12 resultados para Brain - Sampling studies

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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Fear conditioning represents the learning process by which a stimulus, after repeated pairing with an aversive event, comes to evoke fear and becomes intrinsically aversive. This learning is essential to organisms throughout the animal kingdom and represents one the most successful laboratory paradigm to reveal the psychological processes that govern the expression of emotional memory and explore its neurobiological underpinnings. Although a large amount of research has been conducted on the behavioural or neural correlates of fear conditioning, some key questions remain unanswered. Accordingly, this thesis aims to respond to some unsolved theoretic and methodological issues, thus furthering our understanding of the neurofunctional basis of human fear conditioning both in healthy and brain-damaged individuals. Specifically, in this thesis, behavioural, psychophysiological, lesion and non-invasive brain stimulation studies were reported. Study 1 examined the influence of normal aging on context-dependent recall of extinction of fear conditioned stimulus. Study 2 aimed to determine the causal role of the ventromedial PFC (vmPFC) in the acquisition of fear conditioning by systematically test the effect of bilateral vmPFC brain-lesion. Study 3 aimed to interfere with the reconsolidation process of fear memory by the means of non-invasive brain stimulation (i.e. TMS) disrupting PFC neural activity. Finally, Study 4 aimed to investigate whether the parasympathetic – vagal – modulation of heart rate might reflect the anticipation of fearful, as compared to neutral, events during classical fear conditioning paradigm. Evidence reported in this PhD thesis might therefore provide key insights and deeper understanding of critical issues concerning the neurofunctional mechanisms underlying the acquisition, the extinction and the reconsolidation of fear memories in humans.

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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.

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The study of protein fold is a central problem in life science, leading in the last years to several attempts for improving our knowledge of the protein structures. In this thesis this challenging problem is tackled by means of molecular dynamics, chirality and NMR studies. In the last decades, many algorithms were designed for the protein secondary structure assignment, which reveals the local protein shape adopted by segments of amino acids. In this regard, the use of local chirality for the protein secondary structure assignment was demonstreted, trying to correlate as well the propensity of a given amino acid for a particular secondary structure. The protein fold can be studied also by Nuclear Magnetic Resonance (NMR) investigations, finding the average structure adopted from a protein. In this context, the effect of Residual Dipolar Couplings (RDCs) in the structure refinement was shown, revealing a strong improvement of structure resolution. A wide extent of this thesis is devoted to the study of avian prion protein. Prion protein is the main responsible of a vast class of neurodegenerative diseases, known as Bovine Spongiform Encephalopathy (BSE), present in mammals, but not in avian species and it is caused from the conversion of cellular prion protein to the pathogenic misfolded isoform, accumulating in the brain in form of amiloyd plaques. In particular, the N-terminal region, namely the initial part of the protein, is quite different between mammal and avian species but both of them contain multimeric sequences called Repeats, octameric in mammals and hexameric in avians. However, such repeat regions show differences in the contained amino acids, in particular only avian hexarepeats contain tyrosine residues. The chirality analysis of avian prion protein configurations obtained from molecular dynamics reveals a high stiffness of the avian protein, which tends to preserve its regular secondary structure. This is due to the presence of prolines, histidines and especially tyrosines, which form a hydrogen bond network in the hexarepeat region, only possible in the avian protein, and thus probably hampering the aggregation.

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Marine soft bottom systems show a high variability across multiple spatial and temporal scales. Both natural and anthropogenic sources of disturbance act together in affecting benthic sedimentary characteristics and species distribution. The description of such spatial variability is required to understand the ecological processes behind them. However, in order to have a better estimate of spatial patterns, methods that take into account the complexity of the sedimentary system are required. This PhD thesis aims to give a significant contribution both in improving the methodological approaches to the study of biological variability in soft bottom habitats and in increasing the knowledge of the effect that different process (both natural and anthropogenic) could have on the benthic communities of a large area in the North Adriatic Sea. Beta diversity is a measure of the variability in species composition, and Whittaker’s index has become the most widely used measure of beta-diversity. However, application of the Whittaker index to soft bottom assemblages of the Adriatic Sea highlighted its sensitivity to rare species (species recorded in a single sample). This over-weighting of rare species induces biased estimates of the heterogeneity, thus it becomes difficult to compare assemblages containing a high proportion of rare species. In benthic communities, the unusual large number of rare species is frequently attributed to a combination of sampling errors and insufficient sampling effort. In order to reduce the influence of rare species on the measure of beta diversity, I have developed an alternative index based on simple probabilistic considerations. It turns out that this probability index is an ordinary Michaelis-Menten transformation of Whittaker's index but behaves more favourably when species heterogeneity increases. The suggested index therefore seems appropriate when comparing patterns of complexity in marine benthic assemblages. Although the new index makes an important contribution to the study of biodiversity in sedimentary environment, it remains to be seen which processes, and at what scales, influence benthic patterns. The ability to predict the effects of ecological phenomena on benthic fauna highly depends on both spatial and temporal scales of variation. Once defined, implicitly or explicitly, these scales influence the questions asked, the methodological approaches and the interpretation of results. Problem often arise when representative samples are not taken and results are over-generalized, as can happen when results from small-scale experiments are used for resource planning and management. Such issues, although globally recognized, are far from been resolved in the North Adriatic Sea. This area is potentially affected by both natural (e.g. river inflow, eutrophication) and anthropogenic (e.g. gas extraction, fish-trawling) sources of disturbance. Although few studies in this area aimed at understanding which of these processes mainly affect macrobenthos, these have been conducted at a small spatial scale, as they were designated to examine local changes in benthic communities or particular species. However, in order to better describe all the putative processes occurring in the entire area, a high sampling effort performed at a large spatial scale is required. The sedimentary environment of the western part of the Adriatic Sea was extensively studied in this thesis. I have described, in detail, spatial patterns both in terms of sedimentary characteristics and macrobenthic organisms and have suggested putative processes (natural or of human origin) that might affect the benthic environment of the entire area. In particular I have examined the effect of off shore gas platforms on benthic diversity and tested their effect over a background of natural spatial variability. The results obtained suggest that natural processes in the North Adriatic such as river outflow and euthrophication show an inter-annual variability that might have important consequences on benthic assemblages, affecting for example their spatial pattern moving away from the coast and along a North to South gradient. Depth-related factors, such as food supply, light, temperature and salinity play an important role in explaining large scale benthic spatial variability (i.e., affecting both the abundance patterns and beta diversity). Nonetheless, more locally, effects probably related to an organic enrichment or pollution from Po river input has been observed. All these processes, together with few human-induced sources of variability (e.g. fishing disturbance), have a higher effect on macrofauna distribution than any effect related to the presence of gas platforms. The main effect of gas platforms is restricted mainly to small spatial scales and related to a change in habitat complexity due to a natural dislodgement or structure cleaning of mussels that colonize their legs. The accumulation of mussels on the sediment reasonably affects benthic infauna composition. All the components of the study presented in this thesis highlight the need to carefully consider methodological aspects related to the study of sedimentary habitats. With particular regards to the North Adriatic Sea, a multi-scale analysis along natural and anthopogenic gradients was useful for detecting the influence of all the processes affecting the sedimentary environment. In the future, applying a similar approach may lead to an unambiguous assessment of the state of the benthic community in the North Adriatic Sea. Such assessment may be useful in understanding if any anthropogenic source of disturbance has a negative effect on the marine environment, and if so, planning sustainable strategies for a proper management of the affected area.

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Proper ion channels’ functioning is a prerequisite for a normal cell and disorders involving ion channels, or channelopathies, underlie many human diseases. Long QT syndromes (LQTS) for example may arise from the malfunctioning of hERG channel, caused either by the binding of drugs or mutations in HERG gene. In the first part of this thesis I present a framework to investigate the mechanism of ion conduction through hERG channel. The free energy profile governing the elementary steps of ion translocation in the pore was computed by means of umbrella sampling simulations. Compared to previous studies, we detected a different dynamic behavior: according to our data hERG is more likely to mediate a conduction mechanism which has been referred to as “single-vacancy-like” by Roux and coworkers (2001), rather then a “knock-on” mechanism. The same protocol was applied to a model of hERG presenting the Gly628Ser mutation, found to be cause of congenital LQTS. The results provided interesting insights about the reason of the malfunctioning of the mutant channel. Since they have critical functions in viruses’ life cycle, viral ion channels, such as M2 proton channel, are considered attractive targets for antiviral therapy. A deep knowledge of the mechanisms that the virus employs to survive in the host cell is of primary importance in the identification of new antiviral strategies. In the second part of this thesis I shed light on the role that M2 plays in the control of electrical potential inside the virus, being the charge equilibration a condition required to allow proton influx. The ion conduction through M2 was simulated using metadynamics technique. Based on our results we suggest that a potential anion-mediated cation-proton exchange, as well as a direct anion-proton exchange could both contribute to explain the activity of the M2 channel.

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Throughout the world, pressures on water resources are increasing, mainly as a result of human activity. Because of their accessibility, groundwater and surface water are the most used reservoirs. The evaluation of the water quality requires the identification of the interconnections among the water reservoirs, natural landscape features, human activities and aquatic health. This study focuses on the estimation of the water pollution linked to two different environmental issues: salt water intrusion and acid mine drainage related to the exploitation of natural resources. Effects of salt water intrusion occurring in the shallow aquifer north of Ravenna (Italy) was analysed through the study of ion- exchange occurring in the area and its variance throughout the year, applying a depth-specific sampling method. In the study area were identified ion exchange, calcite and dolomite precipitation, and gypsum dissolution and sulphate reduction as the main processes controlling the groundwater composition. High concentrations of arsenic detected only at specific depth indicate its connexion with the organic matter. Acid mine drainage effects related to the tin extraction in the Bolivian Altiplano was studied, on water and sediment matrix. Water contamination results strictly dependent on the seasonal variation, on pH and redox conditions. During the dry season the strong evaporation and scarce water flow lead to low pH values, high concentrations of heavy metals in surface waters and precipitation of secondary minerals along the river, which could be released in oxidizing conditions as demonstrated through the sequential extraction analysis. The increase of the water flow during the wet season lead to an increase of pH values and a decrease in heavy metal concentrations, due to dilution effect and, as e.g. for the iron, to precipitation.

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The Alzheimer’s disease (AD), the most prevalent form of age-related dementia, is a multifactorial and heterogeneous neurodegenerative disease. The molecular mechanisms underlying the pathogenesis of AD are yet largely unknown. However, the etiopathogenesis of AD likely resides in the interaction between genetic and environmental risk factors. Among the different factors that contribute to the pathogenesis of AD, amyloid-beta peptides and the genetic risk factor apoE4 are prominent on the basis of genetic evidence and experimental data. ApoE4 transgenic mice have deficits in spatial learning and memory associated with inflammation and brain atrophy. Evidences suggest that apoE4 is implicated in amyloid-beta accumulation, imbalance of cellular antioxidant system and in apoptotic phenomena. The mechanisms by which apoE4 interacts with other AD risk factors leading to an increased susceptibility to the dementia are still unknown. The aim of this research was to provide new insights into molecular mechanisms of AD neurodegeneration, investigating the effect of amyloid-beta peptides and apoE4 genotype on the modulation of genes and proteins differently involved in cellular processes related to aging and oxidative balance such as PIN1, SIRT1, PSEN1, BDNF, TRX1 and GRX1. In particular, we used human neuroblastoma cells exposed to amyloid-beta or apoE3 and apoE4 proteins at different time-points, and selected brain regions of human apoE3 and apoE4 targeted replacement mice, as in vitro and in vivo models, respectively. All genes and proteins studied in the present investigation are modulated by amyloid-beta and apoE4 in different ways, suggesting their involvement in the neurodegenerative mechanisms underlying the AD. Finally, these proteins might represent novel potential diagnostic and therapeutic targets in AD.

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The monitoring of cognitive functions aims at gaining information about the current cognitive state of the user by decoding brain signals. In recent years, this approach allowed to acquire valuable information about the cognitive aspects regarding the interaction of humans with external world. From this consideration, researchers started to consider passive application of brain–computer interface (BCI) in order to provide a novel input modality for technical systems solely based on brain activity. The objective of this thesis is to demonstrate how the passive Brain Computer Interfaces (BCIs) applications can be used to assess the mental states of the users, in order to improve the human machine interaction. Two main studies has been proposed. The first one allows to investigate whatever the Event Related Potentials (ERPs) morphological variations can be used to predict the users’ mental states (e.g. attentional resources, mental workload) during different reactive BCI tasks (e.g. P300-based BCIs), and if these information can predict the subjects’ performance in performing the tasks. In the second study, a passive BCI system able to online estimate the mental workload of the user by relying on the combination of the EEG and the ECG biosignals has been proposed. The latter study has been performed by simulating an operative scenario, in which the occurrence of errors or lack of performance could have significant consequences. The results showed that the proposed system is able to estimate online the mental workload of the subjects discriminating three different difficulty level of the tasks ensuring a high reliability.

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This thesis regards the study and the development of new cognitive assessment and rehabilitation techniques of subjects with traumatic brain injury (TBI). In particular, this thesis i) provides an overview about the state of art of this new assessment and rehabilitation technologies, ii) suggests new methods for the assessment and rehabilitation and iii) contributes to the explanation of the neurophysiological mechanism that is involved in a rehabilitation treatment. Some chapters provide useful information to contextualize TBI and its outcome; they describe the methods used for its assessment/rehabilitation. The other chapters illustrate a series of experimental studies conducted in healthy subjects and TBI patients that suggest new approaches to assessment and rehabilitation. The new proposed approaches have in common the use of electroencefalografy (EEG). EEG was used in all the experimental studies with a different purpose, such as diagnostic tool, signal to command a BCI-system, outcome measure to evaluate the effects of a treatment, etc. The main achieved results are about: i) the study and the development of a system for the communication with patients with disorders of consciousness. It was possible to identify a paradigm of reliable activation during two imagery task using EEG signal or EEG and NIRS signal; ii) the study of the effects of a neuromodulation technique (tDCS) on EEG pattern. This topic is of great importance and interest. The emerged founding showed that the tDCS can manipulate the cortical network activity and through the research of optimal stimulation parameters, it is possible move the working point of a neural network and bring it in a condition of maximum learning. In this way could be possible improved the performance of a BCI system or to improve the efficacy of a rehabilitation treatment, like neurofeedback.

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Alpha oscillations are linked to visual awareness and to the periodical sampling of visual information, suggesting that alpha rhythm reflect an index of the functionality of the posterior cortices, and hence of the visual system. Therefore, the present work described a series of studies investigating alpha oscillations as a biomarker of the functionality and the plastic modifications of the visual system in response to lesions to the visual cortices or to external stimulations. The studies presented in chapter 5 and 6 showed that posterior lesions alter alpha oscillations in hemianopic patients, with reduced alpha reactivity at the eyes opening and decreased alpha functional connectivity, especially in right-lesioned hemianopics, with concurrent dysfunctions in the theta range, suggesting a specialization of the right hemisphere in orchestrating alpha oscillations and coordinating complex interplays among different brain rhythms. The study presented in chapter 7 investigated a mechanism of rhythmical attentional sampling of visual information in healthy participants, showing that perceptual performance is influenced by a rhythmical mechanism of attentional allocation, occurring at lower-alpha frequencies (i.e., 7 Hz), when a single spatial location is monitored, and at lower frequencies (i.e., 5 Hz), when attention is allocated to two spatial locations. Moreover, the right hemisphere seemed to have a dominance in this rhythmical attentional sampling, distributing attentional resources to the entire visual field. Finally, the study presented in chapter 8 showed that prolonged visual entrainment induce long-term modulations of resting-state alpha activity in healthy participants, suggesting that persistent modifications in the functionality of the visual system are possible. Altogheter, these findings show that functional processes and plastic changes of the visual system are reflected in alpha oscillatory patterns. Therefore, investigating and promoting alpha oscillations may contribute to the development of rehabilitative protocols to ameliorate the functionality of the visual system, in brain lesioned patients.

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The ventral premotor cortex (PMv) is believed to play a pivotal role in a multitude of visuomotor behaviors, such as sensory-guided goal-directed visuomotor transformations, arbitrary visuomotor mapping, and hyper-learnt visuomotor associations underlying automatic imitative tendencies. All these functions are likely carried out through the copious projections connecting PMv to the primary motor cortex (M1). Yet, causal evidence investigating the functional relevance of the PMv-M1 network remains elusive and scarce. In the studies reported in this thesis we addressed this issue using a transcranial magnetic stimulation (TMS) protocol called cortico-cortical paired associative stimulation (ccPAS), which relies on multisite stimulation to induce Hebbian spike-timing dependent plasticity (STDP) by repeatedly stimulating the pathway connecting two target areas to manipulate their connectivity. Firstly, we show that ccPAS protocols informed by both short- and long-latency PMv-M1 interactions effectively modulate connectivity between the two nodes. Then, by pre-activating the network to apply ccPAS in a state-dependent manner, we were able to selectively target specific functional visuo-motor pathways, demonstrating the relevance of PMv-M1 connectivity to arbitrary visuomotor mapping. Subsequently, we addressed the PMv-to-M1 role in automatic imitation, and demonstrated that its connectivity manipulation has a corresponding impact on automatic imitative tendencies. Finally, by combining dual-coil TMS connectivity assessments and ccPAS in young and elderly individuals, we traced effective connectivity of premotor-motor networks and tested their plasticity and relevance to manual dexterity and force in healthy ageing. Our findings provide unprecedent causal evidence of the functional role of the PMv-to-M1 network in young and elderly individuals. The studies presented in this thesis suggest that ccPAS can effectively modulate the strength of connectivity between targeted areas, and coherently manipulate a networks’ behavioral output. Results open new research prospects into the causal role of cortico-cortical connectivity, and provide necessary information to the development of clinical interventions based on connectivity manipulation.

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Brain functioning relies on the interaction of several neural populations connected through complex connectivity networks, enabling the transmission and integration of information. Recent advances in neuroimaging techniques, such as electroencephalography (EEG), have deepened our understanding of the reciprocal roles played by brain regions during cognitive processes. The underlying idea of this PhD research is that EEG-related functional connectivity (FC) changes in the brain may incorporate important neuromarkers of behavior and cognition, as well as brain disorders, even at subclinical levels. However, a complete understanding of the reliability of the wide range of existing connectivity estimation techniques is still lacking. The first part of this work addresses this limitation by employing Neural Mass Models (NMMs), which simulate EEG activity and offer a unique tool to study interconnected networks of brain regions in controlled conditions. NMMs were employed to test FC estimators like Transfer Entropy and Granger Causality in linear and nonlinear conditions. Results revealed that connectivity estimates reflect information transmission between brain regions, a quantity that can be significantly different from the connectivity strength, and that Granger causality outperforms the other estimators. A second objective of this thesis was to assess brain connectivity and network changes on EEG data reconstructed at the cortical level. Functional brain connectivity has been estimated through Granger Causality, in both temporal and spectral domains, with the following goals: a) detect task-dependent functional connectivity network changes, focusing on internal-external attention competition and fear conditioning and reversal; b) identify resting-state network alterations in a subclinical population with high autistic traits. Connectivity-based neuromarkers, compared to the canonical EEG analysis, can provide deeper insights into brain mechanisms and may drive future diagnostic methods and therapeutic interventions. However, further methodological studies are required to fully understand the accuracy and information captured by FC estimates, especially concerning nonlinear phenomena.