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• W4220828751 abstract "Measuring eye movement is a fundamental approach in cognitive science as it provides a variety of insightful parameters that reflect brain states such as visual attention and emotions. Combining eye-tracking with multimodal neural recordings or manipulation techniques is beneficial for understanding the neural substrates of cognitive function. Many commercially-available and custom-built systems have been widely applied to awake, head-fixed small animals. However, the existing eye-tracking systems used in freely-moving animals are still limited in terms of their compatibility with other devices and of the algorithm used to detect eye movements. Here, we report a novel system that integrates a general-purpose, easily compatible eye-tracking hardware with a robust eye feature-detection algorithm. With ultra-light hardware and a detachable design, the system allows for more implants to be added to the animal's exposed head and has a precise synchronization module to coordinate with other neural implants. Moreover, we systematically compared the performance of existing commonly-used pupil-detection approaches, and demonstrated that the proposed adaptive pupil feature-detection algorithm allows the analysis of more complex and dynamic eye-tracking data in free-moving animals. Synchronized eye-tracking and electroencephalogram recordings, as well as algorithm validation under five noise conditions, suggested that our system is flexibly adaptable and can be combined with a wide range of neural manipulation and recording technologies." @default.
• W4220828751 created "2022-04-03" @default.
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• W4220828751 date "2022-03-24" @default.
• W4220828751 modified "2023-10-05" @default.
• W4220828751 title "An Easily Compatible Eye-tracking System for Freely-moving Small Animals" @default.
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• W4220828751 doi "https://doi.org/10.1007/s12264-022-00834-9" @default.
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