Evidence map›Paper›PMID 34155599›Full record

ArticleCognitive, affective & behavioral neuroscience2021

Neurocognitive subprocesses of working memory performance.

Agatha Lenartowicz, Holly Truong, Kristen D Enriquez, Julia Webster, Jean-Baptiste Pochon, Jesse Rissman, Carrie E Bearden, Sandra K Loo, Robert M Bilder

Open access · hybridAbstract read
In one paragraph

Article in Cognitive, affective & behavioral neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.4field-weighted citation impact, top 20% 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

13 citing papers in PubMed, 18 citations in OpenAlex.

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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 1 institution in 1 country.

Agatha LenartowiczUniversity of California Los Angeles, Los Angeles, CA, USA. alenarto@g.ucla.edu.ORCID 0000-0001-8015-8251
Holly TruongUniversity of California Los Angeles, Los Angeles, CA, USA.
Kristen D EnriquezUniversity of California Los Angeles, Los Angeles, CA, USA.
Julia WebsterUniversity of California Los Angeles, Los Angeles, CA, USA.
Jean-Baptiste PochonUniversity of California Los Angeles, Los Angeles, CA, USA.
Jesse RissmanUniversity of California Los Angeles, Los Angeles, CA, USA.
Carrie E BeardenUniversity of California Los Angeles, Los Angeles, CA, USA.
Sandra K LooUniversity of California Los Angeles, Los Angeles, CA, USA.
Robert M BilderUniversity of California Los Angeles, Los Angeles, CA, USA.
University of California, Los Angeles · US

Funding

National Neuropsychological Network (NNN)R01MH118514 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI DANIEL L DRANE, David W. Loring · 2019 to 2026
$9.4M
Alpha oscillations and working memory deficits in ADHD: A multimodal imaging investigationR01MH116268 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI LENARTOWICZ, AGATHA, LOO, SANDRA K · 2019 to 2023
$3.5M
Multi-Level Assays of Working Memory and PsychopathologyR01MH101478 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI BILDER, ROBERT M · 2014 to 2018
$3.0M
NIMH NIH HHS R01 MH101478NIMH NIH HHS R01 MH116268NIMH NIH HHS R01 MH118514
6 · The paper itself

Abstract

Working memory (WM) has been defined as the active maintenance and flexible updating of goal-relevant information in a form that has limited capacity and resists interference. Complex measures of WM recruit multiple subprocesses, making it difficult to isolate specific contributions of putatively independent subsystems. The present study was designed to determine whether neurophysiological indicators of proposed subprocesses of WM predict WM performance. We recruited 200 individuals defined by care-seeking status and measured neural responses using electroencephalography (EEG), while participants performed four WM tasks. We extracted spectral and time-domain EEG features from each task to quantify each of the hypothesized WM subprocesses: maintenance (storage of content), goal maintenance, and updating. We then used EEG measures of each subprocess as predictors of task performance to evaluate their contribution to WM. Significant predictors of WM capacity included contralateral delay activity and frontal theta, features typically associated with maintenance (storage of content) processes. In contrast, significant predictors of reaction time and its variability included contingent negative variation and the P3b, features typically associated with goal maintenance and updating. Broadly, these results suggest two principal dimensions that contribute to WM performance, tonic processes during maintenance contributing to capacity, and phasic processes during stimulus processing that contribute to response speed and variability. The analyses additionally highlight that reliability of features across tasks was greater (and comparable to that of WM performance) for features associated with stimulus processing (P3b and alpha), than with maintenance (gamma, theta and cross-frequency coupling).

Indexed as

ElectroencephalographyMemory, Short-TermCognitionHumansReaction TimeReproducibility of ResultsAlphaCross-frequency couplingEEGGammaGoal maintenanceMaintenanceP3RDoCThetaUpdatingWorking memory

Identifiers

PMID34155599
PMCPMC8563426
OpenAlexW3175574933

What OpenQuestion 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 OpenQuestion graph.