Evidence map›Paper›PMID 30731245›Full record

ArticleNeuroImage2019

Performance of semi-automated hippocampal subfield segmentation methods across ages in a pediatric sample.

Margaret L Schlichting, Michael L Mack, Katharine F Guarino, Alison R Preston

Abstract read
In one paragraph

Article in NeuroImage, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Memory Reactivation during Learning Simultaneously Promotes Dentate Gyrus/CAThe Journal of neuroscience : the official journal of the Society for Neuroscience · 2021
    Article
  9. Article
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

4 authors.

Margaret L SchlichtingCenter for Learning and Memory, The University of Texas at Austin, USA; Department of Psychology, University of Toronto, Canada. Electronic address: schlichting@psych.utoronto.ca.
Michael L MackCenter for Learning and Memory, The University of Texas at Austin, USA; Department of Psychology, University of Toronto, Canada.
Katharine F GuarinoCenter for Learning and Memory, The University of Texas at Austin, USA.
Alison R PrestonCenter for Learning and Memory, The University of Texas at Austin, USA; Department of Psychology, The University of Texas at Austin, USA; Department of Neuroscience, The University of Texas at Austin, USA.

Funding

Hippocampal and prefrontal contributions to memory integrationR01MH100121 · NIMH · UNIVERSITY OF TEXAS AT AUSTIN · PI Alison R Preston · 2013 to 2026
$7.3M
Linking the neurobiological development of memory and reasoningR21HD083785 · NICHD · UNIVERSITY OF TEXAS AT AUSTIN · PI PRESTON, ALISON R · 2016 to 2017
$423k
The mutual influence of attention and learning during knowledge acquisitionF32MH100904 · NIMH · UNIVERSITY OF TEXAS AT AUSTIN · PI MACK, MICHAEL L. · 2013 to 2015
$165k
NICHD NIH HHS R21 HD083785NIMH NIH HHS F32 MH100904NIMH NIH HHS R01 MH100121
6 · The paper itself

Abstract

Episodic memory function has been shown to depend critically on the hippocampus. This region is made up of a number of subfields, which differ in both cytoarchitectural features and functional roles in the mature brain. Recent neuroimaging work in children and adolescents has suggested that these regions may undergo different developmental trajectories-a fact that has important implications for how we think about learning and memory processes in these populations. Despite the growing research interest in hippocampal structure and function at the subfield level in healthy young adults, comparatively fewer studies have been carried out looking at subfield development. One barrier to studying these questions has been that manual segmentation of hippocampal subfields-considered by many to be the best available approach for defining these regions-is laborious and can be infeasible for large cross-sectional or longitudinal studies of cognitive development. Moreover, manual segmentation requires some subjectivity and is not impervious to bias or error. In a developmental sample of individuals spanning 6-30 years, we assessed the degree to which two semi-automated segmentation approaches-one approach based on Automated Segmentation of Hippocampal Subfields (ASHS) and another utilizing Advanced Normalization Tools (ANTs)-approximated manual subfield delineation on each individual by a single expert rater. Our main question was whether performance varied as a function of age group. Across several quantitative metrics, we found negligible differences in subfield validity across the child, adolescent, and adult age groups, suggesting that these methods can be reliably applied to developmental studies. We conclude that ASHS outperforms ANTs overall and is thus preferable for analyses carried out in individual subject space. However, we underscore that ANTs is also acceptable and may be well-suited for analyses requiring normalization to a single group template (e.g., voxelwise analyses across a wide age range). Previous work has supported the use of such methods in healthy young adults, as well as several special populations such as older adults and those suffering from mild cognitive impairment. Our results extend these previous findings to show that ASHS and ANTs can also be used in pediatric populations as young as six.

Indexed as

AdolescentAdultChildCross-Sectional StudiesFemaleHippocampusHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleNeuroimagingYoung AdultDevelopmentHigh-resolution MRIReliabilityStructural MRIVolume

Identifiers

PMID30731245
PMCPMC6524646

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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.