Neural Decoding as Cognitive Inference
The brain maintains stable cognition despite continuously changing neural activity. How to extract stable cognitive states from variable neural observations remains a central problem in neural decoding. Existing neural decoding methods map neural observations to predefined external labels based on the stimulus-response principle, often capturing recording-specific spurious correlations. Inspired by how the brain infers the world, and specifically by Bayesian brain theory, we recast neural decoding as cognitive inference constrained by brain-intrinsic priors, yielding high-level meta-neural semantic representations. In decoding experiments spanning five neural recording modalities and thre...
| Authors | Yi Guo, Changhong Jing, Yong Hu et al. |
|---|---|
| Primary category | q-bio.NC |
| Published | 8 October 2026 |
| Last updated at source | 8 October 2026 |
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