Finding

walsh-2024-prior-cue.psychometric.subject.cue-invalid.subject-k

Walsh K, McGovern DP, Dully J, Kelly SP, O'Connell RG. Prior probability cues bias sensory encoding with increasing task exposure. eLife 12:RP91135, 2024. · Human visual contrast 2AFC keyboard task · psychometric

Observed curve and fits

Fit diagnostics

Variant AIC Δ AIC RMSE Caveats
sdt-2afc winner 848.4 0.0 0.1347 —
logistic-4param 852.9 4.5 0.1353 —
Full diagnostics (logL · n · params · max abs error)
Variant logL n Free params Max |error| Predicted points
sdt-2afc -422.2 715 2 0.1946 6
logistic-4param -422.4 715 4 0.1959 6

Residuals

Fit parameters and provenance

sdt-2afc.walsh-2024-prior-cue.psychometric.subject.cue-invalid.subject-k

dirty fit

criterion=-0.469 · d_prime=0.032

Method
scipy.optimize.minimize
Commit
24fd416
Predicted points
6
BIC
857.6

Fitted with scipy.optimize.minimize via behavtaskatlas.model_fits.sdt-2afc; success=True; CONVERGENCE: RELATIVE REDUCTION OF F <= FACTR*EPSMCH

logistic-4param.walsh-2024-prior-cue.psychometric.subject.cue-invalid.subject-k

dirty fit

bias=-14.871 · lower_lapse=0.000 · slope=19.332 · upper_lapse=0.000

Method
scipy.optimize.minimize
Commit
24fd416
Predicted points
6
BIC
871.2

Fitted with scipy.optimize.minimize via behavtaskatlas.model_fits.logistic-4param; success=True; CONVERGENCE: RELATIVE REDUCTION OF F <= FACTR*EPSMCH

Observed points

Signed target-distractor contrast p_right n
-22.000 0.3333 60
-12.000 0.3412 85
-8.000 0.7633 207
8.000 0.6244 205
12.000 0.8901 91
22.000 0.9552 67

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.