Dynamic representation of multidimensional object properties in the human brain.

Our visual world consists of an immense number of unique objects and yet, we are easily able to identify, distinguish, interact, and reason about the things we see within a few hundred milliseconds. This requires that we integrate and focus on a wide array of object properties to support specific behavioral goals. In the current study, we examined how these rich object representations unfold in the human brain by modelling time-resolved MEG signals evoked by viewing single presentations of tens of thousands of object images. Based on millions of behavioral judgments, the object space can be captured in 66 dimensions that we use to guide our understanding of the neural representation of this space. We find that all dimensions are reflected in the time course of response with distinct temporal profiles for different object dimensions. These profiles fell into two broad types, with either a distinct and early peak (~125 ms) or a slow rise to a late peak (~300 ms). Further, early effects were stable across participants, in contrast to later effects which showed more variability, suggesting that early peaks may carry stimulus-specific and later peaks more participant-specific information. Dimensions with early peaks appeared to be primarily visual dimensions and those with later peaks more conceptual, suggesting that conceptual representations are more variable across people. Together, these data provide a comprehensive account of how behaviorally-relevant object properties unfold in the human brain and contribute to the rich nature of object vision.