Dynamical Theory of Angle-Resolved Electron Energy Loss and Gain Spectroscopies of Phonons and Magnons in Transmission Electron Microscopy Including Multiple Scattering Effects.

We present a method for computing angle-resolved electron energy loss and gain spectroscopies for phonon and magnon excitations in transmission electron microscopy. Fractional scattering intensities are derived from the temperature-dependent time autocorrelation of the auxiliary electron beam wave function. This method captures both single and multiple scattering processes, as well as dynamical diffraction effects, while remaining computationally efficient and easy to parallelize.

Automated analysis of spoken language differentiates multiple system atrophy from Parkinson's disease.

Background And Objectives: Patients with synucleinopathies such as multiple system atrophy (MSA) and Parkinson's disease (PD) frequently display speech and language abnormalities. We explore the diagnostic potential of automated linguistic analysis of natural spontaneous speech to differentiate MSA and PD.

Methods: Spontaneous speech of 39 participants with MSA compared to 39 drug-naive PD and 39 healthy controls matched for age and sex was transcribed and linguistically annotated using automatic speech recognition and natural language processing.

Corrigendum: An automatic measure for speech intelligibility in dysarthrias-validation across multiple languages and neurological disorders.

[This corrects the article DOI: 10.3389/fdgth.2024.

Differentiating Essential and Dystonic Head Tremor: Exploring Arm Position Effects.

Background: Head tremor poses diagnostic problems, especially when present as an isolated or predominant symptom.

Objectives: To assess how maneuvers activating upper limb postural tremor can help differentiate head tremor in essential tremor (ET) from dystonic tremor (DT) in cervical dystonia.

Methods: 48 patients with head tremor (25 ET, 23 DT), underwent clinical examination and accelerometric evaluation of head and upper limb tremor during routine tremor-inducing tasks.

From prodromal stages to clinical trials: The promise of digital speech biomarkers in Parkinson's disease.

Speech impairment is a common and disabling symptom in Parkinson's disease (PD), affecting communication and quality of life. Advances in digital speech processing and artificial intelligence have revolutionized objective speech analysis. Given the complex nature of speech impairment, acoustic speech analysis offers unique biomarkers for neuroprotective treatments from the prodromal stages of PD.

Is speech function lateralised in the basal ganglia? Evidence from de novo Parkinson's disease.

Background: Research on the possible influence of lateralised basal ganglia dysfunction on speech in Parkinson's disease is scarce. This study aimed to compare speech in de-novo, drug-naive patients with Parkinson's disease (PD) with asymmetric nigral dopaminergic dysfunction, predominantly in either the right or left hemisphere.

Methods: Acoustic analyses of reading passages were performed.

An automatic measure for speech intelligibility in dysarthrias-validation across multiple languages and neurological disorders.

Introduction: Dysarthria, a motor speech disorder caused by muscle weakness or paralysis, severely impacts speech intelligibility and quality of life. The condition is prevalent in motor speech disorders such as Parkinson's disease (PD), atypical parkinsonism such as progressive supranuclear palsy (PSP), Huntington's disease (HD), and amyotrophic lateral sclerosis (ALS). Improving intelligibility is not only an outcome that matters to patients but can also play a critical role as an endpoint in clinical research and drug development.

Smartphone Voice Calls Provide Early Biomarkers of Parkinsonism in Rapid Eye Movement Sleep Behavior Disorder.

Background: Speech dysfunction represents one of the initial motor manifestations to develop in Parkinson's disease (PD) and is measurable through smartphone.

Objective: The aim was to develop a fully automated and noise-resistant smartphone-based system that can unobtrusively screen for prodromal parkinsonian speech disorder in subjects with isolated rapid eye movement sleep behavior disorder (iRBD) in a real-world scenario.

Methods: This cross-sectional study assessed regular, everyday voice call data from individuals with iRBD compared to early PD patients and healthy controls via a developed smartphone application.

Automatic speech-based assessment to discriminate Parkinson's disease from essential tremor with a cross-language approach.

Parkinson's disease (PD) and essential tremor (ET) are prevalent movement disorders that mainly affect elderly people, presenting diagnostic challenges due to shared clinical features. While both disorders exhibit distinct speech patterns-hypokinetic dysarthria in PD and hyperkinetic dysarthria in ET-the efficacy of speech assessment for differentiation remains unexplored. Developing technology for automatic discrimination could enable early diagnosis and continuous monitoring.

Noise-dependent bias in quantitative STEM-EMCD experiments revealed by bootstrapping.

Electron magnetic circular dichroism (EMCD) is a powerful technique for estimating element-specific magnetic moments of materials on nanoscale with the potential to reach atomic resolution in transmission electron microscopes. However, the fundamentally weak EMCD signal strength complicates quantification of magnetic moments, as this requires very high precision, especially in the denominator of the sum rules. Here, we employ a statistical resampling technique known as bootstrapping to an experimental EMCD dataset to produce an empirical estimate of the noise-dependent error distribution resulting from application of EMCD sum rules to bcc iron in a 3-beam orientation.

Essential and dystonic head tremor: More similarities than differences.

Introduction: Head tremor is a common symptom of essential tremor (ET) and cervical dystonia (CD). In clinical practice, it is often difficult to distinguish between these two conditions, especially in cases where head tremor predominates.

Objectives: To investigate which clinical and instrumental methods best differentiate ET and CD in patients with head tremor.

Automated Vowel Articulation Analysis in Connected Speech Among Progressive Neurological Diseases, Dysarthria Types, and Dysarthria Severities.

Purpose: Although articulatory impairment represents distinct speech characteristics in most neurological diseases affecting movement, methods allowing automated assessments of articulation deficits from the connected speech are scarce. This study aimed to design a fully automated method for analyzing dysarthria-related vowel articulation impairment and estimate its sensitivity in a broad range of neurological diseases and various types and severities of dysarthria.

Method: Unconstrained monologue and reading passages were acquired from 459 speakers, including 306 healthy controls and 153 neurological patients.

Lexical and syntactic deficits analyzed via automated natural language processing: the new monitoring tool in multiple sclerosis.

Background: Impairment of higher language functions associated with natural spontaneous speech in multiple sclerosis (MS) remains underexplored.

Objectives: We presented a fully automated method for discriminating MS patients from healthy controls based on lexical and syntactic linguistic features.

Methods: We enrolled 120 MS individuals with Expanded Disability Status Scale ranging from 1 to 6.

The automated screening of speech motor development in children based on the sequential motion rate.

Background: Motor skills in children have traditionally been examined via challenging speech tasks such as syllable repetition, and calculating the syllabic rate using a stopwatch or by inspecting the oscillogram followed by a laborious comparison of the scores on a look-up table representing the typical performances of children of the given age and sex. As the commonly used performance tables are over-simplified to allow for manual scoring, we raise the question of whether a computational model of motor skills development could be more informative, and could allow for the automated screening of children to detect underdeveloped motor skills.

Methods: We recruited a total of 275 children aged four to 15 years.

Single scan STEM-EMCD in 3-beam orientation using a quadruple aperture.

The need to acquire multiple angle-resolved electron energy loss spectra (EELS) is one of the several critical challenges associated with electron magnetic circular dichroism (EMCD) experiments. If the experiments are performed by scanning a nanometer to atomic-sized electron probe on a specific region of a sample, the precision of the local magnetic information extracted from such data highly depends on the accuracy of the spatial registration between multiple scans. For an EMCD experiment in a 3-beam orientation, this means that the same specimen area must be scanned four times while keeping all the experimental conditions same.

Quantum-well states at the surface of a heavy-fermion superconductor.

Two-dimensional electronic states at surfaces are often observed in simple wide-band metals such as Cu or Ag (refs. ). Confinement by closed geometries at the nanometre scale, such as surface terraces, leads to quantized energy levels formed from the surface band, in stark contrast to the continuous energy dependence of bulk electron bands.

Speech and gait abnormalities in motor subtypes of de-novo Parkinson's disease.

Aim: To investigate the presence and relationship of temporal speech and gait parameters in patients with postural instability/gait disorder (PIGD) and tremor-dominant (TD) motor subtypes of Parkinson's disease (PD).

Methods: Speech samples and instrumented walkway system assessments were acquired from a total of 60 de-novo PD patients (40 in TD and 20 in PIGD subtype) and 40 matched healthy controls. Objective acoustic vocal assessment of seven distinct speech timing dimensions was related to instrumental gait measures including velocity, cadence, and stride length.

Simulations of magnetic Bragg scattering in transmission electron microscopy.

We have simulated the magnetic Bragg scattering in transmission electron microscopy in two antiferromagnetic compounds, NiO and LaMnAsO. This weak magnetic phenomenon was experimentally observed in NiO by Loudon (2012). We have computationally reproduced Loudon's experimental data, and for comparison we have performed calculations for the LaMnAsO compound as a more challenging case, containing lower concentration of magnetic elements and strongly scattering heavier non-magnetic elements.

Speech biomarkers in Huntington's disease: A cross-sectional study in pre-symptomatic, prodromal and early manifest stages.

Background And Purpose: Motor speech alterations are a prominent feature of clinically manifest Huntington's disease (HD). Objective acoustic analysis of speech can quantify speech alterations. It is currently unknown, however, at what stage of HD speech alterations can be reliably detected.