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Applying graph theory, we investigated how cortical sources small worldness (SW) of resting EEG in eyes-closed/open (EC/EO) differs in mild cognitive impairment (MCI) and Alzheimer’s disease (AD) subjects respect to normal elderly (Nold). EEGs were recorded in 30 Nold, 30 MCI, 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. In Nold, EO condition presented more random network (higher SW) in alpha bands and more regular organization (lower SW) in beta2 and gamma bands. In MCI, SW trend was the same, except for delta and theta bands with more ordered organization. AD showed similar trend of Nold, but with less fluctuations between the conditions. Furthermore, in both conditions, MCI SW architecture presented midway properties between AD and Nold. In low frequencies, Nold showed more random network organization, while SW parameter displayed a more ordered architecture with disease progression. Small world properties had different patterns in pathological aging in open eyes, with different trends in EEG frequency bands. Graph theory provides an excellent tool to characterize neuronal network capacities from coupling parameters of time-varying signals. [ABSTRACT FROM AUTHOR]

Functional brain abnormalities including memory loss are found to be associated with pathological changes in connectivity and network neural structures. Alzheimer’s disease (AD) interferes with memory formation from the molecular level, to synaptic functions and neural networks organization. Here, we determined whether brain connectivity of resting-state networks correlate with memory in patients affected by AD and in subjects with mild cognitive impairment (MCI). One hundred and forty-four subjects were recruited: 70 AD (MMSE Mini Mental State Evaluation 21.4), 50 MCI (MMSE 25.2) and 24 healthy subjects (MMSE 29.8). Undirected and weighted cortical brain network was built to evaluate graph core measures to obtain Small World parameters. eLORETA lagged linear connectivity as extracted by electroencephalogram (EEG) signals was used to weight the network. A high statistical correlation between Small World and memory performance was found. Namely, higher Small World characteristic in EEG gamma frequency band during the resting state, better performance in short-term memory as evaluated by the digit span tests. Such Small World pattern might represent a biomarker of working memory impairment in older people both in physiological and pathological conditions. [ABSTRACT FROM AUTHOR]

Aim of this study was to verify whether the topological organization of human brain functional networks is different for males and females in resting state EEGs. Undirected and weighted brain networks were computed by eLORETA lagged linear connectivity in 130 subjects (59 males and 71 females) within each hemisphere and in four resting state networks (Attentional Network (AN), Frontal Network (FN), Sensorimotor Network (SN), Default Mode Network (DMN)). We found that small-world (SW) architecture in the left hemisphere Frontal network presented differences in both delta and alpha band, in particular lower values in delta and higher in alpha 2 in males respect to females while in the right hemisphere differences were found in lower values of SW in males respect to females in gamma Attentional, delta Sensorimotor and delta and gamma DMNs. Gender small-worldness differences in some of resting state networks indicated that there are specific brain differences in the EEG rhythms when the brain is in the resting-state condition. These specific regions could be considered related to the functions of behavior and cognition and should be taken into account both for research on healthy and brain diseased subjects. [ABSTRACT FROM AUTHOR]

Cortical connectivity in physiological and pathological aging. Physiological aging was evaluated in 113 EEGs, divided in three groups: Young (18–45 years), Adult (50–70) and Elderly (>70). Pathological aging was evaluated in 378 EEGs, divided in: Alzheimer disease (AD), mild cognitive impaired (MCI) and normal elderly subjects. Graph theory parameters were applied to undirected and weighted networks obtained by lagged linear coherence evaluated by eLORETA in delta, theta, alpha1, alpha2, beta1, beta2 and gamma bands. In physiological aging, normalized Characteristic Path Length ( λ ) presented the pattern Young > Adult > Elderly in the higher alpha band, the pattern Elderly > Young in delta and theta bands. Normalized Clustering coefficient ( γ ) and Small-World ( σ ) showed no significant age-modulation. In pathological aging, λ presented differences between healthy and dementia in theta band while γ showed a significant increment for AD in delta, theta and alpha1 bands; finally, σ presented a significant rising in MCI respect to AD in theta band.Functional integration was prejudiced in both physiological and pathological aging, while functional segregation of brain networks is more evident only in the pathological aging. Graph theory can disclose brain network connectivity in physiological and pathological aging, allowing understanding functional integration and segregation processes. [ABSTRACT FROM AUTHOR]

Introduction Transcranial direct current stimulation (tDCS) is a non-invasive method modulating cortical excitability in a polarity-dependent way. At present, only few studies investigated the effects of tDCS on the modulation of functional connectivity between remote cortical areas. Objective In the present study we aimed to investigate the impact of bipolar tDCS on cortical networks connectivity through graph theoretical analysis. Materials & methods High-density EEG recordings were acquired before and after bipolar anodal, cathodal and sham tDCS applied over the primary motor cortex of the dominant hemisphere in 14 healthy subjects. Results Results showed that, after bipolar anodal tDCS stimulation over the dominant primary motor cortex the related brain network presented a more small-worldnessy, meaning a global tendency to be more random in its functional connections respect to prestimulus condition in both hemispheres. Conclusions Our results suggest that tDCS is able to modulate globally the cortical connectivity of the brain, modifying the underlying functional organization via complex pattern of direct and indirect cortical activations or inhibitions of the stimulated networks, which might be related to changes in synaptic efficiency of the motor network and related brain areas. [ABSTRACT FROM AUTHOR]

Functional connectivity, revealed by EEG, evaluates time synchronization in anatomically distinct but functionally collaborating brain regions. Structural connection, revealed by diffusion tensor imaging (DTI), detects fractional anisotropy (FA). FA decreases in pathological aging corpus callosum (CC) and could reflect functional disconnections. We investigated correlations between structural damage of CC (MRI-DTI) and functional abnormalities of brain integration (cortical Characteristic Path Length of EEG). Resting state EEG and MRI were evaluated in 9 healthy controls-Nold, 10 Mild Cognitive Impairment – MCI, 10 mild Alzheimer Disease – AD, 11 moderate AD. Undirected and weighted brain network was built to evaluate graph Path Length weighting network edges by eLORETA lagged connectivity. Callosal FA reduction was associated to a loss of brain interhemispheric functional connectivity characterized by increased delta and decreased alpha Path Length. Global (path length as index of how efficient is the information transfer inside network) functional measure can reflect the reduction of fibers connecting the hemispheres as revealed by DTI. Functional and structural disconnections do not share the same timing (functional coming first) in the prodromal stage of disease, but in disease evolution (from healthy to dementia) it is possible to obtain statistical correlations between connectivity’s indexes. [ABSTRACT FROM AUTHOR]

Objective We explored interictal network properties of EEG from fronto-temporal lobe (FTL) structures in FTL epilepsy. Methods Graph theory parameters of EEG data of 17 patients suffering from FTL focal epilepsy, recorded during interictal periods, were examined and compared in terms of affected versus unaffected hemispheres. EEG connectivity analysis was performed using eLORETA software in 15 fronto-temporal regions on both hemispheres. Results Graph theory parameters, such as ‘global’ (characteristic path length) and ‘local’ (clustering coefficient) connectivity, showed a significant interaction among side (affected and unaffected hemisphere) and band (delta, theta, alpha, beta, gamma). Post hoc testing showed an increase of path length in alpha band in the affected hemisphere with respect to the unaffected one. Affected hemisphere also showed higher values of local connectivity in alpha band. In general, an increase of both local and global graph theory parameters in alpha band was found in affected hemisphere. Conclusions Altogether, both global and local measures can reveal cortical network features distinguishing epileptic affected and non-affected hemispheres. Key message This study opens interesting avenues for future researches investigating eventual modifications of brain connectivity in the epochs approximating a clinical seizure, as well as the impact of antiepileptic drugs on pharmacologically naïve patients. [ABSTRACT FROM AUTHOR]

Objective Functional connectivity is essential for brain functions. Focal brain lesions could have important remote effects on the functions of distant brain regions even if outside the damaged area. Network dysfunction may contribute to neurological deficits observed for example after stroke. We explored how functional network characteristics, measured via EEG recordings, correlate with the lesion volume on MRI. Methods Graph characteristics of EEG data of 30 stroke patients in the acute stage (no more than 5 days after the event), were examined. EEG connectivity analysis was performed using eLORETA in both affected and unaffected hemispheres. Lesional volume were evaluated by MRI. Results Considering all subjects as a group, in the stroke hemisphere both Path length and Clustering positively correlate with lesion volume in delta and theta bands and negatively in alpha1 band. Evaluating the contralateral hemisphere, no significant correlation was observed. Conclusions Lesion volume correlates with a progressive reduction of brain interconnection as provided by the proportional increment of connectivity in low frequency and reduction in higher frequency bands. Key message These results support the study of EEG via graph theory parameters for assessing the connectivity characteristics of brain networks in stroke suggesting a possible implications also in their prognosis. [ABSTRACT FROM AUTHOR]

Objective After cerebral ischemia, disruption and subsequent reorganization of functional connections occur both locally and remote to the lesion. Recently, brain complexity has been described using the graph theory, an elegant approach which depicts important properties of complex systems by quantifying topologies of network representations. We tested whether ischemic stroke may determine changes in smallworldness of cortical networks as measured by cortical sources of EEG. Methods Graph characteristics of EEG of 30 consecutive stroke patients in acute stage (no more than 5 days after the event) were examined. Connectivity analysis was performed using eLORETA in both hemispheres. Results Network rearrangements are mainly detected in delta, theta and alpha bands. Similar findings were observed in both hemispheres regardless the side of ischemic lesion: bilaterally decreased smallworldness in the delta band; similar modification observed in the theta band, but statistically significant only in left hemisphere stroke patients. Conclusions After an acute stroke, brain cortex rearranges its network connections diffusely, in a frequency-dependent modality in order to face the new anatomical and functional condition. Modifications in distinct frequencies suggests that the network remodelling occurs with different modalities. Key message Stroke-related brain network reorganization could reflect a not negligible adaptive process. [ABSTRACT FROM AUTHOR]

Objective Functional connectivity, revealed by EEG, evaluates time synchronization in anatomically distinct but functionally collaborating brain regions. Structural connection, revealed by diffusion tensor imaging (DTI), detects fractional anisotropy (FA). FA decreases in pathological aging corpus callosum (CC) and could reflect functional disconnections. We investigated correlations between structural damage of CC (MRI-DTI) and functional abnormalities of brain integration (cortical Characteristic Path Length of EEG). Methods Resting state EEG and MRI were evaluated in 9 healthy controls-Nold, 10 Mild Cognitive Impairment-MCI, 10 mild Alzheimer Disease-AD, 11 moderate AD. Undirected and weighted brain network was built to evaluate graph Path Length weighting network edges by eLORETA lagged connectivity. Results Callosal FA reduction was associated to a loss of brain interhemispheric functional connectivity characterized by increased delta and decreased alpha Path Length. Conclusions Global (path length as index of how efficient is the information transfer inside network) functional measure can reflect the reduction of fibers connecting the hemispheres as revealed by DTI. Key message Functional and structural disconnections do not share the same timing (functional coming first) in the prodromal stage of disease, but in disease evolution (from healthy to dementia) it is possible to obtain statistical correlations between connectivity’s indexes. [ABSTRACT FROM AUTHOR]