Reassessing Choice Probability: What 59 Macaque Studies Tell Us About Decision-Related Activity in Visual Cortex
Anton PleteneviD, Richard T. BorniD, Gregory C. DeAngelisiD, Raymond C. DoudlahiD, Ichiro Fujita, Joshua I. GoldiD, Robbe L. T. GorisiD, Alexander C. HukiD, Kristine KrugiD, Pooya LaameradiD, Richard D. LangeiD, Aaron J. LeviiD, Hendrikje NienborgiD, Christopher C. PackiD, Andrew J. ParkeriD, Ari RosenbergiD, Mehdi SanayeiiD, Takanori UkaiD, Xuefei YuiD, Adam ZaideliD, Corey M. ZiembaiD, Ralf M. HaefneriD
Abstract
Choice probability (CP) quantifies the trial-by-trial covariation between a sensory neurons response and perceptual reports. Despite extensive interest in CP as a window into how perception is linked to the activity of sensory neurons, the usefulness of CP remains debated. On one hand, reported CP magnitudes vary widely across seemingly equivalent studies, questioning its utility as a metric. On the other hand, the absence of clear patterns in CP variability has made it difficult to use it to adjudicate between competing models of visual perception. Here, we performed a meta-analysis of 150 CP estimates from 59 macaque neurophysiology studies to identify factors that systematically influence CP. We confirmed the positive relationship between CP and neuronal sensitivity both across and within individual studies. When controlled for sensitivity, we found remarkable consistency in CP across varying tasks and brain regions with two notable exceptions. First, CPs were higher in tasks involving bistable percepts, reinforcing the link between CP magnitude and subjective perception. Second, CPs were smaller in area V1, supporting prior suggestions about V1s special role in visual processing. We further found a significant effect of stimulus duration on CP, providing evidence against strictly feedforward models and favoring models with substantial feedback and recurrent processing. Finally, we offer recommendations for future studies to enhance the cross-study comparability and theoretical utility of choice signals as the field transitions to large-scale population recordings. More broadly, our findings demonstrate the benefits of meta-studies that expose patterns across many different tasks and animals - yielding insights that complement large-scale population recordings.
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