Task-specific vision models explain task-specific areas ofvisual cortex

Abstract

Computational models such as deep neural networks (DNN) trained for classification are often used to explain responses of the visual cortex. However, not all the areas of the visual cortex are involved in object/scene classification. For instance, scene selective occipital place area (OPA) plays a role in mapping navigational affordances. Therefore, for explaining responses of such task-specific brain area, we investigate if a model that performs a related task can serve as a better computational model than a model that performs an unrelated task. We found that DNN trained on a task (scene-parsing) related to the function (navigational affordances) of a brain region (OPA) explains its responses better than a DNN trained on a task (scene-classification) which is not explicitly related. In a subsequent analysis, we found that the DNNs that showed high correlation with a particular brain region were trained on a task that was consistent with functions of that brain region reported in previous neuroimaging studies. Our results demonstrate that the task is paramount for selecting a computational model of a brain area. Further, explaining the responses of a brain area by a diverse set of tasks has the potential to shed some light on its functions.\n\nAuthor summaryAreas in the human visual cortex are specialized for specific behaviors either due to supervision and interaction with the world or due to evolution. A standard way to gain insight into the function of these brain region is to design experiments related to a particular behavior, and localize the regions showing significant relative activity corresponding to that behavior. In this work, we investigate if we can figure out the function of a brain area in visual cortex using computational vision models. From our results, we find that explaining responses of a brain region using DNNs trained on a diverse set of possible vision tasks can help us gain insights into its function. The consistency of our results using DNNs with the previous neuroimaging studies suggest that the brain region may be specialized for behavior similar to the tasks for which DNNs showed a high correlation with its responses.