Research map / Probabilistic and scientific modeling / Dynamical systems
A Bayesian method for reducing bias in neural representational similarity analysis
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Replace standard RSA with Bayesian RSA for recovering shared covariance structure | Bayesian RSA · Simulated fMRI, 500 voxels | % of recovered structure not explained by true structure | Helped |
| Lower SNR (f in 1, 2, 4) for standard RSA | Standard RSA · Simulated fMRI | bias in recovered covariance | Hurt |
| Average covariance across 20 simulated participants | Standard RSA · Simulated fMRI | bias in recovered covariance | No clear effect |
| Average covariance across 20 simulated participants | Bayesian RSA · Simulated fMRI | deviation from true covariance | Helped |
| Increase experiment duration from 1 to 2 to 4 runs | Standard RSA · Simulated fMRI | bias | Helped |
| Add Gaussian process smooth prior on log pseudo-SNR with spatial and intensity kernel | Bayesian RSA · Simulated data | variance of pseudo-SNR estimate | Helped |
Closest papers by meaning
- Spectral Analysis of Representational Similarity with Limited Neurons (NeurIPS 2025 · similarity 0.89)
- Gaussian Partial Information Decomposition: Bias Correction and Application to High-dimensional Data (NeurIPS 2023 · similarity 0.86)
- Dynamical Modeling of Behaviorally Relevant Spatiotemporal Patterns in Neural Imaging Data (ICML 2025 · similarity 0.85)
- Neural Representational Consistency Emerges from Probabilistic Neural-Behavioral Representation Alignment (ICML 2025 · similarity 0.85)
- Differentiable Optimization of Similarity Scores Between Models and Brains (ICLR 2025 · similarity 0.85)
- Bayesian Bi-clustering of Neural Spiking Activity with Latent Structures (ICLR 2024 · similarity 0.85)
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