Online Lecture by Kohitij Kar
Recurrent computations during visual object perception—investigating within and beyond the primate ventral stream.
Recurrent circuits are ubiquitous in the primate ventral stream, that supports core object recognition — primate’s ability to rapidly categorize objects. While recurrence has long been thought to be functionally important to visual processing, this has remained mostly a motivating idea and very difficult to mechanistically probe in the visual system; especially at the shorter time scales (<200 ms) of core object recognition. Our work has achieved three advances that help demonstrate and localize the functional importance of recurrent computations during object recognition. Advance 1: We compared primate behavior with feedforward deep convolutional neural networks. This led to the discovery of many “challenge” images that are easily categorized by primates, but not by current models. Further investigation into brain-based solutions for these images revealed evidence of feedback-related neural signals in the macaque IT cortex that are critical for solving these “challenge” images by the primates. However, we do not yet know which brain circuits are most responsible for these additional, recurrent computations. Advance 2: We have started probing with pharmacological inactivation whether feedback from downstream targets of IT like ventral PFC is critical during core object recognition. Advance 3: We have also begun testing an array of chemogenetic neuronal silencing strategies (via viral delivery of DREADDs) that will allow suppression of targeted recurrent circuits in the primate brain. In sum, our approach provides key architectural as well as image-level behavioral and neural constraints that will guide the next-generation recurrent models of the visual system.