEG band synchronization between all possible pairs of electrodes (19) placed over the scalp of 10 sleeping healthy young normal subjects using two graph theoretical measures: the clustering coefficient (Cp) and the characteristic path length (Lp). The measures were obtained during wakefulness and the different sleep stages/CAP conditions from the real EEG connectivity networks and randomized control (surrogate) networks (Cp-s and Lp-s)., Results: We found values of Cp and Lp compatible with a small-world network organization in all sleep stages and for all EEG bands. All bands below 15Hz showed an increase of these features during sleep (and during CAP-A phases in particular), compared to wakefulness., Conclusions: The results of this study seem to confirm our initial hypothesis that during sleep there exists a clear trend for the functional connectivity of the EEG to move forward to an organization more similar to that of a small-world network, at least for the frequency bands lower than 15Hz., Significance: Sleep network "reconfiguration" might be one of the key mechanisms for the understanding of the "global" and "local" neural plasticity taking place during sleep.

Objective: To investigate the presence of EEG abnormalities in frontotemporal lobar degeneration (FTLD) in comparison with Alzheimer's disease (AD) and non-demented individuals with subjective memory complaints (SMC), using an elaborated visual EEG rating scale; furthermore, to investigate whether assessment of resting-state functional connectivity of the EEG is superior to visual evaluation in distinguishing between FTLD, AD and non-demented controls., Methods: EEGs of 15 patients with FTLD, 20 with AD and 23 individuals with SMC were visually compared using the Grand Total EEG (GTE) score. The synchronization likelihood (SL) as a measure of functional connectivity between different EEG channels was calculated for the 0.5-4Hz, 4-8Hz, 8-10Hz, 10-13Hz, 13-30Hz and 30-45Hz frequency bands. Patients had mild to moderate dementia., Results: In AD, as expected, the GTE revealed significant differences from FTLD and SMC, indicating more EEG slowing and loss of reactivity. Patients with FTLD, however, could not be discriminated from individuals with SMC by the GTE score. Analysis of resting-state functional connectivity showed decreased SL in AD compared to both FTLD and SMC in the lower and higher alpha frequency band and decreased SL in AD compared to SMC in the beta frequency band, whereas no differences between FTLD and AD or SMC were found., Conclusions: In patients with mild to moderate FTLD both the visually rated EEG and EEG measures of resting-state functional connectivity are normal., Significance: Although widespread neuronal degeneration takes place in frontotemporal lobar degeneration, this is not reflected in the EEG during the mild to moderate stages of the disease. An abnormal EEG in a mildly demented subject favours a diagnosis of AD.

Considering the brain as a complex network of interacting dynamical systems offers new insights into higher level brain processes such as memory, planning, and abstract reasoning as well as various types of brain pathophysiology. This viewpoint provides the opportunity to apply new insights in network sciences, such as the discovery of small world and scale free networks, to data on anatomical and functional connectivity in the brain. In this review we start with some background knowledge on the history and recent advances in network theories in general. We emphasize the correlation between the structural properties of networks and the dynamics of these networks. We subsequently demonstrate through evidence from computational studies, in vivo experiments, and functional MRI, EEG and MEG studies in humans, that both the functional and anatomical connectivity of the healthy brain have many features of a small world network, but only to a limited extent of a scale free network. The small world structure of neural networks is hypothesized to reflect an optimal configuration associated with rapid synchronization and information transfer, minimal wiring costs, resilience to certain types of damage, as well as a balance between local processing and global integration. Eventually, we review the current knowledge on the effects of focal and diffuse brain disease on neural network characteristics, and demonstrate increasing evidence that both cognitive and psychiatric disturbances, as well as risk of epileptic seizures, are correlated with (changes in) functional network architectural features.

Objective: To analyze the functional connectivity patterns of the EEG slow-wave activity during the different sleep stages and Cyclic Alternating Pattern (CAP) conditions, using concepts derived from Graph Theory., Methods: We evaluated spatial patterns of EEG slow-wave synchronization between all possible pairs of electrodes (19) placed over the scalp of 10 sleeping healthy young normal subjects using two graph theoretical measures: the clustering coefficient (Cp) and the characteristic path length (Lp). The measures were obtained during the different sleep stages and CAP conditions from the real EEG connectivity networks and randomized control (surrogate) networks (Cp-s and Lp-s)., Results: Cp and Cp/Cp-s increased significantly from wakefulness to sleep while Lp and Lp/Lp-s did not show changes. Cp/Cp-s was higher for A1 phases, compared to B phases of CAP., Conclusions: The network organization of the EEG slow-wave synchronization during sleep shows features characteristic of small-world networks (high Cp combined with low Lp); this type of organization is slightly but significantly more evident during the CAP A1 subtypes., Significance: Our results show feasibility of using graph theoretical measures to characterize the complexity of brain networks during sleep and might indicate sleep, and the A1 phases of CAP in particular, as a period during which slow-wave synchronization shows optimal network organization for information processing.

Objective: Cerebral functions are based on the functional interactions between multiple distinct specialized regions of the brain. Functional interactions require anatomical connections as well as the synchronization of brain oscillations. The present work aims at evaluating the impact of brain tumours on spatial patterns of functional connectivity of the brain measured at rest by MEG., Methods: We analyzed the statistical dependency (by computing the synchronization likelihood (SL, a measure of generalized synchronization)) between MEG signals at rest, in 17 patients with a brain tumour and in 15 healthy controls. Following an approach that derives from graph theory, we also analyzed the architectural properties of the networks by computing two parameters from the SL matrix, the cluster coefficient C and the characteristic path length L., Results: Alterations in synchronization levels were found in the patients and were not focal but involved intra-hemispheric connectivity. Effects were different considering the frequencies sub-bands, predominating in a decrease in high frequencies bands for long-distance connections and an increase in slower bands for local connectivity. In addition, graph analysis reveals changes in the normal "small-world" network architecture in addition to changes in synchronization levels with some differences according to the studied frequency sub-bands., Conclusions: Brain tumours alter the functional connectivity and the "network" architecture of the brain. These alterations are not focal and effects are different considering the frequencies sub-bands., Significance: These neurophysiological changes may contribute to the cognitive alterations observed in patients with brain tumours.

In alcohol-dependent individuals, synchronization of brain activity is different from that in non-alcohol-dependent individuals as reflected by EEG differences at alpha and beta frequencies (8-30 Hz). These EEG differences may not only be related to long-term alcohol intake but also to genetic factors that are associated with alcohol dependence. Thus, it is not known what the pure effect of long-term alcohol intake on synchronization of brain activity is. Therefore, we investigated whether EEG synchronization differs between light (0.5-6 drinks per week), moderate (7-20 drinks per week), and heavy (21-53 drinks per week) drinkers. All participants (49 males and 47 females) were free of a personal and family history of alcohol dependence. Eyes-closed EEG was recorded at rest and during mental rehearsal of pictures. EEG synchronization was determined by computing Synchronization Likelihood for six frequency bands (0.5-4 Hz, 4-8 Hz, 8-12 Hz, 12-20 Hz, 20-30 Hz, 30-45 Hz). Both male and female heavy drinkers displayed a loss of lateralization in alpha (8-12 Hz) and slow-beta (12-20 Hz) synchronization. In addition, moderately and heavily drinking males had lower fast-beta (20-30 Hz) synchronization than lightly drinking males. It is concluded that both male and female drinkers who drink 21 alcoholic drinks per week or more have impaired synchronization of brain activity during rest and mental rehearsal at alpha and beta frequencies as compared to individuals who drink less. As individuals with a personal or family history of alcohol dependence were excluded, the confounding effects of genetic factors related to alcohol dependence on synchronization of brain activity were minimized.

Objective: To study the dynamics of spatial synchronization of the slow-wave activity recorded from different scalp electrodes during sleep in healthy normal controls., Methods: We characterized the different levels of EEG synchronization during sleep (in the 0.25-2.5 Hz band) of five healthy subjects by means of the synchronization likelihood (SL) algorithm and analyzed its long-range temporal correlations by means of the detrended fluctuation analysis (DFA)., Results: We found higher levels of interregional synchronization during 'cyclic alternating pattern' (CAP) sleep than during nonCAP with a small but significant difference between its A and B phases. SL during CAP showed fluctuations probably corresponding to the single EEG slow-wave elements. DFA showed the presence of two linear scaling regions in the double-logarithmic plot of the fluctuations of SL level as a function of time scale. This indicates the presence of a characteristic time scale in the underlying dynamics which was very stable among the different subjects (1.23-1.33 s). We also computed the DFA exponent of the two scaling regions; the first, with values approximately 1.5, corresponded to fluctuations with period 0.09-0.75 s and the second, with values approximately 1, corresponded to fluctuations with period 1.5-24.0 s. Only the first exponent showed different values during the different sleep stages., Conclusions: All these results indicate a different role for each sleep stage and CAP condition in the EEG synchronization processes of sleep which show a complex time structure correlated with its neurophysiological mechanisms., Significance: Very slow oscillations in spatial EEG synchronization might play a critical role in the long-range temporal EEG correlations during sleep which might be the chain of events responsible for the maintenance and correct complex development of sleep structure during the night.

Drug and alcohol dependence are associated with enhanced attention for drug-related stimuli. This cognitive processing bias has been suggested to be related to craving and to represent one of the core mechanisms of addition. The present study tests the hypothesis that enhanced attention for heroin cues is mediated by the dopaminergic system using haloperidol as dopamine antagonist. In a double blind, randomized crossover design, 17 detoxified heroin dependent patients received a single oral dose of haloperidol 2 mg and placebo. Patients performed an Emotional Stroop Task to assess the cognitive processing of drug cues under both conditions. In addition, self-reported craving was assessed. In the haloperidol condition, patients performed better on the Emotional Stroop Task than in the placebo condition. However, no effect of haloperidol on subjective craving was found. These findings provide preliminary indications that attentional bias in heroin dependent humans is mediated by dopaminergic mechanisms.

Objective: In alcoholics, grey and white brain matter is damaged. In addition, functional brain connectivity as measured by EEG coherence is abnormal. We investigated whether heavily drinking students, although drinking for a shorter period than alcoholics, already show differences in functional connectivity compared to light-drinking controls., Methods: EEG was recorded in 11 light and 11 heavy male student drinkers during eyes closed, and eyes closed plus mental rehearsal of pictures. Functional connectivity was assessed with the Synchronisation Likelihood method., Results: Heavily drinking students had more synchronisation in the theta (4-8 Hz) and gamma (30-45 Hz) band than lightly drinking students during eyes closed, both with and without a mental-rehearsal task., Conclusions: Heavy student drinkers have increases in EEG synchronisation that are indicative of changes in hippocampal-neocortical connectivity., Significance: Heavy student drinkers show differences in functional connectivity as compared to their lightly drinking counterparts, even though they have a relatively short drinking history.

Objective: In this article we describe the course of synchronization between different EEG channels during nocturnal seizures in one patient with nocturnal frontal lobe epilepsy (NFLE)., Methods: The functional interactions between the different EEG channels during the nocturnal seizures were analyzed by means of the so-called synchronization likelihood (SL). SL is a measure of the dynamical interdependencies between a time series (EEG channel) and one or more other time series. In contrast to coherence, SL measures linear as well as non-linear interdependencies and it can do so as a function of time, making it suitable for non-stationary time series., Results: The main result of our single-patient study is the demonstration of a significant hyper-synchronization during NFLE seizures in the 8-12 Hz band which seems to be stopped by an increase in synchronization in the 0.5-4 Hz band, towards the end of each ictal episode., Conclusions: We suggest that a self-inhibiting complex mechanism might be responsible for the termination of ictal episodes which might take place at the level of the cortical layers and might involve mainly pyramidal neurons., Significance: This study shows that advanced EEG analysis methods can help the current understanding of ictal manifestations of NFLE.

Objective: Recently it has been shown that the adult sleep EEG is mostly determined by high-dimensional, linear dynamics with the exception of the A phase of the cyclic alternating pattern which displays more synchronized nonlinear dynamics. It is not known how these two different types of brain dynamics develop in early life; for this reason the aim of this study was that to extend the nonlinear analysis to the EEG during sleep recorded in premature and full-term newborns., Methods: EEG epochs were chosen from a total of 24 polygraphic recordings from 14 babies (9 males and 5 females) aged between 33 weeks 3 days and 4 months conceptional age. All subjects were neurologically normal and showed normal psychomotor development at follow-up. A total of 243 artifact-free epochs was chosen during active sleep (AS, 74 total epochs), quiet sleep (QS, 76 total epochs) and indeterminate sleep (IS, 93 total epochs). The dynamic properties of the EEG were assessed by means of the nonlinear cross prediction test which uses 3 different 'model' time series in order to predict nonlinearly the original data set (Pred, Ama, and Tir). Pred is a measure of the predictability of the time series, and Ama and Tir are measures of asymmetry, indicating nonlinear structure., Results: Our results show that the structure of sleep EEG in newborns is significantly different from that of adults, it cannot be distinguished from that of high-dimensional noise in the majority of epochs, and shows a tendency to become nonlinear in nature, mostly during QS, in a small percentage of the epochs analyzed., Conclusions: These findings can be interpreted as the effect of immature synaptic interconnections between neurons in the newborn brain.

Objective: To investigate whether epileptic seizure activity can be distinguished from non-epileptic background activity in the neonatal electroenceplalogram (EEG), using synchronization likelihood as a measure of synchronization between EEG channels., Methods: Forty-two 21s EEG epochs and two complete EEGs from 21 different neonatal patients in a 12-channel bipolar recording were studied (AD-conversion 16bit; sample frequency 200Hz; filter setting 0.5-30Hz). For EEG of each patient, we selected one epoch with epileptic discharges and one without. Synchronization was calculated in all epochs. In two complete EEGs, synchronization was calculated and correlated with a visual scoring of the EEG., Results: Synchronization likelihood was higher in all the epochs with epileptic seizures as compared to the epochs without epileptic activity (P<0.01). When synchronization likelihood exceeded 0.11, the sensitivity for the presence of epileptic activity was 0.85 (95% confidence limits [CL(95)]=0.69-1) and the specificity was 0.75 (CL(95)=0.56-0.94).Analysis of EEG score and synchronization likelihood of two complete EEGs revealed a high correlation between the occurrence of epileptic seizures and elevated synchronization likelihood (Spearman r=0.707, P<0.001)., Conclusions: The results of this study demonstrate that synchronization likelihood is a potential tool in the automatic monitoring of high-risk infants for epileptic activity on neonatal wards.

Working memory is associated with an increase in EEG theta synchronization and a decrease in lower alpha band synchronization. We investigated whether such changes in mean synchronization level are accompanied by changes in small scale fluctuations of synchronization. EEGs (19 channels; average reference; sample frequency 250 Hz) were recorded in 21 healthy subjects (12 males; mean age 62.5 years; S.D. 2.1) at rest and during a visual working memory condition. EEG synchronization was computed in six frequency bands (2-6; 6-10; 10-14; 14-18; 18-22; 22-50 Hz) using the synchronization likelihood. Variability of the synchronization was quantified with synchronization entropy. During the working memory condition synchronization increased in the 2-6 Hz band, and decreased in the 6-10, 14-18 and 18-22 Hz bands. Working memory was associated with increased variability in the 2-6 Hz band, and decreased variability in the 6-10 Hz band and, to a lesser extent, in the 14-18 and 18-22 Hz bands. Working memory is accompanied not only by characteristic changes in the mean level of interactions between neural networks, but also by changes in small scale fluctuations in such interactions. Strong, but rapidly fluctuating coupling between neural systems might provide a mechanism to optimize the balance between local differentiation and global integration of brain activity., (Copyright 2002 Elsevier Science B.V.)

This study examined patterns of variation in the ongoing electroencephalogram during performance of three visual tasks. One task required exact arithmetic calculations on Arabic numerals. A second task involved pseudoword processing as a control for the verbal (phonological) component that is, by definition, part of arithmetic tasks. A third task primarily required visual/graphemic processing, which is also involved in the other two tasks. Spectral power in the alpha range was lowest during the pseudoword task, followed by power during the arithmetic task, and finally by power in the visual task, indicating more prominent desynchronization during engagement in the analysis of word-like printed material. Finally, linear (power in the gamma range) and non-linear measures (correlation dimension) provided evidence of predominant right hemisphere engagement during the arithmetic task.

The objective of this work was to study the non-linear aspects of sleep EEG, taking into account the different sleep stages and the peculiar organization of its phasic events in ordered sequences (CAP) by applying a series of new non-linear measures (non-linear cross prediction or NLCP), which appear more reliable for the detection and characterization of non-linear structures in experimental data than the commonly used correlation dimension. Eight healthy subjects aged 18-20 years participated in this study. Polysomnography was performed in all subjects; signals were sampled at 128 Hz and stored on hard disk. The C3 or C4 derivation was used for all the subsequent computational steps, which were performed on EEG epochs (4096 data points) selected from sleep stage 2 (S2) and slow-wave sleep (SWS), in both CAP and non-CAP (NCAP) conditions. Also, epochs from sleep stage 1 (S1), REM and wakefulness preceding sleep were recorded. The dynamic properties of the EEG were assessed by means of the non-linear cross-prediction test, which uses three different 'model' time series in order to predict non-linearly the original data set (Pred, Ama, and Tir). Pred is a measure of the predictability of the time series, and Ama and Tir are measures of asymmetry, indicating non-linear structure. The non-linear measures applied in this study indicate that sleep EEG tends to show non-linear structure only during CAP periods, both during S2 and SWS. Moreover, during CAP periods, non-linearity can only be detected during the phase A1 subtypes (and partially A2) of CAP. The A3 phases show characteristics of non-stationarity and bear some resemblance to wakefulness. Based on the results of this study, sleep might be considered as a dynamically evolving sequence of different states of the EEG, which we could track by detecting non-linearity, mostly in association with CAP. Our results clearly show that detectable non-linearity in the EEG is closely related to the occurrence of the phase A of CAP.