Percezione della direzione del proprio movimento: dalla registrazione dell'attività corticale al modello computazionale.

The main aim of this thesis is strongly interdisciplinary: it involves and presumes a knowledge on Neurophysiology, to understand the mechanisms that undergo the studied phenomena, a knowledge and experience on Electronics, necessary during the hardware experimental set-up to acquire neuronal data, on Informatics and programming to write the code necessary to control the behaviours of the subjects during experiments and the visual presentation of stimuli. At last, neuronal and statistical models should be well known to help in interpreting data. The project started with an accurate bibliographic research: until now the mechanism of perception of heading (or direction of motion) are still poorly known. The main interest is to understand how the integration of visual information relative to our motion with eye position information happens. To investigate the cortical response to visual stimuli in motion and the integration with eye position, we decided to study an animal model, using Optic Flow expansion and contraction as visual stimuli. In the first chapter of the thesis, the basic aims of the research project are presented, together with the reasons why it’s interesting and important to study perception of motion. Moreover, this chapter describes the methods my research group thought to be more adequate to contribute to scientific community and underlines my personal contribute to the project. The second chapter presents an overview on useful knowledge to follow the main part of the thesis: it starts with a brief introduction on central nervous system, on cortical functions, then it presents more deeply associations areas, which are the main target of our study. Furthermore, it tries to explain why studies on animal models are necessary to understand mechanism at a cellular level, that could not be addressed on any other way. In the second part of the chapter, basics on electrophysiology and cellular communication are presented, together with traditional neuronal data analysis methods. The third chapter is intended to be a helpful resource for future works in the laboratory: it presents the hardware used for experimental sessions, how to control animal behaviour during the experiments by means of C routines and a software, and how to present visual stimuli on a screen. The forth chapter is the main core of the research project and the thesis. In the methods, experimental paradigms, visual stimuli and data analysis are presented. In the results, cellular response of area PEc to visual stimuli in motion combined with different eye positions are shown. In brief, this study led to the identification of different cellular behaviour in relation to focus of expansion (the direction of motion given by the optic flow pattern) and eye position. The originality and importance of the results are pointed out in the conclusions: this is the first study aimed to investigate perception of motion in this particular cortical area. In the last paragraph, a neuronal network model is presented: the aim is simulating cellular pre-saccadic and post-saccadic response of neuron in area PEc, during eye movement tasks. The same data presented in chapter four, are further analysed in chapter fifth. The analysis started from the observation of the neuronal responses during 1s time period in which the visual stimulation was the same. It was clear that cells activities showed oscillations in time, that had been neglected by the previous analysis based on mean firing frequency. Results distinguished two cellular behaviour by their response characteristics: some neurons showed oscillations that changed depending on eye and optic flow position, while others kept the same oscillations characteristics independent of the stimulus. The last chapter discusses the results of the research project, comments the originality and interdisciplinary of the study and proposes some future developments.

Shallow and deep deformation in northern Apennines region using seismological data

For its particular position and the complex geological history, the Northern Apennines has been considered as a natural laboratory to apply several kinds of investigations. By the way, it is complicated to joint all the knowledge about the Northern Apennines in a unique picture that explains the structural and geological emplacement that produced it. The main goal of this thesis is to put together all information on the deformation - in the crust and at depth - of this region and to describe a geodynamical model that takes account of it. To do so, we have analyzed the pattern of deformation in the crust and in the mantle. In both cases the deformation has been studied using always information recovered from earthquakes, although using different techniques. In particular the shallower deformation has been studied using seismic moment tensors information. For our purpose we used the methods described in Arvidsson and Ekstrom (1998) that allowing the use in the inversion of surface waves [and not only of the body waves as the Centroid Moment Tensor (Dziewonski et al., 1981) one] allow to determine seismic source parameters for earthquakes with magnitude as small as 4.0. We applied this tool in the Northern Apennines and through this activity we have built up the Italian CMT dataset (Pondrelli et al., 2006) and the pattern of seismic deformation using the Kostrov (1974) method on a regular grid of 0.25 degree cells. We obtained a map of lateral variations of the pattern of seismic deformation on different layers of depth, taking into account the fact that shallow earthquakes (within 15 km of depth) in the region occur everywhere while most of events with a deeper hypocenter (15-40 km) occur only in the outer part of the belt, on the Adriatic side. For the analysis of the deep deformation, i.e. that occurred in the mantle, we used the anisotropy information characterizing the structure below the Northern Apennines. The anisotropy is an earth properties that in the crust is due to the presence of aligned fluid filled cracks or alternating isotropic layers with different elastic properties while in the mantle the most important cause of seismic anisotropy is the lattice preferred orientation (LPO) of the mantle minerals as the olivine. This last is a highly anisotropic mineral and tends to align its fast crystallographic axes (a-axis) parallel to the astenospheric flow as a response to finite strain induced by geodynamic processes. The seismic anisotropy pattern of a region is measured utilizing the shear wave splitting phenomenon (that is the seismological analogue to optical birefringence). Here, to do so, we apply on teleseismic earthquakes recorded on stations located in the study region, the Sileny and Plomerova (1996) approach. The results are analyzed on the basis of their lateral and vertical variations to better define the earth structure beneath Northern Apennines. We find different anisotropic domains, a Tuscany and an Adria one, with a pattern of seismic anisotropy which laterally varies in a similar way respect to the seismic deformation. Moreover, beneath the Adriatic region the distribution of the splitting parameters is so complex to request an appropriate analysis. Therefore we applied on our data the code of Menke and Levin (2003) which allows to look for different models of structures with multilayer anisotropy. We obtained that the structure beneath the Po Plain is probably even more complicated than expected. On the basis of the results obtained for this thesis, added with those from previous works, we suggest that slab roll-back, which created the Apennines and opened the Tyrrhenian Sea, evolved in the north boundary of Northern Apennines in a different way from its southern part. In particular, the trench retreat developed primarily south of our study region, with an eastward roll-back. In the northern portion of the orogen, after a first stage during which the retreat was perpendicular to the trench, it became oblique with respect to the structure.

Model reduction of stochastic groundwater flow and transport processes

This work presents a comprehensive methodology for the reduction of analytical or numerical stochastic models characterized by uncertain input parameters or boundary conditions. The technique, based on the Polynomial Chaos Expansion (PCE) theory, represents a versatile solution to solve direct or inverse problems related to propagation of uncertainty. The potentiality of the methodology is assessed investigating different applicative contexts related to groundwater flow and transport scenarios, such as global sensitivity analysis, risk analysis and model calibration. This is achieved by implementing a numerical code, developed in the MATLAB environment, presented here in its main features and tested with literature examples. The procedure has been conceived under flexibility and efficiency criteria in order to ensure its adaptability to different fields of engineering; it has been applied to different case studies related to flow and transport in porous media. Each application is associated with innovative elements such as (i) new analytical formulations describing motion and displacement of non-Newtonian fluids in porous media, (ii) application of global sensitivity analysis to a high-complexity numerical model inspired by a real case of risk of radionuclide migration in the subsurface environment, and (iii) development of a novel sensitivity-based strategy for parameter calibration and experiment design in laboratory scale tracer transport.

Influence of optic flow on postural control

The study of optic flow on postural control may explain how self-motion perception contributes to postural stability in young males and females and how such function changes in the old falls risk population. Study I: The aim was to examine the optic flow effect on postural control in young people (n=24), using stabilometry and surface-electromyography. Subjects viewed expansion and contraction optic flow stimuli which were presented full field, in the foveral or in the peripheral visual field. Results showed that optic flow stimulation causes an asymmetry in postural balance and a different lateralization of postural control in men and women. Gender differences evoked by optic flow were found both in the muscle activity and in the prevalent direction of oscillation. The COP spatial variability was reduced during the view of peripheral stimuli which evoked a clustered prevalent direction of oscillation, while foveal and random stimuli induced non-distributed directions. Study II was aimed at investigating the age-related mechanisms of postural stability during the view of optic flow stimuli in young (n=17) and old (n=19) people, using stabilometry and kinematic. Results showed that old people showed a greater effort to maintain posture during the view of optic flow stimuli than the young. Elderly seems to use the head stabilization on trunk strategy. Visual stimuli evoke an excitatory input on postural muscles, but the stimulus structure produces different postural effects. Peripheral optic flow stabilizes postural sway, while random and foveal stimuli provoke larger sway variability similar to those evoked in baseline. Postural control uses different mechanisms within each leg to produce the appropriate postural response to interact with extrapersonal environment. Ageing reduce the effortlessness to stabilize posture during optic flow, suggesting a neuronal processing decline associated with difficulty integrating multi-sensory information of self-motion perception and increasing risk of falls.

Numerical simulation of the flow and performance evaluation of an aerospike engine

The main focus of this work is to define a numerical methodology to simulate an aerospike engine and then to analyse the performance of DemoP1, which is a small aerospike demonstrator built by Pangea Aerospace. The aerospike is a promising solution to build more efficient engine than the actual one. Its main advantage is the expansion adaptation that allows to reach the optimal expansion in a wide range of ambient pressures delivering more thrust than an equivalent bell-shaped nozzle. The main drawbacks are the cooling system design and the spike manufacturing but nowadays, these issues seem to be overcome with the use of the additive manufacturing method. The simulations are performed with dbnsTurbFoam which is a solver of OpenFOAM. It has been designed to simulate a supersonic compressible turbulent flow. This work is divided in four chapters. The first one is a short introduction. The second one shows a brief summary of the theoretical performance of the aerospike. The third one introduces the numerical methodology to simulate a compressible supersonic flow. In the fourth chapter, the solver has been verified with an experiment found in literature. And in the fifth chapter, the simulations on DemoP1 engine are illustrated.

Decoding complex flow phenomena via Dynamic Mode Decomposition

In this thesis, the viability of the Dynamic Mode Decomposition (DMD) as a technique to analyze and model complex dynamic real-world systems is presented. This method derives, directly from data, computationally efficient reduced-order models (ROMs) which can replace too onerous or unavailable high-fidelity physics-based models. Optimizations and extensions to the standard implementation of the methodology are proposed, investigating diverse case studies related to the decoding of complex flow phenomena. The flexibility of this data-driven technique allows its application to high-fidelity fluid dynamics simulations, as well as time series of real systems observations. The resulting ROMs are tested against two tasks: (i) reduction of the storage requirements of high-fidelity simulations or observations; (ii) interpolation and extrapolation of missing data. The capabilities of DMD can also be exploited to alleviate the cost of onerous studies that require many simulations, such as uncertainty quantification analysis, especially when dealing with complex high-dimensional systems. In this context, a novel approach to address parameter variability issues when modeling systems with space and time-variant response is proposed. Specifically, DMD is merged with another model-reduction technique, namely the Polynomial Chaos Expansion, for uncertainty quantification purposes. Useful guidelines for DMD deployment result from the study, together with the demonstration of its potential to ease diagnosis and scenario analysis when complex flow processes are involved.