Mathematical models of cognitive processes

The research activity carried out during the PhD course was focused on the development of mathematical models of some cognitive processes and their validation by means of data present in literature, with a double aim: i) to achieve a better interpretation and explanation of the great amount of data obtained on these processes from different methodologies (electrophysiological recordings on animals, neuropsychological, psychophysical and neuroimaging studies in humans), ii) to exploit model predictions and results to guide future research and experiments. In particular, the research activity has been focused on two different projects: 1) the first one concerns the development of neural oscillators networks, in order to investigate the mechanisms of synchronization of the neural oscillatory activity during cognitive processes, such as object recognition, memory, language, attention; 2) the second one concerns the mathematical modelling of multisensory integration processes (e.g. visual-acoustic), which occur in several cortical and subcortical regions (in particular in a subcortical structure named Superior Colliculus (SC)), and which are fundamental for orienting motor and attentive responses to external world stimuli. This activity has been realized in collaboration with the Center for Studies and Researches in Cognitive Neuroscience of the University of Bologna (in Cesena) and the Department of Neurobiology and Anatomy of the Wake Forest University School of Medicine (NC, USA). PART 1. Objects representation in a number of cognitive functions, like perception and recognition, foresees distribute processes in different cortical areas. One of the main neurophysiological question concerns how the correlation between these disparate areas is realized, in order to succeed in grouping together the characteristics of the same object (binding problem) and in maintaining segregated the properties belonging to different objects simultaneously present (segmentation problem). Different theories have been proposed to address these questions (Barlow, 1972). One of the most influential theory is the so called “assembly coding”, postulated by Singer (2003), according to which 1) an object is well described by a few fundamental properties, processing in different and distributed cortical areas; 2) the recognition of the object would be realized by means of the simultaneously activation of the cortical areas representing its different features; 3) groups of properties belonging to different objects would be kept separated in the time domain. In Chapter 1.1 and in Chapter 1.2 we present two neural network models for object recognition, based on the “assembly coding” hypothesis. These models are networks of Wilson-Cowan oscillators which exploit: i) two high-level “Gestalt Rules” (the similarity and previous knowledge rules), to realize the functional link between elements of different cortical areas representing properties of the same object (binding problem); 2) the synchronization of the neural oscillatory activity in the γ-band (30-100Hz), to segregate in time the representations of different objects simultaneously present (segmentation problem). These models are able to recognize and reconstruct multiple simultaneous external objects, even in difficult case (some wrong or lacking features, shared features, superimposed noise). In Chapter 1.3 the previous models are extended to realize a semantic memory, in which sensory-motor representations of objects are linked with words. To this aim, the network, previously developed, devoted to the representation of objects as a collection of sensory-motor features, is reciprocally linked with a second network devoted to the representation of words (lexical network) Synapses linking the two networks are trained via a time-dependent Hebbian rule, during a training period in which individual objects are presented together with the corresponding words. Simulation results demonstrate that, during the retrieval phase, the network can deal with the simultaneous presence of objects (from sensory-motor inputs) and words (from linguistic inputs), can correctly associate objects with words and segment objects even in the presence of incomplete information. Moreover, the network can realize some semantic links among words representing objects with some shared features. These results support the idea that semantic memory can be described as an integrated process, whose content is retrieved by the co-activation of different multimodal regions. In perspective, extended versions of this model may be used to test conceptual theories, and to provide a quantitative assessment of existing data (for instance concerning patients with neural deficits). PART 2. The ability of the brain to integrate information from different sensory channels is fundamental to perception of the external world (Stein et al, 1993). It is well documented that a number of extraprimary areas have neurons capable of such a task; one of the best known of these is the superior colliculus (SC). This midbrain structure receives auditory, visual and somatosensory inputs from different subcortical and cortical areas, and is involved in the control of orientation to external events (Wallace et al, 1993). SC neurons respond to each of these sensory inputs separately, but is also capable of integrating them (Stein et al, 1993) so that the response to the combined multisensory stimuli is greater than that to the individual component stimuli (enhancement). This enhancement is proportionately greater if the modality-specific paired stimuli are weaker (the principle of inverse effectiveness). Several studies have shown that the capability of SC neurons to engage in multisensory integration requires inputs from cortex; primarily the anterior ectosylvian sulcus (AES), but also the rostral lateral suprasylvian sulcus (rLS). If these cortical inputs are deactivated the response of SC neurons to cross-modal stimulation is no different from that evoked by the most effective of its individual component stimuli (Jiang et al 2001). This phenomenon can be better understood through mathematical models. The use of mathematical models and neural networks can place the mass of data that has been accumulated about this phenomenon and its underlying circuitry into a coherent theoretical structure. In Chapter 2.1 a simple neural network model of this structure is presented; this model is able to reproduce a large number of SC behaviours like multisensory enhancement, multisensory and unisensory depression, inverse effectiveness. In Chapter 2.2 this model was improved by incorporating more neurophysiological knowledge about the neural circuitry underlying SC multisensory integration, in order to suggest possible physiological mechanisms through which it is effected. This endeavour was realized in collaboration with Professor B.E. Stein and Doctor B. Rowland during the 6 months-period spent at the Department of Neurobiology and Anatomy of the Wake Forest University School of Medicine (NC, USA), within the Marco Polo Project. The model includes four distinct unisensory areas that are devoted to a topological representation of external stimuli. Two of them represent subregions of the AES (i.e., FAES, an auditory area, and AEV, a visual area) and send descending inputs to the ipsilateral SC; the other two represent subcortical areas (one auditory and one visual) projecting ascending inputs to the same SC. Different competitive mechanisms, realized by means of population of interneurons, are used in the model to reproduce the different behaviour of SC neurons in conditions of cortical activation and deactivation. The model, with a single set of parameters, is able to mimic the behaviour of SC multisensory neurons in response to very different stimulus conditions (multisensory enhancement, inverse effectiveness, within- and cross-modal suppression of spatially disparate stimuli), with cortex functional and cortex deactivated, and with a particular type of membrane receptors (NMDA receptors) active or inhibited. All these results agree with the data reported in Jiang et al. (2001) and in Binns and Salt (1996). The model suggests that non-linearities in neural responses and synaptic (excitatory and inhibitory) connections can explain the fundamental aspects of multisensory integration, and provides a biologically plausible hypothesis about the underlying circuitry.

L’interpretazione simultanea dal polacco all’italiano: le strategie per affrontare le catene nominali

La presente tesi rappresenta il primo studio dedicato all’interpretazione simultanea dal polacco all’italiano. La presente ricerca cerca di identificare il modo in cui interpreti di comprovata esperienza gestiscono alcune difficoltà tipiche della sintassi polacca fortemente divergenti da quella italiana. La scelta di studiare le catene nominali deriva dal confronto di quanto emerso dalle indagini sulla linguistica contrastiva con un’inchiesta tra gli interpreti accreditati presso le istituzioni europee per quella combinazione. Il primo capitolo è dedicato ad una panoramica sui contatti passati e presenti tra l’Italia e la Polonia e ad una riflessione sulla lingua polacca in chiave contrastiva con l’italiano. Il secondo capitolo si concentra sulla ricerca nell’ambito dell’interpretazione simultanea, in particolare sugli studi contrastivi e sulla discussione delle strategie usate dagli interpreti. Il terzo capitolo approfondisce il contesto di questo studio ovvero le istituzioni europee, il il multilinguismo e il regime linguistico al Parlamento Europeo. Il quarto capitolo include l’indagine del lavoro, condotta su un ampio corpus di dati. Sono stati infatti trascritti e analizzati tutti gli interventi tenuti in lingua polacca in occasione delle sedute parlamentari a Strasburgo e a Bruxelles del 2011 e del primo semestre 2009 e le relative interppretazioni in italiano (per un totale di oltre 9 ore di parlato per lingua). Dall’analisi è risultato che l’interprete nella maggior parte dei casi cerca, nonostante la velocità d’eloquio dell’oratore, di riprodurre fedelmente il messaggio. Tuttavia, qualora questo non risulti possibile, si è notato come gli interpreti ricorrano in maniera consapevole all’omissione di quelle informazioni desumibili o dal contesto o dalle conoscenze pregresse dell’ascoltatore. Di conseguenza la riduzione non rappresenta una strategia di emergenza ma una risorsa da applicare consapevolmente per superare le difficoltà poste da lunghe sequenze di sostantivi.

Sustainable exploitation of offshore renewable energy sources

Energy transition is the response of humankind to the concerning effects of fossil fuels depletion, climate change and energy insecurity, and calls for a deep penetration of renewable energy sources (RESs) in power systems and industrial processes. Despite the high potentials, low impacts and long-term availability, RESs present some limits which need to be overcome, such as the strong variability and difficult predictability, which result in scarce reliability and difficult applicability in steady-state processes. Some technological solutions relate to energy storage systems, equipment electrification and hybrid systems deployment, thus accomplishing distributed generation even in remote sites as offshore. However, all of these actions cannot disregard sustainability, which represents a founding principle for any project, bringing together economics, reliability and environmental protection. To entail sustainability in RESs-based innovative projects, previous knowledge and tools are often not tailored or miss the novel objectives. This research proposes three methodological approaches, bridging the gaps. The first contribute adapts literature-based indicators of inherent safety and energy efficiency to capture the specificities of novel process plants and hybrid systems. Minor case studies dealing with novel P2X processes exemplify the application of these novel indicators. The second method guides the conceptual design of hybrid systems for the valorisation of a RES in a site, by considering the sustainability performances of alternative design options. Its application is demonstrated through the comparison of two offshore sites where wave energy can be valorised. Finally, “OHRES”, a comprehensive tool for the sustainable optimisation of hybrid renewable energy systems is proposed. “OHRES” hinges on the exploitation of multiple RESs, by converting ex-post sustainability indicators into discrimination markers screening a large number of possible system configurations, according to the location features. Five case studies demonstrate “OHRES” versatility in the sustainable valorisation of multiple RESs.

Interpreting Judgements using Knowledge Representation Methods and Computational Models of Argument

The goal of the present research is to define a Semantic Web framework for precedent modelling, by using knowledge extracted from text, metadata, and rules, while maintaining a strong text-to-knowledge morphism between legal text and legal concepts, in order to fill the gap between legal document and its semantics. The framework is composed of four different models that make use of standard languages from the Semantic Web stack of technologies: a document metadata structure, modelling the main parts of a judgement, and creating a bridge between a text and its semantic annotations of legal concepts; a legal core ontology, modelling abstract legal concepts and institutions contained in a rule of law; a legal domain ontology, modelling the main legal concepts in a specific domain concerned by case-law; an argumentation system, modelling the structure of argumentation. The input to the framework includes metadata associated with judicial concepts, and an ontology library representing the structure of case-law. The research relies on the previous efforts of the community in the field of legal knowledge representation and rule interchange for applications in the legal domain, in order to apply the theory to a set of real legal documents, stressing the OWL axioms definitions as much as possible in order to enable them to provide a semantically powerful representation of the legal document and a solid ground for an argumentation system using a defeasible subset of predicate logics. It appears that some new features of OWL2 unlock useful reasoning features for legal knowledge, especially if combined with defeasible rules and argumentation schemes. The main task is thus to formalize legal concepts and argumentation patterns contained in a judgement, with the following requirement: to check, validate and reuse the discourse of a judge - and the argumentation he produces - as expressed by the judicial text.