AUTHOR=Castagnola Elisa , Maggiolini Emma , Ceseracciu Luca , Ciarpella Francesca , Zucchini Elena , De Faveri Sara , Fadiga Luciano , Ricci Davide TITLE=pHEMA Encapsulated PEDOT-PSS-CNT Microsphere Microelectrodes for Recording Single Unit Activity in the Brain JOURNAL=Frontiers in Neuroscience VOLUME=10 YEAR=2016 URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2016.00151 DOI=10.3389/fnins.2016.00151 ISSN=1662-453X ABSTRACT=

The long-term reliability of neural interfaces and stability of high-quality recordings are still unsolved issues in neuroscience research. High surface area PEDOT-PSS-CNT composites are able to greatly improve the performance of recording and stimulation for traditional intracortical metal microelectrodes by decreasing their impedance and increasing their charge transfer capability. This enhancement significantly reduces the size of the implantable device though preserving excellent electrical performances. On the other hand, the presence of nanomaterials often rises concerns regarding possible health hazards, especially when considering a clinical application of the devices. For this reason, we decided to explore the problem from a new perspective by designing and testing an innovative device based on nanostructured microspheres grown on a thin tether, integrating PEDOT-PSS-CNT nanocomposites with a soft synthetic permanent biocompatible hydrogel. The pHEMA hydrogel preserves the electrochemical performance and high quality recording ability of PEDOT-PSS-CNT coated devices, reduces the mechanical mismatch between soft brain tissue and stiff devices and also avoids direct contact between the neural tissue and the nanocomposite, by acting as a biocompatible protective barrier against potential nanomaterial detachment. Moreover, the spherical shape of the electrode together with the surface area increase provided by the nanocomposite deposited on it, maximize the electrical contact and may improve recording stability over time. These results have a good potential to contribute to fulfill the grand challenge of obtaining stable neural interfaces for long-term applications.