Adaptive recruitment of cortex-wide recurrence for visual object recognition

Abstract

Theories of the neural mechanism underpinning rapid recognition debate whether it relies solely on a feedforward sweep through the ventral stream or instead requires recurrent processing, possibly engaging additional brain regions. Here we directly tested the "adaptive recurrence hypothesis", that attempts to unify these disparate views by proposing that additional recurrent cortical resources beyond the visual stream are recruited when feedforward processing alone is insufficient to solve object recognition. To investigate this hypothesis, we contrasted functional MRI (fMRI) and electroencephalography (EEG) responses to compare neural responses to images that are equally well recognized by humans, but that differ in whether they could be solved by a feedforward deep neural network; a computational proxy for ventral stream feedforward processing. We found that when feedforward processing in the ventral visual stream is insufficient, additional parieto-frontal networks are rapidly and transiently recruited, representationally reconfiguring the ventral visual stream. Our results reveal that object recognition flexibly adapts through fast, cortex-wide recurrence, providing a unifying framework for competing theories of visual recognition.