Tuning Microelectrodes' Impedance to Improve Fast Ripples Recording.

Epilepsy is a chronic neurological disorder characterized by recurrent seizures resulting from abnormal neuronal hyperexcitability. In the case of pharmacoresistant epilepsy requiring resection surgery, the identification of the Epileptogenic Zone (EZ) is critical. Fast Ripples (FRs; 200-600 Hz) are one of the promising biomarkers that can aid in EZ delineation. However, recording FRs requires physically small electrodes. These microelectrodes suffer from high impedance, which significantly impacts FRs' observability and detection. In this study, we investigated the potential of a conductive polymer coating to enhance FR observability. We employed biophysical modeling to compare two types of microelectrodes: Gold (Au) and Au coated with the conductive polymer poly(3,4-ethylenedioxythiophene)-poly(styrene sulfonate) (Au/PEDOT:PSS). These electrodes were then implanted into the CA1 hippocampal neural network of epileptic mice to record FRs during epileptogenesis. The results showed that the polymer-coated electrodes had a two-order lower impedance as well as a higher transfer function amplitude and cut-off frequency. Consequently, FRs recorded with the PEDOT:PSS-coated microelectrode yielded significantly higher signal energy compared to the uncoated one. The PEDOT:PSS coating improved the observability of the recorded FRs and thus their detection. This work paves the way for the development of signal-specific microelectrode designs that allow for better targeting of pathological biomarkers.

Model-Guided Design of Microelectrodes for HFO Recording.

High Frequency Oscillations (HFOs, 200-600 Hz) are recognized as a biomarker of epileptogenic brain areas. This work aims at designing novel microelectrodes in order to optimize the recording and further detection of HFOs in brain (intracerebral electroencephalography, iEEG). The quality of the recorded iEEG signals is highly dependent on the electrode contact impedance, which is determined by the characteristics of the recording electrode (geometry, position, material). These properties are essential for the observability of HFOs. In this study, a previously published hippocampal neural network model is used for the simulation of interictal HFOs. An additional microelectrode model layer is implemented in order to simulate the impact of using different types and characteristics of microelectrodes on the recorded HFOs. Results indicate that a small layer PEDOT/PSS and PEDOT/CNT on microelectrodes can effectively decrease their impedance resulting in the increase of HFOs observability. This model-based study can lead to the actual design of new electrodes that will ultimately contribute to improved diagnosis prior to invasive therapies.