Diagnosis terms did not show a clear scanner stop response prediction gain in 132 ds000030 v1.0.0 adults with fixed models fitted on separate people

Source diagnosis terms did not show a clear gain in scanner STOP response prediction for 132 adults in OpenNeuro ds000030 version 1.0.0. We fitted fixed logistic models on 134 separate adults in the training task. The base model used planned delay, prior GO behavior, trial position, age, and source gender. Adding three diagnosis terms gave a log loss gain of -0.00054 nats per trial. A 95% person bootstrap interval with refitting was -0.00631 to 0.00129. All seven planned secondary intervals included zero. The package preserves raw source files, code, predictions, resampling draws, and instructions. A fresh download reproduced all 40 result files exactly. This result applies to these models and this split. It does not establish equal inhibition in the clinical groups.

stop-signal task · response prediction · logistic regression · person-level validation · OpenNeuro · diagnosis labels