Evidence map›Paper›PMID 35528322›Full record

ArticleLanguage, cognition and neuroscience2020

Toward a Database of Intracranial Electrophysiology during Natural Language Presentation.

Erik Kaestner, Adam Milton Morgan, Joseph Snider, Meilin Zhan, Xi Jiang, Roger Levy, Victor S Ferreira, Thomas Thesen, Eric Halgren

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Language, cognition and neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.1field-weighted citation impact, top 53% of its field
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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

9 authors at 3 institutions in 1 country.

Erik KaestnerDepartment of Neurosciences, University of California at San Diego, La Jolla, California.
Adam Milton MorganDepartment of Psychology, University of California at San Diego, La Jolla, California.
Joseph SniderInstitute for Neural Computation, University of California at San Diego, La Jolla, California.
Meilin ZhanDepartment of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts.
Xi JiangDepartment of Neurosciences, University of California at San Diego, La Jolla, California.
Roger LevyDepartment of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts.
Victor S FerreiraDepartment of Psychology, University of California at San Diego, La Jolla, California.
Thomas ThesenDepartment of Neurology, New York University Comprehensive Epilepsy Center, New York, New York.
Eric HalgrenDepartment of Neurosciences, University of California at San Diego, La Jolla, California.
University of California, San Diego · USMassachusetts Institute of Technology · USNew York University · US

Funding

Neurosciences Graduate Training ProgramT32NS061847 · NINDS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Brenda L Bloodgood · 2008 to 2026
$7.7M
CRCNS: Multiresolution Modeling of Human Thalamocortical Upstates and DownstatesR01MH099645 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI HALGREN, ERIC · 2012 to 2016
$1.8M
NIMH NIH HHS R01 MH099645NINDS NIH HHS T32 NS061847
6 · The paper itself

Abstract

Intracranial electrophysiology (iEEG) studies using cognitive tasks contribute to the understanding of the neural basis of language. However, though iEEG is recorded continuously during clinical treatment, due to patient considerations task time is limited. To increase the usefulness of iEEG recordings for language study, we provided patients with a tablet pre-loaded with media filled with natural language, wirelessly synchronized to clinical iEEG. This iEEG data collected and time-locked to natural language presentation is particularly applicable for studying the neural basis of combining words into larger contexts. We validate this approach with pilot analyses involving words heard during a movie, tagging syntactic properties and verb contextual probabilities. Event-related averages of high-frequency power (70-170Hz) identified bilateral perisylvian electrodes with differential responses to syntactic class and a linear regression identified activity associated with contextual probabilities, demonstrating the usefulness of aligning media to iEEG. We imagine future multi-site collaborations building an 'intracranial neurolinguistic corpus'.

Identifiers

PMID35528322
PMCPMC9074941
OpenAlexW2884022857

What OpenQuestion holds

Textmetadata
LicenceTDM
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 OpenQuestion graph.