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Computational and Histological Analyses for Investigating Mechanical Interaction of Thermally Drawn Fiber Implants with Brain Tissue
- Source :
- Micromachines, Micromachines, Vol 12, Iss 394, p 394 (2021), Volume 12, Issue 4
- Publication Year :
- 2021
-
Abstract
- The development of a compliant neural probe is necessary to achieve chronic implantation with minimal signal loss. Although fiber-based neural probes fabricated by the thermal drawing process have been proposed as a solution, their long-term effect on the brain has not been thoroughly investigated. Here, we examined the mechanical interaction of thermally drawn fiber implants with neural tissue through computational and histological analyses. Specifically, finite element analysis and immunohistochemistry were conducted to evaluate the biocompatibility of various fiber implants made with different base materials (steel, silica, polycarbonate, and hydrogel). Moreover, the effects of the coefficient of friction and geometric factors including aspect ratio and the shape of the cross-section on the strain were investigated with the finite element model. As a result, we observed that the fiber implants fabricated with extremely softer material such as hydrogel exhibited significantly lower strain distribution and elicited a reduced immune response. In addition, the implants with higher coefficient of friction (COF) and/or circular cross-sections showed a lower strain distribution and smaller critical volume. This work suggests the materials and design factors that need to be carefully considered to develop future fiber-based neural probes to minimize mechanical invasiveness.
- Subjects :
- Materials science
Biocompatibility
lcsh:Mechanical engineering and machinery
02 engineering and technology
soft materials
Signal
Article
03 medical and health sciences
0302 clinical medicine
TDP
lcsh:TJ1-1570
Fiber
Electrical and Electronic Engineering
Polycarbonate
FEA
chemistry.chemical_classification
fiber neural probes
Mechanical Engineering
Polymer
021001 nanoscience & nanotechnology
Aspect ratio (image)
Finite element method
chemistry
Control and Systems Engineering
visual_art
Electrode
visual_art.visual_art_medium
0210 nano-technology
030217 neurology & neurosurgery
Biomedical engineering
IHC
Subjects
Details
- ISSN :
- 2072666X
- Volume :
- 12
- Issue :
- 4
- Database :
- OpenAIRE
- Journal :
- Micromachines
- Accession number :
- edsair.doi.dedup.....16d1cddd33a536b0500f3a618a5955c8