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Conversation with a Hindawi Editor: Dr Liu Xiaozheng  

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Neural Plasticity: Special Issue Lead Guest Editor Q&A

We spoke with Dr. Liu Xiaozheng about his role as Lead Guest Editor of the Special Issue ‘Post-Stroke Neural Plasticity: Functional and Structural Reorganization during Stroke Recovery’ in Neural Plasticity.

Dr. Liu Xiaozheng is the Lead Guest Editor of the annual special issue in Neural Plasticity, 'Post-Stroke Neural Plasticity: Functional and Structural Reorganization during Stroke Recovery'. In this interview, he talks about the latest developments in post-stroke neural plasticity and shares advice on what to consider before submitting to the special issue. 

As a key member of the Brain Function Research Institute of Wenzhou Medical University, Dr Liu focuses on the brain's white matter imaging methods, medical image processing algorithms, and the pathogenesis and early diagnosis of psychiatric diseases.  

Last year, "Post-Stroke Neural Plasticity: Functional and Structural Reorganization during Stroke Recovery" achieved great success among researchers in neuroplasticity by publishing a number of high-impact articles. As a result, it was awarded annual special issue and is open for submissions again. The deadline for submission is August 12th, 2022.  

What is the importance of your chosen special issue topic "Post-Stroke Neural Plasticity: Functional and Structural Reorganization during Stroke Recovery"?  

Stroke is a major cause of disability worldwide. It severely impacts daily activities and affects the level of life. Despite improved treatment strategies, a substantial number of stroke survivors are associated with persistent neurological deficits. Therefore, there is an urgent need to explore the neural plasticity that determines functional recovery from stroke. Advanced neuroimaging techniques are promising, as they enable us to detect neural plasticity changes. Moreover, they provide important information on the brain's capacity for self-repair in stroke. In addition, novel neurorehabilitation for stroke patients is becoming more popular and has been demonstrated to be effective in clinical practice and in research. However, how these promising interventions affect post-stroke neural plasticity is not fully understood. Therefore, post-stroke neural plasticity changes after neurorehabilitation need to be further explored, which may help to elucidate the neural mechanisms of these interventions and provide guidance for future clinical applications. The aim of this special issue is to increase our knowledge of how neurorehabilitation affects neural plasticity. This special issue welcomes human studies and animal studies discussing the use of advanced methods and techniques to explain the mechanisms of neurorehabilitation. Both research and review articles are welcome.  

What is your background in this area of research?  

I have a background in magnetic resonance physics, and I have also done research on optic neuroimaging methodology during my postgraduate studies. Currently, I mainly use multimodal imaging technology to explore the neuroplasticity of neurological and psychiatric diseases, and provide a basis for clinical diagnosis and intervention. The Brain Function Research Institute has close relationships with the Department of Neurology and Department of Rehabilitation and Neurohehabilitation  of the affiliated hospitals of Wenzhou Medical University. I have long focused on the research on the plasticity of neurological recovery after ischemic and hemorrhagic stroke, including the research on post-stroke neurological function and verbal ability recovery as well as neuroimaging plasticity.  

What were some of your key takeaways from the previous publication of this Annual Issue?  

The release and publicity of special issues can increase the academic influence of the editorial team in the field. Through the collection and review of contributions in the special issue, we can know the cutting edge research focus and problems that need to be solved in this discipline, so as to guide our future research interests. Among the contributions received, there is still a lack of research on the cross field of medicine and engineering. Although traditional rehabilitation methods play an important role in clinical practice, new technical methods can directly intervene in brain function activities. Therefore, new technologies are very promising in understanding neural function remodeling.  

What are some of the key developments in this area that you’ve observed in the past few years? 

  • Brain-derived neurotrophic factor (BDNF), a protein that supports and encourages the growth of new neurons and synapses, is essential for neuroplasticity. Aerobic exercise (including any exercise that increases heart rate, such as brisk walking or cycling) and consuming certain foods, such as omega-3 fatty acids, have been proven to be able to promote BDNF.  
  • Transcranial electrical stimulation and magnetic stimulation can regulate the activity of neurons through electromagnetic waves, and also change the neural network in the corresponding brain area and remodel the brain function. This has been widely used in clinical intervention studies. Research on the effects of transcranial electrical stimulation and magnetic stimulation on post-stroke interventions and neuroplasticity is still lacking. For example, different therapeutic targets and how to precisely locate them.  
  • Virtual reality (VR) can make stroke recovery more immersive, interactive and interesting, thereby increasing the patient's initiative in rehabilitation treatment. Moreover, different VR programs and rehabilitation training need to be developed for different post-stroke patients. Understanding the neuroplasticity of VR in post-stroke rehabilitation can provide us with targeted clinical interventions and VR programming.  
  • Brain-computer interface (BCI) can directly obtain brain signals and directly intervene in the training task of the body. During the rehabilitation, real-time feedback training can promote the remodeling of brain neural function.  

What do you encourage authors to think about when preparing their manuscripts for your Special Issue? 

Among the contributions received, there are still few studies on the combination of clinical and engineering technology. Multimodal imaging techniques can be used to explore the functional remodeling mechanism of interventions and understand the functional reorganization of the brain during neurological rehabilitation. New research methods, such as artificial intelligence, robotic-assisted therapy, and transcranial electrical stimulation, are innovative for neuroplasticity in post-stroke rehabilitation. Traditional Chinese medicine therapy, such as acupuncture, is also a modern Chinese medicine research method advocated by the state. We welcome original research and review articles, including:  

  • Effects of physical therapy on post-stroke neural plasticity.  
  • Effects of electrical stimulation or transcranial magnetic stimulation on post-stroke neural plasticity.  
  • Effects of robot-assisted training on post-stroke neural plasticity.  
  • Effects of traditional Chinese medicine therapy on post-stroke neural plasticity.  
  • The role of the brain-gut axis, brain-heart axis, and extracellular matrix in post-stroke neural plasticity.  
  • Machine learning techniques helping to build predictive models based on post-stroke neural plasticity.  

What do you consider the key benefits of being part of the Guest Editorial Team for this Special Issue?

As an academic editor, you need to take the initiative to understand the research trends and focuses in the industry so as to screen out reviewers and provide final comments on contributions. For editors, this is a good process to supplement their knowledge system. As mentioned in the third point, the release and publicity of the special issue can facilitate the communication between the editorial team and peers, and also bring about a lot of cooperation among the science community. This special issue has facilitated our collaboration with stroke multicenter imaging data.  

Submit to this Special Issue >>

This blog post is distributed under the Creative Commons Attribution License (CC-BY). Illustration adapted from Adobe Stock by David Jury.

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