title: Development and Experimental Validation of a Dry Non-Invasive Multi-Channel Mouse Scalp EEG Sensor through Visual Evoked Potential Recordings.
abstract: In this paper, we introduce a dry non-invasive multi-channel sensor for measuring brainwaves on the scalps of mice. The research on laboratory animals provide insights to various practical applications involving human beings and other animals such as working animals, pets, and livestock. An experimental framework targeting the laboratory animals has the potential to lead to successful translational research when it closely resembles the environment of real applications. To serve scalp electroencephalography (EEG) research environments for the laboratory mice, the dry non-invasive scalp EEG sensor with sixteen electrodes is proposed to measure brainwaves over the entire brain area without any surgical procedures. We validated the proposed sensor system with visual evoked potential (VEP) experiments elicited by flash stimulations. The VEP responses obtained from experiments are compared with the existing literature, and analyzed in temporal and spatial perspectives. We further interpret the experimental results usingtime-frequency distribution(TFD) and distance measurements. The developed sensor guarantees stable operations for in vivo experiments in a non-invasive manner without surgical procedures, therefore exhibiting a high potential to strengthen longitudinal experimental studies and reliable translational research exploiting non-invasive paradigms.
authors.affiliation: School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology (GIST), Gwangju 61005, Korea. dhkim518@gist.ac.kr.
authors.forename: Donghyeon
authors.initials: D
authors.lastname: Kim
authors.affiliation: Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology (GIST), Gwangju 61005, Korea. ycmi0331@gist.ac.kr.
authors.forename: Chanmi
authors.initials: C
authors.lastname: Yeon
authors.affiliation: School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology (GIST), Gwangju 61005, Korea. kskim@gist.ac.kr.
authors.forename: Kiseon
authors.initials: K
authors.lastname: Kim
mesh_terms: D000818:Animals; D058256:Brain Waves; D004566:Electrodes; D004569:Electroencephalography; D005074:Evoked Potentials, Visual; D051379:Mice; D012535:Scalp
keywords: EEG; dry-type; laboratory mouse; multi-channel electrodes; non-invasiveness; visual evoked potential