Integrating naturalistic approach to human cognitive mapping in SEEG

Traditional neuroscience paradigms often lack the multimodal complexity that characterizes everyday cognition. This reduction is useful for isolating specific functions, but it also risks oversimplifying the operational space of a given brain region. Advances in neuroimaging, particularly the combination of high-resolution spatial mapping with millisecond-scale intracranial EEG, now allow more ecologically valid approaches to brain function. The anterior insula (AI) illustrates this need for refinement as traditional task-based studies have assigned it a broad range of roles, largely because each paradigm targets a single cognitive demand. Naturalistic tasks, by contrast, rapidly traverse diverse sensory, affective, and cognitive states, embedding multiple micro-paradigms within one continuous sequence. In iEEG, such designs act as ahypotheses filter, identifying the precise contexts that elicit AI engagement and, crucially, the many contexts that do not. This accumulation of negative evidence enables rejection of overly general hypotheses and delineates the true functional boundaries of the AI with unprecedented ecological and temporal precision.