Abstract
Efficient identification of effective neurostimulation strategies is critical due to the growing number of clinical applications and the increasing complexity of the corresponding technology. In consequence, investigators are encouraged to accelerate translational research of neurostimulation technologies and move quickly to clinical applications. However, this process is hampered by rigorous, but necessary, regulations and lack of a mechanistic understanding of the interactions between electric fields and neural circuits. Here we discuss how computational models have influenced the field of neurostimulation for pain and movement recovery, deep brain stimulation, and even device regulations. Finally, we propose our vision on how computational models will be key to accelerate clinical developments through mechanistic understanding.
Highlights
In the age of fast information transfer and social media, we are getting used to direct access to information and Despite this fact, the scientific community, and in particular the neuroscience community, is too quickly focusing on “translational applications”
We describe the general framework of technology development in the neurostimulation industry and provide examples of past, present, and potential future utility of computational models in accelerating technology development
We believe that our interpretation of the recent advancements in the field could help motivate other investigators to invest in the use of computational models, hopefully leading to a more precise interpretation of pre-clinical and clinical results
Summary
In the age of fast information transfer and social media, we are getting used to direct access to information and Despite this fact, the scientific community, and in particular the neuroscience community, is too quickly focusing on “translational applications” (i.e. the translation of scientific discoveries in neuroscience to clinical settings). SCS for pain control was one of the first applications of computational modelling to study the bioelectric effects of a clinical neuromodulation therapy.
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