Visual looming is a primitive for human emotion.

Looming objects afford threat of collision across the animal kingdom. Defensive responses to looming and neural computations for looming detection are strikingly conserved across species. In mammals, information about rapidly approaching threats is conveyed from the retina to the midbrain superior colliculus, where variables that indicate the position and velocity of approach are computed to enable defensive behavior . Neuroscientific theories posit that emotional feelings are based on representations in the midbrain , which are further elaborated in cortical systems . However, how these computations relate to phenomenal experience in humans is largely unknown. Here, we show that a shallow convolutional neural network based on the visual system predicts human behavioral and brain responses across development. In laboratory experiments using controlled visual stimuli, we find that this model explains defensive behaviors to looming objects in infants and superior colliculus responses to optical expansion in adults. Further, examining responses to a broader array of naturalistic video clips, we observe that representations of looming from this model predict self-reported emotion largely on the basis of subjective arousal. Our results illustrate how human emotions may be supported by species-general systems for survival in unpredictable environments.