BrainCause recovers known visual localizations and finds new candidate representations by validating causal specificity via counterfactual stimuli and encoding models, showing activation alone produces many false positives.
Kay, Thomas Naselaris, Ryan J
2 Pith papers cite this work. Polarity classification is still indexing.
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LITcoder introduces a modular open-source library for constructing, benchmarking, and comparing neural encoding models that map continuous stimuli such as stories to fMRI brain data.
citing papers explorer
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From Activation to Causality: Discovery of Causal Visual Representations in the Human Brain
BrainCause recovers known visual localizations and finds new candidate representations by validating causal specificity via counterfactual stimuli and encoding models, showing activation alone produces many false positives.
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LITcoder: A General-Purpose Library for Building and Comparing Encoding Models
LITcoder introduces a modular open-source library for constructing, benchmarking, and comparing neural encoding models that map continuous stimuli such as stories to fMRI brain data.