ANALISI DEGLI STATI METASTABILI DEL CERVELLO

Il cervello umano è un sistema dinamico molto complesso che presenta peculiari caratteristiche di non stazionarietà: in questo lavoro di analisi dei segnali elettrofisiologici, l’attenzione è stata focalizzata proprio su questo aspetto. In particolare sono state valutate le tecniche di segmentazione dei segnali EEG, sia di tipo parametrico che di tipo non parametrico. Queste tecniche permettono la rilevazione dei processi di transizione rapida (RTP), ossia dei punti di transizione rapida tra i segmenti con caratteristiche di quasi-stazionarietà presenti negli EEG. Siamo andati ad analizzare un recente algoritmo di segmentazione, valutandone pregi e difetti. In seguito è stato sviluppato un nostro algoritmo di segmentazione e ricerca degli RTP (FinderRTP), le cui caratteristiche sono state valutate facendo ricorso a segnali EEG artificiali da noi appositamente generati. Dopo aver validato l’algoritmo, abbiamo applicato il finderRTP a dei segnali EEG sperimentali. Infine abbiamo indagato le caratteristiche statistiche degli RTP trovati e dei tempi di attesa tra gli RTP

A proposal for a world database on transport infrastructure regulation

The paper presents the structure and the concepts at the basis of a database on world transport infrastructure regulation, to be launched. The database will be built promoting a “soft” survey on the world regulatory practices, to be filled by scholars and experts on a voluntary basis. The goal of the database is to stimulate research on best practices and interaction among regulators, regulated and scholars. The work is still under construction. The database structure is ready and the survey is already launched, but incomplete. This paper is a preliminary document which provides a detailed description of the aims and of the database structure, in order to circulate the project and collect suggestions from the academic community. The structure of the paper is as follows. After a presentation of the aims of the work, section 2 provides a literature review on existing databases. Section 3 details the project, describing the characteristics of the survey, the strengths and weaknesses of the approach, the network to be activated. Section 4 is giving more details on the actual structure of the database and of the corresponding survey. Section 5 gives notice of the first results obtained with a preliminary survey and a preliminary review of literature on some selected countries. Conclusions will outline the next steps of the research.transport; regulation; investment; infrastructure; database; survey

Wake-like activities and electrical silences in the human sleeping brain: functional roles and spatio-temporal dynamics in the thalamo-cortical network

As pointed out by several papers, the less than one hertz oscillations or Sleep Slow Oscillations (SSOs) are the electrophysiological stigmata of the mammalian sleep. This cellular behavior, mainly involving thalamus and cortex, consisted of hyperpolarized phases (lasting 500 msec, down states) followed by depolarized ones (lasting 500 msec, up states). The electrical silence during down states, on the one hand, prevents any synaptic and network activity and on the other hand, creates the ionic conditions for a rebound of neural discharge (huge synaptic and network activity during up state). The presence of down states clearly marks the phenomenon of cortical bistability, which in turn reflects a deep hyperpolarization sustained by the opening of different K+-channels. According to the Integrated Information Theory of Giulio Tononi, down states prevent the emergence of largescale neural integrations and thus induce the break down of functional connectivity. This allows a functional segregation of independent cortical modules, which represents the condicio sine qua non for sleep unconsciousness. Other functional roles endowed in the SSO are memory consolidation and synaptic downscaling. The aim of this thesis is to investigate, via EEG, in human spontaneous and evoked SSOs: (i) the relationships between wake-like activities and electrical silence; (ii) the role of the thalamus; (iii) the quenching of sensory processing and thus of consciousness. Regarding point (i) we have found a positive bump preceding the down state characterized by an increase of high frequency activities. The presence of this high frequency activity before down state suggests a cortical ignition mechanism for the spontaneous SSO. As far as point (ii) is concerned, we have investigated how the thalamus influences the cortical expression of the SSOs. To this aim, we have studied SSO features in a case of Fatal Familial Insomnia (FFI) with a selective thalamic neurodegeneration of nuclei mainly involved in spindle generation. In the FFI patient, we have found a reduction of SSO event rate, some morphological alterations of SSO structure, and a significant reduction in grouping high frequency activity during up state. As for point (iii), we studied K-Complexes (KCs), namely SSOs evoked by sensory stimulations. The main results of this study are: a positive wave (P200) precedes the down state (N550); the topology of P200 latency depends on the sensory modality of stimulation (acoustic, tactile and visual) with earliest waves in the related primary sensory areas; the P200 travels as a cortical excitation inducing N550 and P900 (up state) in associative fronto-central areas; when KCs are not evoked the P200-like excitations have lower amplitude compared to evoked KC P200; the down state latency topology is affected by the proneness to bistability, i.e. the amount of K+-channel that favor a synchronized falling into down state. As a whole the results of the thesis indicate that Slow Wave Sleep (SWS) is not a mere quiescent state but rather an active state in which changes of neural dynamics allow a well orchestrated interplay of unconscious behavior and memory consolidation. The final consequence is the maintenance of homeostasis. The SSO is the cellular phenomenon capable to coalesce wake-like activities and electrical silences, synthesizing at microscopic level the macroscopic complexity of SWS. This thesis allowed exploring thalamo-cortical dynamics by studying spontaneous and evoked SSOs. In synthesis the human-environment interaction (including visceral stimuli) during sleep overlaps that of wakefulness, since thalamus and cortical areas devoted to the first step of sensory processing are identical. The difference between wake and sleep is only sustained by the down state. In conclusion the study of SSO clarifies many issues linked to sleep and in particular to the real efficacy of a good sleep. This opens the door to the application of SSO study in different preclinical or clinical conditions

Physiological Cybernetics: An Old-Novel Approach for Students in Biomedical Systems

Wiener in a seminal book (Wiener, 1948) associated the ancient Greek word ‘κυβερνητικος’ to the control of physiological systems. “Thus, as far back as four years ago, the group of scientists about Dr. Rosenblueth and myself had already become aware of the essential unity of the set of problems centering about communication, control and statistical mechanics, whether in the machine or in the living tissue. [...] We have decided to call the entire field [...] by the name Cybernetics, which we form from the Greek κυβερνητης or steersman. In choosing this term, we wish to recognize that the first significant paper on feed-back mechanisms is an article on governors, which was published by Clerk Maxwell in 1868 and that governor is derived from a Latin corruption of κυβερνητης. We also wish to refer to the fact that the steering engines of a ship are indeed one of the earliest and best developed forms of feed-back mechanisms.” The increasing knowledge in each sector of science led to a huge diversification of scientific research, especially in a borderline sector like cybernetics applied to physiological systems. A first problem to solve was the following: let’s suppose that two groups, one with a control engineering experience and the other one with a medical background (e.g., physicians), decide to cooperate, because they strongly believe that a joined research could be useful for developing mathematical and statistical models. Usually physicians do not have enough time to study and apply advanced modelling. Wiener approached the communication between scientists belonging to different disciplines: “If a physiologist, who knows no mathematics, works together with a mathematician, who knows no physiology, the one will be unable to state his problem in terms that the other can manipulate, and the second will be unable to put the answers in any form that the first can understand. [...] The mathematician need not have the skill to conduct a physiological experiment, but he must have the skill to understand one, to criticize one, and to suggest one. The physiologist need not be able to prove a certain mathematical theorem, but he must be able to grasp its physiological significance and to tell the mathematician for what he should look.” A correct interaction in terms of a clear communication and reciprocal comprehension of the objectives of the research activity between groups with different competences is a crucial aspect in any interdisciplinary research. In 2003 at the University of Pisa it was decided to introduce a new course for undergraduate students in biomedical engineering, based on the Wiener ‘utopia’, in order to teach a novel discipline useful for helping biomedical students to communicate and cooperate effectively with physicians. We named this new course as Physiological Cybernetics, remembering the old Wiener definition. The organization of this course was a difficult task, and it required to gain experience in order to integrate so different disciplines and to produce a common language between students in biomedical engineer and physicians. At a first glance this attempt seemed to be too ambitious, because the different approaches of biomedical engineers with respect to physicians seemed incompatible and even the languages of the two groups were so different to remember the Babel tower… A great deal of effort and attention was required to produce appealing and stimulating lectures, but after many years we can affirm that this challenge is successful, especially for the enthusiastic answers of the students: their number was increasing year after year (about seventy students per year are now attending the course). A strict and trusted cooperation between different groups of physicians is growing up and several groups of physicians belonging to different medical fields are going to join us for new interactions. The aim of this chapter is to describe how the approach to physiological cybernetics has led to integrate academic lessons with research activities. To be more specific, the basic idea of Physiological Cybernetics was to search for models able to emulate physiological systems based on the feedback theory and/or the system theory. In fact, recently, the widespread use of friendly software packages for modelling, along with the development of powerful identification and control techniques has led to a renewed interest in control (Khoo, 2011; Hoppensteadt & Peskin, 2002; Cobelli & Carson, 2008) and identification (Westwick & Kearney, 2003) of physiological systems. Unfortunately physiological systems are intrinsically time variant and highly non linear. Moreover, an effective balance of the model complexity is a difficult task: low order models are usually too simple to be useful, on the other hand high order models are too complex for simulation purposes and they have too many unknown parameters to be identified. Each model selected for investigation was studied by a group of biomedical students supervised by physicians. Each model required several iterations and reformulations, due to the continuous adjustment of the research objectives, changing their final horizon, because of the gap between experimental data and theoretical models, so that the answers to the doubts and questions were continuously moving with the obtained partial results. A final goal of the research was to apply a mathematical framework for helping medical diagnostic techniques and for testing new therapeutic protocols. The procedure of model extraction followed two main pathways: the first one (pathway A) led to a formulation of a mathematical model usually based on differential equations and on an as deep as possible insight into physiological mechanisms (Marmarelis, 2004; Ottesen et al., 2004; Edelstein-Keshet, 2005; Jones et al., 2009) via a physical description of the system. The second one (pathway B) was founded on a model description based on a black-box and data-driven identification (Westwick & Kearney, 2003; Cobelli & Carson, 2008), usually leaving to stochastic models with a parametric or non-parametric structure (Ljung, 1987), depending on the a-priori knowledge of constitutive laws governing the observed system. In this paper we will describe two examples of research activity based on the Physiological Cybernetics, both of them addressed to produce a biomedical framework for predicting the effects of therapeutic actions, but following the two different pathways. The first example follows a statistical non parametric approach, the second one a mathematical model based on differential equations