Translational network neuroscience: Nine roadblocks and possible solutions

Area of Science:

• Neuroscience
• Medical Imaging
• Data Science

Background:

• Translational network neuroscience seeks to apply advanced neuroimaging and data analysis to clinical practice for neurological disorders.
• Functional MRI (fMRI) and diffusion MRI (dMRI) show promise but face significant translational barriers.

Purpose of the Study:

• To identify and categorize the key challenges impeding the clinical translation of network neuroscience.
• To propose strategies for overcoming these obstacles and facilitating the integration of network neuroscience into routine clinical practice.

Main Methods:

• Identification of nine major roadblocks across theoretical, technical, data-related, resource, collaboration, operational, and ethical domains.
• Development of potential solution strategies to address each identified challenge.

Main Results:

• Key challenges include theoretical foundations, network construction/validation, MRI data issues (access, variability, standardization), data sharing, computational resources, interdisciplinary collaboration, industry partnerships, operational integration, and ethical/legal considerations.
• Proposed solutions emphasize aligning scientific goals with clinical needs and establishing ethical guidelines.

Conclusions:

• Addressing these nine translational hurdles is crucial for advancing network neuroscience.
• An interdisciplinary commitment and a robust ethical framework are essential for integrating advanced neuroimaging and network analysis into personalized medicine and improving patient care for neurological disorders.