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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. We studied whether apathy in DBS-treated PD patients could be a stimulation effect. 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. 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. 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. • Apathy severity increases after deep brain stimulation (DBS) of the subthalamic nucleus in Parkinson's disease. • Post-DBS apathy does not correlate with dose reduction of dopaminergic medication. • Increased post-operative apathy scores correlate with stimulation position. • And with stimulation-induced changes in functional connectivity (MEG). • Apathy after DBS may be an effect of the stimulation itself. [ABSTRACT FROM AUTHOR]

Abstract: 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 &y& Elsevier]

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. [Copyright &y& Elsevier]

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. • PCA-AD subjects show more profound posterior oscillatory slowing compared to typical AD. • Right parietal peak frequency correlates with visual performance in PCA-AD. • PCA-AD functional networks show a decrease of posterior and increase of frontal hubness. [ABSTRACT FROM AUTHOR]

Abstract: 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 &y& Elsevier]

Abstract: Synchronization of neuronal activity within and across distributed brain regions is a fundamental property of cortical and subcortical networks and serves a variety of functions including motor and cognitive processes. Data will be reviewed here from cross-sectional EEG and MEG studies to suggest that Parkinson''s disease is characterized by changing patterns of disturbed neural synchrony that appear to be dependent on the stage of disease. Some of these alterations in neural synchrony may directly account for a number of disease-related impairments in motor and cognitive functions. Future longitudinal studies are required to fully understand the disturbances of functional brain networks in Parkinson''s disease and how they evolve throughout the course of the disease. [Copyright &y& Elsevier]

• Multi-class classification of cognitive decline and dementia subtypes is performed. • MEG biomarkers hold promise to improve diagnostic accuracy. • Diagnostic profiles could provide an intuitive tool to clinicians. 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. [ABSTRACT FROM AUTHOR]

Abstract: Our goal was to measure indices characterizing EEG-reactivity in young and elderly subjects. It was hypothesized that EEG-reactivity as reflected by different measures would be lower in the elderly. In two age groups (young: N =23, mean age=21.5±2.2 years; old: N =25, mean age=66.9±3.6 years) absolute frequency spectra, Omega-complexity, synchronization likelihood and network properties (clustering coefficient and characteristic path length) of the EEG were analyzed in the delta, theta, alpha1, alpha2, beta1 and beta2 frequency bands occurring as a result of eyes opening. Absolute spectral power was higher in the young in the delta, alpha1 and alpha2 bands in the posterior area. The alpha1 peak frequency decreased following eyes opening in the young, while no change was observed in the elderly. Omega-complexity was higher in the elderly especially in the frontal area and increased following eyes opening. Values of the clustering coefficient, path length and that of the “small-world index” decreased as a result of eyes opening, the latter in the fast frequency range. The results suggest reduced reactivity in the elderly as shown by frequency spectra and decreased level of integrative activity particularly in the frontal area probably as a result of reduced interneuronal processing capacity. Indices of network characteristics reveal a shift towards more random topology especially in the beta frequencies caused by eyes opening. [Copyright &y& Elsevier]

Abstract: Previous studies demonstrated that intelligence is significantly related to an impressive array of psychological, social, biological and genetic factors and that working memory (WM) can be considered as a general cognitive resource strongly related with a wide variety of higher order cognitive competencies and intelligence. Also, evaluating the WM of subjects might allow one to test the neural efficiency hypothesis (NEH). WM typically involves functional interactions between frontal and parietal cortices. We recorded EEG signals to study neuronal interactions during one WM test in individuals who had few years of formal education (LE) as compared to individuals with university degrees (UE). The two groups of individuals differed in the scores they obtained in psychological tests. To quantify the synchronization between EEG channels in several frequency bands, we evaluated the “synchronization likelihood” (SL), which takes into consideration nonlinear processes as well as linear ones. SL was then converted into graphs to estimate the distance from “small-world network” (SWN) organization, i.e., an optimally organized network that would give rise to the data. In comparison to LE subjects, those with university degrees exhibited less prominent SWN properties in most frequency bands during the WM task. This finding supports the NEH and suggests that the connections between brain areas of well-educated subjects engaged in WM tasks are not as well-organized in the sense of SWN. [Copyright &y& Elsevier]

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. [Copyright &y& Elsevier]

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+. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Abstract: 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 &y& Elsevier]

Abstract: 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 &y& Elsevier]

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. [ABSTRACT FROM AUTHOR]

Abstract: Objective: We examined the relation between Apolipoprotein E ε4 allele (ApoE ε4) 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 ε4 carriers) and 21 patients with SC (age (SD)=73.2 (5.2), m/f=13/8; 7 ApoE ε4 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 ε4 status and diagnosis. Results: ApoE ε4 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 ε4 on functional connectivity are opposite and independent. Significance: The observed increase in SL in both AD and patients with SC carrying ApoE ε4 suggests a strong genetic impact of ApoE ε4 on brain function. [Copyright &y& Elsevier]

Abstract: 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. [Copyright &y& Elsevier]

Abstract: 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. [Copyright &y& Elsevier]

Abstract: 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. [Copyright &y& Elsevier]

Absract: 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. [Copyright &y& Elsevier]

Abstract: The levels of EEG synchronization, in the 0.25–2.5Hz band, during the A1 subtypes of the sleep “cyclic alternating pattern” (CAP) were measured in five healthy subjects by means of the synchronization likelihood (SL) algorithm. SL was measured for seven electrode pairs (F4-F3, C4-C3, P4-P3 for the analysis of interhemispheric SL and F4-C4, C4-P4, F3-C3, and C3-P3, for the analysis of intrahemispheric SL). During the A1 CAP subtypes, SL tended to be highest between pairs of electrodes situated over different hemispheres; in particular, SL obtained from F4-F3 was the highest, followed by that of P4-P3. These results indicate that the transient high level of synchronization in the slow-wave EEG range, during the sleep A1 CAP subtypes, is a phenomenon involving mostly the anterior parts of the brain and is probably based on interhemispheric interactions, possibly mediated by transcallosal connections. [Copyright &y& Elsevier]

Abstract: Electroencephalographic (EEG) data were recorded in 69 normal elderly (Nold), 88 mild cognitive impairment (MCI), and 109 mild Alzheimer''s disease (AD) subjects at rest condition, to test whether the fronto-parietal coupling of EEG rhythms is in line with the hypothesis that MCI can be considered as a pre-clinical stage of the disease at group level. Functional coupling was estimated by synchronization likelihood of Laplacian-transformed EEG data at electrode pairs, which accounts for linear and non-linear components of that coupling. Cortical rhythms of interest were delta (2–4Hz), theta (4–8Hz), alpha 1 (8–10.5Hz), alpha 2 (10.5–13Hz), beta 1 (13–20Hz), beta 2 (20–30Hz), and gamma (30–40Hz). Compared to the Nold subjects, the AD patients presented a marked reduction of the synchronization likelihood (delta to gamma) at both fronto-parietal and inter-hemispherical (delta to beta 2) electrodes. As a main result, alpha 1 synchronization likelihood progressively decreased across Nold, MCI, and mild AD subjects at midline (Fz–Pz) and right (F4–P4) fronto-parietal electrodes. The same was true for the delta synchronization likelihood at right fronto-parietal electrodes (F4–P4). For these EEG bands, the synchronization likelihood correlated with global cognitive status as measured by the Mini Mental State Evaluation. The present results suggest that at group level, fronto-parietal coupling of the delta and alpha rhythms progressively becomes abnormal though MCI and mild AD. Future longitudinal research should evaluate whether the present EEG approach is able to predict the cognitive decline in individual MCI subjects. [Copyright &y& Elsevier]

Abstract: 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 0.25–2.5Hz 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 (1.23–1.33s). We also computed the DFA exponent of the two scaling regions; the first, with values ≈1.5, corresponded to fluctuations with period 0.09–0.75s and the second, with values ≈1, corresponded to fluctuations with period 1.5–24.0s. 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. [Copyright &y& Elsevier]

Abstract: Using linear and non-linear methods, electroencephalographic (EEG) signals were measured at various brain regions to provide information regarding patterns of local and coordinated activity during performance of three arithmetic tasks (number comparison, single-digit multiplication, and two-digit multiplication) and two control tasks that did not require arithmetic operations. It was hypothesized that these measures would reveal the engagement of local and increasingly complex cortical networks as a function of task specificity and complexity. Results indicated regionally increased neuronal signalling as a function of task complexity at frontal, temporal and parietal brain regions, although more robust task-related changes in EEG-indices of activation were derived over the left hemisphere. Both linear and non-linear indices of synchronization among EEG signals recorded from over different brain regions were consistent with the notion of more “local” processing for the number comparison task. Conversely, multiplication tasks were associated with a widespread pattern of distant signal synchronizations, which could potentially indicate increased demands for neural networks cooperation during performance of tasks that involve a greater number of cognitive operations. [Copyright &y& Elsevier]

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. [Copyright &y& Elsevier]

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 21 s EEG epochs and two complete EEGs from 21 different neonatal patients in a 12-channel bipolar recording were studied (AD-conversion 16 bit; sample frequency 200 Hz; filter setting 0.5–30 Hz). 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 [CL95]=0.69–1) and the specificity was 0.75 (CL95=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. [Copyright &y& Elsevier]