Finding

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

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
logistic-4param winner 494.1 0.0 0.1332 —
sdt-2afc 2449.3 1955.3 0.0898 —
Full diagnostics (logL · n · params · max abs error)
Variant logL n Free params Max |error| Predicted points
logistic-4param -243.0 690 4 0.1884 2
sdt-2afc -1222.7 690 2 0.1111 2

Residuals

Fit parameters and provenance

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

dirty fit

bias=-10.000 · lower_lapse=0.500 · slope=15.965 · upper_lapse=0.000

Method
scipy.optimize.minimize
Commit
24fd416
Predicted points
2
BIC
512.2

Fitted with scipy.optimize.minimize via behavtaskatlas.model_fits.logistic-4param; success=True; CONVERGENCE: NORM OF PROJECTED GRADIENT <= PGTOL

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

dirty fit

criterion=-50.000 · d_prime=1.00e-6

Method
scipy.optimize.minimize
Commit
24fd416
Predicted points
2
BIC
2458.4

Fitted with scipy.optimize.minimize via behavtaskatlas.model_fits.sdt-2afc; success=True; CONVERGENCE: NORM OF PROJECTED GRADIENT <= PGTOL

Observed points

Signed target-distractor contrast p_right n
-10.000 0.9384 357
10.000 0.8889 333

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.