Cooperative particle filtering for tracking ERP subcomponents from multichannel EEG

In this study, we propose a novel method to investigate P300 variability over different trials. The method incorporates spatial correlation between EEG channels to form a cooperative coupled particle filtering method that tracks the P300 subcomponents, P3a and P3b, over trials. Using state space systems, the amplitude, latency, and width of each subcomponent are modeled as the main underlying parameters. With four electrodes, two coupled Rao-Blackwellised particle filter pairs are used to recursively estimate the system state over trials. A number of physiological constraints are also imposed to avoid generating invalid particles in the estimation process. Motivated by the bilateral symmetry of ERPs over the brain, the channels further share their estimates with their neighbors and combine the received information to obtain a more accurate and robust solution. The proposed algorithm is capable of estimating the P300 subcomponents in single trials and outperforms its non-cooperative counterpart

Estimation of single trial ERPs and EEG phase synchronization with application to mental fatigue

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Advances in Blind Source Separation

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Predictability of epileptic seizures by fusion of scalp EEG and fMRI

The systems for prediction of epileptic seizure investigated in recent years mainly rely on the traditional nonlinear analysis of the brain signals from intracranial electroencephalograph (EEG) recordings. The overall objective of this work focuses on investigation of the predictability of seizure from the scalp signals by applying effective blind source separation (BSS) techniques to scalp EEGs, in which the epileptic seizures are considered as independent components of the scalp EEGs. The ultimate goal of the work is to pave the way for epileptic seizure prediction from the scalp EEG. The main contributions of this research are summarized as follows. Firstly, a novel constrained topographic independent component analysis (CTICA) algorithm is developed for the improved separation of the epileptic seizure signals. The related CTICA model is more suitable for brain signal separation due to the relaxation of the independence assumption, as the source signals geometrically close to each other are assumed to have some dependencies. By incorporating the spatial and frequency information of seizure signals as the constraint, CTICA achieves a better performance in separating the seizure signals in comparison with other conventional ICA methods. Secondly, the predictability of seizure is investigated. The traditional method for quantification of the nonlinear dynamics of time series is employed to quantify the level of chaos of the estimated sources. The simultaneously recorded intracranial and scalp EEGs are used for the comparison of the results. The experiment results demonstrate that the separated seizure sources have a similar transition trend as those achieved from the intracranial EEGs. Thirdly, simultaneously recorded EEG and functional Magnetic Resonance Imaging (fMRI) is studied in order to validate the activated area of the brain related to the seizure sources. An effective method to remove the fMRI scanner artifacts from the scalp EEG is established by applying the blind source extraction (BSE) algorithm. The results show that the effect of fMRI scanner artifacts has been reduced in scalp EEG recordings. Finally, a data driven model, spatial ICA (SICA) subject to EEG as the temporal constraint is proposed in order to detect the Blood Oxygen-Level Dependence (BOLD) from the seizure fMRI. In contrast to the popular model driven method General Linear Model (GLM), SICA does not rely on any predefined hemodynamic response function. It is based on the fact that brain areas executing different tasks are spatially independent. Therefore SICA works perfectly for non-event-related fMRI analysis such as seizure fMRI. By incorporating the temporal information existing within the EEG as the constraint, the superiority of the proposed constrained SICA is validated in terms of better algorithm convergence and a higher correlation between the time courses of the component and the seizure EEG signals as compared to SICA

Auditory and visual event-related potential alterations in fragile X syndrome

Le syndrome du X fragile (SXF) est la première cause héréditaire de déficience intellectuelle et également la première cause monogénique d’autisme. Le SXF est causé par l'expansion de la répétition du nucléotide CGG sur le gène FMR1, ce qui empêche l’expression de la protéine FMRP. L’absence du FMRP mène à une altération du développement structurel et fonctionnel de la synapse, ce qui empêche la maturation des synapses induite par l’activité et l’élagage synaptique, qui sont essentiels pour le développement cérébral et cognitif. Nous avons investigué les potentiels reliés aux événements (PRE) évoqués par des stimulations fondamentales auditives et visuelles dans douze adolescents et jeunes adultes (10-22) atteints du SXF, ainsi que des participants contrôles appariés en âge chronologique et développemental. Les résultats indiquent un profil des PRE altéré, notamment l’augmentation de l’amplitude de N1 auditive, par rapport aux deux groupes contrôle, ainsi que l’augmentation des amplitudes de P2 et N2 auditifs et de la latence de N2 auditif. Chez les patients SXF, le traitement sensoriel semble être davantage perturbé qu’immature. En outre, la modalité auditive semble être plus perturbée que la modalité visuelle. En combinaison avec des résultats anatomique du cerveau, des mécanismes biochimiques et du comportement, nos résultats suggèrent une hyperexcitabilité du système nerveux dans le SXF.We investigated early auditory and visual information processing in Fragile X Syndrome (FXS), the most common form of X-linked Intellectual Disability (ID) and the only known monogenetic cause of autism. FXS is caused by a trinucleotide repeat expansion in the FMR1 (‘Fragile X mental retardation 1’) gene, which prevents expression of the ‘fragile X mental retardation protein’ (FMRP). FMRP absence leads to altered structural and functional development of the synapse, while also preventing activity-based synapse maturation and synaptic pruning, which are essential for cerebral and cognitive development. We review the contribution of electrophysiological signal studies for the understanding of information processing in FXS and compare event-related potential (ERP) findings to those concerning other clinical populations that share symptoms with FXS. In our research project, we investigated ERPs evoked by basic auditory and visual stimulation in twelve adolescents and young adults (10-22) with FXS, as well as healthy chronological- and developmental- age matched controls. We found an altered ERP profile in FXS, including increased auditory N1 amplitude, relative to both control groups, as well as increased auditory P2 and N2 amplitudes and increased auditory N2 latencies. Rather than being immature, sensory processing appears to be specifically disrupted in FXS. Furthermore, the auditory modality seems to be more affected than the visual modality. In combination with brain anatomical, biochemical and behavioural findings, our results suggest a hyperexcitable nervous system in FXS

Reach to grasp movement: a simultaneous recording approach

In our everyday life, we interact continually with objects. We reach for them, we grasp them, we manipulate them. All these actions are apparently very simple. Yet, this is not so. The mechanisms that underlie them are complex, and require multiple visuomotor transformations entailing the capacity to transform the visual features of the object in the appropriate hand configuration, and the capacity to execute and control hand and finger movements. In neural terms, grasping behavior can be dissociated into separate reach and grip components. According to this view, computations regarding the grasp component occurs within a lateral parietofrontal circuit involving the anterior intraparietal area (AIP) and both the dorsal (PMd) and the ventral (PMv) premotor areas. The general agreement is that the processes occurring in AIP constitute the initial step of the transformation leading from representation of objects to movement aimed at interacting with such objects. Evidence supporting this view comes from neurophysiological studies showing that the representation of three-dimensional object features influences both the rostral sector of the ventral premotor cortex (area F5) and the ventro-rostral sector of the dorsal premotor area (area F2vr; for review see Filimon, 2010). With respect to the reach component, there is agreement that it is subserved by a more medial parieto-frontal circuit including the medial intraparietal area (mIP) termed as the parietal reach region (PRR), area V6A, and the dorsal premotor area F2. Human neuroimaging studies go in the same direction. They showed the involvement of the anterior portion of the human AIP in grasping behavior and they proposed human homologues of both the ventral and dorsal premotor cortices during grasping. Whereas, reaching activates the medial intraparietal and the superior parieto-occipital cortex (for review see Castiello & Begliomini, 2008). Altogether these studies suggest that in humans, like in monkeys, reach to grasp movements involve a large network of interconnected structures in the parietal and frontal lobes. And, that this cortical network is differentially involved for the control of distinct aspects characterizing the planning and the control of reach to grasp movement. Nevertheless, how the neural control systems interact with the complex biomechanics of moving limbs - as to help us to identify the operational principles to look for in reach to grasp studies and, more in general, in motor control - remains an open question. In this respect, it is only through the use of converging techniques with different characteristics that we might fully understand how the human brain controls the grasping function. What is so far lacking in the literature on cortical control of grasp in humans is a systematic documentation of the time course of neural activity during performance of reach to grasp movement. To fill this gap the present thesis will consider the co-registration of behavioural and neural events in order to provide deeper insights into the neuro-functional basis of reach to grasp movements in humans. In Chapter 1 an overview on the state of the art in many disciplines investigating reach to grasp processes will be provided, with particular attention to neurophysiology, from which most of the knowledge regarding the neural underpinnings of reach to grasp movements comes from. Furthermore, kinematical as well as neuroimaging, and evoked related potentials (ERP) investigations will be reviewed. Particular emphasis will be given to neuroimaging studies, especially those exploring grasping movements by functional magnetic resonance imaging (fMRI), as the technique adopted to conduct the studies presented in this thesis (Chapter 1). Basic principles of co-registration techniques, which are at the core of the methodological aspect of the present thesis, will be reviewed (Chapter 2). In this respect, a description of the methodologies adopted in the present thesis together with general information regarding signal processing and data analysis for these different techniques will be provided in specific appendices (III, IV). Then, three studies focusing on the co-registration of kinematical with ERP (Chapters 3 and 4) and FMRI with ERP (Chapter 5) will be presented and discussed. In Chapter 3 the co-registration of ERP and kinematical signals will be considered with specific reference to hand shaping, that is the grasp component of the targeted movement. A similar co-registration approach will be adopted in Chapter 4 for investigating the underlying circuits of reaching. The focus for Chapter 5 will be the co-registration of ERPs and fMRI signals as to reveal the time course of activation of the differential cortical areas related to the planning, initiation and on-line control of reaching and grasping movements and how such activity varies depending on object size. A general discussion (Chapter 6), contextualizing the results obtained by the studies presented in this thesis will follow

Cognitive Assessment and Rehabilitation of subjects with Traumatic Brain Injury

This thesis regards the study and the development of new cognitive assessment and rehabilitation techniques of subjects with traumatic brain injury (TBI). In particular, this thesis i) provides an overview about the state of art of this new assessment and rehabilitation technologies, ii) suggests new methods for the assessment and rehabilitation and iii) contributes to the explanation of the neurophysiological mechanism that is involved in a rehabilitation treatment. Some chapters provide useful information to contextualize TBI and its outcome; they describe the methods used for its assessment/rehabilitation. The other chapters illustrate a series of experimental studies conducted in healthy subjects and TBI patients that suggest new approaches to assessment and rehabilitation. The new proposed approaches have in common the use of electroencefalografy (EEG). EEG was used in all the experimental studies with a different purpose, such as diagnostic tool, signal to command a BCI-system, outcome measure to evaluate the effects of a treatment, etc. The main achieved results are about: i) the study and the development of a system for the communication with patients with disorders of consciousness. It was possible to identify a paradigm of reliable activation during two imagery task using EEG signal or EEG and NIRS signal; ii) the study of the effects of a neuromodulation technique (tDCS) on EEG pattern. This topic is of great importance and interest. The emerged founding showed that the tDCS can manipulate the cortical network activity and through the research of optimal stimulation parameters, it is possible move the working point of a neural network and bring it in a condition of maximum learning. In this way could be possible improved the performance of a BCI system or to improve the efficacy of a rehabilitation treatment, like neurofeedback