Evidence map›Paper›PMID 26523034›Full record

ArticleCerebral cortex (New York, N.Y. : 1991)2017

Hippocampal Contributions to the Large-Scale Episodic Memory Network Predict Vivid Visual Memories.

Benjamin R Geib, Matthew L Stanley, Erik A Wing, Paul J Laurienti, Roberto Cabeza

Abstract read
In one paragraph

Article in Cerebral cortex (New York, N.Y. : 1991), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing 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

37 citing papers in PubMed.

  1. Hippocampal CA1 gamma power predicts the precision of spatial memory judgments.Proceedings of the National Academy of Sciences of the United States of America · 2018
    Trial
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  6. Connectivity analyses for task-based fMRI.Physics of life reviews · 2024
    Review
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  13. Segregation, integration, and balance of large-scale resting brain networks configure different cognitive abilities.Proceedings of the National Academy of Sciences of the United States of America · 2021
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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

5 authors.

Benjamin R GeibDepartment of Psychology and Neuroscience, Duke University, Durham, NC 27708, USA.
Matthew L StanleyDepartment of Psychology and Neuroscience, Duke University, Durham, NC 27708, USA.
Erik A WingDepartment of Psychology and Neuroscience, Duke University, Durham, NC 27708, USA.
Paul J LaurientiLaboratory for Complex Brain Networks, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA.
Roberto CabezaDepartment of Psychology and Neuroscience, Duke University, Durham, NC 27708, USA.

Funding

Effects of Aging on Visual Memory: Neuroimaging StudiesR01AG019731 · NIA · DUKE UNIVERSITY · PI CABEZA, ROBERTO · 2002 to 2017
$4.6M
NIA NIH HHS R01 AG019731
6 · The paper itself

Abstract

A common approach in memory research is to isolate the function(s) of individual brain regions, such as the hippocampus, without addressing how those regions interact with the larger network. To investigate the properties of the hippocampus embedded within large-scale networks, we used functional magnetic resonance imaging and graph theory to characterize complex hippocampal interactions during the active retrieval of vivid versus dim visual memories. The study yielded 4 main findings. First, the right hippocampus displayed greater communication efficiency with the network (shorter path length) and became a more convergent structure for information integration (higher centrality measures) for vivid than dim memories. Second, vivid minus dim differences in our graph theory measures of interest were greater in magnitude for the right hippocampus than for any other region in the 90-region network. Moreover, the right hippocampus significantly reorganized its set of direct connections from dim to vivid memory retrieval. Finally, beyond the hippocampus, communication throughout the whole-brain network was more efficient (shorter global path length) for vivid than dim memories. In sum, our findings illustrate how multivariate network analyses can be used to investigate the roles of specific regions within the large-scale network, while also accounting for global network changes.

Indexed as

Memory, EpisodicAdolescentAdultBrain MappingFemaleFunctional LateralityHippocampusHumansMagnetic Resonance ImagingMaleMental RecallMultivariate AnalysisNeural PathwaysNeuropsychological TestsVisual PerceptionYoung Adultdeclarative memoryfunctional magnetic resonance imaginggraph theorymedial temporal lobesrecall

Identifiers

PMID26523034
PMCPMC6075474

What OpenQuestion holds

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Read underepoch 390

Registered trials

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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.