Evidence map›Paper›PMID 40568050›Full record

ArticleNeuroimage. Reports2023

Assessing dynamic brain activity during verbal associative learning using MEG/fMRI co-processing.

Sangeeta Nair, Jerzy P Szaflarski, Yingying Wang, Diana Pizarro, Jeffrey F Killen, Jane B Allendorfer

Abstract read
In one paragraph

Article in Neuroimage. Reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

6 authors.

Sangeeta NairUniversity of Alabama at Birmingham, Department of Psychology, USA.
Jerzy P SzaflarskiUniversity of Alabama at Birmingham, Department of Neurology, USA.
Yingying WangUniversity of Nebraska-Lincoln, Department of Special Education and Communication Disorders (SECD), USA.
Diana PizarroUniversity of Alabama at Birmingham, Department of Engineering, USA.
Jeffrey F KillenUniversity of Alabama at Birmingham, Department of Neurology, USA.
Jane B AllendorferUniversity of Alabama at Birmingham, Department of Neurology, USA.

Funding

Exercise for Memory Rehabilitation in EpilepsyR01HD102723 · NICHD · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI ALLENDORFER, JANE B · 2021 to 2025
$3.1M
NICHD NIH HHS R01 HD102723
6 · The paper itself

Abstract

Background: The abilities of individual neuroimaging methods to resolve spatial and temporal contributions of brain regions during cognitive processes are limited. Co-processing of functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) may overcome some of the limitations by utilizing Multiple Sparse Priors (MSP) in a Bayesian framework that takes advantage of the temporal resolution of MEG and spatial resolution of fMRI. Methods: 24 healthy participants were recruited to perform a paired-associate verbal learning task during fMRI and MEG scans. FMRI data were processed within Group ICA fMRI Toolbox. Independent components (ICs) were temporally sorted by task time series (|r|>0.30 threshold identified task-related ICs). Task-positive ("generate") ICs were retained as spatial priors for MEG analyses. MEG data were processed by an event-related potential (ERP) approach and with a theta power approach. MEG source reconstructions were constrained within the task-positive ICs for both ERP and theta-power approaches. Results: For fMRI, five networks were identified as task-related. Four ICs underlying active generation spanned bilateral parietal, orbitofrontal, medial frontal and superior temporal regions, and occipital lobe. FMRI-constrained MEG source reconstructions using the ERP approach yielded early visual cortex activity followed by left inferior frontal gyrus (IFG) and orbito-frontal cortex (OFC) recruitment to coalesce in the left inferior temporal lobe. For the theta approach, MEG source reconstructions showed a progression of activity from bilateral temporal areas to left OFC and middle temporal gyrus, followed by right IFG. Discussion: MSP analyses informed by fMRI produced more focused regional activity than reconstructions without priors suggesting this approach may result in identifying more relevant semantic information during active generation. Constraining MEG source reconstruction to fMRI priors during active generation indicates fronto-temporal and fronto-parietal networks are interconnected across time and space.

Indexed as

Active generationAssociative learningfMRIMEGMultimodal data analysisMultiple sparse priors

Identifiers

PMID40568050
PMCPMC12172716

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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.