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Chitosan‐Based, Biocompatible, Solution Processable Films for In Vivo Localization of Neural Interface Devices
Author(s) -
Rauhala Onni J.,
Dominguez Soledad,
Spyropoulos George D.,
Ferrero Jose Javier,
Boyers Talia R.,
JastrzebskaPerfect Patricia,
Cea Claudia,
Khodagholy Dion,
Gelinas Jennifer N.
Publication year - 2020
Publication title -
advanced materials technologies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.184
H-Index - 42
ISSN - 2365-709X
DOI - 10.1002/admt.201900663
Subject(s) - materials science , biocompatible material , biomedical engineering , chitosan , neurophysiology , interface (matter) , in vivo , fluorescence , electrocorticography , nanotechnology , fluorescence microscope , microscopy , polymer , biological system , chemical engineering , composite material , neuroscience , optics , electroencephalography , contact angle , medicine , physics , microbiology and biotechnology , sessile drop technique , biology , engineering
Chitosan (CS) is a biocompatible, inexpensive organic polymer that is increasingly used in neural tissue applications. However, its intrinsic fluorescence has not yet been leveraged to facilitate localization of neural interface devices, a key procedure to ensure accurate analysis of neurophysiological signals. A process is developed to enable control of mechanical and chemical properties of CS‐based composites, generating freestanding films that are stable in aqueous environments and exhibit concentration‐dependent fluorescence intensity. The shape and location of CS‐coated probes are reliably visualized in vitro and in vivo using fluorescence microscopy. Furthermore, CS neural probe marking is fully compatible with classical immunohistochemical and histological techniques, enabling localization of high spatiotemporal resolution surface electrocorticography arrays in adult rats and mouse pups. CS composites have the potential to simplify and streamline experimental procedures required to efficiently acquire, localize, and interpret neurophysiological data.