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Neural Activity Propagation in an Unfolded Hippocampal Preparation with a Penetrating Micro-electrode Array
Published on: March 27, 2015
Novel glass microprobe arrays for neural recording
Chiung-Wen Lin1, Yu-Tao Lee, Chih-Wei Chang
1Institute of NanoEngineering and MicroSystems, National Tsing Hua University, Hsinchu 30013, Taiwan.
Biosensors & Bioelectronics
|September 4, 2009
Summary
Researchers developed a novel glass microprobe array for neurophysiology. This new tool enables high-quality neural signal recording, advancing the understanding of neural systems.
Area of Science:
- Neuroscience
- Materials Science
- Electrical Engineering
Background:
- Probe arrays are crucial for detecting neural signals in neurophysiology.
- Microfabricated probes offer advantages like fine spacing and smaller footprints.
- Glass offers superior signal isolation and biocompatibility compared to traditional materials.
Purpose of the Study:
- To present a novel fabrication process for a glass 2D-microprobe array.
- To enable vertical integration of microprobe chips using through-silicon vias (TSVs).
- To demonstrate the application of the glass microprobe for neural signal recording.
Main Methods:
- Micromachining process to create glass 2D-microprobe arrays.
- Integration of through-silicon vias (TSVs) for vertical chip assembly.
- Fabrication and characterization of the glass microprobe, including impedance measurements.
- Recording of neural signals from crayfish nerve cord and rat cortex.
Main Results:
- The fabricated 2D glass microprobe exhibited a low impedance of 439 kΩ at 1 kHz.
- Successfully recorded action potentials from crayfish nerve cord (228 μV amplitude, SNR 46.42).
- Successfully recorded spontaneous spikes from rat cortex (90 μV amplitude, SNR 19.72).
Conclusions:
- The novel glass 2D-microprobe array is a viable tool for neurophysiological recordings.
- The integration of TSVs facilitates the development of 3D microprobe arrays.
- The demonstrated performance highlights the potential of glass microprobes for advanced neural interface applications.

