Evidence map›Paper›PMID 39715746›Full record

ArticleScientific data2024

HED LANG - A Hierarchical Event Descriptors library extension for annotation of language cognition experiments.

Monique Denissen, Bernhard Pöll, Kay Robbins, Scott Makeig, Florian Hutzler

Abstract readDataset
In one paragraph

Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Monique DenissenParis-Lodron-University of Salzburg, Department of Psychology, Centre for Cognitive Neuroscience, Salzburg, Austria. monique.denissen@plus.ac.at.ORCID 0000-0002-7120-1075
Bernhard PöllParis-Lodron-University of Salzburg, Department of Romance Studies, Salzburg, Austria.ORCID 0000-0002-3330-0654
Kay RobbinsUniversity of Texas At San Antonio, Department of Computer Science, San Antonio, USA.ORCID 0000-0002-7147-5797
Scott MakeigInstitute for Neural Computation, Swartz Center for Computational Neuroscience, University of California San Diego, San Diego, USA.
Florian HutzlerParis-Lodron-University of Salzburg, Department of Psychology, Centre for Cognitive Neuroscience, Salzburg, Austria.ORCID 0000-0001-8195-4911

Funding

EEGLAB: Software for Analysis of Human Brain DynamicsR01NS047293 · NINDS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Arnaud Delorme, Scott Makeig · 2004 to 2026
$10.2M
BRAIN Initiative: Hierarchical Event Descriptors (HED): a system to characterize events in neurobehavioral dataRF1MH126700 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DELORME, ARNAUD, MAKEIG, SCOTT · 2022 to 2022
$1.0M
Austrian Science Fund (Fonds zur Förderung der Wissenschaftlichen Forschung) W1233-BNIMH NIH HHS RF1 MH126700NINDS NIH HHS R01 NS047293U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) R01MH126700-01A1
6 · The paper itself

Abstract

Experimental design in language cognition research often involves presenting language material while measuring associated behavior and/or neural activity. To make the collected data easily and fully analyzable by both the original data authors and others, it is important to have detailed information about the stimulus presentation events, including the nature and properties of the presented stimuli, using a common vocabulary and syntax. We present HED LANG, a library extension of the Hierarchical Event Descriptors (HED) event annotation schema for time series behavioral and neuroimaging data. HED LANG provides an open source, standardized vocabulary for building detailed, human- and machine-actionable annotations for language cognition datasets. It builds on existing annotation systems in linguistics and is supported by a suite of HED tools for annotating, validating, searching, and characterizing HED-tagged datasets. HED LANG is specific enough to allow event data annotation at the range of levels needed to support many current research paradigms and analyses. Both HED and HED LANG are open to community input and participation, enabling them to evolve with continuing developments in language cognition research.

Indexed as

CognitionLanguageHumansLinguisticsNeuroimaging

Identifiers

PMID39715746
PMCPMC11666789

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.