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bioRxiv · 10.1101/2021.12.18.473315

Pattern similarity in the frontoparietal control network reflects an "off-veridical" template that optimizes target-match decisions during visual search

Yu, X.·Geng, J. J.
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Abstract

Theories of attention hypothesize the existence of an "attentional" or "target" template that contains task-relevant information in memory when searching for an object. The target template contributes to visual search by directing visual attention towards potential targets and serving as a decisional boundary for target identification. However, debate still exists regarding how template information is stored in the human brain. Here, we conducted a pattern-based fMRI study to assess how template information is encoded to optimize target-match decisions during visual search. To ensure that match decisions reflect visual search demands, we used a visual search paradigm in which all distractors were linearly separable but highly similar to the target and were known to shift the target representation away from the distractor features (Yu & Geng, 2019). In a separate match-to-sample probe task, we measured the target representation used for match decisions across two resting state networks that have long been hypothesized to maintain and control target information: the frontoparietal control network (FPCN) and the visual network (VisN). Our results showed that lateral prefrontal cortex in FPCN maintained the context-dependent "off-veridical" template; in contrast, VisN encoded a veridical copy of the target feature during match decisions. By using behavioral drift diffusion modeling, we verified that the decision criterion during visual search and the probe task relied on a common biased target template. Taken together, our results suggest that sensory-veridical information is transformed in lateral prefrontal cortex into an adaptive code of target-relevant information that optimizes decision processes during visual search.

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Yu, X., Geng, J. J.. 2021-12-22. Pattern similarity in the frontoparietal control network reflects an "off-veridical" template that optimizes target-match decisions during visual search. https://doi.org/10.1101/2021.12.18.473315

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