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.

Intangible resources and organization capital: measurement and economic evaluation

Intangible resources have raised the interests of scholars from different research areas due to their importance as crucial factors for firm performance; yet, contributions to this field still lack a theoretical framework. This research analyses the state-of-the-art results reached in the literature concerning intangibles, their main features and evaluation problems and models. In search for a possible theoretical framework, the research draws a kind of indirect analysis of intangibles through the theories of the firm, their critic and developments. The heterodox approaches of the evolutionary theory and resource-based view are indicated as possible frameworks. Based on this theoretical analysis, organization capital (OC) is identified, for its features, as the most important intangible for firm performance. Empirical studies on the relationship intangibles-firm performance have been sporadic and have failed to reach firm conclusions with respect to OC; in the attempt to fill this gap, the effect of OC is tested on a large sample of European firms using the Compustat Global database. OC is proxied by capitalizing an income statement item (Selling, General and Administrative expenses) that includes expenses linked to information technology, business process design, reputation enhancement and employee training. This measure of OC is employed in a cross-sectional estimation of a firm level production function - modeled with different functional specifications (Cobb-Douglas and Translog) - that measures OC contribution to firm output and profitability. Results are robust and confirm the importance of OC for firm performance.

A Unitary Approach to Information and Estimation Theory in Digital Communication Systems

This thesis presents the outcomes of a Ph.D. course in telecommunications engineering. It is focused on the optimization of the physical layer of digital communication systems and it provides innovations for both multi- and single-carrier systems. For the former type we have first addressed the problem of the capacity in presence of several nuisances. Moreover, we have extended the concept of Single Frequency Network to the satellite scenario, and then we have introduced a novel concept in subcarrier data mapping, resulting in a very low PAPR of the OFDM signal. For single carrier systems we have proposed a method to optimize constellation design in presence of a strong distortion, such as the non linear distortion provided by satellites' on board high power amplifier, then we developed a method to calculate the bit/symbol error rate related to a given constellation, achieving an improved accuracy with respect to the traditional Union Bound with no additional complexity. Finally we have designed a low complexity SNR estimator, which saves one-half of multiplication with respect to the ML estimator, and it has similar estimation accuracy.

Architectures and design patterns for functional design of logic control and diagnostics in industrial automation

Recently in most of the industrial automation process an ever increasing degree of automation has been observed. This increasing is motivated by the higher requirement of systems with great performance in terms of quality of products/services generated, productivity, efficiency and low costs in the design, realization and maintenance. This trend in the growth of complex automation systems is rapidly spreading over automated manufacturing systems (AMS), where the integration of the mechanical and electronic technology, typical of the Mechatronics, is merging with other technologies such as Informatics and the communication networks. An AMS is a very complex system that can be thought constituted by a set of flexible working stations, one or more transportation systems. To understand how this machine are important in our society let considerate that every day most of us use bottles of water or soda, buy product in box like food or cigarets and so on. Another important consideration from its complexity derive from the fact that the the consortium of machine producers has estimated around 350 types of manufacturing machine. A large number of manufacturing machine industry are presented in Italy and notably packaging machine industry,in particular a great concentration of this kind of industry is located in Bologna area; for this reason the Bologna area is called “packaging valley”. Usually, the various parts of the AMS interact among them in a concurrent and asynchronous way, and coordinate the parts of the machine to obtain a desiderated overall behaviour is an hard task. Often, this is the case in large scale systems, organized in a modular and distributed manner. Even if the success of a modern AMS from a functional and behavioural point of view is still to attribute to the design choices operated in the definition of the mechanical structure and electrical electronic architecture, the system that governs the control of the plant is becoming crucial, because of the large number of duties associated to it. Apart from the activity inherent to the automation of themachine cycles, the supervisory system is called to perform other main functions such as: emulating the behaviour of traditional mechanical members thus allowing a drastic constructive simplification of the machine and a crucial functional flexibility; dynamically adapting the control strategies according to the different productive needs and to the different operational scenarios; obtaining a high quality of the final product through the verification of the correctness of the processing; addressing the operator devoted to themachine to promptly and carefully take the actions devoted to establish or restore the optimal operating conditions; managing in real time information on diagnostics, as a support of the maintenance operations of the machine. The kind of facilities that designers can directly find on themarket, in terms of software component libraries provides in fact an adequate support as regard the implementation of either top-level or bottom-level functionalities, typically pertaining to the domains of user-friendly HMIs, closed-loop regulation and motion control, fieldbus-based interconnection of remote smart devices. What is still lacking is a reference framework comprising a comprehensive set of highly reusable logic control components that, focussing on the cross-cutting functionalities characterizing the automation domain, may help the designers in the process of modelling and structuring their applications according to the specific needs. Historically, the design and verification process for complex automated industrial systems is performed in empirical way, without a clear distinction between functional and technological-implementation concepts and without a systematic method to organically deal with the complete system. Traditionally, in the field of analog and digital control design and verification through formal and simulation tools have been adopted since a long time ago, at least for multivariable and/or nonlinear controllers for complex time-driven dynamics as in the fields of vehicles, aircrafts, robots, electric drives and complex power electronics equipments. Moving to the field of logic control, typical for industrial manufacturing automation, the design and verification process is approached in a completely different way, usually very “unstructured”. No clear distinction between functions and implementations, between functional architectures and technological architectures and platforms is considered. Probably this difference is due to the different “dynamical framework”of logic control with respect to analog/digital control. As a matter of facts, in logic control discrete-events dynamics replace time-driven dynamics; hence most of the formal and mathematical tools of analog/digital control cannot be directly migrated to logic control to enlighten the distinction between functions and implementations. In addition, in the common view of application technicians, logic control design is strictly connected to the adopted implementation technology (relays in the past, software nowadays), leading again to a deep confusion among functional view and technological view. In Industrial automation software engineering, concepts as modularity, encapsulation, composability and reusability are strongly emphasized and profitably realized in the so-calledobject-oriented methodologies. Industrial automation is receiving lately this approach, as testified by some IEC standards IEC 611313, IEC 61499 which have been considered in commercial products only recently. On the other hand, in the scientific and technical literature many contributions have been already proposed to establish a suitable modelling framework for industrial automation. During last years it was possible to note a considerable growth in the exploitation of innovative concepts and technologies from ICT world in industrial automation systems. For what concerns the logic control design, Model Based Design (MBD) is being imported in industrial automation from software engineering field. Another key-point in industrial automated systems is the growth of requirements in terms of availability, reliability and safety for technological systems. In other words, the control system should not only deal with the nominal behaviour, but should also deal with other important duties, such as diagnosis and faults isolations, recovery and safety management. Indeed, together with high performance, in complex systems fault occurrences increase. This is a consequence of the fact that, as it typically occurs in reliable mechatronic systems, in complex systems such as AMS, together with reliable mechanical elements, an increasing number of electronic devices are also present, that are more vulnerable by their own nature. The diagnosis problem and the faults isolation in a generic dynamical system consists in the design of an elaboration unit that, appropriately processing the inputs and outputs of the dynamical system, is also capable of detecting incipient faults on the plant devices, reconfiguring the control system so as to guarantee satisfactory performance. The designer should be able to formally verify the product, certifying that, in its final implementation, it will perform itsrequired function guarantying the desired level of reliability and safety; the next step is that of preventing faults and eventually reconfiguring the control system so that faults are tolerated. On this topic an important improvement to formal verification of logic control, fault diagnosis and fault tolerant control results derive from Discrete Event Systems theory. The aimof this work is to define a design pattern and a control architecture to help the designer of control logic in industrial automated systems. The work starts with a brief discussion on main characteristics and description of industrial automated systems on Chapter 1. In Chapter 2 a survey on the state of the software engineering paradigm applied to industrial automation is discussed. Chapter 3 presentes a architecture for industrial automated systems based on the new concept of Generalized Actuator showing its benefits, while in Chapter 4 this architecture is refined using a novel entity, the Generalized Device in order to have a better reusability and modularity of the control logic. In Chapter 5 a new approach will be present based on Discrete Event Systems for the problemof software formal verification and an active fault tolerant control architecture using online diagnostic. Finally conclusive remarks and some ideas on new directions to explore are given. In Appendix A are briefly reported some concepts and results about Discrete Event Systems which should help the reader in understanding some crucial points in chapter 5; while in Appendix B an overview on the experimental testbed of the Laboratory of Automation of University of Bologna, is reported to validated the approach presented in chapter 3, chapter 4 and chapter 5. In Appendix C some components model used in chapter 5 for formal verification are reported.

Multiscale fabrication of functional materials for life sciences

Regenerative medicine claims for a better understanding of the cause-effect relation between cell behaviour and environment signals. The latter encompasses topographical, chemical and mechanical stimuli, electromagnetic fields, gradients of chemo-attractants and haptotaxis. In this perspective, a spatial control of the structures composing the environment is required. In this thesis I describe a novel approach for the multiscale patterning of biocompatible functional materials in order to provide systems able to accurately control cell adhesion and proliferation. The behaviour of different neural cell lines in response to several stimuli, specifically chemical, topographical and electrical gradients is presented. For each of the three kind of signals, I chose properly tailored materials and fabrication and characterization techniques. After a brief introduction on the state of art of nanotechnology, nanofabrication techniques and regenerative medicine in Chapter 1 and a detailed description of the main fabrication and characterization techniques employed in this work in Chapter 2, in Chapter 3 an easy route to obtain accurate control over cell proliferation close to 100% is described (chemical control). In Chapter 4 (topographical control) it is shown how the multiscale patterning of a well-established biocompatible material as titanium dioxide provides a versatile and robust method to study the effect of local topography on cell adhesion and growth. The third signal, viz. electric field, is investigated in Chapter 5 (electrical control), where the very early stages of neural cell adhesion are studied in the presence of modest steady electric fields. In Chapter 6 (appendix) a new patterning technique, called Lithographically Controlled Etching (LCE), is proposed. It is shown how LCE can provide at the same time the micro/nanostructuring and functionalization of a surface with nanosized objects, thus being suitable for applications both in regenerative medicine in biosensing.

Lesion detection and classification in breast cancer: evaluation of approaches based on morphological features, tracer kinetic modelling and semi-quantitative parameters in MR functional imaging (DCE-MRI)

The diagnosis, grading and classification of tumours has benefited considerably from the development of DCE-MRI which is now essential to the adequate clinical management of many tumour types due to its capability in detecting active angiogenesis. Several strategies have been proposed for DCE-MRI evaluation. Visual inspection of contrast agent concentration curves vs time is a very simple yet operator dependent procedure, therefore more objective approaches have been developed in order to facilitate comparison between studies. In so called model free approaches, descriptive or heuristic information extracted from time series raw data have been used for tissue classification. The main issue concerning these schemes is that they have not a direct interpretation in terms of physiological properties of the tissues. On the other hand, model based investigations typically involve compartmental tracer kinetic modelling and pixel-by-pixel estimation of kinetic parameters via non-linear regression applied on region of interests opportunely selected by the physician. This approach has the advantage to provide parameters directly related to the pathophysiological properties of the tissue such as vessel permeability, local regional blood flow, extraction fraction, concentration gradient between plasma and extravascular-extracellular space. Anyway, nonlinear modelling is computational demanding and the accuracy of the estimates can be affected by the signal-to-noise ratio and by the initial solutions. The principal aim of this thesis is investigate the use of semi-quantitative and quantitative parameters for segmentation and classification of breast lesion. The objectives can be subdivided as follow: describe the principal techniques to evaluate time intensity curve in DCE-MRI with focus on kinetic model proposed in literature; to evaluate the influence in parametrization choice for a classic bi-compartmental kinetic models; to evaluate the performance of a method for simultaneous tracer kinetic modelling and pixel classification; to evaluate performance of machine learning techniques training for segmentation and classification of breast lesion.

Functional and neural mechanisms of intertemporal choice

People are daily faced with intertemporal choice, i.e., choices differing in the timing of their consequences, frequently preferring smaller-sooner rewards over larger-delayed ones, reflecting temporal discounting of the value of future outcomes. This dissertation addresses two main goals. New evidence about the neural bases of intertemporal choice is provided. Following the disruption of either the medial orbitofrontal cortex or the insula, the willingness to wait for larger-delayed outcomes is affected in odd directions, suggesting the causal involvement of these areas in regulating the value computation of rewards available with different timings. These findings were also supported by a reported imaging study. Moreover, this dissertation provides new evidence about how temporal discounting can be modulated at a behavioral level through different manipulations, e.g., allowing individuals to think about the distant time, pairing rewards with aversive events, or changing their perceived spatial position. A relationship between intertemporal choice, moral judgements and aging is also discussed. All these findings link together to support a unitary neural model of temporal discounting according to which signals coming from several cortical (i.e., medial orbitofrontal cortex, insula) and subcortical regions (i.e., amygdala, ventral striatum) are integrated to represent the subjective value of both earlier and later rewards, under the top-down regulation of dorsolateral prefrontal cortex. The present findings also support the idea that the process of outcome evaluation is strictly related to the ability to pre-experience and envision future events through self-projection, the anticipation of visceral feelings associated with receiving rewards, and the psychological distance from rewards. Furthermore, taking into account the emotions and the state of arousal at the time of decision seems necessary to understand impulsivity associated with preferring smaller-sooner goods in place of larger-later goods.

From inverted pendulum to N-link chain: inertial sensors-based assessment of movement kinematics and dynamics for functional evaluation and rehabilitation

Despite several clinical tests that have been developed to qualitatively describe complex motor tasks by functional testing, these methods often depend on clinicians' interpretation, experience and training, which make the assessment results inconsistent, without the precision required to objectively assess the effect of the rehabilitative intervention. A more detailed characterization is required to fully capture the various aspects of motor control and performance during complex movements of lower and upper limbs. The need for cost-effective and clinically applicable instrumented tests would enable quantitative assessment of performance on a subject-specific basis, overcoming the limitations due to the lack of objectiveness related to individual judgment, and possibly disclosing subtle alterations that are not clearly visible to the observer. Postural motion measurements at additional locations, such as lower and upper limbs and trunk, may be necessary in order to obtain information about the inter-segmental coordination during different functional tests involved in clinical practice. With these considerations in mind, this Thesis aims: i) to suggest a novel quantitative assessment tool for the kinematics and dynamics evaluation of a multi-link kinematic chain during several functional motor tasks (i.e. squat, sit-to-stand, postural sway), using one single-axis accelerometer per segment, ii) to present a novel quantitative technique for the upper limb joint kinematics estimation, considering a 3-link kinematic chain during the Fugl-Meyer Motor Assessment and using one inertial measurement unit per segment. The suggested methods could have several positive feedbacks from clinical practice. The use of objective biomechanical measurements, provided by inertial sensor-based technique, may help clinicians to: i) objectively track changes in motor ability, ii) provide timely feedback about the effectiveness of administered rehabilitation interventions, iii) enable intervention strategies to be modified or changed if found to be ineffective, and iv) speed up the experimental sessions when several subjects are asked to perform different functional tests.

Nano-fabrication of complex functional structures using non- conventional lithography

In Chapter 1 I will present a brief introduction on the state of art of nanotechnologies, nanofabrication techniques and unconventional lithography as a technique to fabricate the novel electronic device as resistive switch so-called memristor is shown. In Chapter 2 a detailed description of the main fabrication and characterization techniques employed in this work is reported. Chapter 3 parallel local oxidation lithography (pLOx) describes as a main technique to obtain accurate patterning process. All the effective parameters has been studied and the optimized condition observed to highly reproducible with excellent patterned nanostructures. The effect of negative bias, calls local reduction (LR) studied. Moreover, the use of AC bias shows faster patterning process respect to DC bias. In Chapter 4 (metal/ e-SiO2/ Si nanojunction) it is shown how the electrochemical oxide nanostructures by using pLOx can be used in the fabrication of novel devices call memristor. We demonstrate a new concept, based on conventional materials, where the lifetime problem is resolved by introducing a “regeneration” step, which restores the nano-memristor to its pristine condition by applying an appropriate voltage cycle. In Chapter 5 (Graphene/ e-SiO2/ Si), Graphene as a building block material is used as an electrode to selectively oxidize the silicon substrate by pLOx set up for the fabrication of novel resistive switch device. In Chapter 6 (surface architecture) I will show another application of pLOx in biotechnology is shown. So the surface functionalization combine with nano-patterning by pLOx used to design a new surface to accurately bind biomolecules with the possibility of studying those properties and more application in nano-bio device fabrication. So, in order to obtain biochips, electronic and optical/photonics devices Nano patterning of DNA used as scaffolds to fabricate small functional nano-components.

Multimodal (EEG-fMRI) functional connectivity study of levodopa effect in Parkinson’s disease

Aim: To assess if the intake of levodopa in patients with Parkinson’s Disease (PD) changes cerebral connectivity, as revealed by simultaneous recording of hemodynamic (functional MRI, or fMRI) and electric (electroencephalogram, EEG) signals. Particularly, we hypothesize that the strongest changes in FC will involve the motor network, which is the most impaired in PD. Methods: Eight patients with diagnosis of PD “probable”, therapy with levodopa exclusively, normal cognitive and affective status, were included. Exclusion criteria were: moderate-severe rest tremor, levodopa induced dyskinesia, evidence of gray or white matter abnormalities on structural MRI. Scalp EEG (64 channels) were acquired inside the scanner (1.5 Tesla) before and after the intake of levodopa. fMRI functional connectivity was computed from four regions of interest: right and left supplementary motor area (SMA) and right and left precentral gyrus (primary motor cortex). Weighted partial directed coherence (w-PDC) was computed in the inverse space after the removal of EEG gradient and cardioballistic artifacts. Results and discussion: fMRI group analysis shows that the intake of levodopa increases hemodynamic functional connectivity among the SMAs / primary motor cortex and: sensory-motor network itself, attention network and default mode network. w-PDC analysis shows that EEG connectivity among regions of the motor network has the tendency to decrease after the intake the levodopa; furthermore, regions belonging to the DMN have the tendency to increase their outflow toward the rest of the brain. These findings, even if in a small sample of patients, suggest that other resting state physiological functional networks, beyond the motor one, are affected in patients with PD. The behavioral and cognitive tasks corresponding to the affected networks could benefit from the intake of levodopa.