Role of BDNF secretion and signaling in the activity-dependent refinement of synaptic connections

Neuronal networks exhibit diverse types of plasticity, including the activity-dependent regulation of synaptic functions and refinement of synaptic connections. In addition, continuous generation of new neurons in the “adult” brain (adult neurogenesis) represents a powerful form of structural plasticity establishing new connections and possibly implementing pre-existing neuronal circuits (Kempermann et al, 2000; Ming and Song, 2005). Neurotrophins, a family of neuronal growth factors, are crucially involved in the modulation of activity-dependent neuronal plasticity. The first evidence for the physiological importance of this role evolved from the observations that the local administration of neurotrophins has dramatic effects on the activity-dependent refinement of synaptic connections in the visual cortex (McAllister et al, 1999; Berardi et al, 2000; Thoenen, 1995). Moreover, the local availability of critical amounts of neurotrophins appears to be relevant for the ability of hippocampal neurons to undergo long-term potentiation (LTP) of the synaptic transmission (Lu, 2004; Aicardi et al, 2004). To achieve a comprehensive understanding of the modulatory role of neurotrophins in integrated neuronal systems, informations on the mechanisms about local neurotrophins synthesis and secretion as well as ditribution of their cognate receptors are of crucial importance. In the first part of this doctoral thesis I have used electrophysiological approaches and real-time imaging tecniques to investigate additional features about the regulation of neurotrophins secretion, namely the capability of the neurotrophin brain-derived neurotrophic factor (BDNF) to undergo synaptic recycling. In cortical and hippocampal slices as well as in dissociated cell cultures, neuronal activity rapidly enhances the neuronal expression and secretion of BDNF which is subsequently taken up by neurons themselves but also by perineuronal astrocytes, through the selective activation of BDNF receptors. Moreover, internalized BDNF becomes part of the releasable source of the neurotrophin, which is promptly recruited for activity-dependent recycling. Thus, we described for the first time that neurons and astrocytes contain an endocytic compartment competent for BDNF recycling, suggesting a specialized form of bidirectional communication between neurons and glia. The mechanism of BDNF recycling is reminiscent of that for neurotransmitters and identifies BDNF as a new modulator implicated in neuro- and glio-transmission. In the second part of this doctoral thesis I addressed the role of BDNF signaling in adult hippocampal neurogenesis. I have generated a transgenic mouse model to specifically investigate the influence of BDNF signaling on the generation, differentiation, survival and connectivity of newborn neurons into the adult hippocampal network. I demonstrated that the survival of newborn neurons critically depends on the activation of the BDNF receptor TrkB. The TrkB-dependent decision regarding life or death in these newborn neurons takes place right at the transition point of their morphological and functional maturation Before newborn neurons start to die, they exhibit a drastic reduction in dendritic complexity and spine density compared to wild-type newborn neurons, indicating that this receptor is required for the connectivity of newborn neurons. Both the failure to become integrated and subsequent dying lead to impaired LTP. Finally, mice lacking a functional TrkB in the restricted population of newborn neurons show behavioral deficits, namely increased anxiety-like behavior. These data suggest that the integration and establishment of proper connections by newly generated neurons into the pre-existing network are relevant features for regulating the emotional state of the animal.

Microglial involvement in brain physiopathology: in vitro studies using rat primary cultures

Microglial involvement in neurological disorders is well-established, being microglial activation not only associated with neurotoxic consequences, but also with neuroprotective effects. The studies presented here, based on microglia rat primary cell cultures and mainly on microglial conditioned medium (MCM), show insights into the mechanism of Superoxide dismutase 1 (SOD1) and Apolipoprotein E (ApoE) secretion by microglia as well as their neuroprotective effect towards primary cerebellar granule neurons (CGNs) exposed to the dopaminergic toxin 6-hydroxydopamine (6-OHDA). SOD1 and ApoE are released respectively through non-classical lysosomal or the classical ER/Golgi-mediated secretion pathway. Microglial conditioned medium, in which SOD1 and ApoE accumulated, protected CGNs from degeneration and these effects were replicated when exogenous SOD1 or ApoE was added to a non-conditioned medium. SOD1 neuroprotective action was mediated by increased cell calcium from an external source. ApoE release is negatively affected by microglia activation, both with lipopolysaccharide (LPS) and Benzoylbenzoyl-ATP (Bz-ATP) but is stimulated by neuronal-conditioned medium as well as in microglia-neurons co-culture conditions. This neuronal-stimulated microglial ApoE release is differently regulated by activation states (i.e. LPS vs ATP) and by 6-hydroxydopamine-induced neurodegeneration. In co-culture conditions, microglial ApoE release is essential for neuroprotection, since microglial ApoE silencing through siRNA abrogated protection of cerebellar granule neurons against 6-OHDA toxicity. Therefore, these molecules could represent a target for manipulation aimed at promoting neuroprotection in brain diseases. Considering a pathological context, and the microglial ability to adopt a neuroprotective or neurotoxic profile, we characterize the microglial M1/M2 phenotype in transgenic rats (McGill-R-Thy1-APP) which reproduce extensively the Alzheimer’s-like amyloid pathology. Here, for the first time, cortical, hippocampal and cerebellar microglia of wild type and transgenic adult rats were compared, at both early and advanced stages of the pathology. In view of possible therapeutic translations, these findings are relevant to test microglial neuroprotection, in animal models of neurodegenerative diseases.

Analysis of cerebral and autonomic response to respiratory events in patients with Sleep Apnea Syndrome

The arousal scoring in Obstructive Sleep Apnea Syndrome (OSAS) is important to clarify the impact of the disease on sleep but the currently applied American Academy of Sleep Medicine (AASM) definition may underestimate the subtle alterations of sleep. The aims of the present study were to evaluate the impact of respiratory events on cortical and autonomic arousal response and to quantify the additional value of cyclic alternating pattern (CAP) and pulse wave amplitude (PWA) for a more accurate detection of respiratory events and sleep alterations in OSAS patients. A retrospective revision of 19 polysomnographic recordings of OSAS patients was carried out. Analysis was focused on quantification of apneas (AP), hypopneas (H) and flow limitation (FL) events, and on investigation of cerebral and autonomic activity. Only 41.1% of FL events analyzed in non rapid eye movement met the AASM rules for the definition of respiratory event-related arousal (RERA), while 75.5% of FL events ended with a CAP A phase. The dual response (EEG-PWA) was the most frequent response for all subtypes of respiratory event with a progressive reduction from AP to H and FL. 87.7% of respiratory events with EEG activation showed also a PWA drop and 53,4% of the respiratory events without EEG activation presented a PWA drop. The relationship between the respiratory events and the arousal response is more complex than that suggested by the international classification. In the estimation of the response to respiratory events, the CAP scoring and PWA analysis can offer more extensive information compared to the AASM rules. Our data confirm also that the application of PWA scoring improves the detection of respiratory events and could reduce the underestimation of OSAS severity compared to AASM arousal.

Adaptive and Maladaptive Implications of Reinforcement Learning Processes: Fronto-Striatal Loops and Behavioural Correlates

That humans and animals learn from interaction with the environment is a foundational idea underlying nearly all theories of learning and intelligence. Learning that certain outcomes are associated with specific actions or stimuli (both internal and external), is at the very core of the capacity to adapt behaviour to environmental changes. In the present work, appetitive and aversive reinforcement learning paradigms have been used to investigate the fronto-striatal loops and behavioural correlates of adaptive and maladaptive reinforcement learning processes, aiming to a deeper understanding of how cortical and subcortical substrates interacts between them and with other brain systems to support learning. By combining a large variety of neuroscientific approaches, including behavioral and psychophysiological methods, EEG and neuroimaging techniques, these studies aim at clarifying and advancing the knowledge of the neural bases and computational mechanisms of reinforcement learning, both in normal and neurologically impaired population.

Human congenital cytomegalovirus infection: characteristics and pathogenesis of fetal brain damage

Human cytomegalovirus (HCMV) causes congenital neurological lifelong disabilities. The study analyzed 10 HCMV-infected human fetuses at 21 weeks of gestation to evaluate the characteristics and pathogenesis of brain injury related to congenital human CMV (cCMV) infection. Specifically, tissues from cortical and white matter areas, subventricular zone, thalamus, hypothalamus, hippocampus, basal ganglia and cerebellum were analysed by: i) immunohistochemistry (IHC) to detect HCMV-infected cell distribution, ii) hematoxylin-eosin staining to evaluate histological damage and iii) real-time PCR to quantify tissue viral load (HCMV-DNA). Viral tropism was assessed by double IHC to detect HCMV-antigens and neural/neuronal markers: nestin (expressed in early differentiation stage), doublecortin (DCX, identifying neuronal precursor cells) and neuronal nuclei (NeuN, identifying mature neurons). HCMV-positive cells and viral DNA were found in the brain of 8/10 (80%) fetuses. For these cases, brain damage was classified in mild (n=4, 50%), moderate (n=3, 37.5%) and severe (n=1, 12.5%) based on presence of i) diffuse astrocytosis, microglial activation and vascular changes; ii) occasional (in mild) or multiple (in moderate/severe) microglial nodules and iii) necrosis (in severe). The highest median HCMV-DNA level was found in the hippocampus (212 copies/5ng of humanDNA [hDNA], range: 10-7,505) as well as the highest mean HCMV-infected cell value (2.9 cells, range: 0-23), followed by that detected in subventricular zone (1.8 cells, range: 0-19). This suggests a preferential HCMV tropism for immature neuronal cells, residing in these regions, confirmed by the detection of DCX and nestin in 94% and 63.3% of HCMV-positive cells, respectively. NeuN was not found among HCMV-positive cells and was nearly absent in the brain with severe damage, suggesting HCMV does not infect mature neurons and immature HCMV-infected neuronal cells do not differentiate into neurons. HCMV preferential tropism in immature neural/neuronal cells delays/inhibits their differentiation interfering with brain development processes that lead to structural and functional brain defects.

Quantitative susceptibility mapping as biomarker of neurodegeneration: methodological models and clinical applications

Quantitative Susceptibility Mapping (QSM) is an advanced magnetic resonance technique that can quantify in vivo biomarkers of pathology, such as alteration in iron and myelin concentration. It allows for the comparison of magnetic susceptibility properties within and between different subject groups. In this thesis, QSM acquisition and processing pipeline are discussed, together with clinical and methodological applications of QSM to neurodegeneration. In designing the studies, significant emphasis was placed on results reproducibility and interpretability. The first project focuses on the investigation of cortical regions in amyotrophic lateral sclerosis. By examining various histogram susceptibility properties, a pattern of increased iron content was revealed in patients with amyotrophic lateral sclerosis compared to controls and other neurodegenerative disorders. Moreover, there was a correlation between susceptibility and upper motor neuron impairment, particularly in patients experiencing rapid disease progression. Similarly, in the second application, QSM was used to examine cortical and sub-cortical areas in individuals with myotonic dystrophy type 1. The thalamus and brainstem were identified as structures of interest, with relevant correlations with clinical and laboratory data such as neurological evaluation and sleep records. In the third project, a robust pipeline for assessing radiomic susceptibility-based features reliability was implemented within a cohort of patients with multiple sclerosis and healthy controls. Lastly, a deep learning super-resolution model was applied to QSM images of healthy controls. The employed model demonstrated excellent generalization abilities and outperformed traditional up-sampling methods, without requiring a customized re-training. Across the three disorders investigated, it was evident that QSM is capable of distinguishing between patient groups and healthy controls while establishing correlations between imaging measurements and clinical data. These studies lay the foundation for future research, with the ultimate goal of achieving earlier and less invasive diagnoses of neurodegenerative disorders within the context of personalized medicine.

Mathematical models of cognitive processes

The research activity carried out during the PhD course was focused on the development of mathematical models of some cognitive processes and their validation by means of data present in literature, with a double aim: i) to achieve a better interpretation and explanation of the great amount of data obtained on these processes from different methodologies (electrophysiological recordings on animals, neuropsychological, psychophysical and neuroimaging studies in humans), ii) to exploit model predictions and results to guide future research and experiments. In particular, the research activity has been focused on two different projects: 1) the first one concerns the development of neural oscillators networks, in order to investigate the mechanisms of synchronization of the neural oscillatory activity during cognitive processes, such as object recognition, memory, language, attention; 2) the second one concerns the mathematical modelling of multisensory integration processes (e.g. visual-acoustic), which occur in several cortical and subcortical regions (in particular in a subcortical structure named Superior Colliculus (SC)), and which are fundamental for orienting motor and attentive responses to external world stimuli. This activity has been realized in collaboration with the Center for Studies and Researches in Cognitive Neuroscience of the University of Bologna (in Cesena) and the Department of Neurobiology and Anatomy of the Wake Forest University School of Medicine (NC, USA). PART 1. Objects representation in a number of cognitive functions, like perception and recognition, foresees distribute processes in different cortical areas. One of the main neurophysiological question concerns how the correlation between these disparate areas is realized, in order to succeed in grouping together the characteristics of the same object (binding problem) and in maintaining segregated the properties belonging to different objects simultaneously present (segmentation problem). Different theories have been proposed to address these questions (Barlow, 1972). One of the most influential theory is the so called “assembly coding”, postulated by Singer (2003), according to which 1) an object is well described by a few fundamental properties, processing in different and distributed cortical areas; 2) the recognition of the object would be realized by means of the simultaneously activation of the cortical areas representing its different features; 3) groups of properties belonging to different objects would be kept separated in the time domain. In Chapter 1.1 and in Chapter 1.2 we present two neural network models for object recognition, based on the “assembly coding” hypothesis. These models are networks of Wilson-Cowan oscillators which exploit: i) two high-level “Gestalt Rules” (the similarity and previous knowledge rules), to realize the functional link between elements of different cortical areas representing properties of the same object (binding problem); 2) the synchronization of the neural oscillatory activity in the γ-band (30-100Hz), to segregate in time the representations of different objects simultaneously present (segmentation problem). These models are able to recognize and reconstruct multiple simultaneous external objects, even in difficult case (some wrong or lacking features, shared features, superimposed noise). In Chapter 1.3 the previous models are extended to realize a semantic memory, in which sensory-motor representations of objects are linked with words. To this aim, the network, previously developed, devoted to the representation of objects as a collection of sensory-motor features, is reciprocally linked with a second network devoted to the representation of words (lexical network) Synapses linking the two networks are trained via a time-dependent Hebbian rule, during a training period in which individual objects are presented together with the corresponding words. Simulation results demonstrate that, during the retrieval phase, the network can deal with the simultaneous presence of objects (from sensory-motor inputs) and words (from linguistic inputs), can correctly associate objects with words and segment objects even in the presence of incomplete information. Moreover, the network can realize some semantic links among words representing objects with some shared features. These results support the idea that semantic memory can be described as an integrated process, whose content is retrieved by the co-activation of different multimodal regions. In perspective, extended versions of this model may be used to test conceptual theories, and to provide a quantitative assessment of existing data (for instance concerning patients with neural deficits). PART 2. The ability of the brain to integrate information from different sensory channels is fundamental to perception of the external world (Stein et al, 1993). It is well documented that a number of extraprimary areas have neurons capable of such a task; one of the best known of these is the superior colliculus (SC). This midbrain structure receives auditory, visual and somatosensory inputs from different subcortical and cortical areas, and is involved in the control of orientation to external events (Wallace et al, 1993). SC neurons respond to each of these sensory inputs separately, but is also capable of integrating them (Stein et al, 1993) so that the response to the combined multisensory stimuli is greater than that to the individual component stimuli (enhancement). This enhancement is proportionately greater if the modality-specific paired stimuli are weaker (the principle of inverse effectiveness). Several studies have shown that the capability of SC neurons to engage in multisensory integration requires inputs from cortex; primarily the anterior ectosylvian sulcus (AES), but also the rostral lateral suprasylvian sulcus (rLS). If these cortical inputs are deactivated the response of SC neurons to cross-modal stimulation is no different from that evoked by the most effective of its individual component stimuli (Jiang et al 2001). This phenomenon can be better understood through mathematical models. The use of mathematical models and neural networks can place the mass of data that has been accumulated about this phenomenon and its underlying circuitry into a coherent theoretical structure. In Chapter 2.1 a simple neural network model of this structure is presented; this model is able to reproduce a large number of SC behaviours like multisensory enhancement, multisensory and unisensory depression, inverse effectiveness. In Chapter 2.2 this model was improved by incorporating more neurophysiological knowledge about the neural circuitry underlying SC multisensory integration, in order to suggest possible physiological mechanisms through which it is effected. This endeavour was realized in collaboration with Professor B.E. Stein and Doctor B. Rowland during the 6 months-period spent at the Department of Neurobiology and Anatomy of the Wake Forest University School of Medicine (NC, USA), within the Marco Polo Project. The model includes four distinct unisensory areas that are devoted to a topological representation of external stimuli. Two of them represent subregions of the AES (i.e., FAES, an auditory area, and AEV, a visual area) and send descending inputs to the ipsilateral SC; the other two represent subcortical areas (one auditory and one visual) projecting ascending inputs to the same SC. Different competitive mechanisms, realized by means of population of interneurons, are used in the model to reproduce the different behaviour of SC neurons in conditions of cortical activation and deactivation. The model, with a single set of parameters, is able to mimic the behaviour of SC multisensory neurons in response to very different stimulus conditions (multisensory enhancement, inverse effectiveness, within- and cross-modal suppression of spatially disparate stimuli), with cortex functional and cortex deactivated, and with a particular type of membrane receptors (NMDA receptors) active or inhibited. All these results agree with the data reported in Jiang et al. (2001) and in Binns and Salt (1996). The model suggests that non-linearities in neural responses and synaptic (excitatory and inhibitory) connections can explain the fundamental aspects of multisensory integration, and provides a biologically plausible hypothesis about the underlying circuitry.

Anomalie cerebellari fetali: confronto tra ecografia e risonanza magnetica prenatale e follow up a distanza

Cerebellar malformation are increasingly diagnosed in utero. To assess the effectiveness of ultrasound and fetal magnetic resonance in the antenatal prediction of long term neurodevelopmental delay. STUDY DESIGN: We collected 105 cases of cerebellum malformation in the period 2000-2010 in Bologna and Bari University. Classification included cystic anomalies of posterior fossa and cerebellar hypoplasia. RESULTS: The greater group included Blake’s pouch cysts and mega cisterna magna cases (58/105). These cases seemed to have a good prognosis with a good outcome both in association with other anomalies and isolated. In cases of Dandy Walker malformation, vermis hypoplasia and cerebellum hypoplasia there were few survivors, so it was so difficult to outline some conclusion for child outcome. Despite great neuroimaging advances, in our study, ultrasound and MR reached a similar sensitivity (62-63%) for the diagnosis of posterior fossa anomalies, but the number of MR was lower compared with ultrasonography. CONCLUSION: Ultrasonography remains the screening method of choice for evaluation of cerebellum anatomy but probably MR imaging can improve some details expecially in the third trimester. Despite the data on Dandy Walker, vermis hypoplasia and cerebellum hypoplasia were conflicting and uncertain, for Blake and mega cisterna magna we can considered a rather good outcome.

Human bone: the tissue characteristics determining its mechanical behaviour

The present thesis illustrates the research carried out during the PhD studies in Bioengineering. The research was aimed to characterise the human bone tissue, with particular regard to the differences between cortical and trabecular bone. The bone tissue characteristics that affect its mechanical properties were verified or identified, using an experimental approach, to corroborate or refute hypotheses based on the state of the art in bone tissue biomechanics. The studies presented in the present PhD thesis were designed to investigate aspects of bone tissue biomechanics, which were in need of a more in-depth examination since the data found in the literature was contradictory or scarce. In particular, the work was focalised on the characterisation of the basic structure of the bone tissue (groups of lamellae), its composition, its spatial organisation (trabecular bone microarchitecture) and their influence on the mechanical properties. In conclusion, the present thesis integrates eight different studies on the characterisation of bone tissue. A more in-depth examination of some of the aspects of bone tissue biomechanics where the data found in the literature was contradictory or scarce was performed. Bone tissue was investigated at several scales, from its composition up to its spatial organization, to determine which parameters influence the mechanical behaviour of the tissue. It was found that although the composition and real density of bone tissue are similar, the differences in structure at different levels cause differences between the two types of bone tissue (cortical and trabecular) in mechanical properties. However, the apparent density can still be considered a good predictor of the mechanical properties of both cortical and trabecular bone. Finally, it was found that the bone tissue characteristics might change when a pathology is present, as demonstrated for OA.

Patologie tiroidee e surrenaliche del cane e del gatto: aspetti epidemiologici, clinici e clinico-patologici

L’ipertiroidismo felino rappresenta oggi la più comune endocrinopatia della specie. I capitoli 2 e 3 costituiscono una revisione della letteratura in merito agli aspetti clinici, diagnostici e terapeutici della patologia. Il capitolo 4 indaga il ruolo della dimetilarginina simmetrica (SDMA) come marker di funzionalità renale nei gatti ipertiroidei prima e dopo terapia medica. La patologia tiroidea più comune nel cane è l’ipotiroidismo. Nello studio riportato al capitolo 5 sono state indagate le performance diagnostiche di freeT3, freeT4, rT3, 3,3-T2 e 3,5-T2, misurati tramite LC-MS/MS, nel differenziare tra cani ipotiroidei, cani con patologie non-tiroidee e cani sani. La presenza di una possibile correlazione tra la gravità della condizione clinica dei pazienti ipotiroidei, le variabili emato-chimiche e le concentrazioni sieriche di cTSH è stata valutata nel capitolo 6. Il capitolo 7 valuta l’andamento dell’SDMA in cani ipotiroidei prima e dopo supplementazione ormonale. A differenza della Sindrome di Cushing dell’uomo, che è considerata una malattia rara, nel cane l’ipercortisolismo spontaneo (HC) è una delle endocrinopatie più comuni. Gli aspetti epidemiologici dell’HC e la ricerca di un metodo di monitoraggio alternativo al test di stimolazione con ACTH nei cani trattati con Trilostano sono stati approfonditi rispettivamente nei capitoli 8 e 9. A differenza dell'HC, l'ipoadrenocorticismo primario (PH) è una patologia rara nel cane. Lo scopo dello studio riportato nel capitolo 10 consiste nel descrivere le frazioni escretorie degli elettroliti urinari nei cani con PH e di indagare se esse possano rappresentare un utile supporto alla diagnosi e al trattamento del PH canino. Il riscontro accidentale di masse surrenaliche rappresenta una criticità diagnostica. Infatti, può essere difficile distinguere morfologicamente tra lesioni corticali e midollari e tra lesioni maligne e benigne. Nel capitolo 11 vengono descritti i rilievi immunoistochimici dell'incidentaloma surrenalico nel cane e viene valutato il ruolo del Ki-67 PI come indicatore di malignità.

Neuroinflammation and the role of glia: relevance for neurodegenerative and neurosupportive roles

Inflammation is thought to contribute to the pathogenesis of neurodegenerative diseases. Among the resident population of cells in the brain, astroglia have been suggested to actively participate in the induction and regulation of neuroinflammation by controlling the secretion of local mediators. However, the initial cellular mechanisms by which astrocytes react to pro-inflammatory molecules are still unclear. Our study identified mitochondria as highly sensitive organelles that rapidly respond to inflammatory stimuli. Time-lapse video microscopy revealed that mitochondrial morphology, dynamics and motility are drastically altered upon inflammation, resulting in perinuclear clustering of mitochondria. These mitochondrial rearrangements are accompanied by an increased formation of reactive oxygen species and a recruitment of autophagic vacuoles. 24 to 48 hours after the acute inflammatory stimulus, however, the mitochondrial network is re-established. Strikingly, the recovery of a tubular mitochondrial network is abolished in astrocytes with a defective autophagic response, indicating that activation of autophagy is required to restore mitochondrial dynamics. By employing co-cultivation assays we observed that primary cortical neurons undergo degeneration in the presence of inflamed astrocytes. However, this effect was not observed when the primary neurons were grown in conditioned medium derived from inflamed astrocytes, suggesting that a direct contact between astrocytes and neurons mediates neuronal dysfunction upon inflammation. Our results suggest that astrocytes react to inflammatory stimuli by transiently rearranging their mitochondria, a process that involves the autophagic machinery.

Methods for the estimation of the cortical activity and connectivity during cognitive tasks in humans

The research activity characterizing the present thesis was mainly centered on the design, development and validation of methodologies for the estimation of stationary and time-varying connectivity between different regions of the human brain during specific complex cognitive tasks. Such activity involved two main aspects: i) the development of a stable, consistent and reproducible procedure for functional connectivity estimation with a high impact on neuroscience field and ii) its application to real data from healthy volunteers eliciting specific cognitive processes (attention and memory). In particular the methodological issues addressed in the present thesis consisted in finding out an approach to be applied in neuroscience field able to: i) include all the cerebral sources in connectivity estimation process; ii) to accurately describe the temporal evolution of connectivity networks; iii) to assess the significance of connectivity patterns; iv) to consistently describe relevant properties of brain networks. The advancement provided in this thesis allowed finding out quantifiable descriptors of cognitive processes during a high resolution EEG experiment involving subjects performing complex cognitive tasks.