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The cochlear implant (CI) is currently the gold standard in treating sensorineural hearing loss (SNHL) as it activates the cochlear nerve bypassing the hair cells, allowing the brain to hear sound waves. The goal of ongoing research is to create self-powered cochlear stimulation devices based on piezoelectric nanomaterials that can improve the quality of life for patients with SNHL and reduce the side effects of traditional CIs. Polyvinyldifluoride (PVDF) piezoelectric nanofibers are a new type of piezoelectric nanostructure developed for biological purposes. The fiber can be coated with barium titan-ate (BaTiO3) nanoparticles or graphene nanosheets (GN) to enhance the piezoelectric coefficients. The purpose of the study is to evaluate the in vitro biocompatibility of PVDF na-nofibers, which appear promising as alternatives for producing next-generation CIs. Pure PVDF, BaTiO3-coated PVDF, and GN-coated PVDF were evaluated on three cell lines: HaCaT, OC-k3, and PC12. Viability, morphological changes, and neuritic outgrowth were evaluated in vitro using these cell lines as a model for the cochlear tissues. The morphology study indicated that HaCaT, OC-k3, and PC12 cells were healthy, well-preserved, and had normal structural characteristics at all times tested. According to cell viability results, the fibers caused an increase in cell metabolism after 72 hours of incubation, especially on OC-k3 and PC12. On the HaCaT cell line, the fibers exhibited a slight but not significant reduction of cell metabolic activity starting from 48 hours of exposure. In addition, BaTiO3-coated PVDF have the most favorable results when it comes to the number of branch points and average length of neurites in PC12 cells, leading to a conclusion that BaTiO3 nanoparti-cles enhance the complex processes of PC12 cells. To summarize, the investigation revealed that the tested na-nofibers exhibited high biocompatibility in vitro, particularly with cochlear and neuronal cells, and the piezoelectric nanofibers with barium titanate particles be used to develop the next generation of self-powered cochlear implants. To conclude, these piezoelectric nanofibers have the ability to stimulate the cochlea, even though additional research is needed to achieve adequate mechanical and electrical performance. [ABSTRACT FROM AUTHOR]

The directed transfer function (DTF) and the partial directed coherence (PDC) are frequency-domain estimators that are able to describe interactions between cortical areas in terms of the concept of Granger causality. However, the classical estimation of these methods is based on the multivariate autoregressive modelling (MVAR) of time series, which requires the stationarity of the signals. In this way, transient pathways of information transfer remains hidden. The objective of this study is to test a time-varying multivariate method for the estimation of rapidly changing connectivity relationships between cortical areas of the human brain, based on DTF/PDC and on the use of adaptive MVAR modelling (AMVAR) and to apply it to a set of real high resolution EEG data. This approach will allow the observation of rapidly changing influences between the cortical areas during the execution of a task. The simulation results indicated that time-varying DTF and PDC are able to estimate correctly the imposed connectivity patterns under reasonable operative conditions of signal-to-noise ratio (SNR) ad number of trials. An SNR of five and a number of trials of at least 20 provide a good accuracy in the estimation. After testing the method by the simulation study, we provide an application to the cortical estimations obtained from high resolution EEG data recorded from a group of healthy subject during a combined foot-lips movement and present the time-varying connectivity patterns resulting from the application of both DTF and PDC. Two different cortical networks were detected with the proposed methods, one constant across the task and the other evolving during the preparation of the joint movement. Index Terms--Cortical connectivity, directed transfer function (DTF), high resolution electroencephalography (EEG), limb movement, partial directed coherence (PDC), recursive least squares (RLS).