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Non-invasive brain stimulation (NIBS) techniques, such as transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS), have shown promise for the treatment of neurological and psychiatric disorders. However, the effectiveness of NIBS varies significantly across individuals, potentially due to differences in brain anatomy, connectivity, and pathology. Recent advances in neuroimaging—including functional MRI, diffusion tensor imaging, and electroencephalography—allow for detailed mapping of brain structures and networks. The integration of these advanced neuroimaging methods provides a unique opportunity to tailor NIBS interventions to individual neurobiological profiles, maximizing efficacy while minimizing adverse effects.
The primary aim of this Research Topic is to address the challenge of inter-individual variability in response to NIBS by leveraging advanced neuroimaging techniques for personalized treatment. Despite significant progress, a gap remains in translating neuroimaging biomarkers into clinically actionable protocols for guiding NIBS. We seek to bring together original research, reviews, and perspectives that explore how structural and functional neuroimaging can inform target selection, optimize stimulation parameters, and ultimately predict individual outcomes. By fostering interdisciplinary collaboration among neuroscientists, clinicians, and engineers, we hope to accelerate the development of precision NIBS strategies that improve therapeutic outcomes and expand the range of treatable conditions.
We invite submissions covering, but not limited to, the following themes:
• Neuroimaging biomarkers that predict or monitor response to NIBS
• Integration of multimodal imaging for personalized brain stimulation strategies
• Computational modeling to inform individualized targeting and dosing
• Case reports or clinical trials incorporating personalized neuroimaging-guided NIBS
• Methodological advances in imaging acquisition, analysis, or co-registration with NIBS
• Perspectives on clinical translation, scalability, and ethical considerations in personalized NIBS
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