Can a Neural Encoding Model Replicate an fMRI Visualization Study?
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Abstract (arXiv)
Most knowledge of graphical perception comes from behavioral studies. Understanding from a neural perspective is much more limited due in part to neuroimaging studies' expensiveness and difficulty to conduct. In this paper, we evaluate whether Meta's Tribe V2 neural encoding model can recover neural contrasts from a visualization fMRI study. Specifically, we evaluate Tribe V2 through a conceptual replication of the visualization-viewing component of a prior comparison of Bubble charts and three-dimensional Surface charts in color and grayscale. We generate TRIBE-predicted cortical responses for the original stimuli and compare the resulting contrasts with those reported in the human study. The model reproduced the direction of 11 of 14 reported cortical effects, with agreement concentrated in visual-processing regions. This agreement characterizes the model's alignment with the prior human-generated fMRI results rather than independently confirming them. We discuss the limitations encountered when working with this model for in-silico replication and hope to encourage future work exploring this new avenue for neuroimaging studies in visualization. Supplemental materials are available at https://osf.io/8a96x/.
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References · 7
- 2026A foundation model of vision, audition, and language for in-silico neurosciencecited by 12
- 2023Vistrust: a Multidimensional Framework and Empirical Study of Trust in Data Visualizationscited by 2
- 2019You Can't Publish Replication Studies (and How to Anyways)cited by 1
- 2024Motion-based visual encoding can improve performance on perceptual tasks with dynamic time seriescited by 1
- 2025Evaluating Graphical Perception with Multimodal LLMscited by 1
- 2026Evaluating Graphical Perception Capabilities of Vision Transformerscited by 1
- 2026Boosting Brain-to-Image Decoding with TRIBE v2 Data Augmentationcited by 1
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