Improving Fast Ripples Recording with Model-Guided Design of Microelectrodes

Objective: Microelectrodes allow for the recording of neural activities with a high spatial resolution. However, their small sizes result in their high impedance, therefore, leading to a high thermal noise and a poor signal- to-noise ratio. In the context of drug-resistant epilepsy, efficient Fast Ripples (FRs; 250-600 Hz) detection can help in pre-surgical investigations and delineation of epileptic zones. Consequently, good quality recordings with a high spatial resolution promise to improve the surgical outcome. This work aims at proposing a reliable model-based microelectrode design that is optimized for FRs recordings and detection.

Methods: A 3D microscale computational model simulates the FRs generated in the CA1 subfield of the hippocampus. It couples with the electrode-tissue interface characteristics that account for the microelectrode’s biophysical properties and their impact on the recorded signal. To validate this model, analyses of the electrode’s geometrical (diameter, position, and direction) and physical (materials, coating) characteristics were con- ducted in order to propose an optimal microelectrode de- sign tuned for FRs recording. In addition, 

Results: Experimental signals were recorded from mice in the hippocampal CA1 subfield from different electrodes for comparison. ( between stainless steel, gold and gold coated with poly(3,4-ethylene dioxythiophene) /Poly(styrene sulfonate) (PEDOT/PSS)).

Conclusion: Both in silico and in vivo quantified results show a clear improvement in FRs observability using PEDOT/PSS coated microelectrode.