Multi-Layer Brain-Mimicking Phantom for Replicating Dura and Pia Membrane Dimpling and Rupture Properties During Neural Interface Implantation
Development of novel neural interfaces faces buckling challenges and heavily relies on trial-and-error tests via <i>in vivo</i> animal brain insertions for design optimizations towards the minimal-damaging version for enhanced recording and stimulation outcome. To enable low-cost and fast-turnaround neural interface development and to enable previously impossible insertions via new understanding of the cutting process, this study developed a reproducible, multi-layer brain-mimicking phantom designed to replicate the rodent pia and dura mater dimpling and rupture force performance observed during <i>in vivo</i> tests. The phantom was composed of a 0.5% (w/v) agarose cortex layer, a 1.01% (w/v) agarose pia mater layer, and a pre-stretched polyvinyl chloride (PVC) dura mater layer, assembled via easily duplicable benchtop protocols. Using a cantilever-beam force measurement system, rupture force and dimpling depth were quantified across microwires of varying diameters (12-100 μm), materials (tungsten, stainless steel), and tip geometries, as well as segmented silicon probe shanks. Phantom test results closely matched <i>in vivo</i> Sprague-Dawley rat data, validating the performance of the developed multi-layer phantom. At the same time, phantom insertion trial variability was substantially lower than <i>in vivo</i> tests, enabling a repeatable, low-cost, early-stage screening platform of novel electrode designs. The phantom's modular design also allowed tuning of layer thickness and stiffness of each layer for different species or devices, offering a validated customizable testing platform to accelerate novel neural implant development and reduce animal use.
Authors
- Kevin Igmidio E. Lat
- Dongyang Yi (ORCID: https://orcid.org/0000-0002-7994-0454)
- Lei Chen (ORCID: https://orcid.org/0000-0002-0192-8682)
Institutions
- University of Massachusetts Lowell (US)
Publication Details
- Journal
- bioRxiv (Cold Spring Harbor Laboratory)
- Published
- 2026-02-09
- DOI
- https://doi.org/10.64898/2026.02.05.704082
- Primary Topic
- Neuroscience and Neural Engineering
- Type
- article
- Field-Weighted Citation Impact
- 0.00