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Aim: Congestive heart failure (CHF) is a very complex clinical syndrome that may lead to ischemic cerebral hypoxia condition. The aim of the present study is to analyze the effects of CHF on brain activity through electroencephalographic (EEG) complexity measures, like approximate entropy (ApEn)., Methods: Twenty patients with CHF and 18 healthy elderly people were recruited. ApEn values were evaluated in the total spectrum (0.2-47 Hz) and main EEG frequency bands: delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-11 Hz), alpha 2 (11-13 Hz), beta 1 (13-20 Hz), beta 2 (20-30 Hz), and gamma (30-45 Hz) to identify differences between CHF group and control. Moreover, a correlation analysis was performed between ApEn parameters and clinical data (i.e., B-type natriuretic peptides (BNP), New York Heart Association (NYHA), and systolic blood pressure (SBP)) within the CHF group., Results: Statistical topographic maps showed statistically significant differences between the two groups in the total spectrum and theta frequency band. Within the CHF group, significant negative correlations were found between total ApEn and BNP in O2 channel and between theta ApEn and NYHA scores in Fp1, Fp2, and Fz channels; instead, a significant positive correlation was found between theta ApEn and SBP in C3 channel and a nearly significant positive correlation was obtained between theta ApEn and SBP in F4 channel., Conclusion: EEG abnormalities in CHF are very similar to those observed in cognitive-impaired patients, suggesting analogies between the effects of neurodegeneration and brain chronic hypovolaemia due to heart disorder and underlying high brain sensitivity to CHF., (© 2023 The Authors. Acta Physiologica published by John Wiley & Sons Ltd on behalf of Scandinavian Physiological Society.)

Aging is the inevitable biological process that results in a progressive structural and functional decline associated with alterations in the resting/task-related brain activity, morphology, plasticity, and functionality. In the present study, we analyzed the effects of physiological aging on the human brain through entropy measures of electroencephalographic (EEG) signals. One hundred sixty-one participants were recruited and divided according to their age into young (n = 72) and elderly (n = 89) groups. Approximate entropy (ApEn) values were calculated in each participant for each EEG recording channel and both for the total EEG spectrum and for each of the main EEG frequency rhythms: delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-11 Hz), alpha 2 (11-13 Hz), beta 1 (13-20 Hz), beta 2 (20-30 Hz), and gamma (30-45 Hz), to identify eventual statistical differences between young and elderly. To demonstrate that the ApEn represents the age-related brain changes, the computed ApEn values were used as features in an age-related classification of subjects (young vs elderly), through linear, quadratic, and cubic support vector machine (SVM). Topographic maps of the statistical results showed statistically significant difference between the ApEn values of the two groups found in the total spectrum and in delta, theta, beta 2, and gamma. The classifiers (linear, quadratic, and cubic SVMs) revealed high levels of accuracy (respectively 93.20 ± 0.37, 93.16 ± 0.30, 90.62 ± 0.62) and area under the curve (respectively 0.95, 0.94, 0.93). ApEn seems to be a powerful, very sensitive-specific measure for the study of cognitive decline and global cortical alteration/degeneration in the elderly EEG activity., (© 2022. The Author(s), under exclusive licence to American Aging Association.)

Background: The objective of the present study is to explore whether acute stroke may result in changes in brain network architecture by electroencephalography functional coupling analysis and graph theory., Methods: Ninety acute stroke patients and 110 healthy subjects were enrolled in different clinical centers in Rome, Italy, starting from 2013, and for each one electroencephalographies were recorded within <15 days from stroke onset. All patients were clinically evaluated through National Institutes of Health Stroke Scale, Barthel Index, and Action Research Arm Test in the acute stage and during the follow-up. Functional connectivity was assessed using Total Coherence and Small World (SW) by comparing the affected and the unaffected hemisphere between groups (Stroke versus Healthy). Correlations between connectivity and poststroke recovery scores have been carried out., Results: In stroke patients, network hemispheric asymmetry, in terms of Total Coherence, was mainly detected in the affected hemisphere with lower values in Delta, Theta, Alpha1, and Alpha2 ( P =0.000001), whereas the unaffected hemisphere showed lower Total Coherence only in Delta and Theta ( P =0.000001). SW revealed a significant difference only in the affected hemisphere in all electroencephalography bands (lower SW in Delta ( P =0.000003), Theta ( P =0.000003), Alpha1 ( P =0.000203), and Alpha2 ( P =0.028) and higher SW in Beta2 ( P =0.000002) and Gamma ( P =0.000002)). We also found significant correlations between SW and improvement in National Institutes of Health Stroke Scale (Theta SW: r=-0.2808), Barthel Index (Delta SW: r=0.3692; Theta SW: r=0.3844, Beta2 SW: r=-0.3589; Gamma SW: r=-04948), and Action Research Arm Test (Beta2 SW: r=-0.4274; Gamma SW: r=-0.4370)., Conclusions: These findings demonstrated changes in global functional connectivity and in the balance of network segregation and integration induced by acute stroke. The findings on the correlations between clinical outcome(s) and poststroke network architecture indicate the possibility to identify a predictive index of recovery useful to address and personalize the rehabilitation program.

Objective. A large part of the cerebral cortex is dedicated to the processing of visual stimuli and there is still much to understand about such processing modalities and hierarchies. The main aim of the present study is to investigate the differences between directional visual stimuli (DS) and non-directional visual stimuli (n-DS) processing by time-frequency analysis of brain electroencephalographic activity during a visuo-motor task. Electroencephalography (EEG) data were divided into four regions of interest (ROIs) (frontal, central, parietal, occipital). Approach. The analysis of the visual stimuli processing was based on the combination of electroencephalographic recordings and time-frequency analysis. Event related spectral perturbations (ERSPs) were computed with spectrum analysis that allow to obtain the average time course of relative changes induced by the stimulus presentation in spontaneous EEG amplitude spectrum. Main results. Visual stimuli processing enhanced the same pattern of spectral modulation in all investigated ROIs with differences in amplitudes and timing. Additionally, statistically significant differences in occipital ROI between the DS and n-DS visual stimuli processing in theta, alpha and beta bands were found. Significance. These evidences suggest that ERSPs could be a useful tool to investigate the encoding of visual information in different brain regions. Because of their simplicity and their capability in the representation of brain activity, the ERSPs might be used as biomarkers of functional recovery for example in the rehabilitation of visual dysfunction and motor impairment following a stroke, as well as diagnostic tool of anomalies in brain functions in neurological diseases tailored to personalized treatments in clinical environment., (© 2022 IOP Publishing Ltd.)

Objective: The hypersynchronous neuronal activity associated with epilepsy causes widespread functional network disruptions extending beyond the epileptogenic zone. This altered network topology is considered a mediator for non-seizure symptoms, such as cognitive impairment. The aim of this study was to investigate functional network alterations in focal epilepsy patients with good seizure control and high quality of life., Methods: We compared twenty-two focal epilepsy patients and sixteen healthy controls on graph metrics derived from functional connectivity of source-level resting-state EEG. Graph metrics were calculated over a range of network densities in five frequency bands., Results: We observed a significantly increased small world index in patients relative to controls. On the local level, two left-hemisphere regions displayed a shift towards greater alpha band "hubness". The findings were not mediated by age, sex or education, nor by age of epilepsy onset, duration or focus lateralisation., Conclusions: Widespread functional network alterations are evident in focal epilepsy, even in a cohort characterised by successful anti-seizure medication therapy and high quality of life. These findings might support the position that functional network analysis could hold clinical relevance for epilepsy., Significance: Focal epilepsy is accompanied by global and local functional network aberrancies which might be implied in the sustenance of non-seizure symptoms., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

Aging is a multifactorial physiological process characterized by the accumulation of degenerative processes impacting on different brain functions, including the cognitive one. A tool largely employed in the investigation of brain networks is the electroencephalogram (EEG). Given the cerebral complexity and dynamism, many non-linear approaches have been applied to explore age-related brain electrical activity modulation detected by the EEG: one of them is the entropy, which measures the disorder of a system. The present study had the aim to investigate aging influence on brain dynamics applying Approximate Entropy (ApEn) parameter to resting state EEG data of 68 healthy adult participants, divided with respect to their age in two groups, focusing on several specialized brain regions. Results showed that elderly participants present higher ApEn values than younger participants in the central, parietal and occipital areas, confirming the hypothesis that aging is characterized by an evolution of brain dynamics. Such findings may reflect a reduced synchronization of the neural networks cyclic activity, due to the reduction of cerebral connections typically found in aging process. Understanding the dynamics of brain networks by applying the entropy parameter could be useful for developing appropriate and personalized rehabilitation programs and for future studies on neurodegenerative diseases., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Objective. In modern neuroscience, the underlying mechanisms of the elaboration and reaction to different kinds of stimuli of the brain hemispheres remain still very challenging to understand, together with the possibility to anticipate certain behaviors to improve the performance. Approach. The purpose of the present study was to investigate the brain rhythms characteristics of electroencephalographic (EEG) recordings and in particular, their interhemispheric differences in resting state condition before a visuo-motor task in a population of healthy adults. During the task, subjects were asked to react to a sequence of visual cues as quick as possible. The reaction times (RTs) to the task were measured, collected and correlated with the EEG signals recorded in a resting state condition immediately preceding the task. The EEG data were analyzed in the space of cortical sources of EEG rhythms by the computation of the global spectra power density (GSPD) in the left and in the right hemisphere, and of an index of brain laterality ( L ). Main results. The results showed a negative correlation between the RTs and the GSPD in the central areas in the left and in the right hemisphere in both eyes open (EO) and eyes closed (EC) conditions. A close to significant and negative correlation was found in the parietal areas. Furthermore, RTs negatively correlated with L in the central areas in EC condition. The results showed a negative correlation between the RTs and the GSPD in the central areas in the left and in the right hemisphere in both EO and EC conditions. Significance. The correlations between the brain activity before a task and the RTs to the task can represent an interesting tool for exploring the brain state characterization for the upcoming tasks performance., (© 2021 IOP Publishing Ltd.)

Aim of the study was to evaluate the influence of the EEG channels number on the brain networks' analysis, to establish whether and how much higher density EEG actually contributes to add supplementary information to brain networks analyses. 59 electrodes EEGs were recorded in 20 healthy subjects in eyes open and closed condition. For each condition, we analyzed the recording dataset of 59 channels, and three sub-datasets obtained by the selection of 44, 30, 19 channels from the 59 ones. Then we computed the EEG sources of current density and evaluated the SW index in the four EEGs data montages. Results showed that in the eyes open condition the number of recording channels influences more the SW index modulation respect that in the eyes closed condition. Conversely, in the eyes closed condition the brain activity is less affected by specific brain regions' activations and the signal's generators produced not significant variations on EEG data and consequently the small world network measure is not affected by the recording channels number. We can conclude that in the eyes closed condition, the 19 EEG channels is an acceptable montage to study brain networks' modulations, to both detect the higher and the lower brain waves' frequencies., (Copyright © 2020. Published by Elsevier Inc.)

Background: Most common progressive brain diseases in the elderly are Alzheimer's disease (AD) and vascular dementia (VaD). They present with relatively similar clinical symptoms of cognitive decline, but the underlying pathophysiological mechanisms are different., Objective: The aim is to explore the brain connectivity differences between AD and VaD patients compared to mild cognitive impairment (MCI) and normal elderly (Nold) subjects applying graph theory, in particular the Small World (SW) analysis., Methods: 274 resting state EEGs were analyzed in 100 AD, 80 MCI, 40 VaD, and 54 Nold subjects. Graph theory analyses were applied to undirected and weighted networks obtained by lagged linear coherence evaluated by eLORETA tool., Results: VaD and AD patients presented more ordered low frequency structure (lower value of SW) than Nold and MCI subjects, and more random organization (higher value of SW) in low and high frequency alpha rhythms. Differences between patients have been found in high frequency alpha rhythms in VaD (higher value of SW) with respect to AD, and in theta band with a trend which is more similar to MCI and Nold than to AD. MCI subjects presented a network organization which is intermediate, in low frequency bands, between Nold and patients., Conclusion: Graph theory applied to EEG data has proved very useful in identifying differences in brain network patterns in subjects with dementia, proving to be a valid tool for differential diagnosis. Future studies will aim to validate this method to diagnose especially in the early stages of the disease and at single subject level.

Objective: Recent findings suggested that subclinical epileptiform activity is prevalent during sleep in a significant proportion of Alzheimer's Disease (AD) patients., The Aims of Our Study Were: (A) comparing the frequency of subclinical epileptiform activity during the sleep in a sample diagnosed with 'probable' AD and Mild Cognitive Impairment (MCI) due to AD, and in healthy subjects; (B) evaluating epileptiform EEG activity as a function of different sleep stages within a well-controlled polysomnographic setting., Methods: We prospectively enrolled 50 'probable' AD patients (73 ± 7.0 years) and 50 subjects with MCI due to AD (72 ± 6.7 years) without history of seizures, comparing them with 50 controls (69 ± 6.7 years). Patients underwent to a full-night video-PSG., Results: Subclinical epileptiform activity was detected in 6.38% of 'probable' AD patients, 11.63% of MCI due to AD subjects and 4.54% of controls (p = 0.43). The comparisons between the three groups for the frequency of epileptiform activity did not reach statistically significant differences neither for total sleep nor for any sleep period considered., Conclusions: Our study shows that, when controlling for sleep stages and the influence of psychoactive drugs, AD patients and MCI due to AD subjects do not exhibit a higher frequency of epileptiform discharges during sleep compared to healthy subjects., Significance: Subclinical epileptiform activity during sleep does not discriminate 'probable' AD from MCI due to AD and healthy controls., Competing Interests: Declaration of Competing of interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

Moving from the hypothesis that aging processes modulate brain connectivity networks, 170 healthy elderly volunteers were submitted to EEG recordings in order to define age-related normative limits. Graph theory functions were applied to exact low-resolution electromagnetic tomography on cortical sources in order to evaluate the small-world parameter as a representative model of network architecture. The analyses were carried out in the whole brain-as well as for the left and the right hemispheres separately-and in three specific resting state subnetworks defined as follows: attentional network (AN), frontal network (FN), and default mode network (DMN) in the EEG frequency bands (delta, theta, alpha 1, alpha 2, beta 1, beta 2, gamma). To evaluate the stability of the investigated parameters, a subgroup of 32 subjects underwent three separate EEG recording sessions in identical environmental conditions after a few days interval. Results showed that the whole right/left hemispheric evaluation did not present side differences, but when individual subnetworks were considered, AN and DMN presented in general higher SW in low (delta and/or theta) and high (gamma) frequency bands in the left hemisphere, while for FN, the alpha 1 band was lower in the left with respect to the right hemisphere. It was also evident the test-retest reliability and reproducibility of the present methodology when carried out in clinically stable subjects.Evidences from the present study suggest that graph theory represents a reliable method to address brain connectivity patterns from EEG data and is particularly suitable to study the physiological impact of aging on brain functional connectivity networks.

Aim of this study was to explore the EEG functional connectivity in amnesic mild cognitive impairments (MCI) subjects with multidomain impairment in order to characterize the Default Mode Network (DMN) in converted MCI (cMCI), which converted to Alzheimer's disease (AD), compared to stable MCI (sMCI) subjects. A total of 59 MCI subjects were recruited and divided -after appropriate follow-up- into cMCI or sMCI. They were further divided in MCI with linguistic domain (LD) impairment and in MCI with executive domain (ED) impairment. Small World (SW) index was measured as index of balance between integration and segregation brain processes. SW, computed restricting to nodes of DMN regions for all frequency bands, evaluated how they differ between MCI subgroups assessed through clinical and neuropsychological four-years follow-up. In addition, SW evaluated how this pattern differs between MCI with LD and MCI with ED. Results showed that SW index significantly decreased in gamma band in cMCI compared to sMCI. In cMCI with LD impairment, the SW index significantly decreased in delta band, while in cMCI with ED impairment the SW index decreased in delta and gamma bands and increased in alpha1 band. We propose that the DMN functional alterations in cognitive impairment could reflect an abnormal flow of brain information processing during resting state possibly associated to a status of pre-dementia.

Background: Several studies investigated clinical and instrumental differences to make diagnosis of dementia in general and in Alzheimer's disease (AD) in particular with the aim to classify, at the individual level, AD patients and healthy controls cooperating with neuropsychological tests for an early diagnosis. Advanced network analysis of electroencephalographic (EEG) rhythms provides information on dynamic brain connectivity and could be used in classification processes. If successfully reached, this goal would add a low-cost, easily accessible, and non-invasive technique with neuropsychological tests., Objective: To investigate the possibility to automatically classify physiological versus pathological aging from cortical sources' connectivity based on a support vector machine (SVM) applied to EEG small-world parameter., Methods: A total of 295 subjects were recruited: 120 healthy volunteers and 175 AD. Graph theory functions were applied to undirected and weighted networks obtained by lagged linear coherence evaluated by eLORETA. A machine-learning classifier (SVM) was applied. EEG frequency bands were: delta (2-4 Hz), theta (4-8 Hz), alpha1 (8-10.5 Hz), alpha2 (10.5-13 Hz), beta1 (13-20 Hz), beta2 (20-30 Hz), and gamma (30-40 Hz)., Results: The receiver operating characteristic curve showed AUC of 0.97±0.03 (indicating very high classification accuracy). The classifier showed 95% ±5% sensitivity, 96% ±3% specificity, and 95% ±3% accuracy for the classification., Conclusion: EEG connectivity analysis via a combination of source/connectivity biomarkers, highly correlating with neuropsychological AD diagnosis, could represent a promising tool in identification of AD patients. This approach represents a low-cost and non-invasive method, one that utilizes widely available techniques which, when combined, reach high sensitivity/specificity and optimal classification accuracy on an individual basis (0.97 of AUC).

Cerebral post-stroke plasticity has been repeatedly investigated via functional neuroimaging techniques mainly based on blood flow/metabolism. However, little is known on predictive value of topological properties of widely distributed neural networks immediately following stroke on rehabilitation outcome and post-stroke recovery measured by early functional outcome. The utility of EEG network parameters (i.e. small world organization) analysis as a potential rough and simple biomarker for stroke outcome has been little explored and needs more validation. A total of 139 consecutive patients within a post-stroke acute stage underwent EEG recording. A group of 110 age paired healthy subjects constituted the control group. All patients were clinically evaluated with 3 scales for stroke: NIHSS, Barthel and ARAT. As a first result, NIHSS, Barthel and ARAT correlated with Small World index as provided by the proportional increment/decrement of low (delta) and viceversa of high (beta2 and gamma) EEG frequency bands. Furthermore, in line with the aim of the present study, we found a strong correlation between NIHSS at follow up and gamma Small World index in the acute post-stroke period, giving SW index a significant weight of recovery prediction. This study aimed to investigate possible correlations between functional abnormalities of brain networks, measured by small world characteristics detected in resting state EEG source investigation, and early post-stroke clinical outcome in order to find a possible predictive index of functional recovery to address and/or correct the rehabilitation program., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Objective: We tested whether acute cerebellar stroke may determine changes in brain network architecture as defined by cortical sources of EEG rhythms., Methods: Graph parameters of 41 consecutive stroke patients (<5 days from the event) were studied using eLORETA EEG sources. Network rearrangements of stroke patients were investigated in delta, alpha 2, beta 2 and gamma bands in comparison with healthy subjects., Results: The delta network remodeling was similar in cerebellar and middle cerebral artery strokes, with a reduction of small-worldness. Beta 2 and gamma small-worldness, in the right hemisphere of patients with cerebellar stroke, increase respect to healthy subjects, while alpha 2 small-worldness increases only among patients with a middle cerebral artery stroke., Conclusions: The network remodeling characteristics are independent on the size of the ischemic lesion. In the early post-acute stages cerebellar stroke differs from the middle cerebral artery one because it does not cause alpha 2 network remodeling while it determines a high frequency network reorganization in beta 2 and gamma bands with an increase of small-worldness characteristics., Significance: These findings demonstrate changes in the balance of local segregation and global integration induced by cerebellar acute stroke in high EEG frequency bands. They need to be integrated with appropriate follow-up to explore whether further network changes are attained during post-stroke outcome stabilization., (Copyright © 2019 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

The aim of the present study was to understand whether modeling brain function in terms of network structure makes it possible to find markers of prediction of motor learning performance in a sensory motor learning task. By applying graph theory indexes of brain segregation - such as modularity and transitivity - to functional connectivity data derived from electroencephalographic (EEG) rhythms, we further studied pre- (baseline) versus post-task brain network architecture to understand whether motor learning induces changes in functional brain connectivity. The results showed that, after the training session with measurable learning, transitivity increased in the alpha1 EEG frequency band and modularity increased in the theta band and decreased in the gamma band, suggesting that brain segregation is modulated by the cognitive task. Furthermore, it was observed that theta modularity at the baseline negatively correlated with the performance improvement; namely, the lower this connectivity index at the baseline pre-task period, the higher the improvement of performance with training. The present results show that brain segregation is modulated by the cognitive task and that it is possible to predict performance by the study of pre-task EEG rhythm connectivity parameters., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Objective: Mild cognitive impairment (MCI) is a condition intermediate between physiological brain aging and dementia. Amnesic-MCI (aMCI) subjects progress to dementia (typically to Alzheimer-Dementia = AD) at an annual rate which is 20 times higher than that of cognitively intact elderly. The present study aims to investigate whether EEG network Small World properties (SW) combined with Apo-E genotyping, could reliably discriminate aMCI subjects who will convert to AD after approximately a year., Methods: 145 aMCI subjects were divided into two sub-groups and, according to the clinical follow-up, were classified as Converted to AD (C-MCI, 71) or Stable (S-MCI, 74)., Results: Results showed significant differences in SW in delta, alpha1, alpha2, beta2, gamma bands, with C-MCI in the baseline similar to AD. Receiver Operating Characteristic(ROC) curve, based on a first-order polynomial regression of SW, showed 57% sensitivity, 66% specificity and 61% accuracy(area under the curve: AUC=0.64). In 97 out of 145 MCI, Apo-E allele testing was also available. Combining this genetic risk factor with Small Word EEG, results showed: 96.7% sensitivity, 86% specificity and 91.7% accuracy(AUC=0.97). Moreover, using only the Small World values in these 97 subjects, the ROC showed an AUC of 0.63; the resulting classifier presented 50% sensitivity, 69% specificity and 59.6% accuracy. When different types of EEG analysis (power density spectrum) were tested, the accuracy levels were lower (68.86%)., Interpretation: Concluding, this innovative EEG analysis, in combination with a genetic test (both low-cost and widely available), could evaluate on an individual basis with great precision the risk of MCI progression. This evaluation could then be used to screen large populations and quickly identify aMCI in a prodromal stage of dementia. Ann Neurol 2018 Ann Neurol 2018;84:302-314., (© 2018 American Neurological Association.)

Rhythmic non-invasive brain stimulations are promising tools to modulate brain activity by entraining neural oscillations in specific cortical networks. The aim of the study was to assess the possibility to influence the neural circuits of the wake-sleep transition in awake subjects via a bilateral transcranial alternating current stimulation at 5 Hz (θ-tACS) on fronto-temporal areas. 25 healthy volunteers participated in two within-subject sessions (θ-tACS and sham), one week apart and in counterbalanced order. We assessed the stimulation effects on cortical EEG activity (28 derivations) and self-reported sleepiness (Karolinska Sleepiness Scale). θ-tACS induced significant increases of the theta activity in temporo-parieto-occipital areas and centro-frontal increases in the alpha activity compared to sham but failed to induce any online effect on sleepiness. Since the total energy delivered in the sham condition was much less than in the active θ-tACS, the current data are unable to isolate the specific effect of entrained theta oscillatory activity per se on sleepiness scores. On this basis, we concluded that θ-tACS modulated theta and alpha EEG activity with a topography consistent with high sleep pressure conditions. However, no causal relation can be traced on the basis of the current results between these rhythms and changes on sleepiness.

Sleep onset is characterized by a specific and orchestrated pattern of frequency and topographical EEG changes. Conventional power analyses of electroencephalographic (EEG) and computational assessments of network dynamics have described an earlier synchronization of the centrofrontal areas rhythms and a spread of synchronizing signals from associative prefrontal to posterior areas. Here, we assess how "small world" characteristics of the brain networks, as reflected in the EEG rhythms, are modified in the wakefulness-sleep transition comparing the pre- and post-sleep onset epochs. The results show that sleep onset is characterized by a less ordered brain network (as reflected by the higher value of small world) in the sigma band for the frontal lobes indicating stronger connectivity, and a more ordered brain network in the low frequency delta and theta bands indicating disconnection on the remaining brain areas. Our results depict the timing and topography of the specific mechanisms for the maintenance of functional connectivity of frontal brain regions at the sleep onset, also providing a possible explanation for the prevalence of the frontal-to-posterior information flow directionality previously observed after sleep onset. Hum Brain Mapp 38:5456-5464, 2017. © 2017 Wiley Periodicals, Inc., (© 2017 Wiley Periodicals, Inc.)

Given the importance of neuronal plasticity in recovery from a stroke and the huge variability of recovery abilities in patients, we investigated neuronal activity in the acute phase to enhance information about the prognosis of recovery in the stabilized phase. We investigated the microstates in 47 patients who suffered a first-ever mono-lesional ischemic stroke in the middle cerebral artery territory and in 20 healthy control volunteers. Electroencephalographic (EEG) activity at rest with eyes closed was acquired between 2 and 10 days (T0) after ischemic attack. Objective criteria allowed for the selection of an optimal number of microstates. Clinical condition was quantified by the National Institute of Health Stroke Scale (NIHSS) both in acute (T0) and stabilized (T1, 5.4 ± 1.7 months) phases and Effective Recovery (ER) was calculated as (NIHSS(T1)-NIHSS(T0))/NIHSS(T0). The microstates A, B, C and D emerged as the most stable. In patients with a left lesion inducing a language impairment, microstate C topography differed from controls. Microstate D topography was different in patients with a right lesion inducing neglect symptoms. In patients, the C vs D microstate duration differed after both a left and a right lesion with respect to controls (C lower than D in left and D lower than C in right lesion). A preserved microstate B in acute phase correlated with a better effective recovery. A regression model indicated that the microstate B duration explained the 11% of ER variance. This first ever study of EEG microstates in acute stroke opens an interesting path to identify neuronal impairments with prognostic relevance, to develop enriched compensatory treatments to drive a better individual recovery.

Brain imaging plays an important role in the study of Alzheimer's disease (AD), where atrophy has been found to occur in the hippocampal formation during the very early disease stages and to progress in parallel with the disease's evolution. The aim of the present study was to evaluate a possible correlation between "Small World" characteristics of the brain connectivity architecture-as extracted from EEG recordings-and hippocampal volume in AD patients. A dataset of 144 subjects, including 110 AD (MMSE 21.3) and 34 healthy Nold (MMSE 29.8) individuals, was evaluated. Weighted and undirected networks were built by the eLORETA solutions of the cortical sources' activities moving from EEG recordings. The evaluation of the hippocampal volume was carried out on a subgroup of 60 AD patients who received a high-resolution T1-weighted sequence and underwent processing for surface-based cortex reconstruction and volumetric segmentation using the Freesurfer image analysis software. Results showed that, quantitatively, more correlation was observed in the right hemisphere, but the same trend was seen in both hemispheres. Alpha band connectivity was negatively correlated, while slow (delta) and fast-frequency (beta, gamma) bands positively correlated with hippocampal volume. Namely, the larger the hippocampal volume, the lower the alpha and the higher the delta, beta, and gamma Small World characteristics of connectivity. Accordingly, the Small World connectivity pattern could represent a functional counterpart of structural hippocampal atrophying and related-network disconnection.

Graph theory applications had spread widely in understanding how human cognitive functions are linked to dynamics of neuronal network structure, providing a conceptual frame that can reduce the analytical brain complexity. This review summarizes methodological advances in this field. Electroencephalographic functional network studies in pathophysiological aging will be presented, focusing on neurodegenerative disease -such Alzheimer's disease-aiming to discuss whether network science is changing the traditional concept of brain disease and how network topology knowledge could help in modeling resilience and vulnerability of diseases. Aim of this work is to open discussion on how network model could better describe brain architecture., (Copyright © 2016 Elsevier B.V. All rights reserved.)

People with multiple sclerosis (MS) frequently complain of excessive fatigue, which is the most disabling symptom for half of them. While the few drugs used to treat MS fatigue are of limited utility, we recently observed the efficacy of a personalized neuromodulation treatment. Here, we aim at strengthening knowledge of the brain network changes that occur when MS fatigue increases, using graph theory. We collected electroencephalographic (EEG; 23 or 64 channels) data in resting state with eyes open in 27 relapsing-remitting (RR) patients with mild MS (EDSS ≤2), suffering a wide range of fatigue as scored by the modified Fatigue Impact Scale (mFIS) (2-69, within a total range 0-84). To estimate graph theory small-world index (SW), we calculated the lagged linear coherence between EEG cortical eLORETA sources, in the standard frequency bands delta (2-4 Hz), theta (4-8 Hz), alpha1 (8-10.5 Hz), alpha2 (10.5-13 Hz), beta1 (13-20 Hz), beta2 (20-30 Hz), and gamma (30-45 Hz). We calculated the SW of these undirected and weighted networks separately in the four left and right frontal (motor) and parieto-occipito-temporal (sensory) brain networks. A correlative analysis demonstrated increased fatigue symptoms along with the SW specifically in the Sensory network of the left dominant hemisphere in the beta1 band (Pearson's r = 0.404, P = .020). Our study indicates a specific involvement of the dominant-hemisphere sensory network in MS fatigue. It suggests that compensatory neuromodulation interventions could enhance efficacy in relieving this debilitating symptom by targeting this area., (© The Author(s) 2016.)

Transcranial direct current stimulation (tDCS) is well established-among the non-invasive brain stimulation techniques-as a method to modulate brain excitability. Polarity-dependent modulations of membrane potentials are detected after the application of anodal and cathodal stimulation, leading to changes in the electrical activity of the neurons. The main aim of the present study was to test the hypothesis that tDCS can affect-in a polarity-specific manner-the functional coupling of the sensorimotor areas during the eyes-open resting condition as revealed by total EEG coherence (i.e., coherence across the average of all combinations of the electrode pairs placed around the stimulation electrode). The changes in the total EEG coherence were evaluated pre-, during, and post-anodal and cathodal tDCS. While no differences were observed in the connectivity characteristics of the two pre-stimulation periods, a connectivity increase was observed in the alpha 2 band in the post-anodal tDCS with respect to pre-anodal and post-cathodal tDCS. The present study suggests that a specific approach based on the analyses of the functional coupling of EEG rhythms might enhance understanding of tDCS-induced effects on cortical connectivity. Moreover, this result suggests that anodal tDCS could possibly modify cortical connectivity more effectively with respect to cathodal tDCS., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Brain activity is complex; a reflection of its structural and functional organization. Among other measures of complexity, the fractal dimension is emerging as being sensitive to neuronal damage secondary to neurological and psychiatric diseases. Here, we calculated Higuchi's fractal dimension (HFD) in resting-state eyes-closed electroencephalography (EEG) recordings from 41 healthy controls (age: 20-89 years) and 67 Alzheimer's Disease (AD) patients (age: 50-88 years), to investigate whether HFD is sensitive to brain activity changes typical in healthy aging and in AD. Additionally, we considered whether AD-accelerating effects of the copper fraction not bound to ceruloplasmin (also called "free" copper) are reflected in HFD fluctuations. The HFD measure showed an inverted U-shaped relationship with age in healthy people (R2 = .575, p < .001). Onset of HFD decline appeared around the age of 60, and was most evident in central-parietal regions. In this region, HFD decreased with aging stronger in the right than in the left hemisphere (p = .006). AD patients demonstrated reduced HFD compared to age- and education-matched healthy controls, especially in temporal-occipital regions. This was associated with decreasing cognitive status as assessed by mini-mental state examination, and with higher levels of non-ceruloplasmin copper. Taken together, our findings show that resting-state EEG complexity increases from youth to maturity and declines in healthy, aging individuals. In AD, brain activity complexity is further reduced in correlation with cognitive impairment. In addition, elevated levels of non-ceruloplasmin copper appear to accelerate the reduction of neural activity complexity. Overall, HDF appears to be a proper indicator for monitoring EEG-derived brain activity complexity in healthy and pathological aging.

Objective: Applying graph theory, we investigated how cortical sources small worldness (SW) of resting EEG in eyes-closed/open (EC/EO) differs in amnestic mild cognitive impairment (aMCI) and Alzheimer's disease (AD) subjects with respect to normal elderly (Nold)., Methods: EEG was recorded in 30 Nold, 30 aMCI, and 30 AD during EC and EO. Undirected and weighted cortical brain network was built to evaluate graph core measures. eLORETA lagged linear connectivity was used to weight the network., Results: In Nold, in EO condition, the brain network is characterized by more SW (higher SW) in alpha bands and less SW (lower SW) in beta2 and gamma bands. In aMCI, SW has the same trend, except for delta and theta bands where the network shows less small worldness. AD shows a similar trend of Nold, but with less fluctuations between EO/EC conditions. Furthermore, in both conditions, aMCI SW architecture presents midway properties between AD and Nold. At low frequencies (delta e theta bands) in EC, aMCI group presents network's architecture similar to Nold, while in EO aMCI, SW is superimposable to AD ones., Conclusions: In resting state condition, aMCI small-world architecture presents midway topological properties between AD subjects and healthy controls, confirming the hypothesis that aMCI is an intermediate step along the disease progression., Significance: We proposed the application of graph theory to EEG in reactivity to EO in order to find a marker of diagnosis that - in association with other techniques of neuroimaging - could be sensitive to the progression of MCI or conversion into AD., (Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.)

Here we presented a single electroencephalographic (EEG) marker for a neurophysiological assessment of Alzheimer's disease (AD) patients already diagnosed by current guidelines. The ability of the EEG marker to classify 127 AD individuals and 121 matched cognitively intact normal elderly (Nold) individuals was tested. Furthermore, its relationship to AD patients' cognitive status and structural brain integrity was examined. Low-resolution brain electromagnetic tomography (LORETA) freeware estimated cortical sources of resting state eyes-closed EEG rhythms. The EEG marker was defined as the ratio between the activity of parieto-occipital cortical sources of delta (2-4 Hz) and low-frequency alpha (8-10.5 Hz) rhythms. Results showed 77.2% of sensitivity in the recognition of the AD individuals; 65% of specificity in the recognition of the Nold individuals; and 0.75 of area under the receiver-operating characteristic curve. Compared to the AD subgroup with the EEG maker within one standard deviation of the Nold mean (EEG-), the AD subgroup with EEG+ showed lower global cognitive status, as revealed by Mini-Mental State Evaluation score, and more abnormal values of white-matter and cerebrospinal fluid normalized volumes, as revealed by structural magnetic resonance imaging. We posit that cognitive and functional status being equal, AD patients with EEG+ should receive special clinical attention due to a neurophysiological "frailty". EEG+ label can be also used in clinical trials (i) to form homogeneous groups of AD patients diagnosed by current guidelines and (ii) as end-point to evaluate intervention effects.

Oscillating transcranial direct current stimulation (osc-tDCS) modulates the spontaneous brain activity in a frequency-specific manner. Most studies evaluated cortical effects of osc-tDCS through spectral measures, without differentiating components associated with rhythmic and non-rhythmic activity. Since osc-tDCS mainly affects brain oscillatory activity, our aim was to investigate on the specific changes of EEG oscillations following a frontal osc-tDCS at 0.8 and at 5 Hz. 20 healthy subjects (26.8 ± 2.5 years) participated in one of two experiments (Exp.1= 0.8-Hz tDCS, n= 10; Exp.2= 5-Hz tDCS, n= 10), consisting of 3 within-subject sessions: two active conditions with different stimulation polarity (anodal osctDCS, cathodal osc-tDCS), and a control condition (sham). EEG oscillatory components (28 cortical derivations) at the stimulation frequency were measured by the Better OSCillation detection method (BOSC). Variations between before and after the osc-tDCS were compared between conditions as a function of polarity (anodal vs. cathodal vs. sham) and frequency (0.8 vs. 5 Hz) of stimulation. The main finding is a significant local increase of 0.81-Hz slow oscillations (F(1,18)=19.97; p=0.0004) and 5.3-Hz theta oscillations (F(1,18)=26.93; p= 0.0001) after 5 Hz compared to 0.8-Hz tDCS. Our study shows larger frequency-specific and cross-frequency effects of 5-Hz compared to 0.8-Hz stimulation, not revealed by conventional FFT analyses. This finding is consistent with a more effective induction of EEG synchronization during wakefulness by means of a stimulation in the theta range, and it suggests to combine measurement of EEG power and EEG oscillations in future studies involving transcranial stimulations.

Objective: It is believed that effective connectivity and optimal network structure are essential for proper information processing in the brain. Indeed, functional abnormalities of the brain are found to be associated with pathological changes in connectivity and network structures. The aim of the present study was to explore the interictal network properties of EEG signals from temporal lobe structures in the context of fronto-temporal lobe epilepsy., Methods: To complete this aim, the graph characteristics of the EEG data of 17 patients suffering from focal epilepsy of the fronto-temporal type, recorded during interictal periods, were examined and compared in terms of the affected versus the unaffected hemispheres. EEG connectivity analysis was performed using eLORETA software in 15 fronto-temporal regions (Brodmann Areas BAs 8, 9, 10, 11, 20, 21, 22, 37, 38, 41, 42, 44, 45, 46, 47) on both affected and unaffected hemispheres., Results: The evaluation of the graph analysis parameters, such as 'global' (characteristic path length) and 'local' connectivity (clustering coefficient) showed a statistically significant interaction among side (affected and unaffected hemisphere) and Band (delta, theta, alpha, beta, gamma). Duncan post hoc testing showed an increase of the path length in the alpha band in the affected hemisphere with respect to the unaffected one, as evaluated by an inter-hemispheric marker. The affected hemisphere also showed higher values of local connectivity in the alpha band. In general, an increase of local and global graph theory parameters in the alpha band was found in the affected hemisphere. It was also demonstrated that these effects were more evident in drug-free patients than in those undergoing pharmacological therapy., Conclusions: The increased measures in the affected hemisphere of both functional local segregation and global integration could result from the combination of overlapping mechanisms, including reactive neuroplastic changes seeking to maintain constant integration and segregation properties., Significance: This reactive neuroplastic mechanism seeking to maintain constant integration and segregation properties seems to be more evident in the absence of antiepileptic treatment., (Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.)

Objective: Despite the increase in mobile telephone technology use and possible effects on brain excitability, no studies have investigated the impact of GSM like (Global System for Mobile Communications) signal on the ongoing spiking activity in human epileptic patients., Methods: Brain electrical (electroencephalogram, EEG) activity of 12 patients with focal epilepsy has been recorded under both Real and Sham exposure following a double-blind, crossover, counterbalanced design: before the exposure (pre-exposure/baseline session), during the Real or Sham 45 min exposure (during-exposure session), and after the exposure (post-exposure session). As dependent variables both spiking activity (spikes count) and EEG quantitative indices (spectral power and coherence data) have been considered., Results: Spiking activity tended to be lower under Real than under Sham exposure. EEG spectral content analysis indicated a significant increase of Gamma band under Real exposure, mainly evident in Parieto-occipital and Temporal areas. Connectivity data indicated increased interhemispheric (left temporal to right frontal Regions of Interest, ROIs) instantaneous coherence, in the Beta frequency band during-exposure with respect to baseline session. No significant modification of lagged coherence was observed., Conclusions: Acute GSM exposure in epileptic patients slightly influences their EEG properties, without reaching any clinical relevance., Significance: No signs were found of an increased risk of incoming seizures for these patients as a consequence of using mobile phones., (Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.)

Occipital sources of resting-state electroencephalographic (EEG) alpha rhythms are abnormal, at the group level, in patients with amnesic mild cognitive impairment (MCI) and Alzheimer's disease (AD). Here, we evaluated the hypothesis that amplitude of these occipital sources is related to neurodegeneration in occipital lobe as measured by magnetic resonance imaging. Resting-state eyes-closed EEG rhythms were recorded in 45 healthy elderly (Nold), 100 MCI, and 90 AD subjects. Neurodegeneration of occipital lobe was indexed by weighted averages of gray matter density, estimated from structural MRIs. EEG rhythms of interest were alpha 1 (8-10.5 Hz) and alpha 2 (10.5-13 Hz). EEG cortical sources were estimated by low-resolution brain electromagnetic tomography. Results showed a positive correlation between occipital gray matter density and amplitude of occipital alpha 1 sources in Nold, MCI, and AD subjects as a whole group (r = 0.3, p = 0.000004, N = 235). Furthermore, there was a positive correlation between the amplitude of occipital alpha 1 sources and cognitive status as revealed by Mini Mental State Examination score across all subjects (r = 0.38, p = 0.000001, N = 235). Finally, amplitude of occipital alpha 1 sources allowed a moderate classification of individual Nold and AD subjects (sensitivity: 87.8%; specificity: 66.7%; area under the receiver operating characteristic curve: 0.81). These results suggest that the amplitude of occipital sources of resting-state alpha rhythms is related to AD neurodegeneration in occipital lobe along pathologic aging., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Anticipating sensorimotor events allows adaptive reactions to environment with crucial implications for self-protection and survival. Here we review several studies of our group that aimed to test the hypothesis that the cortical processes preparing the elaboration of sensorimotor interaction is reflected by the reduction of anticipatory electroencephalographic alpha power (about 8-12Hz; event-related desynchronization, ERD), as an index that regulate task-specific sensorimotor processes, accounted by high-alpha sub-band (10-12Hz), rather than a general tonic alertness, accounted by low-alpha sub-band (8-10Hz). In this line, we propose a model for human cortical processes anticipating warned sensorimotor interactions. Overall, we reported a stronger high-alpha ERD before painful than non-painful somatosensory stimuli that is also predictive of the subjective evaluation of pain intensity. Furthermore, we showed that anticipatory high-alpha ERD increased before sensorimotor interactions between non-painful or painful stimuli and motor demands involving opposite hands. In contrast, sensorimotor interactions between painful somatosensory and sensorimotor demands involving the same hand decreased anticipatory high-alpha ERD, due to a sort of sensorimotor "gating" effect. In conclusion, we suggest that anticipatory cortical high-alpha rhythms reflect the central interference and/or integration of ascending (sensory) and descending (motor) signals relative to one or two hands before non-painful and painful sensorimotor interactions., (Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.)

Objective: Treatment-naïve patients with human immunodeficiency virus (HIV) are characterized by diffuse abnormalities of resting-state cortical electroencephalographic (EEG) rhythms (Babiloni et al., 2012a). Here, we tested the hypothesis that these EEG rhythms vary as a function of the systemic immune activity and antiretroviral therapy (ART) in HIV patients., Methods: Resting-state eyes-closed EEG data were recorded in 68 ART-HIV patients (mini mental state evaluation (MMSE) of 27.5 ± 0.3 SEM), in 60 treatment-naïve HIV subjects (MMSE of 27.5 ± 0.4 SEM) and in 75 age-matched cognitively normal subjects (MMSE of 29.3 ± 0.1 SEM). Based on the CD4 lymphocytes' count, we divided ART-HIV subjects into two subgroups: those with CD4>500 cells/μl (ART-HIV+) and those with CD4<500 cells/μl (ART-HIV-). EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-12 Hz), beta 1 (13-20 Hz), and beta 2 (20-30 Hz). Cortical EEG sources were estimated by LORETA software., Results: Widespread theta, alpha, and beta sources were lower in ART-HIV subjects than in control subjects. Furthermore, occipital and temporal alpha 1 sources were lower in treatment-naïve HIV than in ART-HIV subjects. Moreover, the opposite was true for widespread pathological delta sources. Finally, parietal, occipital, and temporal alpha 1 sources were lower in ART-HIV- than in ART-HIV+ subjects., Conclusions: In ART-HIV subjects, cortical sources of resting-state alpha rhythms are related to systemic immune activity and cART., Significance: This EEG procedure may produce biomarkers of treatment response in patients' brain compartments for longitudinal clinical studies., (Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.)

Objectives: The psychomotor vigilance task (PVT) is a widely used method for the assessment of vigilance after sleep deprivation (SDEP). However, the neural basis of PVT performance during SDEP has not been fully understood. In particular, no studies have investigated the possible relation between EEG topographical changes after sleep loss and PVT performance. The aim of the present study is to assess the EEG topographic correlates of PVT performance after SDEP., Methods: During 40 h of SDEP, 16 healthy male subjects were evaluated in four sessions performed at the same time (11:00 a.m. and 11:00 p.m.) of the first and second day with: (a) subjective sleepiness recordings by means of the Karolinska Sleepiness Scale (KSS); (b) EEG recordings (5 min eyes-open condition); and (c) PVT., Results: SDEP induced a slowing of PVT reaction times (RTs), higher level of subjective sleepiness and an increase of delta, theta, alpha and beta 1 EEG activity. Only slowest PVT RTs were influenced by circadian factors, with longer RTs in the morning. Both fastest PVT RTs and KSS scores were positively correlated with post-SDEP changes in EEG theta activity, mainly in centro-posterior areas, but not with other EEG frequencies. KSS scores and PVT measures were also positively correlated., Conclusions: These findings suggest that SDEP differently affects PVT variables, and that an increase in theta activity may be the principal EEG basis of the post-SDEP slowing of fastest PVT RTs. Similar neural mechanisms seem to underlie both performance deterioration to PVT and the increase of subjective sleepiness., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Purpose: Motor evoked potentials (MEPs) elicited by a train of consecutive, individual transcranial magnetic stimuli demonstrate fluctuations in amplitude with respect to time when recorded from a relaxed muscle. The influence of time-varying, instantaneous modifications of the electroencephalography (EEG) properties immediately preceding the transcranial magnetic stimulation (TMS) has rarely been explored. The aim of this study was to investigate the influence of the pre-TMS motor cortex and related areas EEG profile on time variants of the MEPs amplitude., Method: MRI-navigated TMS and multichannel TMS-compatible EEG devices were used. For each experimental subject, post-hoc analysis of the MEPs amplitude that was based on the 50th percentile of the MEPs amplitude distribution provided two subgroups corresponding to "high" (large amplitude) and "low" (small amplitude). The pre-stimulus EEG characteristics (coherence and spectral profile) from the motor cortex and related areas were analyzed separately for the "high" and "low" MEPs and were then compared., Results: On the stimulated hemisphere, EEG coupling was observed more often in the high compared to the low MEP trials. Moreover, a paradigmatic pattern in which TMS was able to lead to significantly larger MEPs was found when the EEG of the stimulated motor cortex was coupled in the beta 2 band with the ipsilateral prefrontal cortex and in the delta band with the bilateral centro-parietal-occipital cortices., Conclusion: This data provide evidence for a statistically significant influence of time-varying and spatially patterned synchronization of EEG rhythms in determining cortical excitability, namely motor cortex excitability in response to TMS., (Copyright © 2013 Wiley Periodicals, Inc.)

In this paper, we review the contribution of our research group to the study of human consciousness by quantitative electroencephalographic (EEG) techniques. We posit that EEG techniques can be extremely useful for a direct measurement of brain electrophysiological activity related to human consciousness for their unsurpassable high temporal resolution (milliseconds). This activity can be expressed in terms of event-related potentials as well as changes of EEG rhythms of interest, for example the dominant alpha rhythms (about 8-12 Hz). The results of our studies, and those of several independent groups, lead support to the hypothesis that these techniques provide important insights about the neurophysiologic mechanisms underlying cortical neural synchronization/desynchronization and the regulation of neuromodulatory systems (e.g. dopaminergic, noradrenergic, cholinergic, etc.) at the basis of brain arousal and consciousness in healthy subjects and in patients with impairment of the consciousness. A possible interaction of these mechanisms and the drugs administered to patients with consciousness disorders is discussed.

Modern analysis of electroencephalographic (EEG) rhythms provides information on dynamic brain connectivity. To test the hypothesis that aging processes modulate the brain connectivity network, EEG recording was conducted on 113 healthy volunteers. They were divided into three groups in accordance with their ages: 36 Young (15-45 years), 46 Adult (50-70 years), and 31 Elderly (>70 years). To evaluate the stability of the investigated parameters, a subgroup of 10 subjects underwent a second EEG recording two weeks later. Graph theory functions were applied to the undirected and weighted networks obtained by the lagged linear coherence evaluated by eLORETA on cortical sources. EEG frequency bands of interest were: delta (2-4 Hz), theta (4-8 Hz), alpha1 (8-10.5 Hz), alpha2 (10.5-13 Hz), beta1 (13-20 Hz), beta2 (20-30 Hz), and gamma (30-40 Hz). The spectral connectivity analysis of cortical sources showed that the normalized Characteristic Path Length (λ) presented the pattern Young > Adult>Elderly in the higher alpha band. Elderly also showed a greater increase in delta and theta bands than Young. The correlation between age and λ showed that higher ages corresponded to higher λ in delta and theta and lower in the alpha2 band; this pattern reflects the age-related modulation of higher (alpha) and decreased (delta) connectivity. The Normalized Clustering coefficient (γ) and small-world network modeling (σ) showed non-significant age-modulation. Evidence from the present study suggests that graph theory can aid in the analysis of connectivity patterns estimated from EEG and can facilitate the study of the physiological and pathological brain aging features of functional connectivity networks.

Objective: Brain rhythms of both hemispheres are involved in the processing of emotional stimuli but their interdependence between the two hemispheres is poorly known. Here we tested the hypothesis that passive visual perception of facial emotional expressions is related to a coordination of the two hemispheres as revealed by the inter-hemispherical functional coupling of brain electroencephalographic (EEG) rhythms., Methods: To this aim, EEG data were recorded in 14 subjects observing emotional faces with neutral, happy or sad facial expressions (about 33% for each class). The EEG data were analyzed by directed transfer function (DTF), which estimates directional functional coupling of EEG rhythms. The EEG rhythms of interest were theta (about 4-6 Hz), alpha 1 (about 6-8 Hz), alpha 2 (about 8-10 Hz), alpha 3 (about 10-12 Hz), beta 1 (13-20 Hz), beta 2 (21-30 Hz), and gamma (31-44 Hz)., Results: In the frontal regions, inter-hemispherical DTF values were bidirectionally higher in amplitude across all frequency bands, during the perception of faces with sad compared to neutral or happy expressions., Conclusions: These results suggest that the processing of emotional negative facial expressions is related to an enhancement of a reciprocal inter-hemispherical flux of information in frontal cortex, possibly optimizing executive functions and motor control., Significance: Dichotomical view of hemispherical functional specializations does not take into account remarkable reciprocal interactions between frontal areas of the two hemispheres during the processing of negative facial expressions., (Copyright © 2012 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.)

The human brain contains an intricate network of about 100 billion neurons. Aging of the brain is characterized by a combination of synaptic pruning, loss of cortico-cortical connections, and neuronal apoptosis that provoke an age-dependent decline of cognitive functions. Neural/synaptic redundancy and plastic remodeling of brain networking, also secondary to mental and physical training, promote maintenance of brain activity and cognitive status in healthy elderly subjects for everyday life. However, age is the main risk factor for neurodegenerative disorders such as Alzheimer's disease (AD) that impact on cognition. Growing evidence supports the idea that AD targets specific and functionally connected neuronal networks and that oscillatory electromagnetic brain activity might be a hallmark of the disease. In this line, digital electroencephalography (EEG) allows noninvasive analysis of cortical neuronal synchronization, as revealed by resting state brain rhythms. This review provides an overview of the studies on resting state eyes-closed EEG rhythms recorded in amnesic mild cognitive impairment (MCI) and AD subjects. Several studies support the idea that spectral markers of these EEG rhythms, such as power density, spectral coherence, and other quantitative features, differ among normal elderly, MCI, and AD subjects, at least at group level. Regarding the classification of these subjects at individual level, the most previous studies showed a moderate accuracy (70-80%) in the classification of EEG markers relative to normal and AD subjects. In conclusion, resting state EEG makers are promising for large-scale, low-cost, fully noninvasive screening of elderly subjects at risk of AD.

Patients suffering from prodromal (i.e., amnestic mild cognitive impairment, aMCI) and overt Alzheimer's disease (AD) show abnormal cortical sources of resting state electroencephalographic (EEG) rhythms. Here we tested the hypothesis that these sources show extensive abnormalities in liver cirrhosis (LC) patients with a cognitive impairment due to covert and diffuse hepatic encephalopathy (CHE). EEG activity was recorded in 64 LC (including 21 CHE), 21 aMCI, 21 AD, and 21 cognitively intact (Nold) subjects. EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), and beta 2 (20-30 Hz). EEG cortical sources were estimated by LORETA. Widespread sources of theta (all but frontal), alpha 1 (all but occipital), and alpha 2 (parietal, temporal) rhythms were higher in amplitude in all LC patients than in the Nold subjects. In these LC patients, the activity of central, parietal, and temporal theta sources correlated negatively, and parietal and temporal alpha 2 sources correlated positively with an index of global cognitive status. Finally, widespread theta (all but frontal) and alpha 1 (all but occipital) sources showed higher activity in the sub-group of LC patients with CHE than in the patients with aMCI or AD. These results unveiled the larger spatial-frequency abnormalities of the resting state EEG sources in the CHE compared to the AD condition.

Objective: Previous studies have been inconclusive whether dominant resting state alpha rhythms differ in amplitude in dyslexic subjects when compared to control subjects, being these rhythms considered as a reflection of effective cortical neural synchronization and cognition. Here we used a validated EEG source estimation to test the hypothesis that resting state alpha rhythms are abnormal in dyslexic subjects and are related to reading deficits., Methods: Eyes-closed resting state electroencephalographic (EEG) data were recorded in 26 dyslexics (12 males, mean age of 11 years ± 0.5 standard error of mean, SEM) and 11 age-matched normal control subjects (8 males, mean age of 11 years ± 0.7 SEM). EEG rhythms of interest, based on individual alpha frequency peak, were the following: about 2-4 Hz (delta), 4-6 Hz (theta), 6-8 Hz (alpha 1), 8-10 Hz (alpha 2), and 10-12 Hz (alpha 3). For the higher frequencies, we selected beta 1 (13-20 Hz), beta 2 (20-30 Hz), and gamma (30-40 Hz). Cortical EEG sources were estimated by low resolution electromagnetic tomography (LORETA). LORETA solutions were normalized across all voxels and frequencies., Results: Compared to the control children, the dyslexics showed lower amplitude of parietal, occipital, and temporal alpha 2 and alpha 3 sources. In the dyslexics, some of these sources were correlated to reading time of pseudo-words (parietal alpha 2, r=-0.56, p=0.02; parietal alpha 3, r=-0.58, p=0.02; temporal alpha 3, r=-0.57, p=0.02); the higher the alpha power, the shorter the reading time., Conclusions: Dyslexic children are characterized by limited abnormalities of resting state EEG rhythms as to topography (posterior regions) and frequency (alpha), which were related to phonological encoding (pseudo-words reading)., Significance: Dyslexia may be associated to some functional impairment of cortical neuronal synchronization mechanisms involved in the resting state condition., (Copyright © 2012 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.)

Objective: The aim of the study was to test the hypothesis that cortical sources of resting-state electroencephalographic (EEG) rhythms show peculiar frequency/spatial features in naïve human subjects with human immunodeficiency virus (HIV) compared to healthy control subjects., Methods: Resting-state eyes-closed EEG data were recorded in 18 naïve HIV subjects (15 males; mean age 39 years±2.0 standard error of mean, SEM) and in 18 age-matched cognitively normal subjects (15 males; 38.7years±2.2 SEM). EEG rhythms of interest were delta (2-4Hz), theta (4-8Hz), alpha1 (8-10Hz), alpha2 (10-12Hz), beta1 (13-20Hz) and beta2 (20-30Hz). Cortical EEG sources were estimated by normalised, low-resolution electromagnetic tomography (LORETA)., Results: Mini Mental State Evaluation (MMSE) score was lower in HIV (26.5 ± 0.7 SEM) than in healthy (29.2 ± 0.5 SEM) subjects (p<0.05). Central and parietal delta sources showed higher amplitude in the HIV than in control subjects. Furthermore, topographically widespread, cortical sources of resting-state alpha rhythms were lower in amplitude in HIV subjects than in control subjects., Conclusions: The present results suggest that topography and frequency of the cortical sources of resting-state EEG rhythms can distinguish groups of HIV and control subjects., Significance: These results encourage future studies in an enlarged cohort of HIV subjects to test the hypothesis that the present methodological approach provides clinically useful information for an early detection of the effect of HIV infection on brain and cognitive functions., (Copyright © 2012 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.)

Introduction: The brain needs continuous oxygen supply even in resting-state. Hypoxia enhances resting-state electroencephalographic (EEG) rhythms in the delta range, and reduces those in the alpha range, with a pattern similar to that observed in Alzheimer's disease (AD). Here we tested whether resting-state cortical EEG rhythms in patients with congestive heart failure (CHF), as a model of acute hypoxia, present frequency similarities with AD patients, comparable by cognitive status revealed by the mini mental state examination (MMSE)., Methods: Eyes-closed EEG data were recorded in 10 CHF patients, 20 AD patients, and 20 healthy elderly subjects (Nold) as controls. LORETA software estimated cortical EEG generators., Results: Compared to Nold, both AD and CHF groups presented higher delta (2-4Hz) and lower alpha (8-13Hz) temporal sources. The highest delta and lowest alpha sources were observed in CHF subjects. In these subjects, the global amplitude of delta sources correlated with brain natriuretic peptide (BNP) level in the blood, as a marker of disease severity., Conclusions: Resting-state delta and alpha rhythms suggest analogies between the effects of acute hypoxia and AD neurodegeneration on the cortical neurons' synchronization., Significance: Acute ischemic hypoxia could affect the mechanisms of cortical neural synchronization generating resting state EEG rhythms, inducing the "slowing" of EEG rhythms typically observed in AD patients., (Copyright © 2012 Elsevier B.V. All rights reserved.)

Playing music in ensemble represents a unique human condition/performance where musicians should rely on empathic relationships. Recent theories attribute to frontal Brodmann areas (BAs) 44/45 and 10/11 a neural basis for "emotional" and "cognitive" empathy. We hypothesized that activity of these structures reflects empathy trait in professional musicians playing in ensemble. Simultaneous electroencephalographic (EEG) alpha rhythms (8-12 Hz) were recorded in three saxophone quartets during music performance in ensemble (EXECUTION), video observation of their own performance (OBSERVATION), a control task (CONTROL), and resting state (RESTING). EEG source estimation was performed. Results showed that the higher the empathy quotient test score, the higher the alpha desynchronization in right BA 44/45 during the OBSERVATION referenced to RESTING condition. Empathy trait score and alpha desynchronization were not correlated in other control areas or in EXECUTION/CONTROL conditions. These results suggest that alpha rhythms in BA 44/45 reflect "emotional" empathy in musicians observing own performance., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Objective: Here we test the hypothesis that cortical source mapping of resting state electroencephalographic (EEG) rhythms could characterize neurodegenerative disorders inducing cognitive impairment such as Parkinson's disease related dementia (PDD) and Alzheimer's disease (AD)., Methods: To address this issue, eyes-closed resting state EEG rhythms were recorded in 13 PDD, 20 AD, and 20 normal elderly (Nold) subjects. Age, gender, and education were carefully matched across the three groups. Mini Mental State Evaluation (MMSE) score probed subjects' global cognitive status, and was matched between the PDD and AD groups. EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha1 (8-10.5 Hz), alpha2 (10.5-13 Hz), beta1 (13-20 Hz), and beta2 (20-30 Hz). EEG cortical sources were estimated by low resolution brain electromagnetic source tomography (LORETA)., Results: With respect to the Nold and AD groups, the PPD group was characterized by peculiar abnormalities of central delta sources and posterior cortical sources of theta and beta1 rhythms. With respect to the Nold group, the PDD and AD groups mainly pointed to lower posterior cortical sources of alpha1 rhythms, which were positively correlated to MMSE score across all PDD and AD subjects as a whole (the lower the alpha sources, the lower the MMSE score). This alpha decrease was greater in the AD than PPD patients., Conclusions: The results suggest that topography and frequency of eyes-closed resting state cortical EEG rhythms distinguished PDD and AD groups., Significance: We report the existence of different effects of neurodegeneration on the cortical neural synchronization mechanisms generating resting state EEG rhythms in PDD and AD patients., (Copyright © 2011. Published by Elsevier Ireland Ltd.)

In the present study, we tested the hypothesis that compared with non-athletes, elite athletes are characterized by a reduction of reactivity of electroencephalographic (EEG) alpha rhythms (about 8-12 Hz) to eyes opening in the condition of resting state, as a possible index of spatially selective cortical activation (i.e. "neural efficiency"). EEG data (56 channels; Eb-Neuro©) were recorded in 18 elite karate athletes and 28 non-athletes during resting state eyes-closed and eyes-open conditions. The EEG data were spatially enhanced by surface Laplacian estimation. Cortical activity was indexed by task-related power decrease (TRPD), namely the alpha power during the eyes-open referenced to the eyes-closed resting condition. Low-frequency alpha TRPD (about 8-10 Hz) was lower in the elite karate athletes than in the non-athletes in frontal (p<0.00002), central (p<0.008) and right occipital (p<0.02) areas. Similarly, high-frequency alpha TRPD (about 10-12 Hz) was lower in the elite karate athletes than in the non-athletes in frontal (p<0.00009) and central (p<0.01) areas. These results suggest that athletes' brain is characterized by reduced cortical reactivity to eyes opening in the condition of resting state, in line with the "neural efficiency" hypothesis. The present study motivates future research evaluating the extent to which this general functional brain feature is related to heritable trait or intensive visuo-motor training of elite athletes., (Copyright © 2011 Elsevier B.V. All rights reserved.)

It has been shown that frontocentral electroencephalographic (EEG) alpha rhythms (about 10-12 Hz) were higher in amplitude in expert golfers in successful than unsuccessful putts, possibly reflecting the idea that amplitude regulation of frontocentral alpha rhythms is a physiological mechanism implied in motor control and golfer's performance (Babiloni et al., 2008). Here, we tested the ancillary hypothesis that golfer's performance is also associated to an improved coordination of cortical activity, as reflected by functional coupling of alpha rhythms across cortical regions. To this aim, between-electrodes spectral coherence was computed from spatially enhanced EEG data of the mentioned study (i.e. right handed 12 expert golfers; augmented 10-20 system; surface Laplacian estimation). Low- (about 8-10 Hz) and high-frequency (about 10-12 Hz) alpha sub-bands were considered with reference to individual alpha frequency peak. Statistical results showed that intra-hemispheric low-frequency alpha coherence in bilateral parietal-frontal (P3-F3 and P4-F4 electrodes) and parietal-central (P3-C3 and P4-C4 electrodes) was higher in amplitude in successful than unsuccessful putts (p<0.004). The same was true for intra-hemispheric high-frequency alpha coherence in bilateral parietal-frontal regions (p<0.004). These findings suggest that intra-hemispheric functional coupling of cortical alpha rhythms between "visuo-spatial" parietal area and other cortical areas is implicated in fine motor control of golfer's performance., (Copyright © 2011 Elsevier B.V. All rights reserved.)

Previous evidence has shown that resting eyes-closed cortical alpha rhythms are higher in amplitude in mild cognitive impairment (MCI) than Alzheimer's disease (AD) subjects (Babiloni et al. [2006a]: Human Brain Mapp 27:162-172; [2006b]: Clin Neurophysiol 117:252-268; [2006c]: Neuroimage 29:948-964; [2006d]: Ann Neurol 59:323-334; [2006e]: Clin Neurophysiol 117:1113-1129; [2006f]: Neuroimage 31:1650-1665). This study tested the hypothesis that, in amnesic MCI subjects, high amplitude of baseline cortical alpha rhythms is related to long-term stability of global cognition on clinical follow-up. Resting electroencephalographic (EEG) data were recorded in 100 amnesic MCI subjects during eyes-closed condition. EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha1 (8-10.5 Hz), alpha2 (10.5-13 Hz), beta1 (13-20 Hz), and beta2 (20-30 Hz). Cortical EEG sources were estimated by low-resolution brain electromagnetic tomography (LORETA). Global cognition was indexed by mini mental state evaluation (MMSE) score at the time of EEG recordings (baseline) and about after 1 year. Based on the MMSE percentage difference between baseline and 1-year follow-up (MMSEvar), the MCI subjects were retrospectively divided into three arbitrary groups: DECREASED (MMSEvar ≤ -4%; N = 43), STABLE (MMSEvar ≈ 0; N = 27), and INCREASED (MMSEvar ≥ +4%; N = 30). Subjects' age, education, individual alpha frequency, gender, and MMSE scores were used as covariates for statistical analysis. Baseline posterior cortical sources of alpha 1 rhythms were higher in amplitude in the STABLE than in the DECREASED and INCREASED groups. These results suggest that preserved resting cortical neural synchronization at alpha frequency is related to a long-term (1 year) stable cognitive function in MCI subjects. Future studies should use serial MMSE measurements to confirm and refine the present results., (Copyright © 2010 Wiley-Liss, Inc.)