2021
DOI: 10.3389/fncir.2021.743101
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NeuroVis: Real-Time Neural Information Measurement and Visualization of Embodied Neural Systems

Abstract: Understanding the real-time dynamical mechanisms of neural systems remains a significant issue, preventing the development of efficient neural technology and user trust. This is because the mechanisms, involving various neural spatial-temporal ingredients [i.e., neural structure (NS), neural dynamics (ND), neural plasticity (NP), and neural memory (NM)], are too complex to interpret and analyze altogether. While advanced tools have been developed using explainable artificial intelligence (XAI), node-link diagr… Show more

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Cited by 7 publications
(4 citation statements)
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“…For example, image segmentation models based on convolutional neural networks can make excellent contributions to imaging parameters, disease classification, and diagnosis of spinal cord neural injury patients before and after surgery ( 36 , 37 ). Second, AI can track and analyze in real-time all neural components of various nervous systems, i.e., neural structure, neurodynamics, neuroplasticity, and neural memory ( 38 ).…”
Section: Discussionmentioning
confidence: 99%
“…For example, image segmentation models based on convolutional neural networks can make excellent contributions to imaging parameters, disease classification, and diagnosis of spinal cord neural injury patients before and after surgery ( 36 , 37 ). Second, AI can track and analyze in real-time all neural components of various nervous systems, i.e., neural structure, neurodynamics, neuroplasticity, and neural memory ( 38 ).…”
Section: Discussionmentioning
confidence: 99%
“…Additionally, it could not store the emerged gaits for gait recovery. This is because it lacks neural communication between the leg control units, which is an important component for wave gait control and gait memorization, as demonstrated in our previous studies [ 87,101 ] and in neuroWalknet. [ 51 ] Thus, in the future, we will include x – y plane foot trajectories of stick insect data into our control system and further investigate the integration of leg posture control as well as local leg extension and elevation control or neuroWalknet intraleg control.…”
Section: Discussionmentioning
confidence: 99%
“…[ 51 ] Thus, in the future, we will include x – y plane foot trajectories of stick insect data into our control system and further investigate the integration of leg posture control as well as local leg extension and elevation control or neuroWalknet intraleg control. We will further enhance the control system by adding adaptive neural coupling mechanisms (i.e., neural communication) to store emerged gait patterns in the neural structure [ 87 ] and accomplish other stable gaits. [ 101 ] We will also implement muscle models [ 102 ] to achieve high adaptability for traveling over challenging terrain.…”
Section: Discussionmentioning
confidence: 99%
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