This satellite event will show how in-silico experimentation can be used as a practical framework for benchmarking computational models of the human brain. It builds directly on our recent efforts (Wang, Deb et al. in prep) that show how prior experiments can be replayed in silico and used to evaluate which findings replicate across candidate brain models and which do not. Participants will be invited to run in-silico experiments of their own design using a drag-and-drop executable modeling platform.
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How encoding models can move beyond prediction toward replication. Introducing our drag-and-drop executable modeling platform: Cortex.
A brief introduction to how we build encoding models.
Looking into the Past — Replicating Published Findings
An overview of representative in-silico tests we have already performed, and what insights they have revealed.
Participants use the Lab with curated stimuli from published studies to examine whether model predictions reproduce known experimental findings.
A discussion of what the models captured, where they failed, and what replication successes and failures can reveal about both computational models and cognitive theories.
Other Uses Beyond Replication — Education and scientific exploration
How the platform can support teaching, demonstration, and conceptual understanding in vision science.
Short perspectives on how forward-looking simulations and model-based hypotheses can complement replication work when planning new experiments and refining study designs.
Participants use the same Lab workflow with their own stimuli or modified examples to compare predicted responses across ROIs or models and explore how simulations might refine future experimental hypotheses.
A discussion of how model simulations can help generate hypotheses, sharpen experimental designs, and reveal the limits of current models.