Finding

garrett-2023-visual-behavior.hit-rate-by-image-pair

Garrett ME et al. Stimulus novelty uncovers coding diversity in visual cortical circuits. bioRxiv, 2023. · Allen Visual Behavior change detection · hit rate by condition

Observed curve and fits

Fit diagnostics

Caveats on these fits (2 terms)

Each tag below is attached to one or more candidate fits for this finding. The chip column in the table flags which row carries which tag.

condition-rate null
One-parameter Bernoulli baseline over condition levels; useful for categorical or ordinal hit-rate curves without a sensory evidence axis.
condition-rate saturated
Per-condition Bernoulli baseline over categorical or ordinal hit-rate levels; descriptive upper-bound, not a sensory evidence model.
Variant AIC Δ AIC RMSE Caveats
bernoulli-condition-rate winner 260.6 0.0 0.1660
  • condition-rate null
bernoulli-condition-saturated 325.5 64.8 4.63e-10
  • condition-rate saturated
Full diagnostics (logL · n · params · max abs error)
Variant logL n Free params Max |error| Predicted points
bernoulli-condition-rate -129.3 236 1 0.5127 56
bernoulli-condition-saturated -106.7 236 56 1.00e-9 56

Residuals

Fit parameters and provenance

bernoulli-condition-rate.garrett-2023-visual-behavior.hit-rate-by-image-pair

dirty fit

response_rate=0.763

Method
manual
Commit
3ec74b4
Predicted points
56
BIC
264.1

Fitted with manual via behavtaskatlas.model_fits.bernoulli-condition-rate; success=True; closed-form binomial MLE

bernoulli-condition-saturated.garrett-2023-visual-behavior.hit-rate-by-image-pair

dirty fit

response_rate_x0=0.667 · response_rate_x1=0.750 · response_rate_x10=0.667 · response_rate_x11=0.750 · response_rate_x12=0.500 · response_rate_x13=0.500 · response_rate_x14=0.750 · response_rate_x15=0.800 · response_rate_x16=0.750 · response_rate_x17=0.750 · response_rate_x18=1.000 · response_rate_x19=1.000 · response_rate_x2=1.000 · response_rate_x20=1.000 · response_rate_x21=0.750 · response_rate_x22=0.750 · response_rate_x23=0.750 · response_rate_x24=0.500 · response_rate_x25=0.750 · response_rate_x26=0.250 · response_rate_x27=0.750 · response_rate_x28=0.750 · response_rate_x29=0.750 · response_rate_x3=0.600 · response_rate_x30=0.800 · response_rate_x31=0.667 · response_rate_x32=1.000 · response_rate_x33=0.500 · response_rate_x34=1.000 · response_rate_x35=1.000 · response_rate_x36=0.500 · response_rate_x37=0.500 · response_rate_x38=0.750 · response_rate_x39=0.600 · response_rate_x4=1.000 · response_rate_x40=0.750 · response_rate_x41=0.750 · response_rate_x42=0.750 · response_rate_x43=0.750 · response_rate_x44=0.750 · response_rate_x45=0.800 · response_rate_x46=0.750 · response_rate_x47=0.750 · response_rate_x48=0.800 · response_rate_x49=1.000 · response_rate_x5=1.000 · response_rate_x50=0.750 · response_rate_x51=0.500 · response_rate_x52=0.800 · response_rate_x53=0.600 · response_rate_x54=0.750 · response_rate_x55=0.800 · response_rate_x6=0.800 · response_rate_x7=1.000 · response_rate_x8=1.000 · response_rate_x9=0.750

Method
manual
Commit
3ec74b4
Predicted points
56
BIC
519.4

Fitted with manual via behavtaskatlas.model_fits.bernoulli-condition-saturated; success=True; closed-form per-condition Bernoulli MLE

Observed points

Image-pair index (sorted by initial then change image) hit_rate n
0.000 0.6667 3
1.000 0.7500 4
2.000 1.0000 4
3.000 0.6000 5
4.000 1.0000 4
5.000 1.0000 4
6.000 0.8000 5
7.000 1.0000 4
8.000 1.0000 5
9.000 0.7500 4
10.000 0.6667 3
11.000 0.7500 4
12.000 0.5000 4
13.000 0.5000 4
14.000 0.7500 4
15.000 0.8000 5
16.000 0.7500 4
17.000 0.7500 4
18.000 1.0000 4
19.000 1.0000 5
20.000 1.0000 4
21.000 0.7500 4
22.000 0.7500 4
23.000 0.7500 4
24.000 0.5000 4
25.000 0.7500 4
26.000 0.2500 4
27.000 0.7500 4
28.000 0.7500 4
29.000 0.7500 4
30.000 0.8000 5
31.000 0.6667 3
32.000 1.0000 5
33.000 0.5000 4
34.000 1.0000 5
35.000 1.0000 4
36.000 0.5000 4
37.000 0.5000 4
38.000 0.7500 4
39.000 0.6000 5
40.000 0.7500 4
41.000 0.7500 4
42.000 0.7500 4
43.000 0.7500 4
44.000 0.7500 4
45.000 0.8000 5
46.000 0.7500 4
47.000 0.7500 4
48.000 0.8000 5
49.000 1.0000 5
50.000 0.7500 4
51.000 0.5000 4
52.000 0.8000 5
53.000 0.6000 5
54.000 0.7500 4
55.000 0.8000 5

Take it with you

Cover sheet

Self-contained Markdown for citation, slides, or notebooks

The cover sheet pins the finding to the atlas commit and includes the observed points, fit ranking, caveats, and provenance — everything needed to drop into a paper or notebook without losing the trail back to the deploy.