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Large Animal Studies to Reduce the Foreign Body Reaction in Brain-Computer Interfaces: A Systematic Review.

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  • 1Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London SW7 2BX, UK.

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|August 26, 2021
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Summary

Reducing foreign body reaction (FBR) around brain-computer interface (BCI) electrodes is key for signal integrity. This review highlights strategies effective in larger animal models, showing promise for human translation.

Keywords:
animalastrogliosisbrain–computerin vivointerface

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Materials Science

Background:

  • Brain-computer interfaces (BCIs) require stable neural signal detection.
  • Foreign body reaction (FBR) to implanted electrodes disrupts the neural interface and signal quality.
  • Understanding FBR factors is crucial for advancing BCI technology.

Purpose of the Study:

  • To systematically review literature on mitigating FBR in vivo, focusing on large animal models.
  • To identify factors influencing FBR size and potential strategies for reduction.
  • To assess the translation of FBR reduction techniques from small to large animal models.

Main Methods:

  • Systematic literature search across OVID, MEDLINE, EMBASE, SCOPUS, and Scholar databases.
  • Qualitative analysis of 13 selected articles out of 8388 initially yielded.
  • Focus on studies employing large animal models (cats, rabbits, minipigs, marmosets).

Main Results:

  • Interventions targeting FBR demonstrated an average reduction of over 30% in inflammatory cells.
  • Electrode modifications (tip design, flexibility, sinusoidal configuration) showed efficacy in histology.
  • Few studies assessed the impact of FBR reduction on the actual BCI functional performance.

Conclusions:

  • Strategies effective in rodent models can be translated to reduce FBR in larger animals.
  • Further research is needed to correlate FBR reduction with improved BCI functional outcomes.
  • Optimizing electrode-tissue interface is critical for reliable long-term BCI performance.