Precision Microfluidic Control of Neuronal Ensembles in Cultured Cortical Networks

Abstract In vitro neuronal culture is an important research platform in cellular and network neuroscience. However, neurons cultured on a homogeneous scaffold form dense, randomly connected networks and display excessively synchronized activity; this phenomenon has limited their applications in network‐level studies, such as studies of neuronal ensembles, or coordinated activity by a group of neurons. Herein, polydimethylsiloxane‐based microfluidic devices are developed to create small neuronal networks exhibiting a hierarchically modular structure resembling the connectivity observed in the mammalian cortex. The strength of intermodular coupling is manipulated by varying the width and height of the microchannels that connect the modules. Neuronal activity recording via calcium imaging shows that the spontaneous activity in networks with smaller microchannels (2.2–5.5 µm 2 ) has lower synchrony and exhibits a threefold variety of neuronal ensembles. Optogenetic stimulation demonstrates that a reduction in intermodular coupling enriches evoked neuronal activity patterns and that repeated stimulation induces plasticity in neuronal ensembles in these networks. These findings suggest that cell engineering technologies based on microfluidic devices enable in vitro reconstruction of the intricate dynamics of neuronal ensembles, thus providing a robust platform for studying neuronal ensembles in a well‐defined physicochemical environment.

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Publication Details

Journal
Advanced Materials Technologies
Published
2024-11-23
DOI
https://doi.org/10.1002/admt.202400894
Citations
7
Primary Topic
Neuroscience and Neural Engineering
Type
article
Field-Weighted Citation Impact
1.88

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article

Precision Microfluidic Control of Neuronal Ensembles in Cultured Cortical Networks

Hakuba Murota, Hideaki Yamamoto, Ayumi Hirano‐Iwata, Nobuaki Monma et al.
7 citations
Advanced Materials Technologies
Neuroscience and Neural Engineering
1.88
article

Precision Microfluidic Control of Neuronal Ensembles in Cultured Cortical Networks

Hakuba Murota, Hideaki Yamamoto, Ayumi Hirano‐Iwata, Nobuaki Monma, Shigeo Sato
article en
7 citations

Abstract

Abstract In vitro neuronal culture is an important research platform in cellular and network neuroscience. However, neurons cultured on a homogeneous scaffold form dense, randomly connected networks and display excessively synchronized activity; this phenomenon has limited their applications in network‐level studies, such as studies of neuronal ensembles, or coordinated activity by a group of neurons. Herein, polydimethylsiloxane‐based microfluidic devices are developed to create small neuronal networks exhibiting a hierarchically modular structure resembling the connectivity observed in the mammalian cortex. The strength of intermodular coupling is manipulated by varying the width and height of the microchannels that connect the modules. Neuronal activity recording via calcium imaging shows that the spontaneous activity in networks with smaller microchannels (2.2–5.5 µm 2 ) has lower synchrony and exhibits a threefold variety of neuronal ensembles. Optogenetic stimulation demonstrates that a reduction in intermodular coupling enriches evoked neuronal activity patterns and that repeated stimulation induces plasticity in neuronal ensembles in these networks. These findings suggest that cell engineering technologies based on microfluidic devices enable in vitro reconstruction of the intricate dynamics of neuronal ensembles, thus providing a robust platform for studying neuronal ensembles in a well‐defined physicochemical environment.

Advanced Materials TechnologiesVol. 10(4)
Tohoku University (JP), Advanced Institute of Materials Science (JP)
Japan Science and Technology Corporation, Ministry of Education, Culture, Sports, Science and Technology, Japan Society for the Promotion of Science, Research Institute of Electrical Communication, Tohoku University, Core Research for Evolutional Science and Technology
Openalex Percentile: Top 14%
Neuroscience and Neural Engineering
1.88
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