Head motion and Inattention/Hyperactivity share common genetic influences: Implications for fMRI studies of ADHD

Head motion (HM) is a well known confound in analyses of functional MRI (fMRI) data. Neuroimaging researchers therefore typically treat HM as a nuisance covariate in their analyses. Even so, it is possible that HM shares a common genetic influence with the trait of interest. Here we investigate the extent to which this relationship is due to shared genetic factors, using HM extracted from resting-state fMRI and maternal and self report measures of Inattention and Hyperactivity-Impulsivity from the Strengths and Weaknesses of ADHD Symptoms and Normal Behaviour (SWAN) scales. Our sample consisted of healthy young adult twins (N = 627 (63% females) including 95 MZ and 144 DZ twin pairs, mean age 22, who had mother-reported SWAN; N = 725 (58% females) including 101 MZ and 156 DZ pairs, mean age 25, with self reported SWAN). This design enabled us to distinguish genetic from environmental factors in the association between head movement and ADHD scales. HM was moderately correlated with maternal reports of Inattention (r = 0.17, p-value = 7.4E-5) and Hyperactivity-Impulsivity (r = 0.16, p-value = 2.9E-4), and these associations were mainly due to pleiotropic genetic factors with genetic correlations [95% CIs] of rg = 0.24 [0.02, 0.43] and rg = 0.23 [0.07, 0.39]. Correlations between self-reports and HM were not significant, due largely to increased measurement error. These results indicate that treating HM as a nuisance covariate in neuroimaging studies of ADHD will likely reduce power to detect between-group effects, as the implicit assumption of independence between HM and Inattention or Hyperactivity-Impulsivity is not warranted. The implications of this finding are problematic for fMRI studies of ADHD, as failing to apply HM correction is known to increase the likelihood of false positives. We discuss two ways to circumvent this problem: censoring the motion contaminated frames of the RS-fMRI scan or explicitly modeling the relationship between HM and Inattention or Hyperactivity-Impulsivity

Heritability of the network architecture of intrinsic brain functional connectivity

The brain's functional network exhibits many features facilitating functional specialization, integration, and robustness to attack. Using graph theory to characterize brain networks, studies demonstrate their small-world, modular, and "rich-club" properties, with deviations reported in many common neuropathological conditions. Here we estimate the heritability of five widely used graph theoretical metrics (mean clustering coefficient (γ), modularity (Q), rich-club coefficient (ϕnorm), global efficiency (λ), small-worldness (σ)) over a range of connection densities (k=5-25%) in a large cohort of twins (N=592, 84 MZ and 89 DZ twin pairs, 246 single twins, age 23±2.5). We also considered the effects of global signal regression (GSR). We found that the graph metrics were moderately influenced by genetic factors h2 (γ=47-59%, Q=38-59%, ϕnorm=0-29%, λ=52-64%, σ=51-59%) at lower connection densities (≤15%), and when global signal regression was implemented, heritability estimates decreased substantially h2 (γ=0-26%, Q=0-28%, ϕnorm=0%, λ=23-30%, σ=0-27%). Distinct network features were phenotypically correlated (|r|=0.15-0.81), and γ, Q, and λ were found to be influenced by overlapping genetic factors. Our findings suggest that these metrics may be potential endophenotypes for psychiatric disease and suitable for genetic association studies, but that genetic effects must be interpreted with respect to methodological choices.

Phase synchronization in brain networks derived from correlation between probabilities of recurrences in functional MRI data

It is increasingly being recognized that resting state brain connectivity derived from functional magnetic resonance imaging (fMRI) data is an important marker of brain function both in healthy and clinical populations. Though linear correlation has been extensively used to characterize brain connectivity, it is limited to detecting first order dependencies. In this study, we propose a framework where in phase synchronization (PS) between brain regions is characterized using a new metric ``correlation between probabilities of recurrence'' (CPR) and subsequent graph-theoretic analysis of the ensuing networks. We applied this method to resting state fMRI data obtained from human subjects with and without administration of propofol anesthetic. Our results showed decreased PS during anesthesia and a biologically more plausible community structure using CPR rather than linear correlation. We conclude that CPR provides an attractive nonparametric method for modeling interactions in brain networks as compared to standard correlation for obtaining physiologically meaningful insights about brain function.

La aventura no cumplida : el camino hacia el ocaso del caballero andante

Resumen: Los movimientos del héroe hacia su gloria implican una serie de acontecimientos, en los cuales la magia y la maravilla se unen para prodigar este derrotero de auxilios y obstáculos que fortifican el carácter del caballero y ayudan a este a alcanzar su ethos caballeresco. Batallas, encuentros fabulosos y apariciones extrañas se engarzan como cuentas en un collar para conducirlo a su plena realización. De forma similar, las aventuras no cumplidas indican al héroe que la hora del reposo ha llegado, que su andar, si bien en algunas oportunidades continúa, será menos intenso, y que debe dejar el lugar para su heredero. El universo mágico interviene igualmente en esta especie de ocaso del protagonismo para señalarle que la aventura no puede ser llevada a cabo por él, sino por su hijo. En este trabajo se pretende examinar cómo el elemento mágico interviene en este “estado de reposo” del caballero andante, que implica frecuentemente su entronización como gobernante de un reino o imperio, y el nacimiento del nuevo futuro caballero.

Neurotransmitter signaling in the pathophysiology of microglia

Erratun publicado en Frontiers in Cellular Neuroscience 7 : (2013) // Article ID 107

Mathematical study of complex networks : brain, internet, and power grid

The dissertation is concerned with the mathematical study of various network problems. First, three real-world networks are considered: (i) the human brain network (ii) communication networks, (iii) electric power networks. Although these networks perform very different tasks, they share similar mathematical foundations. The high-level goal is to analyze and/or synthesis each of these systems from a “control and optimization” point of view. After studying these three real-world networks, two abstract network problems are also explored, which are motivated by power systems. The first one is “flow optimization over a flow network” and the second one is “nonlinear optimization over a generalized weighted graph”. The results derived in this dissertation are summarized below.

Brain Networks: Neuroimaging data reveals the coordinated activity of spatially distinct brain regions, which may be represented mathematically as a network of nodes (brain regions) and links (interdependencies). To obtain the brain connectivity network, the graphs associated with the correlation matrix and the inverse covariance matrix—describing marginal and conditional dependencies between brain regions—have been proposed in the literature. A question arises as to whether any of these graphs provides useful information about the brain connectivity. Due to the electrical properties of the brain, this problem will be investigated in the context of electrical circuits. First, we consider an electric circuit model and show that the inverse covariance matrix of the node voltages reveals the topology of the circuit. Second, we study the problem of finding the topology of the circuit based on only measurement. In this case, by assuming that the circuit is hidden inside a black box and only the nodal signals are available for measurement, the aim is to find the topology of the circuit when a limited number of samples are available. For this purpose, we deploy the graphical lasso technique to estimate a sparse inverse covariance matrix. It is shown that the graphical lasso may find most of the circuit topology if the exact covariance matrix is well-conditioned. However, it may fail to work well when this matrix is ill-conditioned. To deal with ill-conditioned matrices, we propose a small modification to the graphical lasso algorithm and demonstrate its performance. Finally, the technique developed in this work will be applied to the resting-state fMRI data of a number of healthy subjects.

Communication Networks: Congestion control techniques aim to adjust the transmission rates of competing users in the Internet in such a way that the network resources are shared efficiently. Despite the progress in the analysis and synthesis of the Internet congestion control, almost all existing fluid models of congestion control assume that every link in the path of a flow observes the original source rate. To address this issue, a more accurate model is derived in this work for the behavior of the network under an arbitrary congestion controller, which takes into account of the effect of buffering (queueing) on data flows. Using this model, it is proved that the well-known Internet congestion control algorithms may no longer be stable for the common pricing schemes, unless a sufficient condition is satisfied. It is also shown that these algorithms are guaranteed to be stable if a new pricing mechanism is used.

Electrical Power Networks: Optimal power flow (OPF) has been one of the most studied problems for power systems since its introduction by Carpentier in 1962. This problem is concerned with finding an optimal operating point of a power network minimizing the total power generation cost subject to network and physical constraints. It is well known that OPF is computationally hard to solve due to the nonlinear interrelation among the optimization variables. The objective is to identify a large class of networks over which every OPF problem can be solved in polynomial time. To this end, a convex relaxation is proposed, which solves the OPF problem exactly for every radial network and every meshed network with a sufficient number of phase shifters, provided power over-delivery is allowed. The concept of “power over-delivery” is equivalent to relaxing the power balance equations to inequality constraints.

Flow Networks: In this part of the dissertation, the minimum-cost flow problem over an arbitrary flow network is considered. In this problem, each node is associated with some possibly unknown injection, each line has two unknown flows at its ends related to each other via a nonlinear function, and all injections and flows need to satisfy certain box constraints. This problem, named generalized network flow (GNF), is highly non-convex due to its nonlinear equality constraints. Under the assumption of monotonicity and convexity of the flow and cost functions, a convex relaxation is proposed, which always finds the optimal injections. A primary application of this work is in the OPF problem. The results of this work on GNF prove that the relaxation on power balance equations (i.e., load over-delivery) is not needed in practice under a very mild angle assumption.

Generalized Weighted Graphs: Motivated by power optimizations, this part aims to find a global optimization technique for a nonlinear optimization defined over a generalized weighted graph. Every edge of this type of graph is associated with a weight set corresponding to the known parameters of the optimization (e.g., the coefficients). The motivation behind this problem is to investigate how the (hidden) structure of a given real/complex valued optimization makes the problem easy to solve, and indeed the generalized weighted graph is introduced to capture the structure of an optimization. Various sufficient conditions are derived, which relate the polynomial-time solvability of different classes of optimization problems to weak properties of the generalized weighted graph such as its topology and the sign definiteness of its weight sets. As an application, it is proved that a broad class of real and complex optimizations over power networks are polynomial-time solvable due to the passivity of transmission lines and transformers.

Electron flow through cytochrome P450

The cytochromes P450 (P450s) are a remarkable class of heme enzymes that catalyze the metabolism of xenobiotics and the biosynthesis of signaling molecules. Controlled electron flow into the thiolate-ligated heme active site allows P450s to activate molecular oxygen and hydroxylate aliphatic C–H bonds via the formation of high-valent metal-oxo intermediates (compounds I and II). Due to the reactive nature and short lifetimes of these intermediates, many of the fundamental steps in catalysis have not been observed directly. The Gray group and others have developed photochemical methods, known as “flash-quench,” for triggering electron transfer (ET) and generating redox intermediates in proteins in the absence of native ET partners. Photo-triggering affords a high degree of temporal precision for the gating of an ET event; the initial ET and subsequent reactions can be monitored on the nanosecond-to-second timescale using transient absorption (TA) spectroscopies. Chapter 1 catalogues critical aspects of P450 structure and mechanism, including the native pathway for formation of compound I, and outlines the development of photochemical processes that can be used to artificially trigger ET in proteins. Chapters 2 and 3 describe the development of these photochemical methods to establish electronic communication between a photosensitizer and the buried P450 heme. Chapter 2 describes the design and characterization of a Ru-P450-BM3 conjugate containing a ruthenium photosensitizer covalently tethered to the P450 surface, and nanosecond-to-second kinetics of the photo-triggered ET event are presented. By analyzing data at multiple wavelengths, we have identified the formation of multiple ET intermediates, including the catalytically relevant compound II; this intermediate is generated by oxidation of a bound water molecule in the ferric resting state enzyme. The work in Chapter 3 probes the role of a tryptophan residue situated between the photosensitizer and heme in the aforementioned Ru-P450 BM3 conjugate. Replacement of this tryptophan with histidine does not perturb the P450 structure, yet it completely eliminates the ET reactivity described in Chapter 2. The presence of an analogous tryptophan in Ru-P450 CYP119 conjugates also is necessary for observing oxidative ET, but the yield of heme oxidation is lower. Chapter 4 offers a basic description of the theoretical underpinnings required to analyze ET. Single-step ET theory is first presented, followed by extensions to multistep ET: electron “hopping.” The generation of “hopping maps” and use of a hopping map program to analyze the rate advantage of hopping over single-step ET is described, beginning with an established rhenium-tryptophan-azurin hopping system. This ET analysis is then applied to the Ru-tryptophan-P450 systems described in Chapter 2; this strongly supports the presence of hopping in Ru-P450 conjugates. Chapter 5 explores the implementation of flash-quench and other phototriggered methods to examine the native reductive ET and gas binding events that activate molecular oxygen. In particular, TA kinetics that demonstrate heme reduction on the microsecond timescale for four Ru-P450 conjugates are presented. In addition, we implement laser flash-photolysis of P450 ferrous–CO to study the rates of CO rebinding in the thermophilic P450 CYP119 at variable temperature. Chapter 6 describes the development and implementation of air-sensitive potentiometric redox titrations to determine the solution reduction potentials of a series of P450 BM3 mutants, which were designed for non-native cyclopropanation of styrene in vivo. An important conclusion from this work is that substitution of the axial cysteine for serine shifts the wild type reduction potential positive by 130 mV, facilitating reduction by biological redox cofactors in the presence of poorly-bound substrates. While this mutation abolishes oxygenation activity, these mutants are capable of catalyzing the cyclopropanation of styrene, even within the confines of an E. coli cell. Four appendices are also provided, including photochemical heme oxidation in ruthenium-modified nitric oxide synthase (Appendix A), general protocols (Appendix B), Chapter-specific notes (Appendix C) and Matlab scripts used for data analysis (Appendix D).

Modelagem do potencial elétrico através da membrana do neurônio ganglionar e células de neuroblastoma: efeitos das cargas superficiais.

O objetivo do presente trabalho é comparar, do ponto de vista elétrico, a membrana do neurônio ganglionar com a da célula de neuroblastoma, analisando os efeitos das cargas fixas sobre o potencial elétrico nas superfícies da bicamada lipídica e também sobre o comportamento do perfil de potencial através da membrana, considerando as condiçõesfísico-químicas do estado de repouso e do estado de potencial de ação. As condições para a ocorrência dos referidos estados foram baseadas em valores numéricos de parâmetros elétricos e químicos, característicos dessas células, obtidos na literatura. O neurônio ganglionar exemplifica um neurônio sadio, e a célula de neuroblastoma, que é uma célula tumoral, exemplifica um neurônio patológico, alterado por esta condição. O neuroblastoma é um tumor que se origina das células da crista neural (neuroblastos), que é uma estrutura embrionária que dá origem a muitas partes do sistema nervoso, podendo surgir em diversos locais do organismo, desde a região do crânio até a área mais inferior da coluna. O modelo adotado para simular a membrana de neurônio inclui: (a) as distribuições espaciais de cargas elétricas fixas no glicocálix e na rede de proteínas citoplasmáticas; (b) as distribuições de cargas na solução eletrolítica dos meios externo e interno; e (c) as cargas superficiais da bicamada lipídica. Os resultados que obtivemos mostraram que, nos estados de repouso e de ação, os potenciais superficiais da bicamada interno (ÁSbc) e externo (ÁSgb) da célula de neuroblastoma não sofrem alteração mensurável, quando a densidade de carga na superfície interna (QSbc) torna-se 50 vezes mais negativa, tanto para uma densidade de carga na superfície externa da bicamada nula (QSgb = 0), como para um valor de QSgb 6= 0. Porém, no estado de repouso, uma leve queda em ÁSbc do neur^onio ganglionar pode ser observada com este nível de variação de carga, sendo que ÁSgb do neurônio ganglionar é mais negativo quando QSgb = 1=1100 e/A2. No estado de ação, para QSgb = 0, o aumento da negatividade de QSbc não provoca alteração detectável de ÁSbc e ÁSgb para os dois neurônios. Quando consideramos QSgb = 1=1100 e/A2, ÁSgb do neurônio ganglionar se torna mais negativo, não se observando variações detectáveis nos potenciais superficiais da célula de neuroblastoma. Tanto no repouso quanto no estado de ação, ÁSgb das duas células não sofre variação sensível com o aumento da negatividade da carga fixa distribuída espacialmente no citoplasma. Já a ÁSbc sofre uma queda gradativa nos dois tipos celulares; porém, no estado de ação, esta queda é mais rápida. Descobrimos diferenças importantes nos perfis de potencial das duas células, especialmente na região do glicocálix.

Proton-Coupled Reduction of N2 Facilitated by Molecular Fe Complexes

The activation of Fe-coordinated N₂ via the formal addition of hydrogen atom equivalents is explored in this thesis. These reactions may occur in nitrogenase enzymes during the biological conversion of N₂ to NH₃. To understand these reactions, the N₂ reactivity of a series of molecular Fe(N₂) platforms is investigated. A trigonal pyramidal, carbon-ligated Fe^I complex was prepared that displays a similar geometry to that of the resting state 'belt' Fe atoms of nitrogenase. Upon reduction, this species was shown to coordinate N₂, concomitant with significant weakening of the C-Fe interaction. This hemilability of the axial ligand may play a critical role in mediating the interconversion of Fe(N_xH_y) species during N₂ conversion to NH₃. In fact, a trigonal pyramidal borane-ligated Fe complex was shown to catalyze this transformation, generating up to 8.49 equivalents of NH₃. To shed light on the mechanistic details of this reaction, protonation of a borane-ligated Fe(N₂) complex was investigated and found to give rise to a mixture of species that contains an iron hydrazido(2-) [Fe(NNH₂)] complex. The identification of this species is suggestive of an early N-N bond cleavage event en route to NH₃ production, but the highly-reactive nature of this complex frustrated direct attempts to probe this possibility. A structurally-analogous silyl-ligated Fe(N₂) complex was found to react productively with hydrogen atom equivalents, giving rise to an isolable Fe(NNH₂) species. Spectroscopic and crystallographic studies benefited from the enhanced stability of this complex relative to the borane analogue. One-electron reduction of this species initiates a spontaneous disproportionation reaction with an iron hydrazine [Fe(NH₂NH₂)] complex as the predominant reaction product. This transformation provides support for an Fe-mediated N₂ activation mechanism that proceeds via a late N-N bond cleavage. In hopes of gaining more fundamental insight into these reactions, a series of Fe(CN) complexes were prepared and reacted with hydrogen-atom equivalents. Significant quantities of CH₄ and NH₃ are generated in these reactions as a result of complete C-N bond activation. A series of Fe(CNH_x) were found to be exceptionally stable and may be intermediates in these reactions. The stability of these compounds permitted collection of thermodynamic parameters pertinent to the unique N-H bonds. This data is comparatively discussed with the theoretically-predicted data of the N₂-derived Fe(NNH_x) species. Exceptionally-weak N-H bond enthalpies are found for many of these compounds, and sheds light on their short-lived nature and tendency to evolve H₂. As a whole, these works both establish and provide a means to understand Fe-mediated N₂ activation via the addition of hydrogen atom equivalents.

A novel brain partition highlights the modular skeleton shared by structure and function

Elucidating the intricate relationship between brain structure and function, both in healthy and pathological conditions, is a key challenge for modern neuroscience. Recent progress in neuroimaging has helped advance our understanding of this important issue, with diffusion images providing information about structural connectivity (SC) and functional magnetic resonance imaging shedding light on resting state functional connectivity (rsFC). Here, we adopt a systems approach, relying on modular hierarchical clustering, to study together SC and rsFC datasets gathered independently from healthy human subjects. Our novel approach allows us to find a common skeleton shared by structure and function from which a new, optimal, brain partition can be extracted. We describe the emerging common structure-function modules (SFMs) in detail and compare them with commonly employed anatomical or functional parcellations. Our results underline the strong correspondence between brain structure and resting-state dynamics as well as the emerging coherent organization of the human brain.

抑郁症首次发病患者静息态脑功能局部一致性的研究

下载PDF阅读器目的 利用功能磁共振(fMRI)和局部一致性(regional homogeneity,ReHo)探讨抑郁症首次发病(以下简称首发)患者在静息态脑功能是否存在异常及异常部位.方法 对34例符合美国精神疾病诊断与统计手册第4版诊断标准的首发抑郁症患者(抑郁症组)和34名性别、年龄、文化程度匹配的健康志愿者(对照组)进行静息态fMRI扫描.结果 抑郁症组静息态脑血氧水平依赖信号的ReHo高于对照组的脑区有左侧额叶眶回、顶下小叶、颞上回,右侧额内侧回、顶下小叶、小脑后叶;低于对照组的脑区有左颞下回、右颞上同和胼胝体、双侧后扣带回(P＜0.005,K≥10).结论首发抑郁症患者在静息态存在多个腩区功能活动的异常,并可能和抑郁症的病理机制有关.

Abnormal regional homogeneity of drug-naive obsessive-compulsive patients

To explore the possible abnormal resting-state activity in patients with obsessive-compulsive disorder (OCD), the regional homogeneity (ReHo) of 22 pairs of patients and well-matched healthy controls was calculated. Compared with controls, the patients showed higher ReHo in the left anterior cingulate cortex, but lower ReHo in the left inferior temporal gyrus. These findings supported the abnormal resting-state brain activity in drug-naive OCD patients. No significant correlations between ReHo value and four clinical characteristics were found, suggesting that abnormal ReHo might be trait-related in OCD. NeuroReport 21:786-790 (C) 2010 Wolters Kluwer Health vertical bar Lippincott Williams & Wilkins.

Life history strategies of Calanus sinicus in the southern Yellow Sea in summer

Ecological and physiological features of the planktonic copepod Calanus sinicus in the southern Yellow Sea in summer were studied to reveal its life history strategy. From the coastal shallow waters to the central part of the southern Yellow Sea, a shift of the stage composition occurs from being dominated by the egg-nauplius stage to being dominated by the fifth copepodite (CV) stage. Most CVs reside in the Yellow Sea Cold Water Mass (YSCWM), where both temperature and food abundance are low. CVs in the YSCWM have longer body lengths, heavier body weights and higher carbon contents than those outside the YSCWM. Onboard incubations show that the development of CVs in the YSCWM is suspended. Energy conservation, development suspension and lack of diel vertical migration (DVM) behavior suggest a diapause status for the CVs in the YSCWM, although vertical distribution patterns indicate the CV individuals are not fully synchronous in physiology and development. This adaptive oversummering strategy would help C. sinicus to live through the warm and food-limited summer in the central part of the southern Yellow Sea; both low temperature and low food supply are necessary for CV to maintain the resting state in the YSCWM. Calanus sinicus exhibits different life history strategies in different regions of the southern Yellow Sea in summer.

基于可复制性的独立成分分析——应用于功能磁共振成像数据

This dissertation systematically depicted and improved the application of Independent Component Analysis (ICA) to Functional Magnetic Resonance Imaging (fMRI), following the logic of verification, improvement, extension, and application. The concept of “reproducibility” was the philosophy throughout its four concluded studies. In the “verification” study, ICA was applied to the resting-state fMRI data, verified the resultant components with reproducibility, and examined the consistency of the results from ICA and traditional “seed voxel” method. At the meantime, the limitation of ICA application on fMRI data analysis was presented. In the “improvement” study, an improved ICA algorithm based on reproducibility, RAICAR, was developed to aid some of the limitations of ICA application. RAICAR was able to rank ICA components by reproducibility, determine the number of reliable components, and obtain more stable results. RAICAR provided useful tools for validation and interpretation of ICA results. In the “extension” study, RAICAR as well as the concept of “reproducibility” was extended to multi-subject ICA analysis, and gRAICAR algorithm was developed. gRAICAR allows some variation across subjects, examining common components among subjects. gRAICAR is also capable to detect potential subject grouping on some components. It is a new way for exploratory group analysis on fMRI. In the “application” study, two newly developed methods, RAICAR and gRAICAR, were used to investigate the effect of early music training on the brain mechanism of memory and learning. The results showed brain mechanism difference in memory retrieval and learning process between two groups of subjects. This study also verified the usefulness and importance of the new methods.

Reti complesse e analisi del segnale elettroencefalografico

The identification of subject-specific traits extracted from patterns of brain activity still represents an important challenge. The need to detect distinctive brain features, which is relevant for biometric and brain computer interface systems, has been also emphasized in monitoring the effect of clinical treatments and in evaluating the progression of brain disorders. Graph theory and network science tools have revealed fundamental mechanisms of functional brain organization in resting-state M/EEG analysis. Nevertheless, it is still not clearly understood how several methodological aspects may bias the topology of the reconstructed functional networks. In this context, the literature shows inconsistency in the chosen length of the selected epochs, impeding a meaningful comparison between results from different studies. In this study we propose an approach which aims to investigate the existence of a distinctive functional core (sub-network) using an unbiased reconstruction of network topology. Brain signals from a public and freely available EEG dataset were analyzed using a phase synchronization based measure, minimum spanning tree and k-core decomposition. The analysis was performed for each classical brain rhythm separately. Furthermore, we aim to provide a network approach insensitive to the effects that epoch length has on functional connectivity (FC) and network reconstruction. Two different measures, the phase lag index (PLI) and the Amplitude Envelope Correlation (AEC), were applied to EEG resting-state recordings for a group of eighteen healthy volunteers. Weighted clustering coefficient (CCw), weighted characteristic path length (Lw) and minimum spanning tree (MST) parameters were computed to evaluate the network topology. The analysis was performed on both scalp and source-space data. Results about distinctive functional core, show highest classification rates from k-core decomposition in gamma (EER=0.130, AUC=0.943) and high beta (EER=0.172, AUC=0.905) frequency bands. Results from scalp analysis concerning the influence of epoch length, show a decrease in both mean PLI and AEC values with an increase in epoch length, with a tendency to stabilize at a length of 12 seconds for PLI and 6 seconds for AEC. Moreover, CCw and Lw show very similar behaviour, with metrics based on AEC more reliable in terms of stability. In general, MST parameters stabilize at short epoch lengths, particularly for MSTs based on PLI (1-6 seconds versus 4-8 seconds for AEC). At the source-level the results were even more reliable, with stability already at 1 second duration for PLI-based MSTs. Our results confirm that EEG analysis may represent an effective tool to identify subject-specific characteristics that may be of great impact for several bioengineering applications. Regarding epoch length, the present work suggests that both PLI and AEC depend on epoch length and that this has an impact on the reconstructed network topology, particularly at the scalp-level. Source-level MST topology is less sensitive to differences in epoch length, therefore enabling the comparison of brain network topology between different studies.