Shijie Qu¹ (), Marvin M. Chun¹, Yaoda Xu¹; ¹Yale University

Visual processing often involves attending to different object features under various task loads. Past studies reported that some object and task features are encoded independently, while others are represented interactively in the human occipitotemporal cortex (OTC) and posterior parietal cortex (PPC). However, the mechanisms underlying their coding in the prefrontal cortex (PFC) are not fully understood. As a hub for cognitive control, it is possible that PFC primarily encodes task-related features, such as attention and load, but not object identity. Alternatively, it may simultaneously encode object identity alongside attention and load. If the latter holds, delineating how these distinct features are coded together in PFC can provide a mechanistic understanding of how it processes diverse information during visual tasks. In this fMRI study, 12 human participants performed an n-back task on colored visual stimuli, with task load (1-back and 2-back) and attention content (color and shape) varied orthogonally. Using multi-voxel pattern analysis, we found that PFC can decode not only task features such as attention and load, but also object identity. Comparison across brain regions showed that load representation was the strongest in PFC while object representation was the strongest in OTC. Attention representation, however, appears to be weaker in PFC than in OTC. Additional analyses revealed that while object representation only interacts with attention in OTC and PPC, it is further modulated by task loads in PFC. Apart from these differences, the three regions converge in that attention representation is modulated by load and object, while load representation remains independent of attention and object. Overall, our results extend prior findings and show a representational gradient across the human brain where object identity information decreases, and load information increases from posterior to anterior regions. We further show that PFC employs distinctive mechanisms to encode objects interactively along with task demands.

Acknowledgements: This research was supported by NIH grant R01EY030854 to YX.