Time course of EEG complexity reflects attentional engagement during listening to speech in noise.

Auditory distractions are recognized to considerably challenge the quality of information encoding during speech comprehension. This study explores electroencephalography (EEG) microstate dynamics in ecologically valid, noisy settings, aiming to uncover how these auditory distractions influence the process of information encoding during speech comprehension. We examined three listening scenarios: (1) speech perception with background noise (LA), (2) focused attention on the background noise (BA), and (3) intentional disregard of the background noise (BUA).

Health Outcomes with Curative and Palliative Therapies in Real World: Role of the Quality of Life Summary Score in Thoracic Oncology Patients.

Background: For patients receiving therapy with curative or palliative intent for a thoracic malignancy, prediction of quality of life (QOL), once therapy starts, remains challenging. The role of health assessments by the patient instead of the doctor herein remains ill-defined.

Aims: To assess the evolution of QOL in patients with thoracic malignancies treated with curative and palliative intent, respectively.

Parkinson's disease affects the neural alpha oscillations associated with speech-in-noise processing.

Parkinson's disease (PD) has increasingly been associated with auditory dysfunction, including alterations regarding the control of auditory information processing. Although these alterations may interfere with the processing of speech in degraded listening conditions, behavioural studies have generally found preserved speech-in-noise recognition in PD. However, behavioural speech audiometry does not capture the neurophysiological mechanisms supporting speech-in-noise processing.

Developing a Multi-channel Beamformer by Enhancing Spatially Constrained ICA for Recovery of Correlated EEG Sources.

Background: Brain source imaging based on electroencephalogram (EEG) data aims to recover the neuron populations' activity producing the scalp potentials. This procedure is known as the EEG inverse problem. Recently, beamformers have gained a lot of consideration in the EEG inverse problem.

EEG Correlates of Learning From Speech Presented in Environmental Noise.

How the human brain retains relevant vocal information while suppressing irrelevant sounds is one of the ongoing challenges in cognitive neuroscience. Knowledge of the underlying mechanisms of this ability can be used to identify whether a person is distracted during listening to a target speech, especially in a learning context. This paper investigates the neural correlates of learning from the speech presented in a noisy environment using an ecologically valid learning context and electroencephalography (EEG).

Analysis of induced error by susceptibility effect in low-density gel dosimeters.

Purpose: In low-density (LD) gel dosimeter, diffusive spin-spin relaxation rate (R2)-dispersion caused by susceptibility-induced internal gradient leads to a significant deviation in the measured R2 from the real value. In this study, the effect of induced internal gradient on R2 was visualized and quantified algebraically as an important cause of inaccuracy in LD gel dosimeters.

Materials And Methods: In this method, two sets of LD and unit-density (UD) gel dosimeters were prepared.

A novel quantification method for low-density gel dosimeter.

Aim: Low signal-to-noise ratio (SNR) images of lung-like (low-density [LD]) gel dosimeters, compared to unit-density (UD) gels, necessitate the use of different quantification methods.

Setting And Design: In this study, a new method is introduced based on noise correction and exponential (NCEXP) fitting. The feasibility of NCEXP method for quantifying dose absorption in LD gels is evaluated.

Prenatal transplantation of epidermal neural crest stem cells in malformation of cortical development mouse model.

Prenatal interventions may offer an immense opportunity in therapeutic protocols of malformations of cortical development (MCD). Epidermal neural crest stem cells (EPI-NCSCs) of the hair follicle bulge exhibit features of both embryonic and adult stem cells; these cells maintain their neurologic differentiation capability because of their neural crest origin. However, it is unknown if prenatal use of EPI-NCSCs could be beneficial in targeting methylazoxymethanol (MAM)-induced MCD, which further addressed in the present work.

A statistical approach in human brain connectome of Parkinson Disease in elderly people using Network Based Statistics.

Parkinson's Disease (PD) is a progressive neurodegenerative disorder assumed to involve different areas of CNS and PNS. Thus, Diffusion Tensor Imaging (DTI) is used to examine the areas engaged in PD neurodegeneration. In the present study, we computed average tract length and fiber volume as a measure of white matter integrity and adopted Network Based Statistics (NBS) to conduct group analyses between age- and gender-matched PD patients and healthy control connectivity matrices.

Evaluation of adaptive PARAFAC alogorithms for tracking of simulated moving brain sources.

In this paper, we proposed an online 2D localization method for tracking of dynamic moving brain sources. For this purpose, we used an adaptive version of PARAllel FACtor (PARAFAC) analysis for factorization of electroencephalographic (EEG) signals. We utilized Boundary Element Method (BEM) with four layers to solve the forward problem for the simulated EEG signals caused by two moving dipoles within the brain.