Voicing quantification is more relevant than period perturbation in substitution voices: an advanced acoustical study

Quality of substitution voicing—i.e., phonation with a voice that is not generated by the vibration of two vocal folds—cannot be adequately evaluated with routinely used software for acoustic voice analysis that is aimed at ‘common’ dysphonias and nearly periodic voice signals. The AMPEX analysis program (Van Immerseel and Martens) has been shown previously to be able to detect periodicity in irregular signals with background noise, and to be suited for running speech. The validity of this analysis program is first tested using realistic synthesized voice signals with known levels of cycle-to-cycle perturbations and additive noise. Second, exhaustive acoustic analysis is performed of the voices of 116 patients surgically treated for advanced laryngeal cancer and recorded in seven European academic centers. All of them read out a short phonetically balanced passage. Patients were divided into six groups according to the oscillating structures they used to phonate. Results show that features related to quantification of voicing enable a distinction between the different groups, while the features reporting F0-instability fail to do so. Acoustic evaluation of voice quality in substitution voices thus best relies upon voicing quantification

Dynamical principles in neuroscience

Dynamical modeling of neural systems and brain functions has a history of success over the last half century. This includes, for example, the explanation and prediction of some features of neural rhythmic behaviors. Many interesting dynamical models of learning and memory based on physiological experiments have been suggested over the last two decades. Dynamical models even of consciousness now exist. Usually these models and results are based on traditional approaches and paradigms of nonlinear dynamics including dynamical chaos. Neural systems are, however, an unusual subject for nonlinear dynamics for several reasons: (i) Even the simplest neural network, with only a few neurons and synaptic connections, has an enormous number of variables and control parameters. These make neural systems adaptive and flexible, and are critical to their biological function. (ii) In contrast to traditional physical systems described by well-known basic principles, first principles governing the dynamics of neural systems are unknown. (iii) Many different neural systems exhibit similar dynamics despite having different architectures and different levels of complexity. (iv) The network architecture and connection strengths are usually not known in detail and therefore the dynamical analysis must, in some sense, be probabilistic. (v) Since nervous systems are able to organize behavior based on sensory inputs, the dynamical modeling of these systems has to explain the transformation of temporal information into combinatorial or combinatorial-temporal codes, and vice versa, for memory and recognition. In this review these problems are discussed in the context of addressing the stimulating questions: What can neuroscience learn from nonlinear dynamics, and what can nonlinear dynamics learn from neuroscience?This work was supported by NSF Grant No. NSF/EIA-0130708, and Grant No. PHY 0414174; NIH Grant No. 1 R01 NS50945 and Grant No. NS40110; MEC BFI2003-07276, and Fundación BBVA

Features of Mild-to-Moderate COVID-19 Patients with Dysphonia

Introduction To explore the prevalence of dysphonia in European patients with mild-to-moderate COVID-19 and the clinical features of dysphonic patients. Methods The clinical and epidemiological data of 702 patients with mild-to-moderate COVID-19 were collected from 19 European Hospitals. The following data were extracted: age, sex, ethnicity, tobacco consumption, comorbidities, general and otolaryngological symptoms. Dysphonia and otolaryngological symptoms were self-assessed through a 4-point scale. The prevalence of dysphonia, as part of the COVID-19 symptoms, was assessed. The outcomes were compared between dysphonic and non-dysphonic patients. The association between dysphonia severity and outcomes was studied through Bayesian analysis. Results A total of 188 patients were dysphonic, accounting for 26.8% of cases. Females developed more frequently dysphonia than males (p=0.022). The proportion of smokers was significantly higher in the dysphonic group (p=0.042). The prevalence of the following symptoms was higher in dysphonic patients compared with non-dysphonic patients: cough, chest pain, sticky sputum, arthralgia, diarrhea, headache, fatigue, nausea and vomiting. The severity of dyspnea, dysphagia, ear pain, face pain, throat pain and nasal obstruction was higher in dysphonic group compared with non-dysphonic group. There were significant associations between the severity of dysphonia, dysphagia and cough. Conclusion Dysphonia may be encountered in a quarter of patients with mild-to-moderate COVID-19 and should be considered as a symptom list of the infection. Dysphonic COVID-19 patients are more symptomatic than non-dysphonic individuals. Future studies are needed to investigate the relevance of dysphonia in the COVID-19 clinical presentation

Gebiss: an ImageJ plugin for the specification of ground truth and the performance evaluation of 3D segmentation algorithms.

Background: Image segmentation is a crucial step in quantitative microscopy that helps to define regions of tissues, cells or subcellular compartments. Depending on the degree of user interactions, segmentation methods can be divided into manual, automated or semi-automated approaches. 3D image stacks usually require automated methods due to their large number of optical sections. However, certain applications benefit from manual or semi-automated approaches. Scenarios include the quantification of 3D images with poor signal-to-noise ratios or the generation of so-called ground truth segmentations that are used to evaluate the accuracy of automated segmentation methods. Results: We have developed Gebiss; an ImageJ plugin for the interactive segmentation, visualisation and quantification of 3D microscopic image stacks. We integrated a variety of existing plugins for threshold-based segmentation and volume visualisation. Conclusions: We demonstrate the application of Gebiss to the segmentation of nuclei in live Drosophila embryos and the quantification of neurodegeneration in Drosophila larval brains. Gebiss was developed as a cross-platform ImageJ plugin and is freely available on the web at http://imaging.bii.a-star.edu.sg/projects/gebiss

Carpal Tunnel Syndrome: A Review of the Recent Literature

Carpal Tunnel Syndrome (CTS) remains a puzzling and disabling condition present in 3.8% of the general population. CTS is the most well-known and frequent form of median nerve entrapment, and accounts for 90% of all entrapment neuropathies. This review aims to provide an overview of this common condition, with an emphasis on the pathophysiology involved in CTS. The clinical presentation and risk factors associated with CTS are discussed in this paper. Also, the various methods of diagnosis are explored; including nerve conduction studies, ultrasound, and magnetic resonance imaging

Modeling Brain Resonance Phenomena Using a Neural Mass Model

Stimulation with rhythmic light flicker (photic driving) plays an important role in the diagnosis of schizophrenia, mood disorder, migraine, and epilepsy. In particular, the adjustment of spontaneous brain rhythms to the stimulus frequency (entrainment) is used to assess the functional flexibility of the brain. We aim to gain deeper understanding of the mechanisms underlying this technique and to predict the effects of stimulus frequency and intensity. For this purpose, a modified Jansen and Rit neural mass model (NMM) of a cortical circuit is used. This mean field model has been designed to strike a balance between mathematical simplicity and biological plausibility. We reproduced the entrainment phenomenon observed in EEG during a photic driving experiment. More generally, we demonstrate that such a single area model can already yield very complex dynamics, including chaos, for biologically plausible parameter ranges. We chart the entire parameter space by means of characteristic Lyapunov spectra and Kaplan-Yorke dimension as well as time series and power spectra. Rhythmic and chaotic brain states were found virtually next to each other, such that small parameter changes can give rise to switching from one to another. Strikingly, this characteristic pattern of unpredictability generated by the model was matched to the experimental data with reasonable accuracy. These findings confirm that the NMM is a useful model of brain dynamics during photic driving. In this context, it can be used to study the mechanisms of, for example, perception and epileptic seizure generation. In particular, it enabled us to make predictions regarding the stimulus amplitude in further experiments for improving the entrainment effect

Proposition d’une sous-classification des cordectomies par voie endoscopique au laser des cancers glottiques

National audienc

Multidimensional Voice Quality Evaluation After Transoral CO2 Laser Cordectomy: A Prospective Study

International audienceObjective: To investigate voice quality changes of patients treated by transoral laser cordectomy (TLC) for early glottic cancer according to the type of cordectomies. Methods: A total of 164 consecutive male patients with an early glottic cancer were prospectively recruited from the Department of Otolaryngology—Head and Neck Surgery of the Georges Pompidou European Hospital. Depending on the tumor characteristics, patients benefited from type I to VI CO2 cordectomy regarding the European Laryngological Society classification. The following voice quality outcomes were pre- to postoperatively assessed: voice handicap index (VHI), perceptual grade of dysphonia, roughness, breathiness, maximum phonation time, and acoustic parameters. Results: Fifty-five patients with Tis, T1, or T2 vocal fold cancer completed the study (mean age: 61.7 years). Of these patients, 34 and 21 composed group 1 (types I-III TLC) and group 2 (types IV-VI TLC), respectively. Voice handicap index, grade of dysphonia, and breathiness significantly improved from pre- to 3- and 6-month posttreatment in group 1. In group 2, only VHI significantly improved from pre- to 3- and 6-month posttreatment. Acoustic and aerodynamic measurements did not change throughout the postoperative course. Patients with types I to III TLC exhibited better postoperative voice outcomes compared to those treated by types IV to VI TLC. Conclusion: Irrespective to the types of TLC, the subjective voice quality of patients treated by CO2 laser cordectomy for early glottic cancer significantly improved from pre- to 3- and 6-month posttreatment. The usefulness of aerodynamic and acoustic measurements as postoperative outcomes of voice quality changes remain controversial and require future studies considering multidimensional assessment of voice