Task Switching Task

Field	Value
Name	Task Switching Task
Version	v0.2.0-dev
URL / Repository	https://github.com/TaskBeacon/T000027-task-switching
Short Description	Cued task-switching paradigm with explicit rule transitions and switch-cost metrics.
Created By	TaskBeacon
Date Updated	2026-02-19
PsyFlow Version	0.1.9
PsychoPy Version	2025.1.1
Modality	Behavior
Language	Chinese
Voice Name	zh-CN-YunyangNeural (voice disabled by default)

1. Task Overview

This task implements a cue-based task-switching paradigm. Each trial first presents a rule cue (奇偶判断 or 大小判断), then a target digit appears and participants respond with a two-key mapping.

The implementation computes trial transitions (switch/repeat) online and records accuracy, reaction time, timeout behavior, and cumulative score, enabling direct switch-cost analysis.

2. Task Flow

Block-Level Flow

Step	Description
1. Block init	Controller resets block counters and transition history.
2. Trial loop	run_trial(...) executes fixation, cue, decision, feedback, and ITI for each trial.
3. Block summary	Display accuracy, switch/repeat accuracy, mean RT, switch cost, and score.
4. Final summary	Display session-level switching metrics and final score.

Trial-Level Flow

Step	Description
fixation	Jittered fixation baseline before cue.
cue	Show active rule and trial transition tag (起始/重复/切换).
decision	Present one digit and capture F/J response under current rule.
feedback	Show correct/incorrect/timeout feedback with score update.
iti	Jittered inter-trial fixation.

Controller Logic

Component	Description
Rule transition sampling	Controller samples current rule based on switch_probability, then derives trial_type.
Target generation	Digit target sampled from [1,2,3,4,6,7,8,9].
Scoring	Correct +1, incorrect -1, timeout 0.
Metrics	Supports accuracy/RT for overall, switch, repeat, and switch-cost derivation.

Runtime Context Phases

Phase Label	Meaning
fixation	Pre-trial baseline.
cue	Rule cue preparation stage.
decision	Active response window for digit categorization.
feedback	Outcome feedback stage.
iti	Inter-trial transition stage.

3. Configuration Summary

a. Subject Info

Field	Meaning
subject_id	3-digit participant identifier.

b. Window Settings

Parameter	Value
size	[1280, 720]
units	pix
screen	0
bg_color	black
fullscreen	false
monitor_width_cm	35.5
monitor_distance_cm	60

c. Stimuli

Stimulus Group	Description
cue_parity, cue_magnitude, trial_type_tag	Rule cue and transition label stimuli.
Runtime target_digit	Single large digit target rendered during decision phase.
rule_prompt, key_hint	Rule-specific response mapping prompts.
feedback_correct, feedback_incorrect, feedback_timeout	Outcome-dependent feedback texts.
instruction_text, score_text, block_break, good_bye, fixation	Envelope and summary stimuli.

d. Timing

Stage	Duration
fixation	jittered ([0.3, 0.6] s)
cue	fixed (0.6 s)
decision	deadline (2.0 s)
feedback	fixed (0.8 s)
iti	jittered ([0.3, 0.6] s)

e. Triggers

Trigger	Code
exp_onset	1
exp_end	2
block_onset	10
block_end	11
fixation_onset	20
cue_onset	30
decision_onset	40
choice_left	41
choice_right	42
choice_timeout	43
feedback_correct	50
feedback_incorrect	51
feedback_timeout	52
iti_onset	60

f. Adaptive Controller

Parameter Group	Description
switch_probability	Controls likelihood of rule switch vs repeat on each trial.
digit_pool	Candidate target digits used for categorization.
score_deltas	Signed score update policy for correct/incorrect/timeout trials.
random_seed	Enables deterministic QA/sim behavior when set.

4. Methods (for academic publication)

Participants completed a cued task-switching paradigm in which each trial provided an explicit rule cue followed by a single digit requiring binary categorization. Rule transitions were sampled online to create repeat and switch trials, enabling estimation of switching-specific performance costs.

Trial-level outputs include task rule, transition type, target digit, response, correctness, reaction time, timeout status, and cumulative score. The implementation emits trigger-aligned phase events (fixation, cue, decision, feedback, iti) for reproducible behavioral and synchronized acquisition workflows.