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Chronic Brain Cortex Signal Recording Based on a Soft Conductive Hydrogel Biointerface. | LitMetric

AI Article Synopsis

  • Researchers aim to develop better neural interfaces to improve brain signal acquisition for analyzing brain processes and detecting disorders.
  • A new biointerface made from soft polyacrylamide hydrogels with silver nanocubes shows enhanced conductivity and compatibility with brain tissue, reducing tissue damage and improving signal accuracy.
  • Biological tests indicate that this novel interface supports neural growth without causing inflammation, allowing for long-term recording of brain signals effectively.

Article Abstract

In neuroscience, the acquisition of neural signals from the brain cortex is crucial to analyze brain processes, detect neurological disorders, and offer therapeutic brain-computer interfaces. The design of neural interfaces conformable to the brain tissue is one of today's major challenges since the insufficient biocompatibility of those systems provokes a fibrotic encapsulation response, leading to an inaccurate signal recording and tissue damage precluding long-term/permanent implants. The design and production of a novel soft neural biointerface made of polyacrylamide hydrogels loaded with plasmonic silver nanocubes are reported herein. Hydrogels are surrounded by a silicon-based template as a supporting element for guaranteeing an intimate neural-hydrogel contact while making possible stable recordings from specific sites in the brain cortex. The nanostructured hydrogels show superior electroconductivity while mimicking the mechanical characteristics of the brain tissue. Furthermore, biological tests performed by culturing neural progenitor cells demonstrate the biocompatibility of hydrogels along with neuronal differentiation. chronic neuroinflammation tests on a mouse model show no adverse immune response toward the nanostructured hydrogel-based neural interface. Additionally, electrocorticography acquisitions indicate that the proposed platform permits long-term efficient recordings of neural signals, revealing the suitability of the system as a chronic neural biointerface.

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Source
http://dx.doi.org/10.1021/acsami.2c17025DOI Listing

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