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The Use of Magnetic Resonance Spectroscopy as a Tool for the Measurement of Bi-hemispheric Transcranial Electric Stimulation Effects on Primary Motor Cortex Metabolism
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MRI magnetic compatible electrical neural interface: From materials to application.

Yuan Zhang1, Song Le1, Hui Li2

  • 1Laboratory for Neural Interface and Brain Computer Interface, Institute of AI and Robotics, Academy for Engineering and Technology, FUDAN University, 220 Handan Rd., Yangpu District, Shanghai, 200433, China; Ji Hua Laboratory, 28 Island Ring South Rd., Foshan City, 528200, China; Engineering Research Center of AI & Robotics, Ministry of Education, Shanghai Engineering Research Center of AI & Robotics, MOE Frontiers Center for Brain Science, Shanghai 200433, China; Research Center for Intelligent Sensing, Zhejiang Lab, Hangzhou, 311100, China; Yiwu Research Institute of Fudan University, Chengbei Road, Yiwu City, 322000, Zhejiang, China.

Biosensors & Bioelectronics
|September 10, 2021
PubMed
Summary
This summary is machine-generated.

Developing MRI-compatible neural interfaces is crucial for simultaneous brain signal recording. This research analyzes material trends and challenges for integrating neural recording with magnetic resonance imaging for better brain function understanding.

Keywords:
BioelectronicsMagnetic resonance imaging (MRI) compatibleMicrofabricationNeural electrodeNeural interfaceSusceptibility

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Materials Science

Background:

  • Neural electrical interfaces are vital for neural stimulation, recording, and brain-computer interfaces (BCI).
  • Magnetic Resonance Imaging (MRI) non-invasively maps brain structures and activity.
  • Simultaneous neural signal and MRI recording offers insights into brain function.

Purpose of the Study:

  • To analyze trends in material selection for MRI-compatible neural interfaces.
  • To outline material design, function, and applications for neural interfaces.
  • To identify challenges in fabricating MRI-compatible neural interfaces.

Main Methods:

  • Analysis of material magnetic susceptibility for MRI compatibility.
  • Review of material design principles for neural interface devices.
  • Examination of current applications and limitations.

Main Results:

  • Identified key material properties balancing magnetic and electrical performance.
  • Outlined strategies for neural interface material design.
  • Highlighted the ongoing challenge of artifact-free simultaneous recording.

Conclusions:

  • Material selection is critical for achieving MRI compatibility in neural interfaces.
  • Further research is needed to overcome fabrication challenges for integrated systems.
  • Advancements promise enhanced understanding of neural activity and brain disorders.