Independent predictors and a prognostic model for surgical outcome in refractory frontal lobe epilepsy

Purpose: Refractory frontal lobe epilepsy (FLE) remains one of the most challenging surgically remediable epilepsy syndromes. Nevertheless, definition of independent predictors and predictive models of postsurgical seizure outcome remains poorly explored in FLE. Methods: We retrospectively analyzed data from 70 consecutive patients with refractory FLE submitted to surgical treatment at our center from July 1994 to December 2006. Univariate results were submitted to logistic regression models and Cox proportional hazards regression to identify isolated risk factors for poor surgical results and to construct predictive models for surgical outcome in FLE. Results: From 70 patients submitted to surgery, 45 patients (64%) had favorable outcome and 37 (47%) became seizure free. Isolated risk factors for poor surgical outcome are expressed in hazard ratio (H.R.) and were time of epilepsy (H.R.=4.2; 95% C.I.=.1.5-11.7; p=0.006), ictal EEG recruiting rhythm (H.R. = 2.9; 95% C.I. = 1.1-7.7; p=0.033); normal MRI (H.R. = 4.8; 95% C.I. = 1.4-16.6; p = 0.012), and MRI with lesion involving eloquent cortex (H.R. = 3.8; 95% C.I. = 1.2-12.0; p = 0.021). Based on these variables and using a logistic regression model we constructed a model that correctly predicted long-term surgical outcome in up to 80% of patients. Conclusion: Among independent risk factors for postsurgical seizure outcome, epilepsy duration is a potentially modifiable factor that could impact surgical outcome in FLE. Early diagnosis, presence of an MRI lesion not involving eloquent cortex, and ictal EEG without recruited rhythm independently predicted favorable outcome in this series. (C) 2011 Elsevier B.V. All rights reserved.

Clinical Efficacy of a New Automated Hemoencefalographic Neurofeedback Protocol

Among the ongoing attempts to enhance cognitive performance, an emergent and yet underrepresented venue is brought by hemoencefalographic neurofeedback (HEG). This paper presents three related advances in HEG neurofeedback for cognitive enhancement: a) a new HEG protocol for cognitive enhancement, as well as b) the results of independent measures of biological efficacy (EEG brain maps) extracted in three phases, during a one year follow up case study; c) the results of the first controlled clinical trial of HEG, designed to assess the efficacy of the technique for cognitive enhancement of an adult and neurologically intact population. The new protocol was developed in the environment of a software that organizes digital signal algorithms in a flowchart format. Brain maps were produced through 10 brain recordings. The clinical trial used a working memory test as its independent measure of achievement. The main conclusion of this study is that the technique appears to be clinically promising. Approaches to cognitive performance from a metabolic viewpoint should be explored further. However, it is particularly important to note that, to our knowledge, this is the world's first controlled clinical study on the matter and it is still early for an ultimate evaluation of the technique.

Treatment of snoring and sleep apnea syndrome with a removable mandibular advancement device in patients without TMD

INTRODUCTION: Among the sleep disorders reported by the American Academy of Sleep, the most common is obstructive sleep apnea-hypopnea syndrome (OSAHS), which is caused by difficulties in air passage and complete interruption of air flow in the airway. This syndrome is associated with increased morbidity and mortality in apneic individuals. OBJECTIVE: It was the objective of this paper to evaluate a removable mandibular advancement device as it provides a noninvasive, straightforward treatment readily accepted by patients. METHODS: In this study, 15 patients without temporomandibular disorders (TMD) and with excessive daytime sleepiness or snoring were evaluated. Data were collected by means of: Polysomnography before and after placement of an intraoral appliance, analysis of TMD signs and symptoms using a patient history questionnaire, muscle and TMJ palpation. RESULTS: After treatment, the statistical analysis (t-test, and the "before and after" test) showed a mean reduction of 77.6% (p=0.001) in the apnea-hypopnea index, an increase in lowest oxyhemoglobin saturation (p=0.05), decrease in desaturation (p=0.05), decrease in micro-awakenings or EEG arousals (p=0.05) and highly significant improvement in daytime sleepiness (p=0.005), measured by the Epworth Sleepiness Scale. No TMD appeared during the monitoring period. CONCLUSION: The oral device developed in this study was considered effective for mild to moderate OSAHS.

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.

Seizure prediction and control in epilepsy

The first part of my thesis presents an overview of the different approaches used in the past two decades in the attempt to forecast epileptic seizure on the basis of intracranial and scalp EEG. Past research could reveal some value of linear and nonlinear algorithms to detect EEG features changing over different phases of the epileptic cycle. However, their exact value for seizure prediction, in terms of sensitivity and specificity, is still discussed and has to be evaluated. In particular, the monitored EEG features may fluctuate with the vigilance state and lead to false alarms. Recently, such a dependency on vigilance states has been reported for some seizure prediction methods, suggesting a reduced reliability. An additional factor limiting application and validation of most seizure-prediction techniques is their computational load. For the first time, the reliability of permutation entropy [PE] was verified in seizure prediction on scalp EEG data, contemporarily controlling for its dependency on different vigilance states. PE was recently introduced as an extremely fast and robust complexity measure for chaotic time series and thus suitable for online application even in portable systems. The capability of PE to distinguish between preictal and interictal state has been demonstrated using Receiver Operating Characteristics (ROC) analysis. Correlation analysis was used to assess dependency of PE on vigilance states. Scalp EEG-Data from two right temporal epileptic lobe (RTLE) patients and from one patient with right frontal lobe epilepsy were analysed. The last patient was included only in the correlation analysis, since no datasets including seizures have been available for him. The ROC analysis showed a good separability of interictal and preictal phases for both RTLE patients, suggesting that PE could be sensitive to EEG modifications, not visible on visual inspection, that might occur well in advance respect to the EEG and clinical onset of seizures. However, the simultaneous assessment of the changes in vigilance showed that: a) all seizures occurred in association with the transition of vigilance states; b) PE was sensitive in detecting different vigilance states, independently of seizure occurrences. Due to the limitations of the datasets, these results cannot rule out the capability of PE to detect preictal states. However, the good separability between pre- and interictal phases might depend exclusively on the coincidence of epileptic seizure onset with a transition from a state of low vigilance to a state of increased vigilance. The finding of a dependency of PE on vigilance state is an original finding, not reported in literature, and suggesting the possibility to classify vigilance states by means of PE in an authomatic and objectic way. The second part of my thesis provides the description of a novel behavioral task based on motor imagery skills, firstly introduced (Bruzzo et al. 2007), in order to study mental simulation of biological and non-biological movement in paranoid schizophrenics (PS). Immediately after the presentation of a real movement, participants had to imagine or re-enact the very same movement. By key release and key press respectively, participants had to indicate when they started and ended the mental simulation or the re-enactment, making it feasible to measure the duration of the simulated or re-enacted movements. The proportional error between duration of the re-enacted/simulated movement and the template movement were compared between different conditions, as well as between PS and healthy subjects. Results revealed a double dissociation between the mechanisms of mental simulation involved in biological and non-biologial movement simulation. While for PS were found large errors for simulation of biological movements, while being more acurate than healthy subjects during simulation of non-biological movements. Healthy subjects showed the opposite relationship, making errors during simulation of non-biological movements, but being most accurate during simulation of non-biological movements. However, the good timing precision during re-enactment of the movements in all conditions and in both groups of participants suggests that perception, memory and attention, as well as motor control processes were not affected. Based upon a long history of literature reporting the existence of psychotic episodes in epileptic patients, a longitudinal study, using a slightly modified behavioral paradigm, was carried out with two RTLE patients, one patient with idiopathic generalized epilepsy and one patient with extratemporal lobe epilepsy. Results provide strong evidence for a possibility to predict upcoming seizures in RTLE patients behaviorally. In the last part of the thesis it has been validated a behavioural strategy based on neurobiofeedback training, to voluntarily control seizures and to reduce there frequency. Three epileptic patients were included in this study. The biofeedback was based on monitoring of slow cortical potentials (SCPs) extracted online from scalp EEG. Patients were trained to produce positive shifts of SCPs. After a training phase patients were monitored for 6 months in order to validate the ability of the learned strategy to reduce seizure frequency. Two of the three refractory epileptic patients recruited for this study showed improvements in self-management and reduction of ictal episodes, even six months after the last training session.

Influenza dell'Omeostasi Idrico-Elettrolitica sul Ciclo Veglia-Sonno

During the wake sleep (W-S) cycle in mammals, the alternation of the different states, wake, NREM sleep (NREMS) and REM sleep (REMS), is associated not only with electroencephalographic or behavioural changes, but also with modifications in the physiological regulations of the organism. The most evident change is the existence of a suspension of the somatic and autonomic thermoregulatory responses during REMS. Since thermoregulation is prevalently controlled by the Preoptic Area-Anterior Hypothalamus (PO-AH), its suspension during REM sleep has been taken as a sign of an impairment of the hypothalamic integrative activity that could explain the modifications in physiological regulation observed in this sleep stage. The recent finding from our laboratory that the secretion of the antidiuretic hormone arginine-vasopressin (AVP) in response to a central osmotic stimulation is quantitatively the same throughout the different stages of the W-S cycle, has shown that hypothalamic osmoregulation is not suspended during REMS. In order to clarify the extent of the hypothalamic involvement in the regulation of the W-S cycle, we have studied the effects of three days of water deprivation and of two days of recovery during which animals were allowed a free access to water, on the architecture of the W-S cycle. The condition of water deprivation represents a severe challenge involving neuroendocrine and autonomic hypothalamic regulations. In contradiction with thermoregulatory studies, in which it has been clearly demonstrated that a thermal challenge selectively reduces REMS occurrence, the results of this study show that REMS occurrence is mildly reduced only in the third day of water deprivation. The most striking effects produced by water deprivation appear to concern NREMS, which shows a selective and significant reduction in its slow EEG activity (delta-power) but not in its duration. The recovery period is mainly characterized by a disruption of the normal circadian rhythm of REMS occurrence and by a rebound of the delta power in NREMS. Thus, an autonomic challenge different from those related to thermoregulation and an endocrine challenge as the continuous secretion of AVP show to exert different effects on the stages of the wake-sleep cycle. Also, this study demonstrates that the impairment of the hypothalamic integrative activity thought to characterize the occurrence of REMS only involves thermoregulatory structures.

Heterogeneous multicore systems for signal processing

This thesis explores the capabilities of heterogeneous multi-core systems, based on multiple Graphics Processing Units (GPUs) in a standard desktop framework. Multi-GPU accelerated desk side computers are an appealing alternative to other high performance computing (HPC) systems: being composed of commodity hardware components fabricated in large quantities, their price-performance ratio is unparalleled in the world of high performance computing. Essentially bringing “supercomputing to the masses”, this opens up new possibilities for application fields where investing in HPC resources had been considered unfeasible before. One of these is the field of bioelectrical imaging, a class of medical imaging technologies that occupy a low-cost niche next to million-dollar systems like functional Magnetic Resonance Imaging (fMRI). In the scope of this work, several computational challenges encountered in bioelectrical imaging are tackled with this new kind of computing resource, striving to help these methods approach their true potential. Specifically, the following main contributions were made: Firstly, a novel dual-GPU implementation of parallel triangular matrix inversion (TMI) is presented, addressing an crucial kernel in computation of multi-mesh head models of encephalographic (EEG) source localization. This includes not only a highly efficient implementation of the routine itself achieving excellent speedups versus an optimized CPU implementation, but also a novel GPU-friendly compressed storage scheme for triangular matrices. Secondly, a scalable multi-GPU solver for non-hermitian linear systems was implemented. It is integrated into a simulation environment for electrical impedance tomography (EIT) that requires frequent solution of complex systems with millions of unknowns, a task that this solution can perform within seconds. In terms of computational throughput, it outperforms not only an highly optimized multi-CPU reference, but related GPU-based work as well. Finally, a GPU-accelerated graphical EEG real-time source localization software was implemented. Thanks to acceleration, it can meet real-time requirements in unpreceeded anatomical detail running more complex localization algorithms. Additionally, a novel implementation to extract anatomical priors from static Magnetic Resonance (MR) scansions has been included.

Cyclic alternating pattern in sleep and its relationship to creativity

Background/Objectives: Sleep has been shown to enhance creativity, but the reason for this enhancement is not entirely known. There are several different physiological states associated with sleep. In addition to rapid (REM) and non-rapid eye movement (NREM) sleep, NREM sleep can be broken down into Stages (1-4) that are characterized by the degree of EEG slow wave activity. In addition, during NREM sleep there are transient but cyclic alternating patterns (CAP) of EEG activity and these CAPs can also be divided into three subtypes (A1-A3) according to speed of the EEG waves. Differences in CAP ratios have been previously linked to cognitive performances. The purpose of this study was to learn the relationship CAP activity during sleep and creativity. Methods: The participants were 8 healthy young adults (4 women), who underwent 3 consecutive nights of polysomnographic recording and took the Abbreviated Torrance Test for Adults (ATTA) on the 2 and 3rd mornings after the recordings. Results: There were positive correlations between Stage 1 of NREM sleep and some measures of creativity such as fluency (R= .797; p=.029) and flexibility ( R=.43; p=.002), between Stage 4 of Non-REM sleep and originality (R= .779; p=.034) and a global measure of figural creativity (R= .758; p=.040). There was also a negative correlation between REM sleep and originality (R= -.827; p= .042) . During NREM sleep the CAP rate, which in young people is primarily the A1 subtype, also correlated with originality (R= .765; p =.038). Conclusions: NREM sleep is associated with low levels of cortical arousal and low cortical arousal may enhance the ability of people to access to the remote associations that are critical for creative innovations. In addition, A1 CAP activity reflects frontal activity and the frontal lobes are important for divergent thinking, also a critical aspect of creativity.

Predittori precoci di outcome neurologico nei neonati affetti da Encefalopatia Ipossico-Ischemica sottoposti a trattamento ipotermico. Studio combinato Elettroencefalogramma ad integrazione di ampiezza e Spettroscopia nel vicino infrarosso

Background: Brain cooling (BC) represents the elective treatment in asphyxiated newborns. Amplitude Integrated Electroencephalography (aEEG) and Near Infrared Spectroscopy (NIRS) monitoring may help to evaluate changes in cerebral electrical activity and cerebral hemodynamics during hypothermia. Objectives: To evaluate the prognostic value of aEEG time course and NIRS data in asphyxiated cooled infants. Methods: 12 term neonates admitted to our NICU with moderate-severe Hypoxic-Ischemic Encephalopathy (HIE) underwent selective BC. aEEG and NIRS monitoring were started as soon as possible and maintained during the whole hypothermic treatment. Follow-up was scheduled at regular intervals; adverse outcome was defined as death, cerebral palsy (CP) or global quotient < 88.7 at Griffiths’ Scale. Results: 2/12 infants died, 2 developed CP, 1 was normal at 6 months of age and then lost at follow-up and 7 showed a normal outcome at least at 1 year of age. The aEEG background pattern at 24 hours of life was abnormal in 10 newborns; only 4 of them developed an adverse outcome, whereas the 2 infants with a normal aEEG developed normally. In infants with adverse outcome NIRS showed a higher Tissue Oxygenation Index (TOI) than those with normal outcome (80.0±10.5% vs 66.9±7.0%, p=0.057; 79.7±9.4% vs 67.1±7.9%, p=0.034; 80.2±8.8% vs 71.6±5.9%, p=0.069 at 6, 12 and 24 hours of life, respectively). Conclusions: The aEEG background pattern at 24 hours of life loses its positive predictive value after BC implementation; TOI could be useful to predict early on infants that may benefit from other innovative therapies.

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.

Aspetti ipnici e vegetativi dell'inibizione del controllo nervoso centrale della termogenesi nel ratto

La possibilità di indurre stati ipotermici ed ipometabolici come il torpore o l’ibernazione in animali non ibernanti può avere dei risvolti utili nella pratica medica, in quanto permetterebbe di trarre vantaggio dagli effetti benefici dell’ipotermia senza gli effetti compensatori negativi causati dalla risposta omeostatica dell’organismo. Con questo lavoro vogliamo proporre un nuovo approccio, che coinvolge il blocco farmacologico dell’attività dei neuroni nel bulbo rostroventromediale (RVMM), un nucleo troncoencefalico che si è rivelato essere uno snodo chiave nella regolazione della termogenesi attraverso il controllo dell’attività del tessuto adiposo bruno, della vasomozione cutanea e del cuore. Nel nostro esperimento, sei iniezioni consecutive del agonista GABAA muscimolo nel RVMM, inducono uno stato reversibile di profonda ipotermia (21°C al Nadir) in ratti esposti ad una temperatura ambientale di 15°C. Lo stato ipotermico/ipomentabolico prodotto dall’inibizione dei neuroni del RVMM mostra forti similitudini col torpore naturale, anche per quanto concerne le modificazioni elettroencefalografiche osservate durante e dopo la procedura. Come negli ibernati naturali, nei ratti cui viene inibito il controllo della termogenesi si osserva uno spostamento verso le regioni lente delle spettro di tutte le frequenze dello spettro EEG durante l’ipotermia, ed un forte incremento dello spettro EEG dopo il ritorno alla normotermia, in particolare della banda Delta (0,5-4Hz) durante il sonno NREM. Per concludere, questi risultati dimostrano che l’inibizione farmacologica selettiva di un nucleo troncoencefalico chiave nel controllo della termogenesi è sufficiente per indurre uno stato di psuedo-torpore nel ratto, una specie che non presenta stati di torpore spontaneo. Un approccio di questo tipo può aprire nuove prospettive per l’utilizzo in ambito medico dell’ipotermia.

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.

An fmri study of brain functional connectivity in parkinson's disease patients

Argomento del presente lavoro è l’analisi di dati fMRI (functional Magnetic Resonance Imaging) nell’ambito di uno studio EEG-fMRI su pazienti affetti da malattia di Parkinson idiopatica. L’EEG-fMRI combina due diverse tecniche per lo studio in vivo dell’attività cerebrale: l'elettroencefalografia (EEG) e la risonanza magnetica funzionale. La prima registra l’attività elettrica dei neuroni corticali con ottima risoluzione temporale; la seconda misura indirettamente l’attività neuronale registrando gli effetti metabolici ad essa correlati, con buona risoluzione spaziale. L’acquisizione simultanea e la combinazione dei due tipi di dati permettono di sfruttare i vantaggi di ciascuna tecnica. Scopo dello studio è l’indagine della connettività funzionale cerebrale in condizioni di riposo in pazienti con malattia di Parkinson idiopatica ad uno stadio precoce. In particolare, l’interesse è focalizzato sulle variazioni della connettività con aree motorie primarie e supplementari in seguito alla somministrazione della terapia dopaminergica. Le quattro fasi principali dell’analisi dei dati sono la correzione del rumore fisiologico, il pre-processing usuale dei dati fMRI, l’analisi di connettività “seed-based “ e la combinazione dei dati relativi ad ogni paziente in un’analisi statistica di gruppo. Usando ’elettrocardiogramma misurato contestualmente all’EEG ed una stima dell’attività respiratoria, è stata effettuata la correzione del rumore fisiologico, ottenendo risultati consistenti con la letteratura. L’analisi di connettività fMRI ha mostrato un aumento significativo della connettività dopo la somministrazione della terapia: in particolare, si è riscontrato che le aree cerebrali maggiormente connesse alle aree motorie sono quelle coinvolte nel network sensorimotorio, nel network attentivo e nel default mode network. Questi risultati suggeriscono che la terapia dopaminergica, oltre ad avere un effetto positivo sulle performance motorie durante l’esecuzione del movimento, inizia ad agire anche in condizioni di riposo, migliorando le funzioni attentive ed esecutive, componenti integranti della fase preparatoria del movimento. Nel prossimo futuro questi risultati verranno combinati con quelli ottenuti dall’analisi dei dati EEG.

Stimulus-induced gamma activity in the electrocorticogram of freely moving telemetric implanted rats: the neuronal signature of novelty detection

During this thesis a new telemetric recording system has been developed allowing ECoG/EEG recordings in freely behaving rodents (Lapray et al., 2008; Lapray et al., in press). This unit has been shown to not generate any discomfort in the implanted animals and to allow recordings in a wide range of environments. In the second part of this work the developed technique has been used to investigate what cortical activity was related to the process of novelty detection in rats’ barrel cortex. We showed that the detection of a novel object is accompanied in the barrel cortex by a transient burst of activity in the γ frequency range (40-47 Hz) around 200 ms after the whiskers contact with the object (Lapray et al., accepted). This activity was associated to a decrease in the lower range of γ frequencies (30-37 Hz). This network activity may represent the optimal oscillatory pattern for the propagation and storage of new information in memory related structures. The frequency as well as the timing of appearance correspond well with other studies concerning novelty detection related burst of activity in other sensory systems (Barcelo et al., 2006; Haenschel et al., 2000; Ranganath & Rainer, 2003). Here, the burst of activity is well suited to induce plastic and long-lasting modifications in neuronal circuits (Harris et al., 2003). The debate is still open whether synchronised activity in the brain is a part of information processing or an epiphenomenon (Shadlen & Movshon, 1999; Singer, 1999). The present work provides further evidence that neuronal network activity in the γ frequency range plays an important role in the neocortical processing of sensory stimuli and in higher cognitive functions.

Brain-Computer Interfaces for augmented communication: Asynchronous and adaptive algorithms and evaluation with end users

This thesis aimed at addressing some of the issues that, at the state of the art, avoid the P300-based brain computer interface (BCI) systems to move from research laboratories to end users’ home. An innovative asynchronous classifier has been defined and validated. It relies on the introduction of a set of thresholds in the classifier, and such thresholds have been assessed considering the distributions of score values relating to target, non-target stimuli and epochs of voluntary no-control. With the asynchronous classifier, a P300-based BCI system can adapt its speed to the current state of the user and can automatically suspend the control when the user diverts his attention from the stimulation interface. Since EEG signals are non-stationary and show inherent variability, in order to make long-term use of BCI possible, it is important to track changes in ongoing EEG activity and to adapt BCI model parameters accordingly. To this aim, the asynchronous classifier has been subsequently improved by introducing a self-calibration algorithm for the continuous and unsupervised recalibration of the subjective control parameters. Finally an index for the online monitoring of the EEG quality has been defined and validated in order to detect potential problems and system failures. This thesis ends with the description of a translational work involving end users (people with amyotrophic lateral sclerosis-ALS). Focusing on the concepts of the user centered design approach, the phases relating to the design, the development and the validation of an innovative assistive device have been described. The proposed assistive technology (AT) has been specifically designed to meet the needs of people with ALS during the different phases of the disease (i.e. the degree of motor abilities impairment). Indeed, the AT can be accessed with several input devices either conventional (mouse, touchscreen) or alterative (switches, headtracker) up to a P300-based BCI.