bioRxivNeurosciencePreprint
Neural Representations of Task-relevant and Task-irrelevant Features of Attended Objects
Jiageng CheniD, Paul S. ScottiiD, Emma Wu DowdiD, Julie D. GolombiD
Abstract
Visual attention plays an essential role in selecting task-relevant and ignoring task-irrelevant information, for both object features and their locations. In the real world, multiple objects with multiple features are often simultaneously present in a scene. When spatial attention selects an object, how are the task-relevant and task-irrelevant features represented in the brain? Previous literature has shown conflicting results on whether and how irrelevant features are represented in visual cortex. In an fMRI task, we used a modified inverted encoding model (IEM, e.g., Sprague & Serences, 2015) to test whether we can reconstruct the task-relevant and task-irrelevant features of spatially attended objects in a multi-feature (color + orientation), multi-item display. Subjects were briefly shown an array of three colored, oriented gratings. Subjects were instructed as to which feature (color or orientation) was relevant before each block, and on each trial were asked to report the task-relevant feature of the object that appeared at a spatially pre-cued location, using a continuous color or orientation wheel. By applying the IEM, we achieved reliable feature reconstructions for the task-relevant features of the attended object from visual ROIs (V1 and V4v) and Intraparietal sulcus. Preliminary searchlight analyses showed that task-irrelevant features of attended objects could be reconstructed from activity in some intraparietal areas, but the reconstructions were much weaker and less reliable compared with task-relevant features. These results suggest that both relevant and irrelevant features may be represented in visual and parietal cortex but in different forms. Our method provides potential tools to noninvasively measure unattended feature representations and probe the extent to which spatial attention acts as a "glue" to bind task-relevant and task-irrelevant features.
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