Evidence map›Paper›PMID 38846339›Full record

ArticleFrontiers in neuroinformatics2024

Events in context-The HED framework for the study of brain, experience and behavior.

Scott Makeig, Kay Robbins

Abstract read
In one paragraph

Article in Frontiers in neuroinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Scott MakeigSwartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla, CA, United States.
Kay RobbinsDepartment of Computer Science, University of Texas San Antonio, San Antonio, TX, United States.

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
NIMH NIH HHS RF1 MH126700NINDS NIH HHS R01 NS047293
6 · The paper itself

Abstract

The brain is a complex dynamic system whose current state is inextricably coupled to awareness of past, current, and anticipated future threats and opportunities that continually affect awareness and behavioral goals and decisions. Brain activity is driven on multiple time scales by an ever-evolving flow of sensory, proprioceptive, and idiothetic experience. Neuroimaging experiments seek to isolate and focus on some aspect of these complex dynamics to better understand how human experience, cognition, behavior, and health are supported by brain activity. Here we consider an event-related data modeling approach that seeks to parse experience and behavior into a set of time-delimited events. We distinguish between

Indexed as

analysis-ready dataBIDScontextdata standardseventHEDHierarchical Event Descriptorsneuroimaging

Identifiers

PMID38846339
PMCPMC11153828

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.