Neural sensing of electrical activity with stretchable microelectrode arrays

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Abstract

Sensing neural activity within mechanically active tissues poses particular hurdles because most electrodes are much stiffer than biological tissues. As the tissue deforms, the rigid electrodes may damage the surrounding tissue. The problem is exacerbated when sensing neural activity in experimental models of traumatic brain injury (TBI) which is caused by the rapid and large deformation of brain tissue. We have developed a stretchable microelectrode array (SMEA) that can withstand large elastic deformations (> 5% biaxial strain) while continuing to function. The SMEA were fabricated from thin metal conductors patterned on polydimethylsiloxane (PDMS) and encapsulated with a photo-patternable silicone. SMEA were used to record spontaneous activity from brain slice cultures, as well as evoked activity after stimulating through SMEA electrodes. Slices of brain tissue were grown on SMEA in long-term culture and then mechanically injured with our well-characterized in vitro injury model by stretching the SMEA and the adherent culture, which was confirmed by image analysis. Because brain tissue was grown on the substrate-integrated SMEA, post-injury changes in electrophysiological function were normalized to pre-injury function since the SMEA deformed with the tissue and remained in place during mechanical stimulation. The combination of our injury model and SMEA could help elucidate mechanisms responsible for post-traumatic neuronal dysfunction in the quest for TBI therapies. The SMEA may have additional sensing applications in other mechanically active tissues such as peripheral nerve and heart. ©2009 IEEE.

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Yu, Z., Graudejus, O., Lacour, S. P., Wagner, S., & Morrison, B. (2009). Neural sensing of electrical activity with stretchable microelectrode arrays. In Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 (pp. 4210–4213). IEEE Computer Society. https://doi.org/10.1109/IEMBS.2009.5333791

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