Thin Film Multi-Electrode Softening Cuffs for Selective Neuromodulation.

Area of Science:

• Biomaterials Science
• Neuroscience
• Medical Devices

Background:

• Silicone nerve cuff electrodes are standard for peripheral neural interfaces but their thick walls cause fibrotic tissue growth, compromising function.
• The self-closing mechanism of silicone cuffs necessitates thick walls, leading to poor biocompatibility and reduced interface efficacy.

Purpose of the Study:

• To develop and evaluate thin-film, multi-electrode softening cuffs (MSC) using shape memory polymers (SMP) as a more compliant peripheral neural interface.
• To compare the biocompatibility and performance of MSC against traditional silicone cuffs in peripheral nerve recording and stimulation.

Main Methods:

• Fabrication of MSC using thiol-ene/acrylate SMP with integrated titanium nitride (TiN) and gold (Au) electrodes.
• Assessment of MSC mechanical properties, including modulus softening at physiological conditions and reduced flexural forces compared to silicone cuffs.
• In vivo implantation in rat sciatic and pelvic nerves to record neural signals and perform selective fascicular stimulation, followed by histological analysis after 30 days.

Main Results:

• MSC exhibited significantly lower flexural forces (70-700x) due to their 30 μm thin film design compared to 600 μm silicone cuffs.
• Successful recording of neural signals from rat sciatic and pelvic nerves and demonstration of selective fascicular stimulation.
• Histological analysis revealed significantly reduced inflammation (70-80% fewer macrophages) and fibrosis (54-56% less vimentin) for MSC implants compared to controls.

Conclusions:

• Thin-film SMP-based MSC represent a compliant and adaptable technology for peripheral neural interfacing.
• MSC demonstrate superior biocompatibility, significantly reducing inflammation and fibrotic tissue response compared to conventional silicone cuffs.
• The developed MSC technology holds promise for improved long-term performance in both somatic and autonomic peripheral neural applications.