What type of changes do fMRI scans primarily capture in neurosensory AI applications?

Functional Magnetic Resonance Imaging (fMRI) scans primarily capture changes in brain activity by monitoring blood flow and oxygenation levels. This capability is grounded in the principle of neurovascular coupling, where increased neuronal activity leads to a greater demand for oxygen and nutrients in specific brain areas. When neurons activate, they consume more oxygen, and blood flow to these regions increases to meet this metabolic demand.

fMRI detects these changes through variations in the magnetic resonance signal associated with oxygenated and deoxygenated blood. This allows researchers to infer which areas of the brain are engaged during different tasks or stimuli. The activation maps generated by fMRI provide valuable insights into the functional organization of the brain, making it a critical tool in neurosensory AI applications focused on understanding brain behavior and processing in response to various cognitive challenges.

The other options do not directly pertain to the primary function of fMRI. For instance, while changes in bone density are important for different assessments, they are not the focus of fMRI technology. Similarly, external reflexes to stimuli and changes in body temperature are monitored by other methodologies, not fMRI, which is specifically designed to track cerebral blood flow and oxygenation levels related to brain activity.