Research map / Probabilistic and scientific modeling / Dynamical systems
System Identification with Biophysical Constraints: A Circuit Model of the Inner Retina
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use BCN biophysical model instead of LN model | BC response model · chirp training data | Pearson correlation: 0.80 -> 0.96 (local chirp) | Helped |
| use BCN instead of LN model on held-out stimuli | BC response model · natural movies | Pearson correlation: 0.18 -> 0.24 | Helped |
| use BCN instead of parameter-matched LSTM | BC response model · natural movies | Pearson correlation: 0.24 -> 0.24 | No clear effect |
| use BCN instead of LSTM on training chirps | BC response model · local chirp | Pearson correlation: 1.00 -> 0.96 | Hurt |
| add AC feedback terms to the LNR model (ablation) | BCN · chirp responses | training correlation | Helped |
| add vesicle release block (ablation) | BCN · chirp responses | training correlation | Helped |
| use trained feedback weights instead of random initialized feedback weights (ablation) | BCN · training chirp | correlation | Helped |
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