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Attentional Blink Task

T000058T000058-attentional-blinkDraftWeb preview availableUpdated Jul 11, 2026

This task measures the reduced ability to report a second target presented shortly after a first target in a rapid serial visual presenta...

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Quick start

Clone locally, then follow the README for install and run instructions.

git clone https://github.com/TaskBeacon/T000058-attentional-blink.git
cd T000058-attentional-blink
# Follow the README for local setup and run steps

README

View on GitHub

Attentional Blink Task

Field	Value
Name	Attentional Blink Task
Version	v0.1.0
Repository	https://github.com/TaskBeacon/T000058-attentional-blink
Date Updated	2026-07-11
PsyFlow Version	0.1.0
PsychoPy Version	2025.1.1
Modality	Behavior
Language	Chinese
Primary construct	Temporal attention

1. Task Overview

This task measures the reduced ability to report a second target presented shortly after a first target in a rapid serial visual presentation (RSVP). Participants view uppercase letters containing one or two digit targets, then report the targets in order. The primary outcome is T2 accuracy conditional on correct T1 report, compared between 336-ms and 672-ms intervals.

2. Task Flow

Task Flow

Block-Level Flow

Step	Description
Instructions	Explain targets, ordered report, and the T2-absent zero response.
Practice	Run 34 practice trials with brief feedback in human mode.
Scored blocks	Run four intermixed 102-trial blocks with exact counts.
Block summary	Show T1 and conditional T2 accuracy.
Save	Export one reduced row per RSVP trial.

Trial-Level Flow

Phase	Duration	Visible content / response
Fixation	1,780 ms	Central `+`.
RSVP item	50 ms	One letter, digit, or planned blank.
Inter-item blank	34 ms	Gray blank.
Post-stream delay	1,000 ms	Gray blank.
T1 report	5 s max	Press 2-9.
T2 report	5 s max	Press 2-9, or 0 for confident absence.
ITI	200 ms	Gray blank.

Controller Logic

No adaptive controller is used. src/utils.py deterministically preplans exact condition counts, target identities, constrained positions, letter streams, and optional blank distractors before trials begin.

Other Logic

T2 accuracy is conditionalized on correct T1 report. Blink magnitude is long-present conditional T2 accuracy minus short-present conditional T2 accuracy.

3. Configuration Summary

a. Subject Info

Field	Meaning
`subject_id`	Three-digit participant identifier.

b. Window Settings

Parameter	Value
Resolution	1024 x 768
Units	visual degrees
Background	gray

c. Stimuli

Element	Implementation
Distractors	Uppercase letters excluding B, I, O, Q, S.
Targets	Distinct digits from 2-9.
Optional blanks	20% of eligible distractor positions.
Prompts	Config-defined Chinese text using SimHei.

d. Timing

Parameter	Value
Fixation	1.780 s
Item / blank	0.050 / 0.034 s
Short / long interval	0.336 / 0.672 s
Post-stream delay	1.000 s
ITI	0.200 s

Triggers

Separate codes mark fixation, distractors, T1, T2, T2-absent positions, reports, responses, timeouts, practice feedback, and ITI. See config/config.yaml.

Adaptive Controller

None.

4. Methods (for academic publication)

Participants completed a digit-target attentional-blink task adapted from Slagter et al. (2007). Each trial began with a 1,780-ms fixation, followed by a 15- or 19-item RSVP stream. Items appeared for 50 ms with a 34-ms blank between items. One or two digits from 2-9 were embedded among uppercase letter distractors. T2 occurred either 336 ms or 672 ms after T1, or was replaced by a blank on T2-absent trials. One second after the stream, participants reported T1 and then T2; zero indicated confident T2 absence. T2 accuracy was analyzed conditional on correct T1 report.

Running

python main.py
python main.py qa --config config/config_qa.yaml
python main.py sim --config config/config_scripted_sim.yaml
python main.py sim --config config/config_sampler_sim.yaml