Functional and neural mechanisms of human fear conditioning: studies in healthy and brain-damaged individuals

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.

Molecular mechanisms controlling physiological plasticity in marine mussels under the influence of natural and anthropogenic stress factors

Marine mussels are exceptionally well-adapted to live in transitional habitats where they are exposed to fluctuating environmental parameters and elevated levels of natural and anthropogenic stressors throughout their lifecycle. However, there is a dearth of information about the molecular mechanisms that assist in dealing with environmental changes. This project aims to investigate the molecular mechanisms governing acclimatory and stress responses of the Mediterranean mussel (Mytilus galloprovincialis) by addressing relevant life stages and environmental stressors of emerging concern. The experimental approach consisted of two phases to explore (i) the physiological processes at early life history and the consequences of plastic pollution and (ii) the adult physiology processes under natural habitats. As the first phase, I employed a plastic leachate (styrene monomer), and polystyrene microplastics to understand the modulation of cytoprotective mechanisms during the early embryo stages. Results revealed the onset of transcriptional impairments of genes involved in MXR-related transporters and other physiological processes induced by styrene and PS-MPs. In the second phase, as a preliminary analysis, microbiota profile of adult mussels at the tissue scale and its surrounding water was explored to understand microbiota structures that may reflect peculiar adaptations to the respective tissue functions. The broader experiment has been implemented to understand the variability of transcriptional profiles in the mussel digestive glands in the natural setting. All the genes employed in this study have shown possibilities to use as molecular biomarker responses throughout the year for monitoring the physiology of mussels living in a particular environment and, in turn, more properly detecting changes in the environment. As a whole, my studies provide insights into the interactions between environmental parameters, and intrinsic characters, and physiology of marine bivalves, and it could help to interpretation of responses correctly under stress conditions and climate change scenarios.

Seeing emotions in others: Improving cognitive and neuronal mechanisms of facial expression processing

In the conceptual framework of affective neuroscience, this thesis intends to advance the understanding of the plasticity mechanisms of other’s emotional facial expression representations. Chapter 1 outlines a description of the neurophysiological bases of Hebbian plasticity, reviews influential studies that adopted paired associative stimulation procedures, and introduces new lines of research where the impact of cortico-cortical paired associative stimulation protocols on higher order cognitive functions is investigated. The experiments in Chapter 2 aimed to test the modulatory influence of a perceptual-motor training, based on the execution of emotional expressions, on the subsequent emotion intensity judgements of others’ high (i.e., full visible) and low-intensity (i.e., masked) emotional expressions. As a result of the training-induced learning, participants showed a significant congruence effect, as indicated by relatively higher expression intensity ratings for the same emotion as the one that was previously trained. Interestingly, although judged as overall less emotionally intense, surgical facemasks did not prevent the emotion-specific effects of the training to occur, suggesting that covering the lower part of other’s face do not interact with the training-induced congruence effect. In Chapter 3 it was implemented a transcranial magnetic stimulation study targeting neural pathways involving re-entrant input from higher order brain regions into lower levels of the visual processing hierarchy. We focused on cortical visual networks within the temporo-occipital stream underpinning the processing of emotional faces and susceptible to plastic adaptations. Importantly, we tested the plasticity-induced effects in a state dependent manner, by administering ccPAS while presenting different facial expressions yet afferent to a specific emotion. Results indicated that the discrimination accuracy of emotion-specific expressions is enhanced following the ccPAS treatment, suggesting that a multi-coil TMS intervention might represent a suitable tool to drive brain remodeling at a neural network level, and consequently influence a specific behavior.

Advanced studies on two animal models, murine and fish. RadKI21A626T mouse model: new insights into molecular mechanisms of enteric neuro-epithelial pathology. European sea bass: study of the effects of essential oils in different diets on the gastric system.

My PhD research period was focused on the anatomical, physiological and functional study of the gastrointestinal system on two different animal models. In two different contexts, the purpose of these two lines of research was contribute to understand how a specific genetic mutation or the adoption of a particular dietary supplement can affect gastrointestinal function. Functional gastrointestinal disorders are chronic conditions characterized by symptoms for which no organic cause can be found. Although symptoms are generally mild, a small subset of cases shows severe manifestations. This subset of patients may also have recurrent intestinal sub-occlusive episodes, but in absence of mechanical causes. This condition is referred to as chronic intestinal pseudo-obstruction, a rare, intractable chronic disease. Some mutations have been associated with CIPO. A novel causative RAD21 missense mutation was identified in a large consanguineous family, segregating a recessive form of CIPO. The present thesis was aimed to elucidate the mechanisms leading to neuropathy underlying CIPO via a recently developed conditional KI mouse carrying the RAD21 mutation. The experimental studies are based on the characterization and functional analysis of the conditional KI Rad21A626T mouse model. On the other hand aquaculture is increasing the global supply of foods. The species selected and feeds used affects the nutrients available from aquaculture, with a need to improve feed efficiency, both for economic and environmental reasons, but this will require novel innovative approaches. Nutritional strategies focused on the use of botanicals have attracted interest in animal production. Previous research indicates the positive results of using essential oils (EOs) as natural feed additives for several farmed animals. Therefore, the present study was designed to compare the effects of feed EO supplementation in two different forms (natural and composed of active ingredients obtained by synthesis) on the gastric mucosa in European sea bass.

Enhancing the reliability of electric transportation motors through insulation coordination and improved qualification

The ambitious goals of increasing the efficiency, performance and power densities of transportation drives cannot be met with compromises in the motor reliability. For the insulation specialists the challenge will be critical as the use of wide-bandgap converters (WBG, based on SiC and GaN switches) and the higher operating voltages expected for the next generation drives will enhance the electrical stresses to unprecedented levels. It is expected for the DC bus in aircrafts to reach 800 V (split +/-400 V) and beyond, driven by the urban air mobility sector and the need for electrification of electro-mechanical/electro-hydraulic actuators (an essential part of the "More Electric Aircraft" concept). Simultaneously the DC bus in electric vehicles (EV) traction motors is anticipated to increase up to 1200 V very soon. The electrical insulation system is one of the most delicate part of the machine in terms of failure probability. In particular, the appearance of partial discharges (PD) is disruptive on the reliability of the drive, especially under fast repetitive transients. Extensive experimental activity has been performed to extend the body of knowledge on PD inception, endurance under PD activity, and explore and identify new phenomena undermining the reliability. The focus has been concentrated on the impact of the WGB-converter produced waveforms and the environmental conditions typical of the aeronautical sector on insulation models. Particular effort was put in the analysis at the reduced pressures typical of aircraft cruise altitude operation. The results obtained, after a critical discussion, have been used to suggest a coordination between the insulation PD inception voltage with the converter stresses and to propose an improved qualification procedure based on the existing IEC 60034-18-41 standard.

Physical modeling and numerical simulations of degradation mechanisms in devices and insulators for power applications

In this thesis, a TCAD approach for the investigation of charge transport in amorphous silicon dioxide is presented for the first time. The proposed approach is used to investigate high-voltage silicon oxide thick TEOS capacitors embedded in the back-end inter-level dielectric layers for galvanic insulation applications. In the first part of this thesis, a detailed review of the main physical and chemical properties of silicon dioxide and the main physical models for the description of charge transport in insulators are presented. In the second part, the characterization of high-voltage MIM structures at different high-field stress conditions up to the breakdown is presented. The main physical mechanisms responsible of the observed results are then discussed in details. The third part is dedicated to the implementation of a TCAD approach capable of describing charge transport in silicon dioxide layers in order to gain insight into the microscopic physical mechanisms responsible of the leakage current in MIM structures. In particular, I investigated and modeled the role of charge injection at contacts and charge build-up due to trapping and de-trapping mechanisms in the oxide layer to the purpose of understanding its behavior under DC and AC stress conditions. In addition, oxide breakdown due to impact-ionization of carriers has been taken into account in order to have a complete representation of the oxide behavior at very high fields. Numerical simulations have been compared against experiments to quantitatively validate the proposed approach. In the last part of the thesis, the proposed approach has been applied to simulate the breakdown in realistic structures under different stress conditions. The TCAD tool has been used to carry out a detailed analysis of the most relevant physical quantities, in order to gain a detailed understanding on the main mechanisms responsible for breakdown and guide design optimization.

Development of machine learning methods for multi-modal biomarkers detection and integration

In medicine, innovation depends on a better knowledge of the human body mechanism, which represents a complex system of multi-scale constituents. Unraveling the complexity underneath diseases proves to be challenging. A deep understanding of the inner workings comes with dealing with many heterogeneous information. Exploring the molecular status and the organization of genes, proteins, metabolites provides insights on what is driving a disease, from aggressiveness to curability. Molecular constituents, however, are only the building blocks of the human body and cannot currently tell the whole story of diseases. This is why nowadays attention is growing towards the contemporary exploitation of multi-scale information. Holistic methods are then drawing interest to address the problem of integrating heterogeneous data. The heterogeneity may derive from the diversity across data types and from the diversity within diseases. Here, four studies conducted data integration using customly designed workflows that implement novel methods and views to tackle the heterogeneous characterization of diseases. The first study devoted to determine shared gene regulatory signatures for onco-hematology and it showed partial co-regulation across blood-related diseases. The second study focused on Acute Myeloid Leukemia and refined the unsupervised integration of genomic alterations, which turned out to better resemble clinical practice. In the third study, network integration for artherosclerosis demonstrated, as a proof of concept, the impact of network intelligibility when it comes to model heterogeneous data, which showed to accelerate the identification of new potential pharmaceutical targets. Lastly, the fourth study introduced a new method to integrate multiple data types in a unique latent heterogeneous-representation that facilitated the selection of important data types to predict the tumour stage of invasive ductal carcinoma. The results of these four studies laid the groundwork to ease the detection of new biomarkers ultimately beneficial to medical practice and to the ever-growing field of Personalized Medicine.