Simulation of developing human neuronal cell networks.

BACKGROUND: Microelectrode array (MEA) is a widely used technique to study for example the functional properties of neuronal networks derived from human embryonic stem cells (hESC-NN). With hESC-NN, we can investigate the earliest developmental stages of neuronal network formation in the human brain. METHODS: In this paper, we propose an in silico model of maturating hESC-NNs based on a phenomenological model called INEX. We focus on simulations of the development of bursts in hESC-NNs, which are the main feature of neuronal activation patterns. The model was developed with data from developing hESC-NN recordings on MEAs which showed increase in the neuronal activity during the investigated six measurement time points in the experimental and simulated data. RESULTS: Our simulations suggest that the maturation process of hESC-NN, resulting in the formation of bursts, can be explained by the development of synapses. Moreover, spike and burst rate both decreased at the last measurement time point suggesting a pruning of synapses as the weak ones are removed. CONCLUSIONS: To conclude, our model reflects the assumption that the interaction between excitatory and inhibitory neurons during the maturation of a neuronal network and the spontaneous emergence of bursts are due to increased connectivity caused by the forming of new synapses.

Hearing Care Providers' Perspectives on the Utility of Datalogging Information.

Purpose The aim of the study was to learn (a) how datalogging information is being used in clinical practice by hearing care providers (HCPs) in the United States and (b) HCPs' opinions about how information collected through the hearing aids could be broadened in clinical application. Method A mixed-method approach was undertaken consisting of an online quantitative survey and qualitative structured telephone interviews. Survey data were analyzed using descriptives and chi-square analyses. The interview data were transcribed and analyzed using inductive content analysis. Results In total, 154 HCPs completed the survey, of whom 10 also completed an interview. Survey data showed that most HCPs use datalogging for conventional applications, such as counseling and fine-tuning during a hearing aid trial. Interview data highlighted four additional desirable datalogging features: (a) data about the sound environment, (b) details about operational aspects of hearing aid use, (c) data about use and nonuse, and (d) automated diagnosis of a hearing aid malfunction. HCPs also envisaged using datalogging in novel ways, such as for demonstrating hearing aid value and supporting decision making. Conclusions Today, datalogging is primarily used as a tool for counseling clients about hours and patterns of hearing aid use and for troubleshooting and fine-tuning. However, HCPs suggested novel and more ambitious uses of datalogging such as for sending alerts about nonuse, for automated diagnosis of a hearing aid malfunction, and for helping the client in their decision making. It remains to be seen whether in the future these will be implemented into clinical practice.

Associations Between Hearing Performance and Physiological Measures - An Overview and Outlook.

The current paper summarises the research investigating associations between physiological data and hearing performance. An overview of state-of-the-art research and literature is given as well as promising directions for associations between physiological data and data regarding hearing loss and hearing performance. The physiological parameters included in this paper are: electrodermal activity, heart rate variability, blood pressure, blood oxygenation and respiratory rate. Furthermore, the environmental and behavioural measurements of physical activity and body mass index, alcohol consumption and smoking have been included. So far, only electrodermal activity and heart rate variability are physiological signals simultaneously associated with hearing loss or hearing performance. Initial findings suggest blood pressure and respiratory rate to be the most promising physiological measures that relate to hearing loss and hearing performance.