دورية أكاديمية

Three dimensional microelectrodes enable high signal and spatial resolution for neural seizure recordings in brain slices and freely behaving animals

التفاصيل البيبلوغرافية
العنوان: Three dimensional microelectrodes enable high signal and spatial resolution for neural seizure recordings in brain slices and freely behaving animals
المؤلفون: P. Wijdenes, K. Haider, C. Gavrilovici, B. Gunning, M. D. Wolff, T. Lijnse, R. Armstrong, G. C. Teskey, J. M. Rho, C. Dalton, Naweed I. Syed
المصدر: Scientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
بيانات النشر: Nature Portfolio, 2021.
سنة النشر: 2021
المجموعة: LCC:Medicine
LCC:Science
مصطلحات موضوعية: Medicine, Science
الوصف: Abstract Neural recordings made to date through various approaches—both in-vitro or in-vivo—lack high spatial resolution and a high signal-to-noise ratio (SNR) required for detailed understanding of brain function, synaptic plasticity, and dysfunction. These shortcomings in turn deter the ability to further design diagnostic, therapeutic strategies and the fabrication of neuro-modulatory devices with various feedback loop systems. We report here on the simulation and fabrication of fully configurable neural micro-electrodes that can be used for both in vitro and in vivo applications, with three-dimensional semi-insulated structures patterned onto custom, fine-pitch, high density arrays. These microelectrodes were interfaced with isolated brain slices as well as implanted in brains of freely behaving rats to demonstrate their ability to maintain a high SNR. Moreover, the electrodes enabled the detection of epileptiform events and high frequency oscillations in an epilepsy model thus offering a diagnostic potential for neurological disorders such as epilepsy. These microelectrodes provide unique opportunities to study brain activity under normal and various pathological conditions, both in-vivo and in in-vitro, thus furthering the ability to develop drug screening and neuromodulation systems that could accurately record and map the activity of large neural networks over an extended time period.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2045-2322
Relation: https://doaj.org/toc/2045-2322
DOI: 10.1038/s41598-021-01528-4
URL الوصول: https://doaj.org/article/07111a50d0a94ec8bdbd64b85d857050
رقم الأكسشن: edsdoj.07111a50d0a94ec8bdbd64b85d857050
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20452322
DOI:10.1038/s41598-021-01528-4