Tuning the Impedance of Flexible Neural Interfaces by Controlled Polymerization of PEDOT:PSS to Resolve Epileptic Fast Ripples

In drug-resistant partial epilepsies, resective surgery is the treatment of choice to suppress seizures. In this context, the capacity to rely on objective biomarkers of the EZ is fundamental to define the optimal surgical approach in the specific context of each patient. Electrophysiological signals are one of the most reliable biomarkers which represent local field potential variations generated by a network of neurons. Among electrophysiological signals, fast ripples (FR) are specific to the epileptogenic zone (EZ). Their frequencies range between 250 to 600 Hz and they are mixed with ongoing activities. Routine clinical use of FRs as a reliable biomarker needs better understanding of which information they carry and how it correlates with epileptogenic seizures [1].<br/>We propose a novel solution to tune the recording electrodes properties for improving the detection of FRs. In the first step, we optimized the electrode's properties such as size and material . Computational model of eplipetic hippocampus neural network [2] allows us to characterize the response of the electrodes to the local field potential and subsequently attenuation of FRs .<br/>Simulations show that small electrodes have better resolution due to spatial averaging. However FRs attenuation scales up by lowering the electrode size due to the electrod’s low electrical performance. In this context, coating electrodes with conductive polymers is a successful strategy to reduce the interface impedance. The most common conductive polymer is Poly(3,4-ethylenedioxythiophene)-poly (styrene sulfonate) (PEDOT/PSS) [3]. Here, the impedance of electrodes is tuned by controlling the kinetic of PEDOT:PSS electropolymerization. PEDOT:PSS coated electrodes are characterized in terms of structure, impedance, electrical conductivity, electrochemical stability, uv-visible and fourier transform infrared spectrum. The double layer capacitance of the electrodes is measured experimentally and modeled with an equivalent circuit.<br/>Finally, microelectrodes with various impedance were implanted in a kainate mice model of temporal lobe epilepsy and the local field potential was recorded for 28 days. Signals were classified with restrictive criteria to detect the FRs. In vivo evaluations reveal that the amplitude of the FRs signals and the signal to background ratio increased by lowering the impedance at the tissue-electrode interface. This result is compatible with the computational neural model. We also found that the cut-off frequency of the electrodes influences the resolvability of FRs. Signals above cut-off frequency are phase shifted and nonlinearly distorted. We modulated the cut-off frequency of electrodes by controlling the PEDOT:PSS thickness and lowered it to the frequencies below FR’s band.<br/>References:<br/>[1] J. Jacobs and M. Zijlmans, “HFO to Measure Seizure Propensity and Improve Prognostication in Patients With Epilepsy,” Epilepsy Curr., vol. 20, no. 6, pp. 338–347, 2020.<br/>[2] M. Al Harrach, H. Mousavi, G. Dieuset, E. Ismailova, and F. Wendling, “Model-Guided Design of Microelectrodes for HFO Recording,” Proc. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. EMBS, vol. 2020-July, pp. 3428–3431, 2020.<br/>[3] M. J. Donahue et al., “Tailoring PEDOT properties for applications in bioelectronics,” Mater. Sci. Eng. R Reports, vol. 140, no. January, p. 100546, 2020.