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.

Self-Organizing Mechanisms for Task Allocation in a Knowledge-Based Economy

A prevalent claim is that we are in knowledge economy. When we talk about knowledge economy, we generally mean the concept of “Knowledge-based economy” indicating the use of knowledge and technologies to produce economic benefits. Hence knowledge is both tool and raw material (people’s skill) for producing some kind of product or service. In this kind of environment economic organization is undergoing several changes. For example authority relations are less important, legal and ownership-based definitions of the boundaries of the firm are becoming irrelevant and there are only few constraints on the set of coordination mechanisms. Hence what characterises a knowledge economy is the growing importance of human capital in productive processes (Foss, 2005) and the increasing knowledge intensity of jobs (Hodgson, 1999). Economic processes are also highly intertwined with social processes: they are likely to be informal and reciprocal rather than formal and negotiated. Another important point is also the problem of the division of labor: as economic activity becomes mainly intellectual and requires the integration of specific and idiosyncratic skills, the task of dividing the job and assigning it to the most appropriate individuals becomes arduous, a “supervisory problem” (Hogdson, 1999) emerges and traditional hierarchical control may result increasingly ineffective. Not only specificity of know how makes it awkward to monitor the execution of tasks, more importantly, top-down integration of skills may be difficult because ‘the nominal supervisors will not know the best way of doing the job – or even the precise purpose of the specialist job itself – and the worker will know better’ (Hogdson,1999). We, therefore, expect that the organization of the economic activity of specialists should be, at least partially, self-organized. The aim of this thesis is to bridge studies from computer science and in particular from Peer-to-Peer Networks (P2P) to organization theories. We think that the P2P paradigm well fits with organization problems related to all those situation in which a central authority is not possible. We believe that P2P Networks show a number of characteristics similar to firms working in a knowledge-based economy and hence that the methodology used for studying P2P Networks can be applied to organization studies. Three are the main characteristics we think P2P have in common with firms involved in knowledge economy: - Decentralization: in a pure P2P system every peer is an equal participant, there is no central authority governing the actions of the single peers; - Cost of ownership: P2P computing implies shared ownership reducing the cost of owing the systems and the content, and the cost of maintaining them; - Self-Organization: it refers to the process in a system leading to the emergence of global order within the system without the presence of another system dictating this order. These characteristics are present also in the kind of firm that we try to address and that’ why we have shifted the techniques we adopted for studies in computer science (Marcozzi et al., 2005; Hales et al., 2007 [39]) to management science.

Il ruolo del collicolo superiore nell'orientamento spaziale

This thesis was aimed at verifying the role of the superior colliculus (SC) in human spatial orienting. To do so, subjects performed two experimental tasks that have been shown to involve SC’s activation in animals, that is a multisensory integration task (Experiment 1 and 2) and a visual target selection task (Experiment 3). To investigate this topic in humans, we took advantage of neurophysiological finding revealing that retinal S-cones do not send projections to the collicular and magnocellular pathway. In the Experiment 1, subjects performed a simple reaction-time task in which they were required to respond as quickly as possible to any sensory stimulus (visual, auditory or bimodal audio-visual). The visual stimulus could be an S-cone stimulus (invisible to the collicular and magnocellular pathway) or a long wavelength stimulus (visible to the SC). Results showed that when using S-cone stimuli, RTs distribution was simply explained by probability summation, indicating that the redundant auditory and visual channels are independent. Conversely, with red long-wavelength stimuli, visible to the SC, the RTs distribution was related to nonlinear neural summation, which constitutes evidence of integration of different sensory information. We also demonstrate that when AV stimuli were presented at fixation, so that the spatial orienting component of the task was reduced, neural summation was possible regardless of stimulus color. Together, these findings provide support for a pivotal role of the SC in mediating multisensory spatial integration in humans, when behavior involves spatial orienting responses. Since previous studies have shown an anatomical asymmetry of fibres projecting to the SC from the hemiretinas, the Experiment 2 was aimed at investigating temporo-nasal asymmetry in multisensory integration. To do so, subjects performed monocularly the same task shown in the Experiment 1. When spatially coincident audio-visual stimuli were visible to the SC (i.e. red stimuli), the RTE depended on a neural coactivation mechanism, suggesting an integration of multisensory information. When using stimuli invisible to the SC (i.e. purple stimuli), the RTE depended only on a simple statistical facilitation effect, in which the two sensory stimuli were processed by independent channels. Finally, we demonstrate that the multisensory integration effect was stronger for stimuli presented to the temporal hemifield than to the nasal hemifield. Taken together, these findings suggested that multisensory stimulation can be differentially effective depending on specific stimulus parameters. The Experiment 3 was aimed at verifying the role of the SC in target selection by using a color-oddity search task, comprising stimuli either visible or invisible to the collicular and magnocellular pathways. Subjects were required to make a saccade toward a target that could be presented alone or with three distractors of another color (either S-cone or long-wavelength). When using S-cone distractors, invisible to the SC, localization errors were similar to those observed in the distractor-free condition. Conversely, with long-wavelength distractors, visible to the SC, saccadic localization error and variability were significantly greater than in either the distractor-free condition or the S-cone distractors condition. Our results clearly indicate that the SC plays a direct role in visual target selection in humans. Overall, our results indicate that the SC plays an important role in mediating spatial orienting responses both when required covert (Experiments 1 and 2) and overt orienting (Experiment 3).

Effetti dell'integrazione visuo-acustica in pazienti con disturbo di campo visivo

Human brain is provided with a flexible audio-visual system, which interprets and guides responses to external events according to spatial alignment, temporal synchronization and effectiveness of unimodal signals. The aim of the present thesis was to explore the possibility that such a system might represent the neural correlate of sensory compensation after a damage to one sensory pathway. To this purpose, three experimental studies have been conducted, which addressed the immediate, short-term and long-term effects of audio-visual integration on patients with Visual Field Defect (VFD). Experiment 1 investigated whether the integration of stimuli from different modalities (cross-modal) and from the same modality (within-modal) have a different, immediate effect on localization behaviour. Patients had to localize modality-specific stimuli (visual or auditory), cross-modal stimulus pairs (visual-auditory) and within-modal stimulus pairs (visual-visual). Results showed that cross-modal stimuli evoked a greater improvement than within modal stimuli, consistent with a Bayesian explanation. Moreover, even when visual processing was impaired, cross-modal stimuli improved performance in an optimal fashion. These findings support the hypothesis that the improvement derived from multisensory integration is not attributable to simple target redundancy, and prove that optimal integration of cross-modal signals occurs in processing stage which are not consciously accessible. Experiment 2 examined the possibility to induce a short term improvement of localization performance without an explicit knowledge of visual stimulus. Patients with VFD and patients with neglect had to localize weak sounds before and after a brief exposure to a passive cross-modal stimulation, which comprised spatially disparate or spatially coincident audio-visual stimuli. After exposure to spatially disparate stimuli in the affected field, only patients with neglect exhibited a shifts of auditory localization toward the visual attractor (the so called Ventriloquism After-Effect). In contrast, after adaptation to spatially coincident stimuli, both neglect and hemianopic patients exhibited a significant improvement of auditory localization, proving the occurrence of After Effect for multisensory enhancement. These results suggest the presence of two distinct recalibration mechanisms, each mediated by a different neural route: a geniculo-striate circuit and a colliculus-extrastriate circuit respectively. Finally, Experiment 3 verified whether a systematic audio-visual stimulation could exert a long-lasting effect on patients’ oculomotor behaviour. Eye movements responses during a visual search task and a reading task were studied before and after visual (control) or audio-visual (experimental) training, in a group of twelve patients with VFD and twelve controls subjects. Results showed that prior to treatment, patients’ performance was significantly different from that of controls in relation to fixations and saccade parameters; after audiovisual training, all patients reported an improvement in ocular exploration characterized by fewer fixations and refixations, quicker and larger saccades, and reduced scanpath length. Similarly, reading parameters were significantly affected by the training, with respect to specific impairments observed in left and right hemisphere–damaged patients. The present findings provide evidence that a systematic audio-visual stimulation may encourage a more organized pattern of visual exploration with long lasting effects. In conclusion, results from these studies clearly demonstrate that the beneficial effects of audio-visual integration can be retained in absence of explicit processing of visual stimulus. Surprisingly, an improvement of spatial orienting can be obtained not only when a on-line response is required, but also after either a brief or a long adaptation to audio-visual stimulus pairs, so suggesting the maintenance of mechanisms subserving cross-modal perceptual learning after a damage to geniculo-striate pathway. The colliculus-extrastriate pathway, which is spared in patients with VFD, seems to play a pivotal role in this sensory compensation.

Structure learning of graphical models for task-oriented robot grasping

In the collective imaginaries a robot is a human like machine as any androids in science fiction. However the type of robots that you will encounter most frequently are machinery that do work that is too dangerous, boring or onerous. Most of the robots in the world are of this type. They can be found in auto, medical, manufacturing and space industries. Therefore a robot is a system that contains sensors, control systems, manipulators, power supplies and software all working together to perform a task. The development and use of such a system is an active area of research and one of the main problems is the development of interaction skills with the surrounding environment, which include the ability to grasp objects. To perform this task the robot needs to sense the environment and acquire the object informations, physical attributes that may influence a grasp. Humans can solve this grasping problem easily due to their past experiences, that is why many researchers are approaching it from a machine learning perspective finding grasp of an object using information of already known objects. But humans can select the best grasp amongst a vast repertoire not only considering the physical attributes of the object to grasp but even to obtain a certain effect. This is why in our case the study in the area of robot manipulation is focused on grasping and integrating symbolic tasks with data gained through sensors. The learning model is based on Bayesian Network to encode the statistical dependencies between the data collected by the sensors and the symbolic task. This data representation has several advantages. It allows to take into account the uncertainty of the real world, allowing to deal with sensor noise, encodes notion of causality and provides an unified network for learning. Since the network is actually implemented and based on the human expert knowledge, it is very interesting to implement an automated method to learn the structure as in the future more tasks and object features can be introduced and a complex network design based only on human expert knowledge can become unreliable. Since structure learning algorithms presents some weaknesses, the goal of this thesis is to analyze real data used in the network modeled by the human expert, implement a feasible structure learning approach and compare the results with the network designed by the expert in order to possibly enhance it.