Delivering the Lee Silverman Voice Treatment (LSVT) by web camera: a feasibility study

Background: Speech disorders are a feature of Parkinson's disease, typically worsening as the disease progresses. The Lee Silverman Voice Treatment (LSVT) was developed to address these difficulties. It targets vocal loudness as a means of increasing vocal effort and improving coordination across the subsystems of speech. Aims: Currently LSVT is not widely available, and there are practical difficulties associated with the delivery of an intensive treatment in an environment of resource constraints in the National Health Service (NHS). Delivery of LSVT over the World-Wide Web may address some of these difficulties. Methods & Procedures: A feasibility study is reported in which three individuals with speech disorders resulting from Parkinson's disease received LSVT over the Internet, using broadband connection and a web camera. Participants were seen face to face for every fourth session in order to build a personal relationship, measure vocal sound pressure level (SPL) during treatment, and to review and prepare homework tasks. All other sessions were delivered over the Internet. Outcomes & Results: Broadly similar treatment gains were found between individuals treated over the Internet and those treated face to face. Gains were maintained or improved at an assessment two months after the treatment. Conclusions & Implications: This study demonstrates that delivery of LSVT over the Internet is feasible, and that a larger trial would be appropriate to establish cost and treatment effectiveness

Recent Developments in Computer Methods for fMRI Data Processing

Non

A review of brain circuitries involved in stuttering.

Stuttering has been the subject of much research, nevertheless its etiology remains incompletely understood. This article presents a critical review of the literature on stuttering, with particular reference to the role of the basal ganglia (BG). Neuroimaging and lesion studies of developmental and acquired stuttering, as well as pharmacological and genetic studies are discussed. Evidence of structural and functional changes in the BG in those who stutter indicates that this motor speech disorder is due, at least in part, to abnormal BG cues for the initiation and termination of articulatory movements. Studies discussed provide evidence of a dysfunctional hyperdopaminergic state of the thalamocortical pathways underlying speech motor control in stuttering. Evidence that stuttering can improve, worsen or recur following deep brain stimulation for other indications is presented in order to emphasize the role of BG in stuttering. Further research is needed to fully elucidate the pathophysiology of this speech disorder, which is associated with significant social isolation

Effects of deep brain stimulation on speech in patients with Parkinson’s disease and dystonia

Disorders affecting the basal ganglia can have a severe effect on speech motor control. The effect can vary depending on the pathophysiology of the basal ganglia disease but in general terms it can be classified as hypokinetic or hyperkinetic dysarthria. Despite the role of basal ganglia on speech, there is a marked discrepancy between the effect of medical and surgical treatments on limb and speech motor control. This is compounded by the complex nature of speech and communication in general, and the lack of animal models of speech motor control. The emergence of deep brain stimulation of basal ganglia structures gives us the opportunity to record systematically the effects on speech and attempt some assumptions on the role of basal ganglia on speech motor control. The aim of the present work was to examine the impact of bilateral subthalamic nucleus deep brain stimulation (STN-DBS) for Parkinson’s disease (PD) and globus pallidus internus (GPi-DBS) for dystonia on speech motor control. A consecutive series of PD and dystonia patients who underwent DBS was evaluated. Patients were studied in a prospective longitudinal manner with both clinical assessment of their speech intelligibility and acoustical analysis of their speech. The role of pre-operative clinical factors and electrical parameters of stimulation, mainly electrode positioning and voltage amplitude was systematically examined. In addition, for selected patients, tongue movements were studied using electropalatography. Aerodynamic aspects of speech were also studied. The impact of speech therapy was assessed in a subgroup of patients. The clinical evaluation of speech intelligibility one and three years post STN-DBS in PD patients showed a deterioration of speech, partly related to medially placed electrodes and high amplitude of stimulation. Pre-operative predictive factors included low speech intelligibility before surgery and longer disease duration. Articulation rather than voice was most frequently affected with a distinct dysarthria type emerging, mainly hyperkinetic-dystonic, rather than hypokinetic. Traditionally effective therapy for PD dysarthria had little to no benefit following STN-DBS. Speech following GPi-DBS for dystonia did not significantly change after one year of stimulation. A subgroup of patients showed hypokinetic features, mainly reduced voice volume and fast rate of speech more typical of Parkinsonian speech. Speech changes in both STN-DBS and GPi-DBS were apparent after six months of stimulation. This progressive deterioration of speech and the critical role of the electrical parameters of stimulation suggest a long-term effect of electrical stimulation of basal ganglia on speech motor control

Evaluation Of The Nature Of Seismogenetic Systems Along The North-Western Rim Of The Circum-Pacific Belt, Based On (Non-Extensive) Statistical Physics And Complexity Science Methods

Σκοπός της διπλωματικής αυτής είναι η μελέτη των φυσικών χαρακτηριστικών της σεισμογένεσης με μεθόδους μη- εκτατικής στατιστικής φυσικής, στην ΒΔ Περι-Ειρηνική ζώνη. Η εκτατική στατιστική των Boltzmann-Gibbs δεν μπορεί να εφαρμοστεί για συστήματα τα οποία βρίσκονται εκτός ισορροπίας και τα μέλη του αλληλεπιδρούν. Τέτοιο σύστημα αποτελεί και ο ενεργός τεκτονικός ιστός. Για αυτά τα συστήματα εισέρχεται η θεωρία της μη-εκτατικής στατιστικής φυσικής (NESP) η οποία αποτελεί μια γενίκευση της στατιστικής των Boltzmann-Gibbs. Αυτό που εξετάζεται, χρησιμοποιώντας το φορμαλισμό της NESP, είναι το αν η σεισμικότητα αποτελεί ένα τέτοιο σύστημα που βρίσκεται σε ισορροπία. Αν ναι, τότε θα αποτελεί μια σημειακή Poissonian διεργασία η οποία ακολουθεί τους κανόνες της θερμοδυναμικής Boltzmann-Gibbs,αν όχι, τότε θα ερμηνεύεται από τους κανόνες της μη-εκτατικής στατιστικής φυσικής. Ο κατάλογος που χρησιμοποιήθηκε για την μελέτη αυτή είναι ο ενοποιημένος σεισμικός κατάλογος της Japan Meteorological Agency (JMA) και αφορά το διάστημα 01/01/2002 μέχρι και τις 31/05/2016. Επιλέχθηκε ένα κατώφλι μεγέθους Μ3 και ο συνολικός αριθμός των δεδομένων είναι 103.696. Συγκεκριμένα αυτό που εξετάζεται είναι η ύπαρξη αλληλεπιδράσεων (συσχετίσεων μακριάς εμβέλειας) μελετώντας q-κατανομές για παραμέτρους α) Μεγέθους - Γενικευμένος Νόμος των Gutenberg-Richter, β) Χρόνου αναμονής - Interevent times - όπου αποτελεί τον χρόνο μεταξύ διαδοχικών γεγονότων, και, γ) Ενδιαμέσων αποστάσεων - Interevent Ditance- όπου αποτελούν τις αποστάσεις μεταξύ διαδοχικών γεγονότων. Επιπλέον υπολογίζονται b-values τα οποία παράγονται από τους εντροπικούς δείκτες, και συγκρίνονται με το b-value των Gutenberg-Richter για να διαπιστωθεί το αν η ανάλυση αυτή πλησιάζει τις πραγματικές τιμές.The Thesis examines the nature of seismogenetic systems along the north-western rim of the Circum-Pacific belt by searching for evidence of complexity and non-extensivity in the earthquake record. The objective is to determine whether earthquakes are generated by a self-excited Poisson process, in which case they obey Boltzmann-Gibbs thermodynamics, or by a Critical process, in which long-range interactions in non-equilibrium states are expected (correlation) and the thermodynamics deviate from the Boltzmann-Gibbs formalism. Emphasis is given to background seismicity since it is generally agreed that aftershock sequences comprise correlated sets. Because the study area features convergent plate boundaries that include both crustal (in the lithosphere), and sub-crustal (in the Wadati-Benioff zones) earthquakes, the analysis was carried out by roughly separating crustal and sub-crustal seismicity according to the depth of the Mohorovičić discontinuity, in an attempt inquire whether environmental conditions (e.g. temperature, pressure), or/and boundary conditions (free at the surface vs. fixed at depth), affect the dynamic expression and evolution of seismogenetic fault networks. The analysis uses the complete and homogeneous Unified Seismic Catalogue of Japan, obtained from The earthquake data used in the study span the time period 1/1/2002 – 31/5/2016 and was provided by the National Research Institute for Earth Science and Disaster Resilience, the Japan Meteorological Agency, Hokkaido University, Hirosaki University, Tohoku University, the University of Tokyo, Nagoya University, Kyoto University, Kochi University, Kyushu University, Kagoshima University, the National Institute of Advanced Industrial Science and Technology, the Geographical Survey Institute, Tokyo Metropolis, Shizuoka Prefecture, Hot Springs Research Institute of Kanagawa Prefecture, Yokohama City, and Japan Agency for Marine-Earth Science and Technology. The earthquake catalogue is available in the website of the National Research Institute for Earth Sciences and Disaster Prevention (NIED). The analysis examined multivariate cumulative frequency distributions of earthquake magnitude, interevent time and interevent distance in the context of Non-Extensive Statistical Physics, which is a generalization of extensive Boltzmann-Gibbs thermodynamics to non-equilibrating (non-extensive) systems. It follows that the results are obtained through a physics-based approach and not through any type of model-based (or model-driven) consideration, as usually is the case in earthquake statistical studies. The analysis was applied to different catalogue realizations in which aftershocks were either included, or had been removed by a stochastic declustering procedure. The results provide evidence that in the seismogenetic systems of the NW Circum-Pacific belt, background seismicity is complex sub-extensive of nature, although it exhibits significant differences between systems (plates): Complexity is certainly prominent in the Okhotsk and Pacific plates and definitely less evident in the Eurasia and Philippine plates where the systems appear to verge on randomness. In the Okhotsk and Pacific plates background seismicity exhibits strong long-range interaction as evident by the overall high correlation observed in highly declustered catalogues and, primarily, in the long-range interaction observed in earthquake groups separated by long interevent distances. The increase in the level of complexity after declustering can be neatly explained by the exposition of long range interactions after curtailing the effect of short-range interactions associated with aftershock sequences. It is also highly probable –but was not be investigated herein– that the elevated complexity (sub-extensivity) of the Okhotsk and Pacific seismicity is closely related to the 2011 M9 Tohoku mega-earthquake, whose preparation phase and aftermath has organized the seismogenetic systems over long ranges. Criticality is a likely explanation for the complexity observed in the background seismicity of Okhotsk and Pacific plates, inasmuch as power-laws and long-range interaction are its hallmarks. However, the question is still very far from having been answered as there may be alternative (albeit less likely) mechanisms by which complexity and power-laws and may arise. It is therefore clear that additional work is required before the complexity mechanism of background seismicity can be proposed with confidence

A six stage approach for the diagnosis of the Alzheimer’s disease based on fMRI data

AbstractThe aim of this work is to present an automated method that assists in the diagnosis of Alzheimer’s disease and also supports the monitoring of the progression of the disease. The method is based on features extracted from the data acquired during an fMRI experiment. It consists of six stages: (a) preprocessing of fMRI data, (b) modeling of fMRI voxel time series using a Generalized Linear Model, (c) feature extraction from the fMRI data, (d) feature selection, (e) classification using classical and improved variations of the Random Forests algorithm and Support Vector Machines, and (f) conversion of the trees, of the Random Forest, to rules which have physical meaning. The method is evaluated using a dataset of 41 subjects. The results of the proposed method indicate the validity of the method in the diagnosis (accuracy 94%) and monitoring of the Alzheimer’s disease (accuracy 97% and 99%)

Adaptive deep brain stimulation for Parkinson's disease demonstrates reduced speech side effects compared to conventional stimulation in the acute setting.

Deep brain stimulation (DBS) for Parkinson's disease (PD) is currently limited by costs, partial efficacy and surgical and stimulation-related side effects. This has motivated the development of adaptive DBS (aDBS) whereby stimulation is automatically adjusted according to a neurophysiological biomarker of clinical state, such as β oscillatory activity (12–30 Hz). aDBS has been studied in parkinsonian primates and patients and has been reported to be more energy efficient and effective in alleviating motor symptoms than conventional DBS (cDBS) at matched amplitudes

Long-term success of low-frequency subthalamic nucleus stimulation for Parkinson's disease depends on tremor severity and symptom duration

Patients with Parkinson's disease can develop axial symptoms, including speech, gait and balance difficulties. Chronic high-frequency (>100 Hz) deep brain stimulation can contribute to these impairments while low-frequency stimulation (<100 Hz) may improve symptoms but only in some individuals. Factors predicting which patients benefit from low-frequency stimulation in the long term remain unclear. This study aims to confirm that low-frequency stimulation improves axial symptoms, and to go further to also explore which factors predict the durability of its effects. We recruited patients who developed axial motor symptoms while using high-frequency stimulation and objectively assessed the short-term impact of low-frequency stimulation on axial symptoms, other aspects of motor function and quality of life. A retrospective chart review was then conducted on a larger cohort to identify which patient characteristics were associated with not only the need to trial low-frequency stimulation, but also those which predicted its sustained use. Among 20 prospective patients, low-frequency stimulation objectively improved mean motor and axial symptom severity and quality of life in the short term. Among a retrospective cohort of 168 patients, those with less severe tremor and those in whom axial symptoms had emerged sooner after subthalamic nucleus deep brain stimulation were more likely to be switched to and remain on long-term low-frequency stimulation. These data suggest that low-frequency stimulation results in objective mean improvements in overall motor function and axial symptoms among a group of patients, while individual patient characteristics can predict sustained long-term benefits. Longer follow-up in the context of a larger, controlled, double-blinded study would be required to provide definitive evidence of the role of low-frequency deep brain stimulation

Predicting Heart Failure Patient Events by Exploiting Saliva and Breath Biomarkers Information

The aim of this work is to present a machine learning based method for the prediction of adverse events (mortality and relapses) in patients with heart failure (HF) by exploiting, for the first time, measurements of breath and saliva biomarkers (Tumor Necrosis Factor Alpha, Cortisol and Acetone). Data from 27 patients are used in the study and the prediction of adverse events is achieved with high accuracy (77%) using the Rotation Forest algorithm. As in the near future, biomarkers can be measured at home, together with other physiological data, the accurate prediction of adverse events on the basis of home based measurements can revolutionize HF management