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A depth-customizable double-sided 3D neural probe array for simultaneous investigation of multiple brain regions

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Title
A depth-customizable double-sided 3D neural probe array for simultaneous investigation of multiple brain regions
Issued Date
2025-12
Citation
SENSORS AND ACTUATORS A-PHYSICAL, v.395
Type
Article
Author Keywords
Functional connectivityDepth-customizableFlexible PCBNeural signal recording3D configurationDouble-sided neural probe
Keywords
ELECTRODE ARRAY
ISSN
0924-4247
Abstract

Understanding the complex neural circuits within the brain requires advanced tools capable of simultaneously recording signals from multiple regions and depths. However, previously developed tools have limited capability to address 3D structures in the brain as they typically feature fixed probe lengths and single-sided electrode configurations. To overcome these challenges, we developed a depth-customizable 3D electrode array structure comprising double-sided 2D neural probe arrays via flexible printed circuit board technology with a zeroinsertion-force connector and a supporting board without requiring additional fabrication steps. This enables precise depth adjustments and the double-sided electrode configuration effectively doubles the number of recording sites, thereby facilitating volumetric and comprehensive neural signal acquisition. Our device allows user-defined adjustment of probe spacing, achieving a minimum inter-probe distance of 1 mm, and enables finetuned control of insertion depth for precise targeting of specific brain regions, with a maximum depth difference of only 0.168 mm. Also, by employing a PSR ink insulation layer, we achieved a total probe thickness of approximately 80 mu m, resulting in a compact design that eliminates the need for complex semiconductor processes. Validation of the device in vivo demonstrated its capability to simultaneously monitor neural signals from multiple brain regions. Its depth-customizable design facilitated functional connectivity studies across various depths, the results of which could provide critical insights into neural network dynamics. Our approach significantly enhances the flexibility, scalability, and efficiency of neural probes and provides a powerful platform for neuroscience research into areas such as brain-machine interface development and functional connectivity.

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URI
https://scholar.dgist.ac.kr/handle/20.500.11750/60450
DOI
10.1016/j.sna.2025.117084
Publisher
ELSEVIER SCIENCE SA
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