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.

The special rights other than shares in cross-border mergers of limited liability companies within the European Union. A perspective from the Spanish Law

The present research aims to study the special rights other than shares in Spanish Law and the protection of their holders in cross-border mergers of limited liability companies within the European Union frame. Special rights other than shares are recognised as an independent legal category within legal systems of some EU Member States, such as Germany or Spain, through the implementation of the Third Directive 78/855/CEE concerning mergers of public limited liability companies. The above-cited Directive contains a special regime of protection for the holders of securities, other than shares, to which special rights are attached, consisting of being given rights in the acquiring company, at least equivalent to those they possessed in the company being acquired. This safeguard is to highlight the intimate connection between this type of rights and the company whose extinction determines the existence of those. Pursuant to the Directive 2005/56/CE on cross-border mergers of limited liability companies, each company taking part in these operations shall comply with the safeguards of members and third parties provided in their respective national law to which is subject. In this regard, the protection for holders of special rights other than shares shall be ruled by the domestic M&A regime. As far as Spanish Law are concerned, holders of these special rights are recognized a right of merger information, in the same terms as shareholders, as well as equal rights in the company resulting from the cross-border merger. However, these measures are not enough guarantee for a suitable protection, thus considering those holders of special rights as special creditors, sometimes it will be necessary to go to the general protection regime for creditors. In Spanish Law, it would involve the recognition of right to the merger opposition, whose exercise would prevent the operation was completed until ensuring equal rights.

Stone architecture in Carso plateau. Settlement patterns and construction techniques of historic buildings

The use of stone and its types of processing have been very important in the vernacular architecture of the cross-border Carso. In Carso this represents an important legacy of centuries and has a uniform typological characteristic to a great extent. The stone was the main constituent of the local architecture, setting and shaping the human environment, incorporating the history of places through their specific symbolic and constructive language. The primary aim of this research is the recognition of the constructive rules and the values embedded in the Carso rural architecture by use and processing of stone. Central to this investigation is the typological reading, aimed to analyze the constructive language expressed by this legacy, through the analysis of the relationship between type, technique and material.

New markov chain based methods for single and cross-domain sentiment classification

Nowadays communication is switching from a centralized scenario, where communication media like newspapers, radio, TV programs produce information and people are just consumers, to a completely different decentralized scenario, where everyone is potentially an information producer through the use of social networks, blogs, forums that allow a real-time worldwide information exchange. These new instruments, as a result of their widespread diffusion, have started playing an important socio-economic role. They are the most used communication media and, as a consequence, they constitute the main source of information enterprises, political parties and other organizations can rely on. Analyzing data stored in servers all over the world is feasible by means of Text Mining techniques like Sentiment Analysis, which aims to extract opinions from huge amount of unstructured texts. This could lead to determine, for instance, the user satisfaction degree about products, services, politicians and so on. In this context, this dissertation presents new Document Sentiment Classification methods based on the mathematical theory of Markov Chains. All these approaches bank on a Markov Chain based model, which is language independent and whose killing features are simplicity and generality, which make it interesting with respect to previous sophisticated techniques. Every discussed technique has been tested in both Single-Domain and Cross-Domain Sentiment Classification areas, comparing performance with those of other two previous works. The performed analysis shows that some of the examined algorithms produce results comparable with the best methods in literature, with reference to both single-domain and cross-domain tasks, in $2$-classes (i.e. positive and negative) Document Sentiment Classification. However, there is still room for improvement, because this work also shows the way to walk in order to enhance performance, that is, a good novel feature selection process would be enough to outperform the state of the art. Furthermore, since some of the proposed approaches show promising results in $2$-classes Single-Domain Sentiment Classification, another future work will regard validating these results also in tasks with more than $2$ classes.

Deep learning for computer vision: a comparison between convolutional neural networks and hierarchical temporal memories on object recognition tasks

In recent years, Deep Learning techniques have shown to perform well on a large variety of problems both in Computer Vision and Natural Language Processing, reaching and often surpassing the state of the art on many tasks. The rise of deep learning is also revolutionizing the entire field of Machine Learning and Pattern Recognition pushing forward the concepts of automatic feature extraction and unsupervised learning in general. However, despite the strong success both in science and business, deep learning has its own limitations. It is often questioned if such techniques are only some kind of brute-force statistical approaches and if they can only work in the context of High Performance Computing with tons of data. Another important question is whether they are really biologically inspired, as claimed in certain cases, and if they can scale well in terms of "intelligence". The dissertation is focused on trying to answer these key questions in the context of Computer Vision and, in particular, Object Recognition, a task that has been heavily revolutionized by recent advances in the field. Practically speaking, these answers are based on an exhaustive comparison between two, very different, deep learning techniques on the aforementioned task: Convolutional Neural Network (CNN) and Hierarchical Temporal memory (HTM). They stand for two different approaches and points of view within the big hat of deep learning and are the best choices to understand and point out strengths and weaknesses of each of them. CNN is considered one of the most classic and powerful supervised methods used today in machine learning and pattern recognition, especially in object recognition. CNNs are well received and accepted by the scientific community and are already deployed in large corporation like Google and Facebook for solving face recognition and image auto-tagging problems. HTM, on the other hand, is known as a new emerging paradigm and a new meanly-unsupervised method, that is more biologically inspired. It tries to gain more insights from the computational neuroscience community in order to incorporate concepts like time, context and attention during the learning process which are typical of the human brain. In the end, the thesis is supposed to prove that in certain cases, with a lower quantity of data, HTM can outperform CNN.

Processing-dependent and -independent pathways for recognition of iodinated contrast media by specific human T cells

One to three percent of patients exposed to intravenously injected iodinated contrast media (CM) develop delayed hypersensitivity reactions. Positive patch test reactions, immunohistological findings, and CM-specific proliferation of T cells in vitro suggest a pathogenetic role for T cells. We have previously demonstrated that CM-specific T cell clones (TCCs) show a broad range of cross-reactivity to different CM. However, the mechanism of specific CM recognition by T cell receptors (TCRs) has not been analysed so far.

Pathogen recognition by the long pentraxin PTX3

Innate immunity represents the first line of defence against pathogens and plays key roles in activation and orientation of the adaptive immune response. The innate immune system comprises both a cellular and a humoral arm. Components of the humoral arm include soluble pattern recognition molecules (PRMs) that recognise pathogen-associated molecular patterns (PAMPs) and initiate the immune response in coordination with the cellular arm, therefore acting as functional ancestors of antibodies. The long pentraxin PTX3 is a prototypic soluble PRM that is produced at sites of infection and inflammation by both somatic and immune cells. Gene targeting of this evolutionarily conserved protein has revealed a nonredundant role in resistance to selected pathogens. Moreover, PTX3 exerts important functions at the cross-road between innate immunity, inflammation, and female fertility. Here, we review the studies on PTX3, with emphasis on pathogen recognition and cross-talk with other components of the innate immune system.

Interethnic Interaction Dynamics in the Russian Federation

The collapse of the Soviet Union at the beginning of the 1990s also meant the end of the idea of a common soviet identity incarnated in the "soviet man" and the new "historic community of the soviet people". While this idea still lives on in the generations of the 1920s to 1940s, the younger generations tend to prefer identification with family, profession, ethnic group or religion. Ms. Alexakhina set out to investigate different interethnic interaction strategies in the multi-ethnic context of the Russian Federation, with an emphasis on analysing the role of cultural and ethno-demographic characteristics of minority ethnic groups. It aimed to identify those specific patterns of interaction dynamics that have emerged in response to the political and economic transformation at present under way. The basic supposition was that the size and growth of an ethnic population are defined not only by demographic features such as fertility, mortality and net migration, but are also dependent on processes interethnic interaction and ethnic transition. The central hypothesis of the project was that the multi-ethnic and multi-cultural composition of Russia is apparently manifesting itself in the ethnic minority groups in various forms, but particularly in the form of ethnic revival and/or assimilation. The results of these complex phenomena are manifested as changes in ethnic attachments (national re-identification and language behaviour (multi-lingualism, language transition and loss of the mother tongue). The stress of the political and economic crisis has stimulated significant changes in ethnographic, social and cultural characteristics of inter-ethnic dynamics such as the rate of national re-identification, language behaviour, migration activity and the spread of mixed marriages, among both those minorities with a long history of settlement in Russia and those that were annexed during the soviet period. Patterns of language behaviour and the spread of mixed marriages were taken as the main indicators of the directions of interethnic interaction described as assimilation, ethnic revival and cultural pluralism. The first stage of the research involved a statistical analysis of census data from 1959 to 1994 in order to analyse the changing demographic composition of the largest ethnic groups of the Russian Federation. Until 1989 interethnic interaction in soviet society was distinguished by the process of russification but the political and economic transformation has stimulated the process of ethnic revival, leading to an apparent fall in the size of the Russian population due to ethnic re-identification by members of other ethnic groups who had previously identified themselves as Russian. Cross-classification of nationalities by demographic, social and cultural indicators has shown that the most important determinants of the nature of interethnic interaction are cultural factors such as religion and language affiliation. The analysis of the dynamics of language shift through the study of bilingualism and the domains of language usage for different demographic groups revealed a strong correlation between recognition of Russian as a mother tongue among some non-Russian ethnic groups and the declining size of these groups. The main conclusion from this macro-analysis of census data was the hypothesis of the growing importance of social and political factors upon ethnic succession, that ethnic identity is no longer a stable characteristic but has become dynamic in nature. In order to verify this hypothesis Ms. Alexakhina conducted a survey in four regions showing different patterns of interethnic interaction: the Karelian Republic, Buryatiya, the Nenezkii Autonomous Region and Tatarstan. These represented the west, east, north and south of the Russian Federation. Samples for the survey were prepared on the basis of census lists so as to exclude mono-Russian families in favour of mixed and ethnic-minority families. The survey confirmed the significant growth in the importance of ethnic affiliation in the everyday lives of people in the Federation following the de-centralisation of the political and economic spheres. Language was shown to be a key symbol of the consciousness of national distinction, confirmed by the fact that the process of russification has been reversed by the active mastering of the languages of titular nationalities. The results also confirmed that individual ethnic identity has ceased to be a fixed personal characteristic of one's cultural and genetic belonging, and people's social adaptation to the current political, social and economic conditions is also demonstrated in changes in individual ethnic self-identification. In general terms, the dynamic nature of national identity means that ethnic identity is at present acquiring the special features of overall social identity, for which the frequent change of priorities is an inherent feature of a person's life cycle. These are mainly linked with a multi-ethnic environment and high individual social mobility. From her results Ms. Alexakhina concludes that the development of national languages and multi-lingualism, together with the preservation of Russian as a state language, seems to be the most promising path to peaceful coexistence and the development of the national cultures of different ethnic groups within the Russian Federation.

The Semantics and Typology of Yes/No Particles (A Cross-Linguistic Study)

Taking the three basic systems of Yes/No particles the group looked at the relative deep and surface structures, and asked what types of systems are present in the Georgian, Polish and Armenian languages. The choice of languages was of particular interest as the Caucasian and Indo-European languages usually have different question-answering systems, but Georgian (Caucasian) and Polish (Indo-European) in fact share the same system. The Armenian language is Indo-European, but the country is situated in the southern Caucasus, on Georgia's southern border, making it worth analysing Armenian in comparison with Georgian (from the point of view of language interference) and with Polish (as two relative languages). The group identified two different deep structures, tracing the occurrence of these in different languages, and showed that one is more natural in the majority of languages. They found no correspondence between relative languages and their question-answer systems and demonstrated that languages in the same typological class may show different systems, as with Georgian and the North Caucasian languages. It became clear that Georgian, Armenian and Polish all have an agree/disagree question-answering system defined by the same deep structure. From this they conclude that the lingual mentalities of Georgians, Armenians and Poles are more oriented to the communicative act. At the same time the Yes/No system, in which a positive particle stands for a positive answer and a negative particle for a negative answer, also functions in these languages, indicating that the second deep structure identified also functions alongside the first.

Transfection of drug-specific T-cell receptors into hybridoma cells: tools to monitor drug interaction with T-cell receptors and evaluate cross-reactivity to related compounds

In the context of drug hypersensitivity, our group has recently proposed a new model based on the structural features of drugs (pharmacological interaction with immune receptors; p-i concept) to explain their recognition by T cells. According to this concept, even chemically inert drugs can stimulate T cells because certain drugs interact in a direct way with T-cell receptors (TCR) and possibly major histocompatibility complex molecules without the need for metabolism and covalent binding to a carrier. In this study, we investigated whether mouse T-cell hybridomas transfected with drug-specific human TCR can be used as an alternative to drug-specific T-cell clones (TCC). Indeed, they behaved like TCC and, in accordance with the p-i concept, the TCR recognize their specific drugs in a direct, processing-independent, and dose-dependent way. The presence of antigen-presenting cells was a prerequisite for interleukin-2 production by the TCR-transfected cells. The analysis of cross-reactivity confirmed the fine specificity of the TCR and also showed that TCR transfectants might provide a tool to evaluate the potential of new drugs to cause hypersensitivity due to cross-reactivity. Recombining the alpha- and beta-chains of sulfanilamide- and quinolone-specific TCR abrogated drug reactivity, suggesting that both original alpha- and beta-chains were involved in drug binding. The TCR-transfected hybridoma system showed that the recognition of two important classes of drugs (sulfanilamides and quinolones) by TCR occurred according to the p-i concept and provides an interesting tool to study drug-TCR interactions and their biological consequences and to evaluate the cross-reactivity potential of new drugs of the same class.

Application and comparison of classification algorithms for recognition of Alzheimer's disease in electrical brain activity (EEG)

The early detection of subjects with probable Alzheimer's disease (AD) is crucial for effective appliance of treatment strategies. Here we explored the ability of a multitude of linear and non-linear classification algorithms to discriminate between the electroencephalograms (EEGs) of patients with varying degree of AD and their age-matched control subjects. Absolute and relative spectral power, distribution of spectral power, and measures of spatial synchronization were calculated from recordings of resting eyes-closed continuous EEGs of 45 healthy controls, 116 patients with mild AD and 81 patients with moderate AD, recruited in two different centers (Stockholm, New York). The applied classification algorithms were: principal component linear discriminant analysis (PC LDA), partial least squares LDA (PLS LDA), principal component logistic regression (PC LR), partial least squares logistic regression (PLS LR), bagging, random forest, support vector machines (SVM) and feed-forward neural network. Based on 10-fold cross-validation runs it could be demonstrated that even tough modern computer-intensive classification algorithms such as random forests, SVM and neural networks show a slight superiority, more classical classification algorithms performed nearly equally well. Using random forests classification a considerable sensitivity of up to 85% and a specificity of 78%, respectively for the test of even only mild AD patients has been reached, whereas for the comparison of moderate AD vs. controls, using SVM and neural networks, values of 89% and 88% for sensitivity and specificity were achieved. Such a remarkable performance proves the value of these classification algorithms for clinical diagnostics.

Family satisfaction in the intensive care unit: cross-cultural adaptation of a questionnaire

PURPOSE: Family needs and expectations are often unmet in the intensive care unit (ICU), leading to dissatisfaction. This study assesses cross-cultural adaptability of an instrument evaluating family satisfaction in the ICU. MATERIALS AND METHODS: A Canadian instrument on family satisfaction was adapted for German language and central European culture and then validated for feasibility, validity, internal consistency, reliability, and sensitivity. RESULTS: Content validity of a preliminary translated version was assessed by staff, patients, and next of kin. After adaptation, content and comprehensibility were considered good. The adapted translation was then distributed to 160 family members. The return rate was 71.8%, and 94.4% of questions in returned forms were clearly answered. In comparison with a Visual Analogue Scale, construct validity was good for overall satisfaction with care (Spearman rho = 0.60) and overall satisfaction with decision making (rho = 0.65). Cronbach alpha was .95 for satisfaction with care and .87 for decision-making. Only minor differences on repeated measurements were found for interrater and intrarater reliability. There was no floor or ceiling effect. CONCLUSIONS: A cross-cultural adaptation of a questionnaire on family satisfaction in the ICU can be feasible, valid, internally consistent, reliable, and sensitive.

Hip2Norm: an object-oriented cross-platform program for 3D analysis of hip joint morphology using 2D pelvic radiographs

We developed an object-oriented cross-platform program to perform three-dimensional (3D) analysis of hip joint morphology using two-dimensional (2D) anteroposterior (AP) pelvic radiographs. Landmarks extracted from 2D AP pelvic radiographs and optionally an additional lateral pelvic X-ray were combined with a cone beam projection model to reconstruct 3D hip joints. Since individual pelvic orientation can vary considerably, a method for standardizing pelvic orientation was implemented to determine the absolute tilt/rotation. The evaluation of anatomically morphologic differences was achieved by reconstructing the projected acetabular rim and the measured hip parameters as if obtained in a standardized neutral orientation. The program had been successfully used to interactively objectify acetabular version in hips with femoro-acetabular impingement or developmental dysplasia. Hip(2)Norm is written in object-oriented programming language C++ using cross-platform software Qt (TrollTech, Oslo, Norway) for graphical user interface (GUI) and is transportable to any platform.

CONVERSION OF DOMAIN TYPE ENFORCEMENT LANGUAGE TO THE JAVA SECURITY MANAGER

With today's prevalence of Internet-connected systems storing sensitive data and the omnipresent threat of technically skilled malicious users, computer security remains a critically important field. Because of today's multitude of vulnerable systems and security threats, it is vital that computer science students be taught techniques for programming secure systems, especially since many of them will work on systems with sensitive data after graduation. Teaching computer science students proper design, implementation, and maintenance of secure systems is a challenging task that calls for the use of novel pedagogical tools. This report describes the implementation of a compiler that converts mandatory access control specification Domain-Type Enforcement Language to the Java Security Manager, primarily for pedagogical purposes. The implementation of the Java Security Manager was explored in depth, and various techniques to work around its inherent limitations were explored and partially implemented, although some of these workarounds do not appear in the current version of the compiler because they would have compromised cross-platform compatibility. The current version of the compiler and implementation details of the Java Security Manager are discussed in depth.