OBJECTIVE: The objective of this research is to characterize the mechanical interactions of (1) soft, compliant and (2) non-compliant implants with the surrounding brain tissue in a rodent brain. Understanding such interactions will enable the engineering of novel materials that will improve stability and reliability of brain implants. APPROACH: Acute force measurements were made using a load cell in n = 3 live rats, each with 4 craniotomies. Using an indentation method, brain tissue was tested for changes in force using established protocols. A total of 4 non-compliant, bare silicon microshanks, 3 non-compliant polyvinyl acetate (PVAc)-coated silicon microshanks, and 6 compliant, nanocomposite microshanks were tested. Stress values were calculated by dividing the force by surface area and strain was estimated using a linear stress-strain relationship. Micromotion effects from breathing and vascular pulsatility on tissue stress were estimated from a 5 s interval of steady-state measurements. Viscoelastic properties were estimated using a second-order Prony series expansion of stress-displacement curves for each shank. MAIN RESULTS: The distribution of strain values imposed on brain tissue for both compliant nanocomposite microshanks and PVAc-coated, non-compliant silicon microshanks were significantly lower compared to non-compliant bare silicon shanks. Interestingly, step-indentation experiments also showed that compliant, nanocomposite materials significantly decreased stress relaxation rates in the brain tissue at the interface (p < 0.05) compared to non-compliant silicon and PVAc-coated silicon materials. Furthermore, both PVAc-coated non-compliant silicon and compliant nanocomposite shanks showed significantly reduced (by 4-5 fold) stresses due to tissue micromotion at the interface. SIGNIFICANCE: The results of this study showed that soft, adaptive materials reduce strains and strain rates and micromotion induced stresses in the surrounding brain tissue. Understanding the material behavior at the site of tissue contact will help to improve neural implant design.
OBJECTIVE: The objective of this research is to characterize the mechanical interactions of (1) soft, compliant and (2) non-compliant implants with the surrounding brain tissue in a rodent brain. Understanding such interactions will enable the engineering of novel materials that will improve stability and reliability of brain implants. APPROACH: Acute force measurements were made using a load cell in n = 3 live rats, each with 4 craniotomies. Using an indentation method, brain tissue was tested for changes in force using established protocols. A total of 4 non-compliant, bare silicon microshanks, 3 non-compliant polyvinyl acetate (PVAc)-coated silicon microshanks, and 6 compliant, nanocomposite microshanks were tested. Stress values were calculated by dividing the force by surface area and strain was estimated using a linear stress-strain relationship. Micromotion effects from breathing and vascular pulsatility on tissue stress were estimated from a 5 s interval of steady-state measurements. Viscoelastic properties were estimated using a second-order Prony series expansion of stress-displacement curves for each shank. MAIN RESULTS: The distribution of strain values imposed on brain tissue for both compliant nanocomposite microshanks and PVAc-coated, non-compliant silicon microshanks were significantly lower compared to non-compliant bare silicon shanks. Interestingly, step-indentation experiments also showed that compliant, nanocomposite materials significantly decreased stress relaxation rates in the brain tissue at the interface (p < 0.05) compared to non-compliant silicon and PVAc-coated silicon materials. Furthermore, both PVAc-coated non-compliant silicon and compliant nanocomposite shanks showed significantly reduced (by 4-5 fold) stresses due to tissue micromotion at the interface. SIGNIFICANCE: The results of this study showed that soft, adaptive materials reduce strains and strain rates and micromotion induced stresses in the surrounding brain tissue. Understanding the material behavior at the site of tissue contact will help to improve neural implant design.
Authors: Terrence R Oakes; Diego A Pizzagalli; Andrew M Hendrick; Katherine A Horras; Christine L Larson; Heather C Abercrombie; Stacey M Schaefer; John V Koger; Richard J Davidson Journal: Hum Brain Mapp Date: 2004-04 Impact factor: 5.038
Authors: Steven M Wellman; James R Eles; Kip A Ludwig; John P Seymour; Nicholas J Michelson; William E McFadden; Alberto L Vazquez; Takashi D Y Kozai Journal: Adv Funct Mater Date: 2017-07-19 Impact factor: 18.808
Authors: Zhanhong Jeff Du; Christi L Kolarcik; Takashi D Y Kozai; Silvia D Luebben; Shawn A Sapp; Xin Sally Zheng; James A Nabity; X Tracy Cui Journal: Acta Biomater Date: 2017-02-06 Impact factor: 8.947
Authors: Aldo Garcia-Sandoval; Edgar Guerrero; Seyed Mahmoud Hosseini; Pedro E Rocha-Flores; Rashed Rihani; Bryan J Black; Ajay Pal; Jason B Carmel; Joseph J Pancrazio; Walter E Voit Journal: Biomaterials Date: 2021-08-16 Impact factor: 15.304
Authors: Negar Geramifard; Behnoush Dousti; Christopher Nguyen; Justin Abbott; Stuart F Cogan; Victor D Varner Journal: J Neural Eng Date: 2022-04-08 Impact factor: 5.043
Authors: Jessica K Nguyen; Mehdi Jorfi; Kelly L Buchanan; Daniel J Park; E Johan Foster; Dustin J Tyler; Stuart J Rowan; Christoph Weder; Jeffrey R Capadona Journal: Acta Biomater Date: 2015-11-06 Impact factor: 8.947
Authors: Joseph J Pancrazio; Felix Deku; Atefeh Ghazavi; Allison M Stiller; Rashed Rihani; Christopher L Frewin; Victor D Varner; Timothy J Gardner; Stuart F Cogan Journal: Neuromodulation Date: 2017-10-27
Authors: Sagar Singh; Meng-Chen Lo; Vinod B Damodaran; Hilton M Kaplan; Joachim Kohn; Jeffrey D Zahn; David I Shreiber Journal: Sensors (Basel) Date: 2016-03-04 Impact factor: 3.576
Authors: Kevin C Spencer; Jay C Sy; Khalil B Ramadi; Ann M Graybiel; Robert Langer; Michael J Cima Journal: Sci Rep Date: 2017-05-16 Impact factor: 4.379