Neuroimaging encompasses a broad set of techniques used to observe the brain’s structure, function, and physiology, either directly or through indirect biological signals. These technologies make it possible to study how the brain is organized, how it changes over time, and how neural activity relates to behavior, disease, and treatment response.

Imaging modalities vary widely in what they measure and how they operate, ranging from structural approaches such as MRI to functional and physiological techniques including fMRI, EEG, fNIRS, PET, and emerging ultrasound-based methods. Each modality involves trade-offs across spatial resolution, temporal resolution, invasiveness, cost, and portability, shaping where and how it can be deployed.

Historically, neuroimaging has been central to clinical neurology and neuroscience research, supporting diagnosis, disease monitoring, and functional brain mapping. More recently, advances in hardware miniaturization and computational analysis have expanded neuroimaging beyond the hospital, enabling wearable, point-of-care, and longitudinal brain monitoring in more naturalistic settings.

As the field evolves, neuroimaging is increasingly defined not by individual modalities, but by multimodal and AI-enhanced approaches that combine complementary data sources to extract actionable insights. Rather than serving as a single diagnostic tool, neuroimaging is becoming a foundational layer for biomarker discovery, precision medicine, and the development of brain-based technologies across healthcare and research.