PsychoPy in Persian linguistics (Session three)

This presentation explores how to use PsychoPy to design and run three widely used psycholinguistic tasks: the Stroop Task, the Lexical Decision Task, and the Picture-Word Matching Task. The Stroop Task looks at how our brains handle conflicting information, for example, asking participants to say the color of a word while ignoring what the word actually says. This helps researchers understand automatic processing and how we control our attention. The Lexical Decision Task focuses on word recognition. Participants are shown a string of letters and asked whether it’s a real word or not, which gives insights into how we access words in our mental lexicon and process language. The Picture-Word Matching Task examines how we connect visual and verbal information. Participants decide whether a word matches the image shown, shedding light on how we process meaning and integrate different types of information. The presentation walks through how to build these tasks in PsychoPy, including how to create condition files, set up routines, and use different components like text, images, and keyboard responses. It highlights how flexible and useful these tasks are for studying various cognitive and language-related processes, especially in areas like multilingualism, semantic integration, and even clinical research. There are also plenty of practical tips, like keeping stimuli simple and using relative file paths, to help make experiments smoother and more effective.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-16
DOI
https://doi.org/10.5281/zenodo.15433816
Primary Topic
Neurobiology of Language and Bilingualism
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

PsychoPy in Persian linguistics (Session three)

Zenodo (CERN European Organization for Nuclear Research)
Neurobiology of Language and Bilingualism
article

PsychoPy in Persian linguistics (Session three)

article en

Abstract

This presentation explores how to use PsychoPy to design and run three widely used psycholinguistic tasks: the Stroop Task, the Lexical Decision Task, and the Picture-Word Matching Task. The Stroop Task looks at how our brains handle conflicting information, for example, asking participants to say the color of a word while ignoring what the word actually says. This helps researchers understand automatic processing and how we control our attention. The Lexical Decision Task focuses on word recognition. Participants are shown a string of letters and asked whether it’s a real word or not, which gives insights into how we access words in our mental lexicon and process language. The Picture-Word Matching Task examines how we connect visual and verbal information. Participants decide whether a word matches the image shown, shedding light on how we process meaning and integrate different types of information. The presentation walks through how to build these tasks in PsychoPy, including how to create condition files, set up routines, and use different components like text, images, and keyboard responses. It highlights how flexible and useful these tasks are for studying various cognitive and language-related processes, especially in areas like multilingualism, semantic integration, and even clinical research. There are also plenty of practical tips, like keeping stimuli simple and using relative file paths, to help make experiments smoother and more effective.

Zenodo (CERN European Organization for Nuclear Research)
Alzahra University (IR)
Quality Education
Openalex Percentile: Top 56%
Neurobiology of Language and Bilingualism
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.