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pilot · 2026-05-05_10h44.37.285

pilot_ANT_2026-05-05_10h44.31.827.csv

Participantpilot
Session001
Date2026-05-05_10h44.37.285
Duration4m 01s
Blocks ran1
nBlocks setting4
Trials120
Accuracy95.0%
Mean RT0.635 s
PsychoPy2026.1.3

Aggregate scores

Computed on correct trials only across 1 block(s); positive scores are interpreted as the network being engaged (slower RT in the harder condition). The ± figure is the standard error of the mean difference; the 95% CI uses the normal approximation. For Bayesian credible intervals (CrI) updated against literature priors, see the Bayesian tab.

Alerting
+10 ms ± 47 ms
95% CI [-82, +103] ms
RT(NC) − RT(DC)
Fan&Posner ref: μ=47, σ=18 ms
Orienting
+63 ms ± 47 ms
95% CI [-29, +156] ms
RT(CC) − RT(SC)
Fan&Posner ref: μ=51, σ=21 ms
Conflict
+62 ms ± 43 ms
95% CI [-23, +147] ms
RT(IC) − RT(CG)
Fan&Posner ref: μ=84, σ=25 ms

Per-block scores

NC No cueCC Centre cueDC Double cueSC Spatial cue
Block Trials Accuracy Mean RT Alerting Orienting Conflict
Block 1 block_h.csv12095.0%0.635 s+10 ms+63 ms+62 ms
Aggregate12095.0%0.635 s+10 ms+63 ms+62 ms

Mean RT by cue (correct trials)

CueMean RT
NC No cue0.647 s
CC Centre cue0.659 s
DC Double cue0.637 s
SC Spatial cue0.596 s

Mean RT by congruency (correct trials)

congruentincongruentneutral
CongruencyMean RT
congruent0.645 s
incongruent0.707 s
neutral0.557 s
NC No cueCC Centre cueDC Double cueSC Spatial cue
Block 1 · block_h.csv 120 trials · accuracy 95.0% · mean RT 0.635 s
Alerting +10 ms · Orienting +63 ms · Conflict +62 ms
NC 0.647 s · CC 0.659 s · DC 0.637 s · SC 0.596 s

Timeline

RT distribution by cue

RT distribution by cue type

NC No cueCC Centre cueDC Double cueSC Spatial cue

Histogram + Gaussian KDE per cue type, correct trials only. Click a legend entry to hide that series.

RT distribution by flanker congruency

congruentincongruentneutral

Same data grouped by the central-arrow's flanker congruency. Neutral trials use the dashed neutral target.

Posterior summary

Closed-form Normal–Normal conjugate update: prior on the participant's mean μ for each ANT score, then per-block scores treated as observations x_i ~ Normal(μ, σ_L) with σ_L = 100 ms. The posterior is analytic, no MCMC needed. Priors come from the per-block Turing model in the previous Julia analysis (centred on Fan&Posner-style population means with σ=100 ms, deliberately broad). Reference column is the population distribution from Fan & Posner.

ScoreBlocks (n) Prior μ ± σ (ms) Reference μ ± σ (ms) Posterior μ ± σ (ms) 95% CrI for μ
Alerting140 ± 10047 ± 1825.1 ± 70.7[-113.5, 163.7]
Orienting150 ± 10051 ± 2156.7 ± 70.7[-81.9, 195.3]
Conflict198 ± 10084 ± 2579.9 ± 70.7[-58.7, 218.5]

Caveat: with only one block of data, the per-score posterior is dominated by the prior. Run more blocks to let the data update beliefs more strongly.

Alerting: RT(NC) − RT(DC)

Orienting: RT(CC) − RT(SC)

Conflict: RT(IC) − RT(CG)