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.

Spectrum Sensing Algorithms for Cognitive Radio Applications

Future wireless communications systems are expected to be extremely dynamic, smart and capable to interact with the surrounding radio environment. To implement such advanced devices, cognitive radio (CR) is a promising paradigm, focusing on strategies for acquiring information and learning. The first task of a cognitive systems is spectrum sensing, that has been mainly studied in the context of opportunistic spectrum access, in which cognitive nodes must implement signal detection techniques to identify unused bands for transmission. In the present work, we study different spectrum sensing algorithms, focusing on their statistical description and evaluation of the detection performance. Moving from traditional sensing approaches we consider the presence of practical impairments, and analyze algorithm design. Far from the ambition of cover the broad spectrum of spectrum sensing, we aim at providing contributions to the main classes of sensing techniques. In particular, in the context of energy detection we studied the practical design of the test, considering the case in which the noise power is estimated at the receiver. This analysis allows to deepen the phenomenon of the SNR wall, providing the conditions for its existence and showing that presence of the SNR wall is determined by the accuracy of the noise power estimation process. In the context of the eigenvalue based detectors, that can be adopted by multiple sensors systems, we studied the practical situation in presence of unbalances in the noise power at the receivers. Then, we shift the focus from single band detectors to wideband sensing, proposing a new approach based on information theoretic criteria. This technique is blind and, requiring no threshold setting, can be adopted even if the statistical distribution of the observed data in not known exactly. In the last part of the thesis we analyze some simple cooperative localization techniques based on weighted centroid strategies.

Neurodegenerative diseases: molecular mechanisms and new strategies for neuroprotection

The term neurodegeneration defines numerous conditions that modify neuron’s normal functions in the human brain where is possible to observe a progressive and consistent neuronal loss. The mechanisms involved in neurodegenerative chronic and acute diseases evolution are not completely understood yet, however they share common characteristics such as misfolded proteins, oxidative stress, inflammation, excitotoxicity, and neuronal loss. Many studies have shown the frequency to develop neurodegenerative chronic diseases several years after an acute brain injury. In addition, many patients show, after a traumatic brain injury, motor and cognitive manifestations that are close to which are observed in neurodegenerative chronic patients. For this reason it is evident how is fundamental the concept of neuroprotection as a way to modulate the neurodegenerative processes evolution. Neuroinflammation, oxidative stress and the apoptotic process may be functional targets where operate to this end. Taking into account these considerations, the aim of the present study is to identify potential common pathogenetic pathways in neurodegenerative diseases using an integrated approach of preclinical studies. The goal is to delineate therapeutic strategies for the prevention of neuroinflammation, neurodegeneration and dysfunctions associated to Parkinson’s disease (PD) and cerebral ischemia. In the present study we used a murine model of PD treated with an isothiocyanate, 6-MSITC, able to quench ROS formation, restore the antioxidant GSH system, slow down the apoptotic neuronal death and counteract motor dysfunction induced by 6-OHDA. In the second study we utilized a transgenic mouse model knockout for CD36 receptor to investigate the inflammation involvement in a long term study of MCAo, which shows a better outcome after the damage induced. In conclusion, results in this study allow underlying the connection among these pathologies, and the importance of a neuroprotective strategy able to restore neurons activity where current drugs therapies have shown palliative but not healing abilities.