A generative-model simulator of decoded neurofeedback shows that alternative-class choice, initial cognitive state, and random exploration jointly determine whether simulated participants learn or appear as non-responders.
Self-regulation of the anterior insula: Reinforcement learning using real-time fMRI neurofeedback
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DecNefSimulator: A Modular, Interpretable Framework for Decoded Neurofeedback Simulation Using Generative Models
A generative-model simulator of decoded neurofeedback shows that alternative-class choice, initial cognitive state, and random exploration jointly determine whether simulated participants learn or appear as non-responders.