An improved platform for cultured neuronal network electrophysiology: multichannel optogenetics integrated with MEAs

Bayat F. K., ALP M. İ., BOSTAN S., Gülçür H. Ö., ÖZTÜRK G., Güveniş A.

European Biophysics Journal, vol.51, no.6, pp.503-514, 2022 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 51 Issue: 6
  • Publication Date: 2022
  • Doi Number: 10.1007/s00249-022-01613-0
  • Journal Name: European Biophysics Journal
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, BIOSIS, EMBASE, INSPEC, MEDLINE
  • Page Numbers: pp.503-514
  • Keywords: Microelectrode array (MEA), Optogenetic stimulation, Cultured neuronal networks (CNN), Digital light processing (DLP), Closed-loop electrophysiology, Network electrophysiology
  • Istanbul Medipol University Affiliated: Yes


Cultured neuronal networks (CNNs) are powerful tools for studying how neuronal representation and adaptation emerge in networks of controlled populations of neurons. To ensure the interaction of a CNN and an artificial setting, reliable operation in both open and closed loops should be provided. In this study, we integrated optogenetic stimulation with microelectrode array (MEA) recordings using a digital micromirror device and developed an improved research tool with a 64-channel interface for neuronal network control and data acquisition. We determined the ideal stimulation parameters including light intensity, frequency, and duty cycle for our configuration. This resulted in robust and reproducible neuronal responses. We also demonstrated both open and closed loop configurations in the new platform involving multiple bidirectional channels. Unlike previous approaches that combined optogenetic stimulation and MEA recordings, we did not use binary grid patterns, but assigned an adjustable-size, non-binary optical spot to each electrode. This approach allowed simultaneous use of multiple input–output channels and facilitated adaptation of the stimulation parameters. Hence, we advanced a 64-channel interface in that each channel can be controlled individually in both directions simultaneously without any interference or interrupts. The presented setup meets the requirements of research in neuronal plasticity, network encoding and representation, closed-loop control of firing rate and synchronization. Researchers who develop closed-loop control techniques and adaptive stimulation strategies for network activity will benefit much from this novel setup.