Models for the study of neuronal activity during cognitive tasks

Assessment of brain connectivity among different brain areas during cognitive or motor tasks is a crucial problem in neuroscience today. Aim of this research study is to use neural mass models to assess the effect of various connectivity patterns in cortical EEG power spectral density (PSD), and investigate the possibility to derive connectivity circuits from EEG data. To this end, two different models have been built. In the first model an individual region of interest (ROI) has been built as the parallel arrangement of three populations, each one exhibiting a unimodal spectrum, at low, medium or high frequency. Connectivity among ROIs includes three parameters, which specify the strength of connection in the different frequency bands. Subsequent studies demonstrated that a single population can exhibit many different simultaneous rhythms, provided that some of these come from external sources (for instance, from remote regions). For this reason in the second model an individual ROI is simulated only with a single population. Both models have been validated by comparing the simulated power spectral density with that computed in some cortical regions during cognitive and motor tasks. Another research study is focused on multisensory integration of tactile and visual stimuli in the representation of the near space around the body (peripersonal space). This work describes an original neural network to simulate representation of the peripersonal space around the hands, in basal conditions and after training with a tool used to reach the far space. The model is composed of three areas for each hand, two unimodal areas (visual and tactile) connected to a third bimodal area (visual-tactile), which is activated only when a stimulus falls within the peripersonal space. Results show that the peripersonal space, which includes just a small visual space around the hand in normal conditions, becomes elongated in the direction of the tool after training, thanks to a reinforcement of synapses.

Effetto crowding e dislessia evolutiva: un confronto inter e intra-linguistico

Crowding is defined as the negative effect obtained by adding visual distractors around a central target which has to be identified. Some studies have suggested the presence of a marked crowding effect in developmental dyslexia (e.g. Atkinson, 1991; Spinelli et al., 2002). Inspired by Spinelli’s (2002) experimental design, we explored the hypothesis that the crowding effect may affect dyslexics’ response times (RTs) and accuracy in identification tasks dealing with words, pseudowords, illegal non-words and symbolstrings. Moreover, our study aimed to clarify the relationship between the crowding phenomenon and the word-reading process, in an inter-language comparison perspective. For this purpose we studied twenty-two French dyslexics and twenty-two Italian dyslexics (total forty-four dyslexics), compared to forty-four subjects matched for reading level (22 French and 22 Italians) and forty-four chronological age-matched subjects (22 French and 22 Italians). Children were all tested on reading and cognitive abilities. Results showed no differences between French and Italian participants suggesting that performances were homogenous. Dyslexic children were all significantly impaired in words and pseudowords reading compared to their normal reading controls. Regarding the identification task with which we assessed crowding effect, both accuracy and RTs showed a lexicality effect which meant that the recognition of words was more accurate and faster in words than pseudowords, non-words and symbolstrings. Moreover, compared to normal readers, dyslexics’ RTs and accuracy were impaired only for verbal materials but not for non-verbal material; these results are in line with the phonological hypothesis (Griffiths & Snowling, 2002; Snowling, 2000; 2006) . RTs revealed a general crowding effect (RTs in the crowding condition were slower than those recorded in the isolated condition) affecting all the subjects’ performances. This effect, however, emerged to be not specific for dyslexics. Data didn’t reveal a significant effect of language, allowing the generalization of the obtained results. We also analyzed the performance of two subgroups of dyslexics, categorized according to their reading abilities. The two subgroups produced different results regarding the crowding effect and type of material, suggesting that it is meaningful to take into account also the heterogeneity of the dyslexia disorder. Finally, we also analyzed the relationship of the identification task with both reading and cognitive abilities. In conclusion, this study points out the importance of comparing visual tasks performances of dyslexic participants with those of their reading level-matched controls. This approach may improve our comprehension of the potential causal link between crowding and reading (Goswami, 2003).

Language and Embodiment: sensory-motor and linguistic-social experience. Evidence on sentence comprehension

In this work I address the study of language comprehension in an “embodied” framework. Firstly I show behavioral evidence supporting the idea that language modulates the motor system in a specific way, both at a proximal level (sensibility to the effectors) and at the distal level (sensibility to the goal of the action in which the single motor acts are inserted). I will present two studies in which the method is basically the same: we manipulated the linguistic stimuli (the kind of sentence: hand action vs. foot action vs. mouth action) and the effector by which participants had to respond (hand vs. foot vs. mouth; dominant hand vs. non-dominant hand). Response times analyses showed a specific modulation depending on the kind of sentence: participants were facilitated in the task execution (sentence sensibility judgment) when the effector they had to use to respond was the same to which the sentences referred. Namely, during language comprehension a pre-activation of the motor system seems to take place. This activation is analogous (even if less intense) to the one detectable when we practically execute the action described by the sentence. Beyond this effector specific modulation, we also found an effect of the goal suggested by the sentence. That is, the hand effector was pre-activated not only by hand-action-related sentences, but also by sentences describing mouth actions, consistently with the fact that to execute an action on an object with the mouth we firstly have to bring it to the mouth with the hand. After reviewing the evidence on simulation specificity directly referring to the body (for instance, the kind of the effector activated by the language), I focus on the specific properties of the object to which the words refer, particularly on the weight. In this case the hypothesis to test was if both lifting movement perception and lifting movement execution are modulated by language comprehension. We used behavioral and kinematics methods, and we manipulated the linguistic stimuli (the kind of sentence: the lifting of heavy objects vs. the lifting of light objects). To study the movement perception we measured the correlations between the weight of the objects lifted by an actor (heavy objects vs. light objects) and the esteems provided by the participants. To study the movement execution we measured kinematics parameters variance (velocity, acceleration, time to the first peak of velocity) during the actual lifting of objects (heavy objects vs. light objects). Both kinds of measures revealed that language had a specific effect on the motor system, both at a perceptive and at a motoric level. Finally, I address the issue of the abstract words. Different studies in the “embodied” framework tried to explain the meaning of abstract words The limit of these works is that they account only for subsets of phenomena, so results are difficult to generalize. We tried to circumvent this problem by contrasting transitive verbs (abstract and concrete) and nouns (abstract and concrete) in different combinations. The behavioral study was conducted both with German and Italian participants, as the two languages are syntactically different. We found that response times were faster for both the compatible pairs (concrete verb + concrete noun; abstract verb + abstract noun) than for the mixed ones. Interestingly, for the mixed combinations analyses showed a modulation due to the specific language (German vs. Italian): when the concrete word precedes the abstract one responses were faster, regardless of the word grammatical class. Results are discussed in the framework of current views on abstract words. They highlight the important role of developmental and social aspects of language use, and confirm theories assigning a crucial role to both sensorimotor and linguistic experience for abstract words.

Models for the Study of Cortical Activity During Cognitive ans Motor Tasks

This thesis is mainly devoted to show how EEG data and related phenomena can be reproduced and analyzed using mathematical models of neural masses (NMM). The aim is to describe some of these phenomena, to show in which ways the design of the models architecture is influenced by such phenomena, point out the difficulties of tuning the dozens of parameters of the models in order to reproduce the activity recorded with EEG systems during different kinds of experiments, and suggest some strategies to cope with these problems. In particular the chapters are organized as follows: chapter I gives a brief overview of the aims and issues addressed in the thesis; in chapter II the main characteristics of the cortical column, of the EEG signal and of the neural mass models will be presented, in order to show the relationships that hold between these entities; chapter III describes a study in which a NMM from the literature has been used to assess brain connectivity changes in tetraplegic patients; in chapter IV a modified version of the NMM is presented, which has been developed to overcomes some of the previous version’s intrinsic limitations; chapter V describes a study in which the new NMM has been used to reproduce the electrical activity evoked in the cortex by the transcranial magnetic stimulation (TMS); chapter VI presents some preliminary results obtained in the simulation of the neural rhythms associated with memory recall; finally, some general conclusions are drawn in chapter VII.

Semantic under-determinacy, Content and Context

The aim of the thesis is to investigate the topic of semantic under-determinacy, i.e. the failure of the semantic content of certain expressions to determine a truth-evaluable utterance content. In the first part of the thesis, I engage with the problem of setting apart semantic under-determinacy as opposed to other phenomena such as ambiguity, vagueness, indexicality. As I will argue, the feature that distinguishes semantic under-determinacy from these phenomena is its being explainable solely in terms of under-articulation. In the second part of the thesis, I discuss the topic of how communication is possible, despite the semantic under-determinacy of language. I discuss a number of answers that have been offered: (i) the Radical Contextualist explanation which emphasises the role of pragmatic processes in utterance comprehension; (ii) the Indexicalist explanation in terms of hidden syntactic positions; (iii) the Relativist account, which regards sentences as true or false relative to extra coordinates in the circumstances of evaluation (besides possible worlds). In the final chapter, I propose an account of the comprehension of utterances of semantically under-determined sentences in terms of conceptual constraints, i.e. ways of organising information which regulate thought and discourse on certain matters. Conceptual constraints help the hearer to work out the truth-conditions of an utterance of a semantically under-determined sentence. Their role is clearly semantic, in that they contribute to “what is said” (rather than to “what is implied”); however, they do not respond to any syntactic constraint. The view I propose therefore differs, on the one hand, from Radical Contextualism, because it stresses the role of semantic-governed processes as opposed to pragmatics-governed processes; on the other hand, it differs from Indexicalism in its not endorsing any commitment as to hidden syntactic positions; and it differs from Relativism in that it maintains a monadic notion if truth.

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.

Cognition in context: Evidence on affordances and verbal language

This thesis investigated affordances and verbal language to demonstrate the flexibility of embodied simulation processes. Starting from the assumption that both object/action understanding and language comprehension are tied to the context in which they take place, six studies clarified the factors that modulate simulation. The studies in chapter 4 and 5 investigated affordance activation in complex scenes, revealing the strong influence of the visual context, which included either objects and actions, on compatibility effects. The study in chapter 6 compared the simulation triggered by visual objects and objects names, showing differences depending on the kind of materials processed. The study in chapter 7 tested the predictions of the WAT theory, confirming that the different contexts in which words are acquired lead to the difference typically observed in the literature between concrete and abstract words. The study in chapter 8 on the grounding of abstract concepts tested the mapping of temporal contents on the spatial frame of reference of the mental timeline, showing that metaphoric congruency effects are not automatic, but flexibly mediated by the context determined by the goals of different tasks. The study in chapter 9 investigated the role of iconicity in verbal language, showing sound-to-shape correspondences when every-day object figures, result that validated the reality of sound-symbolism in ecological contexts. On the whole, this evidence favors embodied views of cognition, and supports the hypothesis of a high flexibility of simulation processes. The reported conceptual effects confirm that the context plays a crucial role in affordances emergence, metaphoric mappings activation and language grounding. In conclusion, this thesis highlights that in an embodied perspective cognition is necessarily situated and anchored to a specific context, as it is sustained by the existence of a specific body immersed in a specific environment.

Big Code Applications and Approaches

The availability of a huge amount of source code from code archives and open-source projects opens up the possibility to merge machine learning, programming languages, and software engineering research fields. This area is often referred to as Big Code where programming languages are treated instead of natural languages while different features and patterns of code can be exploited to perform many useful tasks and build supportive tools. Among all the possible applications which can be developed within the area of Big Code, the work presented in this research thesis mainly focuses on two particular tasks: the Programming Language Identification (PLI) and the Software Defect Prediction (SDP) for source codes. Programming language identification is commonly needed in program comprehension and it is usually performed directly by developers. However, when it comes at big scales, such as in widely used archives (GitHub, Software Heritage), automation of this task is desirable. To accomplish this aim, the problem is analyzed from different points of view (text and image-based learning approaches) and different models are created paying particular attention to their scalability. Software defect prediction is a fundamental step in software development for improving quality and assuring the reliability of software products. In the past, defects were searched by manual inspection or using automatic static and dynamic analyzers. Now, the automation of this task can be tackled using learning approaches that can speed up and improve related procedures. Here, two models have been built and analyzed to detect some of the commonest bugs and errors at different code granularity levels (file and method levels). Exploited data and models’ architectures are analyzed and described in detail. Quantitative and qualitative results are reported for both PLI and SDP tasks while differences and similarities concerning other related works are discussed.

Movement analysis on the field in young football players: biomechanical patterns of performance and injury prevention

The integration of quantitative data from movement analysis technologies is reshaping the analysis of athletes’ performances and injury mitigation, e.g., anterior cruciate ligament (ACL) rupture. Most of the movement assessments are performed in laboratory environments. Recent progress provides the chance to shift the paradigm to a more ecological approach with sport-specific elements and a closer examination of “real” movement patterns associated with performance and (ACL) injury risk. The present PhD thesis aimed at investigating the on-field motion patterns related to performance and injury prevention in young football players. The objectives of the thesis were: (I) in-lab measures of high-dynamics movements were used to validate wearable inertial sensors technology; (II) in-laboratory and on-field agility movement tasks were compared to inspect the effect of football-specific environment; (III) on-field analysis was conducted to challenge wearable sensors technology in the assessment of dangerous movement patterns towards the ACL rupture; (IV) an overview of technologies that could shape present and future assessment of ACL injury risk in daily practice was presented. The validity of wearables in the assessment of high-dynamics movements was confirmed. Relevant differences emerged between the movements performed in a laboratory setting and on the football pitch, supporting the inclusion of an ecological dynamics approach in preventive protocols. The on-field analysis of football-specific movement tasks demonstrated good reliability of wearable sensors and the presence of residual dangerous patterns in the injured players. A tool to inspect at-risk movement patterns on the field through objective measurements was presented. It discussed how potential alternatives to wearable inertial sensors embrace artificial intelligence and closer collaboration between clinical and technical expertise. The present thesis was meant to contribute to setting the basis for data-driven prevention protocols. A deeper comprehension of injury-related principles and counteractions will contribute to preserving athletes’ careers and health over time.