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Methods to Explore Sensorimotor Tasks

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Quanying Liu

Quanying Liu

SUSTech

Quanying Liu is an assistant professor at SUSTech, Shenzhen, China now, PI of Neural Computing and Control lab. She received the B.S. degree in electrical engineering at Lanzhou University, China, in 2010 and the M.S. degree in computer science at Lanzhou University, in 2013. After receiving her Ph.D. degree in biomedical engineering at ETH Zurich in 2017, she moved to the US as a postdoctoral fellow at CalTech. Quanying’s research interests are mainly in developing cutting-edge tools using high-density EEG and fMRI techniques, and applying the advanced neuroimaging tools and computational models to solve the fundamental questions in the neuroscience field.  

Collection Overview

Sensorimotor tasks involve the process of receiving sensory signals (sensory input) and producing a response (motor output). A variety of sensorimotor tasks have been proposed by researchers to investigate brain functions, such as multisensory integration, sensory learning, and motor control. Deficits in sensorimotor skills are well documented in aging and clinical populations. However, the experimental results of sensorimotor tasks largely rely on the experimental device, platform and set-up, task protocol, data collection, and data analysis. 

This collection aims to collect novel task designs, cutting-edge data analysis methods, and novel applications by recording the details about how to set up a sensorimotor task and how to record the behavioral or biological data in a healthy or clinical population. 

This video collection will have the following benefits: 1) provide a video-based platform to publish methods; 2)facilitate replicability of results; 3)nurture and educate young researchers who are interested in studying sensorimotor systems.

 

Articles

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
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WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

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Cited by 3

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2020

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