About this Research Topic
Increasing evidence confirms that mechanics plays a critical role for brain function and dysfunction. In recent years, computational mechanics has emerged as a powerful tool to study and predict the behavior of the human brain under both physiological and pathological conditions. Yet, important challenges remain unresolved that have hindered realistic and reliable numerical predictions. Brain tissue is ultra-soft, biphasic, and highly heterogeneous. In addition, it is a continuously evolving material; its microstructural composition and architecture, as well as its mechanical properties, change throughout its lifetime, in close relation to brain function. Living brain cells actively sense and respond to their mechanical environment, leading to sophisticated coupling effects. Considering these highly dynamic effects will be critical to refining existing brain models and achieving personalized simulation of brain injury, disease or surgical procedures.
This Research topic will cover recent advances in brain mechanics, including novel experimental and modeling approaches, computational solid and fluid mechanics, and data-driven modeling, targeted toward personalized simulations that will provide value to the clinical community. The aim is to demonstrate how the powerful methods of engineering mechanics can unravel the behavior of the brain. Understanding brain mechanics will illuminate features of brain development (such as cortical folding), aging and diseases (such as Alzheimer’s disease or hydrocephalus), as well as traumatic events (such as traumatic brain injury or blast). Through the collection of recent advances in the rapidly-evolving field of brain mechanics, we aim to encourage synergies between different experimental and modeling approaches, which will help to overcome the remaining challenges and frontiers. This endeavor will be an important step towards realizing high-fidelity models that are capable of providing novel insights into injury and disease, and ultimately improving strategies for diagnosis and treatment of brain disease and brain injury.
Manuscripts of different types can be submitted related to the Research Topic that include, but are not limited to the following:
• Experimental characterization of brain tissue and the brain-skull interface
• In vivo versus ex vivo mechanical properties
• ‘Mechanosensing’ of neural cells
• Multi-field and multi-scale approaches
• Data-integrated modeling
• Patient-specific modeling
• Robust computational techniques
• Quantitative evaluation of models using experimental data
• Modeling of development, aging, injury and disease
This Research topic will cover recent advances in brain mechanics, including novel experimental and modeling approaches, computational solid and fluid mechanics, and data-driven modeling, targeted toward personalized simulations that will provide value to the clinical community. The aim is to demonstrate how the powerful methods of engineering mechanics can unravel the behavior of the brain. Understanding brain mechanics will illuminate features of brain development (such as cortical folding), aging and diseases (such as Alzheimer’s disease or hydrocephalus), as well as traumatic events (such as traumatic brain injury or blast). Through the collection of recent advances in the rapidly-evolving field of brain mechanics, we aim to encourage synergies between different experimental and modeling approaches, which will help to overcome the remaining challenges and frontiers. This endeavor will be an important step towards realizing high-fidelity models that are capable of providing novel insights into injury and disease, and ultimately improving strategies for diagnosis and treatment of brain disease and brain injury.
Manuscripts of different types can be submitted related to the Research Topic that include, but are not limited to the following:
• Experimental characterization of brain tissue and the brain-skull interface
• In vivo versus ex vivo mechanical properties
• ‘Mechanosensing’ of neural cells
• Multi-field and multi-scale approaches
• Data-integrated modeling
• Patient-specific modeling
• Robust computational techniques
• Quantitative evaluation of models using experimental data
• Modeling of development, aging, injury and disease
Keywords: Mechanical Testing, Computational Mechanics, Neuromechanics, Brain Injury, Neurological Diseases
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
