Purpose: Variations in neural survival along the cochlear implant electrode array leads to off-place listening, resulting in poorer speech understanding outcomes for recipients. Therefore, it is important to develop and compare clinically viable tests to identify these patient-specific intra-cochlear neural differences.
Methods: Nineteen experienced cochlear implant recipients (9 males and 10 females) were recruited for this study. We estimated the neural health along the electrode array for a group of experienced adult implant recipients using two methods: the difference between psychophysical detection thresholds in bipolar vs. monopolar mode and the panoramic electrically evoked compound action potential method (PECAP). We hypothesised that: neural health estimated using both methods at single electrodes will be correlated at the participant level and the group level; and participants with larger variations in neural health along the electrode array will have poorer speech outcomes.
Results: At the individual level, the two neural measures correlated significantly across electrodes (p < 0.05) for 5 out of 15 participants. At the group level, we observed a weak but significant across-electrode correlation (R = 0.111, p < 0.001). While a larger variation in neural measures estimated from psychophysical thresholds was associated with lower phoneme speech scores (R = 0.499, p < 0.01), no significant association was found between variations in PECAP's neural health estimates and phoneme speech scores (R = 0.082, p = 0.366).
Conclusion: Our evidence suggests that both methods likely quantify a shared underlying neural basis, hypothesised to be the neural health along the cochlear implant array. The differences between the two measures may be attributed to differences in stimulus rate or loudness used to elicit responses and/or the influence of factors arising more centrally than the auditory nerve.
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http://dx.doi.org/10.1007/s10162-024-00972-z | DOI Listing |
Front Public Health
January 2025
Department of Computer Science, College of Engineering and Computer Science, Jazan University, Jazan, Saudi Arabia.
Introduction: The growing demand for real-time, affordable, and accessible healthcare has underscored the need for advanced technologies that can provide timely health monitoring. One such area is predicting arterial blood pressure (BP) using non-invasive methods, which is crucial for managing cardiovascular diseases. This research aims to address the limitations of current healthcare systems, particularly in remote areas, by leveraging deep learning techniques in Smart Health Monitoring (SHM).
View Article and Find Full Text PDFFront Neural Circuits
January 2025
Department of Advanced Medical and Surgical Sciences, Advanced MRI Research Center, University of Campania "Luigi Vanvitelli", Naples, Italy.
The substantia nigra pars compacta (SNc), one of the main dopaminergic nuclei of the brain, exerts a regulatory function on the basal ganglia circuitry via the nigro-striatal pathway but its possible dopaminergic innervation of the thalamus has been only investigated in non-human primates. The impossibility of tract-tracing studies in humans has boosted advanced MRI techniques and multi-shell high-angular resolution diffusion MRI (MS-HARDI) has promised to shed more light on the structural connectivity of subcortical structures. Here, we estimated the possible dopaminergic innervation of the human thalamus via an MS-HARDI tractography of the SNc in healthy human young adults.
View Article and Find Full Text PDFWorld Allergy Organ J
January 2025
Guangdong Provincial Engineering Research Center of Public Health Detection and Assessment, NMPA Key Laboratory for Technology Research and Evaluation of Pharmacovigilance, School of Public Health, Guangdong Pharmaceutical University, Guangzhou, 510006, Guangdong, PR China.
Background: Many studies reported the influence of infants' gut microbiota on atopic dermatitis (AD) postnatally, yet the role of maternal gut microbiota and plasma metabolites in infants' AD remains largely unexplored.
Methods: Sixty-three pregnant mother-infants were enrolled and followed after childbirth in Guangzhou, China. Demographic information, maternal stool and plasma samples, and records for infants' AD were collected.
Front Cardiovasc Med
January 2025
Shengli Clinical Medical College of Fujian Medical University, Fujian Medical University, Fuzhou, Fujian, China.
Background: Depression is being increasingly acknowledged as an important risk factor contributing to coronary heart disease (CHD). Currently, there is no predictive model specifically designed to evaluate the risk of coronary heart disease among individuals with depression. We aim to develop a machine learning (ML) model that will analyze risk factors and forecast the probability of coronary heart disease in individuals suffering from depression.
View Article and Find Full Text PDFBioact Mater
April 2025
Beijing Key Laboratory for Biomaterials and Neural Regeneration, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing 100083, China.
The mammalian brain has an extremely limited ability to regenerate lost neurons and to recover function following ischemic stroke. A biomaterial strategy of slowly-releasing various regeneration-promoting factors to activate endogenous neurogenesis represents a safe and practical neuronal replacement therapy. In this study, basic fibroblast growth factor (bFGF)-Chitosan gel is injected into the stroke cavity.
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