Honeycomb: a template for reproducible psychophysiological tasks for clinic, laboratory, and home use

Autor: Nicole R. Provenza, Luiz Fernando Fracassi Gelin, Wasita Mahaphanit, Mary C. McGrath, Evan M. Dastin-van Rijn, Yunshu Fan, Rashi Dhar, Michael J. Frank, Maria I. Restrepo, Wayne K. Goodman, David A. Borton
Jazyk: English<br />Portuguese
Rok vydání: 2021
Předmět:
Zdroj: Brazilian Journal of Psychiatry (2021)
Druh dokumentu: article
ISSN: 1809-452X
1516-4446
DOI: 10.1590/1516-4446-2020-1675
Popis: Objective: To improve the ability of psychiatry researchers to build, deploy, maintain, reproduce, and share their own psychophysiological tasks. Psychophysiological tasks are a useful tool for studying human behavior driven by mental processes such as cognitive control, reward evaluation, and learning. Neural mechanisms during behavioral tasks are often studied via simultaneous electrophysiological recordings. Popular online platforms such as Amazon Mechanical Turk (MTurk) and Prolific enable deployment of tasks to numerous participants simultaneously. However, there is currently no task-creation framework available for flexibly deploying tasks both online and during simultaneous electrophysiology. Methods: We developed a task creation template, termed Honeycomb, that standardizes best practices for building jsPsych-based tasks. Honeycomb offers continuous deployment configurations for seamless transition between use in research settings and at home. Further, we have curated a public library, termed BeeHive, of ready-to-use tasks. Results: We demonstrate the benefits of using Honeycomb tasks with a participant in an ongoing study of deep brain stimulation for obsessive compulsive disorder, who completed repeated tasks both in the clinic and at home. Conclusion: Honeycomb enables researchers to deploy tasks online, in clinic, and at home in more ecologically valid environments and during concurrent electrophysiology.
Databáze: Directory of Open Access Journals
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