Stop-Signal Task (SST)

Field	Value
Name	Stop-Signal Task (SST)
Version	v1.1.2
URL / Repository	https://github.com/TaskBeacon/T000012-sst
Short Description	Response inhibition task with adaptive stop-signal delay (SSD) using go/stop directional arrow trials.
Created By	Zhipeng Cao (zhipeng30@foxmail.com)
Date Updated	2026-03-02
PsyFlow Version	0.1.9
PsychoPy Version	2025.1.1
Modality	Behavior / EEG
Language	Chinese
Voice Name	zh-CN-YunyangNeural

Run Modes

• Human (default): python main.py
• QA: python main.py qa --config config/config_qa.yaml
• Scripted Sim: python main.py sim --config config/config_scripted_sim.yaml
• Sampler Sim: python main.py sim --config config/config_sampler_sim.yaml

1. Task Overview

This SST measures the ability to suppress an already prepared motor response. Participants respond quickly to left/right white arrows on go trials. On stop trials, the arrow turns red after a stop-signal delay (SSD); participants should withhold responding. SSD is updated online with a staircase controller targeting approximately 50% stop success.

2. Task Flow

Block-Level Flow

Step	Description
Setup	Load config, initialize runtime context (human/qa/sim), open window, load stimuli, initialize triggers and SSD controller.
Instruction	Show participant instructions (voice optional in human mode).
Block Loop	For each block, generate constrained go/stop condition list and run trial loop.
Block Summary	Compute go hit rate and stop success rate, then show break screen.
Finalize	Show goodbye screen, send exp_end, save CSV, close trigger runtime, quit PsychoPy.

Trial-Level Flow

Step	Description
Fixation	Present fixation cross for sampled duration (0.8 to 1.0 s).
Go Trial	Show white arrow, collect response up to go_duration. Timeout logs go miss and shows miss feedback.
Stop Trial (Phase 1)	Show white arrow during SSD (pre_stop_go_window) and capture early responses.
Stop Trial (Phase 2)	Replace with red arrow (stop_signal_window) for remaining go window and capture failed-stop responses.
Update	Mark stop success/failure and update SSD staircase.

Controller Logic

Component	Description
Controller	1-up/1-down SSD staircase in src/utils.py.
Target	target_success = 0.5 for stop success convergence.
Bounds	SSD constrained to 0.05 to 0.5 seconds.
Step	SSD step size 0.05 seconds.
Pooling	Shared SSD by default (condition_specific = false).

3. Configuration Summary

All runtime settings are in config/config.yaml (with config_qa.yaml and sim variants for non-human modes).

a. Subject Info

Field	Meaning
subject_id	Participant ID (3-digit constrained form entry).
subname	Participant name (pinyin).
age	Age (5 to 60).
gender	Gender (Male/Female).

b. Window Settings

Parameter	Value
window.size	[1920, 1080]
window.units	deg
window.fullscreen	true
window.bg_color	gray
window.monitor_width_cm	60
window.monitor_distance_cm	72

c. Stimuli

Name	Type	Description
fixation	text	Central fixation cross.
go_left / go_right	shape	White directional arrows for go responses.
stop_left / stop_right	shape	Red directional arrows as stop signals.
no_response_feedback	text	Message shown after go timeout.
block_break	text	Inter-block summary with go/stop metrics.
instruction_text	textbox	Chinese instructions (voice-convertible in human mode).
good_bye	textbox	End-of-task message.

d. Timing

Phase	Duration
fixation_duration	Random in [0.8, 1.0] s
go_duration	1.0 s
no_response_feedback_duration	0.8 s
ssd	Adaptive (0.05 to 0.5 s)

e. Triggers

Event	Code
exp_onset	98
exp_end	99
block_onset	100
block_end	101
fixation_onset	1
go_onset	10
go_response	11
go_miss	12
stop_onset	22
pre_stop_response	23
on_stop_response	24
no_response_feedback_onset	30

f. Adaptive Controller

Parameter	Value
initial_ssd	0.25
step	0.05
min_ssd	0.05
max_ssd	0.5
target_success	0.5

4. Methods (for academic publication)

Participants completed a stop-signal task comprising directional go responses and infrequent stop-signal inhibition trials. On each trial, a fixation cross preceded a directional arrow. Participants responded to white arrows with left/right button presses. On stop trials, the arrow changed to red after a variable stop-signal delay (SSD), and participants were instructed to withhold responses.

The task used an adaptive staircase controller to adjust SSD online based on stop-trial outcomes (increase after successful stopping, decrease after failed stopping), targeting approximately 50% stop success. Trial-level events (including go onset, stop onset, and response classes) were trigger-marked for synchronization with behavioral/EEG analysis pipelines.