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Translational Organic Neural Interface Devices at Single Neuron Resolution

Recording from the human brain at the spatiotemporal resolution of action potentials provides critical insight into mechanisms of higher cognitive functions and neuropsychiatric disease that is challenging to derive from animal models. Here, organic materials and conformable electronics are employed...

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Detalles Bibliográficos
Autores principales: Hassan, Ahnaf Rashik, Zhao, Zifang, Ferrero, Jose J., Cea, Claudia, Jastrzebska‐Perfect, Patricia, Myers, John, Asman, Priscella, Ince, Nuri Firat, McKhann, Guy, Viswanathan, Ashwin, Sheth, Sameer A., Khodagholy, Dion, Gelinas, Jennifer N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9507374/
https://www.ncbi.nlm.nih.gov/pubmed/35908811
http://dx.doi.org/10.1002/advs.202202306
Descripción
Sumario:Recording from the human brain at the spatiotemporal resolution of action potentials provides critical insight into mechanisms of higher cognitive functions and neuropsychiatric disease that is challenging to derive from animal models. Here, organic materials and conformable electronics are employed to create an integrated neural interface device compatible with minimally invasive neurosurgical procedures and geared toward chronic implantation on the surface of the human brain. Data generated with these devices enable identification and characterization of individual, spatially distribute human cortical neurons in the absence of any tissue penetration (n = 229 single units). Putative single‐units are effectively clustered, and found to possess features characteristic of pyramidal cells and interneurons, as well as identifiable microcircuit interactions. Human neurons exhibit consistent phase modulation by oscillatory activity and a variety of population coupling responses. The parameters are furthermore established to optimize the yield and quality of single‐unit activity from the cortical surface, enhancing the ability to investigate human neural network mechanisms without breaching the tissue interface and increasing the information that can be safely derived from neurophysiological monitoring.