Computational and Histological Analyses for Investigating Mechanical Interaction of Thermally Drawn Fiber Implants with Brain Tissue
- Authors
- Kim, Kanghyeon; Sung, Changhoon; Lee, Jungjoon; Won, Joonhee; Jeon, Woojin; Seo, Seungbeom; Yoon, Kyungho; Park, Seongjun
- Issue Date
- 2021-04
- Publisher
- MDPI
- Citation
- MICROMACHINES, v.12, no.4
- 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.
- Keywords
- NEURAL PROBE; INTERFACE; BIOCOMPATIBILITY; MICROMOTION; SIMULATION; ELECTRODES; POLYMERS; DESIGN; MODELS; STRAIN; NEURAL PROBE; INTERFACE; BIOCOMPATIBILITY; MICROMOTION; SIMULATION; ELECTRODES; POLYMERS; DESIGN; MODELS; STRAIN; fiber neural probes; TDP; FEA; soft materials; IHC
- ISSN
- 2072-666X
- URI
- https://pubs.kist.re.kr/handle/201004/117214
- DOI
- 10.3390/mi12040394
- Appears in Collections:
- KIST Article > 2021
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