Ultra‐Flexible µ‐ECoG Arrays Based on PEDOT:PSS Micropillars

Abstract Devices capable of recording electrophysiological signals with high signal‐to‐noise ratio (SNR) and spatiotemporal resolution are crucial in neurological research. The introduction of flexible materials and conductive polymers in the fabrication of multi electrode arrays (MEAs) for electrocorticography (ECoG) enabled higher quality of recorded signals thanks to device conformability and to low‐impedance electrodes. Advances in microfabrication techniques allow a dramatic reduction in electrode size, leading to highly‐dense microelectrode arrays with increased spatial resolution. Here, the synergic contribution of surface micropatterning and of conductive polymers on the recording performance of a home‐built µECoG device is explored. The device is fabricated through a combination of conventional and unconventional micropatterning techniques, leading to an ultra‐conformable polydimethylsiloxane (PDMS) array featuring different‐size flexible micropillars forests coated with a thin layer of poly(3,4‐ethylenedioxythiophene) poly(styrenesulfonate) (PEDOT:PSS). The performance of the device is assessed in vitro by electrochemical impedance spectroscopy and in vivo by detecting somatosensory evoked potentials from the somatosensory cortex of a rat. The increasing of the geometric area has only limited effect on the recording capability in the in vivo model investigated. Nevertheless, the extremely high SNR values obtained place the proposed approach as an innovative and versatile strategy for the prototyping of ultra‐conformable µECoG devices.

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Institutions

Publication Details

Journal
Advanced Materials Interfaces
Published
2025-03-20
DOI
https://doi.org/10.1002/admi.202500051
Citations
5
Primary Topic
Neuroscience and Neural Engineering
Type
article
Field-Weighted Citation Impact
4.55
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article

Ultra‐Flexible µ‐ECoG Arrays Based on PEDOT:PSS Micropillars

Riccardo Viaro, Alice Lunghi, Fabio Biscarini, Michele Bianchi et al.
5 citations
Advanced Materials Interfaces
Neuroscience and Neural Engineering
4.55
article

Ultra‐Flexible µ‐ECoG Arrays Based on PEDOT:PSS Micropillars

Riccardo Viaro, Alice Lunghi, Fabio Biscarini, Michele Bianchi, Luciano Fadiga, Michele Di Lauro, Pierpaolo Greco
article en
5 citations

Abstract

Abstract Devices capable of recording electrophysiological signals with high signal‐to‐noise ratio (SNR) and spatiotemporal resolution are crucial in neurological research. The introduction of flexible materials and conductive polymers in the fabrication of multi electrode arrays (MEAs) for electrocorticography (ECoG) enabled higher quality of recorded signals thanks to device conformability and to low‐impedance electrodes. Advances in microfabrication techniques allow a dramatic reduction in electrode size, leading to highly‐dense microelectrode arrays with increased spatial resolution. Here, the synergic contribution of surface micropatterning and of conductive polymers on the recording performance of a home‐built µECoG device is explored. The device is fabricated through a combination of conventional and unconventional micropatterning techniques, leading to an ultra‐conformable polydimethylsiloxane (PDMS) array featuring different‐size flexible micropillars forests coated with a thin layer of poly(3,4‐ethylenedioxythiophene) poly(styrenesulfonate) (PEDOT:PSS). The performance of the device is assessed in vitro by electrochemical impedance spectroscopy and in vivo by detecting somatosensory evoked potentials from the somatosensory cortex of a rat. The increasing of the geometric area has only limited effect on the recording capability in the in vivo model investigated. Nevertheless, the extremely high SNR values obtained place the proposed approach as an innovative and versatile strategy for the prototyping of ultra‐conformable µECoG devices.

Advanced Materials InterfacesVol. 12(12)
University of Modena and Reggio Emilia (IT), University of Ferrara (IT), Italian Institute of Technology (IT), Center for Translational Neurophysiology of Speech and Communication (IT)
Openalex Percentile: Top 6%
Neuroscience and Neural Engineering
4.55
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