The application of a new psychotherapeutic strategy for enhancing eudaimonic well-being in children with mood and anxiety disorders

The aim of the dissertation was to test the feasibility of a new psychotherapeutic protocol for treating children and adolescents with mood and anxiety disorders: Child-Well-Being Therapy (CWBT). It originates from adult Well-Being Therapy protocol (WBT) and represents a conceptual innovation for treating affective disorders. WBT is based on the multidimensional model of well-being postulated by Ryff (eudaimonic perspective), in sequential combination with cognitive-behavioral therapy (CBT). Results showed that eudaimonic well-being was impaired in children with affective disorders in comparison with matched healthy students. A first open investigation aimed at exploring the feasibility of a 8-session CWBT protocol in a group of children with emotional and behavioural disorders has been implemented. Data showed how CWBT resulted associated to symptoms reduction, together with the decrease of externalizing problems, maintained at 1-year follow-up. CWBT triggered also an improvement in psychological well-being as well as an increasing flourishing trajectory over time. Subsequently, a modified and extended version of CWBT (12-sessions) has been developed and then tested in a controlled study with 34 patients (8 to 16 years) affected by mood and anxiety disorders. They were consecutively randomized into 3 different groups: CWBT, CBT, 6-month waiting list (WL). Both treatments resulted effective in decreasing distress and in improving well-being. Moreover, CWBT was associated with higher improvement in anxiety and showed a greater recovery rate (83%) than CBT (54%). Both groups maintained beneficial effects and CWBT group displayed a lower level of distress as well as a higher positive trend in well-being scores over time. Findings need to be interpret with caution, because of study limitations, however important clinical implications emerged. Further investigations should determine whether the sequential integration of well-being and symptom-oriented strategies could play an important role in children and adolescents’ psychotherapeutic options, fostering a successful adaptation to adversities during the growth process.

Interactions between normative systems and software cognitive agents. A formalization in temporal modal defeasible logic and its implementation

Sustainable computer systems require some flexibility to adapt to environmental unpredictable changes. A solution lies in autonomous software agents which can adapt autonomously to their environments. Though autonomy allows agents to decide which behavior to adopt, a disadvantage is a lack of control, and as a side effect even untrustworthiness: we want to keep some control over such autonomous agents. How to control autonomous agents while respecting their autonomy? A solution is to regulate agents’ behavior by norms. The normative paradigm makes it possible to control autonomous agents while respecting their autonomy, limiting untrustworthiness and augmenting system compliance. It can also facilitate the design of the system, for example, by regulating the coordination among agents. However, an autonomous agent will follow norms or violate them in some conditions. What are the conditions in which a norm is binding upon an agent? While autonomy is regarded as the driving force behind the normative paradigm, cognitive agents provide a basis for modeling the bindingness of norms. In order to cope with the complexity of the modeling of cognitive agents and normative bindingness, we adopt an intentional stance. Since agents are embedded into a dynamic environment, things may not pass at the same instant. Accordingly, our cognitive model is extended to account for some temporal aspects. Special attention is given to the temporal peculiarities of the legal domain such as, among others, the time in force and the time in efficacy of provisions. Some types of normative modifications are also discussed in the framework. It is noteworthy that our temporal account of legal reasoning is integrated to our commonsense temporal account of cognition. As our intention is to build sustainable reasoning systems running unpredictable environment, we adopt a declarative representation of knowledge. A declarative representation of norms will make it easier to update their system representation, thus facilitating system maintenance; and to improve system transparency, thus easing system governance. Since agents are bounded and are embedded into unpredictable environments, and since conflicts may appear amongst mental states and norms, agent reasoning has to be defeasible, i.e. new pieces of information can invalidate formerly derivable conclusions. In this dissertation, our model is formalized into a non-monotonic logic, namely into a temporal modal defeasible logic, in order to account for the interactions between normative systems and software cognitive agents.

Integration of cognitive and affective processes in perception and decision-making

The relationship between emotion and cognition is a topic that raises great interest in research. Recently, a view of these two processes as interactive and mutually influencing each other has become predominant. This dissertation investigates the reciprocal influences of emotion and cognition, both at behavioral and neural level, in two specific fields, such as attention and decision-making. Experimental evidence on how emotional responses may affect perceptual and attentional processes has been reported. In addition, the impact of three factors, such as personality traits, motivational needs and social context, in modulating the influence that emotion exerts on perception and attention has been investigated. Moreover, the influence of cognition on emotional responses in decision-making has been demonstrated. The current experimental evidence showed that cognitive brain regions such as the dorsolateral prefrontal cortex are causally implicated in regulation of emotional responses and that this has an effect at both pre and post decisional stages. There are two main conclusions of this dissertation: firstly, emotion exerts a strong influence on perceptual and attentional processes but, at the same time, this influence may also be modulated by other factors internal and external to the individuals. Secondly, cognitive processes may modulate emotional prepotent responses, by serving a regulative function critical to driving and shaping human behavior in line with current goals.

Ribosome-inactivating proteins and their immunotoxins for cancer therapy: insights into the mechanism of cell death

Ribosome-inactivating proteins (RIPs) are a family of plant toxic enzymes that permanently damage ribosomes and possibly other cellular substrates, thus causing cell death involving different and still not completely understood pathways. The high cytotoxic activity showed by many RIPs makes them ideal candidates for the production of immunotoxins (ITs), chimeric proteins designed for the selective elimination of unwanted or malignant cells. Saporin-S6, a type 1 RIP extracted from Saponaria officinalis L. seeds, has been extensively employed to construct anticancer conjugates because of its high enzymatic activity, stability and resistance to conjugation procedures, resulting in the efficient killing of target cells. Here we investigated the anticancer properties of two saporin-based ITs, anti-CD20 RTX/S6 and anti-CD22 OM124/S6, designed for the experimental treatment of B-cell NHLs. Both ITs showed high cytotoxicity towards CD20-positive B-cells, and their antitumor efficacy was enhanced synergistically by a combined treatment with proteasome inhibitors or fludarabine. Furthermore, the two ITs showed differencies in potency and ability to activate effector caspases, and a different behavior in the presence of the ROS scavenger catalase. Taken together, these results suggest that the different carriers employed to target saporin might influence saporin intracellular routing and saporin-induced cell death mechanisms. We also investigated the early cellular response to stenodactylin, a recently discovered highly toxic type 2 RIP representing an interesting candidate for the design and production of a new IT for the experimental treatment of cancer.

Methods for objective and interpretative evaluation of function and motor control: gait in perturbed condition and in the aquatic therapy

Gait analysis allows to characterize motor function, highlighting deviations from normal motor behavior related to an underlying pathology. The widespread use of wearable inertial sensors has opened the way to the evaluation of ecological gait, and a variety of methodological approaches and algorithms have been proposed for the characterization of gait from inertial measures (e.g. for temporal parameters, motor stability and variability, specific pathological alterations). However, no comparative analysis of their performance (i.e. accuracy, repeatability) was available yet, in particular, analysing how this performance is affected by extrinsic (i.e. sensor location, computational approach, analysed variable, testing environmental constraints) and intrinsic (i.e. functional alterations resulting from pathology) factors. The aim of the present project was to comparatively analyze the influence of intrinsic and extrinsic factors on the performance of the numerous algorithms proposed in the literature for the quantification of specific characteristics (i.e. timing, variability/stability) and alterations (i.e. freezing) of gait. Considering extrinsic factors, the influence of sensor location, analyzed variable, and computational approach on the performance of a selection of gait segmentation algorithms from a literature review was analysed in different environmental conditions (e.g. solid ground, sand, in water). Moreover, the influence of altered environmental conditions (i.e. in water) was analyzed as referred to the minimum number of stride necessary to obtain reliable estimates of gait variability and stability metrics, integrating what already available in the literature for over ground gait in healthy subjects. Considering intrinsic factors, the influence of specific pathological conditions (i.e. Parkinson’s Disease) was analyzed as affecting the performance of segmentation algorithms, with and without freezing. Finally, the analysis of the performance of algorithms for the detection of gait freezing showed how results depend on the domain of implementation and IMU position.

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.

Development and Implementation of the Plasma Focus Technology for Radiation Therapy Applications

A Plasma Focus device can confine in a small region a plasma generated during the pinch phase. When the plasma is in the pinch condition it creates an environment that produces several kinds of radiations. When the filling gas is nitrogen, a self-collimated backwardly emitted electron beam, slightly spread by the coulomb repulsion, can be considered one of the most interesting outputs. That beam can be converted into X-ray pulses able to transfer energy at an Ultra-High Dose-Rate (UH-DR), up to 1 Gy pulse-1, for clinical applications, research, or industrial purposes. The radiation fields have been studied with the PFMA-3 hosted at the University of Bologna, finding the radiation behavior at different operating conditions and working parameters for a proper tuning of this class of devices in clinical applications. The experimental outcomes have been compared with available analytical formalisms as benchmark and the scaling laws have been proposed. A set of Monte Carlo models have been built with direct and adjoint techniques for an accurate X-ray source characterization and for setting fast and reliable irradiation planning for patients. By coupling deterministic and Monte Carlo codes, a focusing lens for the charged particles has been designed for obtaining a beam suitable for applications as external radiotherapy or intra-operative radiation therapy. The radiobiological effectiveness of the UH PF DR, a FLASH source, has been evaluated by coupling different Monte Carlo codes estimating the overall level of DNA damage at the multi-cellular and tissue levels by considering the spatial variation effects as well as the radiation field characteristics. The numerical results have been correlated to the experimental outcomes. Finally, ambient dose measurements have been performed for tuning the numerical models and obtaining doses for radiation protection purposes. The PFMA-3 technology has been fully characterized toward clinical implementation and installation in a medical facility.

Hierarchical active inference for cognitive architectures

This thesis explores the methods based on the free energy principle and active inference for modelling cognition. Active inference is an emerging framework for designing intelligent agents where psychological processes are cast in terms of Bayesian inference. Here, I appeal to it to test the design of a set of cognitive architectures, via simulation. These architectures are defined in terms of generative models where an agent executes a task under the assumption that all cognitive processes aspire to the same objective: the minimization of variational free energy. Chapter 1 introduces the free energy principle and its assumptions about self-organizing systems. Chapter 2 describes how from the mechanics of self-organization can emerge a minimal form of cognition able to achieve autopoiesis. In chapter 3 I present the method of how I formalize generative models for action and perception. The architectures proposed allow providing a more biologically plausible account of more complex cognitive processing that entails deep temporal features. I then present three simulation studies that aim to show different aspects of cognition, their associated behavior and the underlying neural dynamics. In chapter 4, the first study proposes an architecture that represents the visuomotor system for the encoding of actions during action observation, understanding and imitation. In chapter 5, the generative model is extended and is lesioned to simulate brain damage and neuropsychological patterns observed in apraxic patients. In chapter 6, the third study proposes an architecture for cognitive control and the modulation of attention for action selection. At last, I argue how active inference can provide a formal account of information processing in the brain and how the adaptive capabilities of the simulated agents are a mere consequence of the architecture of the generative models. Cognitive processing, then, becomes an emergent property of the minimization of variational free energy.