Evidence map›Paper›PMID 33767350›Full record

ArticleCommunications biology2021

Neurocognitive modeling of latent memory processes reveals reorganization of hippocampal-cortical circuits underlying learning and efficient strategies.

Kaustubh Supekar, Hyesang Chang, Percy K Mistry, Teresa Iuculano, Vinod Menon

Open access · goldAbstract read
In one paragraph

Article in Communications biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
1.1field-weighted citation impact, top 26% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Foundational Number Sense Training Gains Are Predicted by Hippocampal-Parietal Circuits.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2022
    Pooled it
  2. Uncovering Latent Cognitive, Metacognitive, and Neural Bases of Problem-Solving Deficits in Children with Developmental Dyscalculia.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
    Article
  3. Latent Neurocognitive Mechanisms Underlying Quantity Discrimination in Children with and without Mathematical Learning Disabilities.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
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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 at 4 institutions in 2 countries.

Kaustubh Supekar *Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA. ksupekar@stanford.edu.
Hyesang Chang *Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA.
Percy K Mistry *Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA.
Teresa IuculanoDepartment of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA.ORCID 0000-0002-8573-3662
Vinod MenonDepartment of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA. menon@stanford.edu.ORCID 0000-0003-1622-9857
Stanford University · USDélégation Paris 5 · FRNeurosciences Institute · USStanford Medicine · US

Funding

Interventions in Math Learning Disabilities: Cognitive and Neural CorrelatesR01HD059205 · NICHD · STANFORD UNIVERSITY · PI Vinod Menon · 2009 to 2026
$10.8M
Longitudinal Neurocognitive Studies of Mathematical Disabilities: trajectories and outcomesR37HD094623 · NICHD · STANFORD UNIVERSITY · PI Vinod Menon · 2018 to 2026
$6.8M
Integrative computational models of latent behavioral and neural constructs in children: a longitudinal developmental big-data approachR01MH121069 · NIMH · STANFORD UNIVERSITY · PI MENON, VINOD · 2019 to 2023
$3.9M
Novel Bayesian linear dynamical systems-based methods for discovering human brain circuit dynamics in health and diseaseR01EB022907 · NIBIB · STANFORD UNIVERSITY · PI MENON, VINOD · 2016 to 2018
$1.6M
NIBIB NIH HHS R01 EB022907NICHD NIH HHS R01 HD059205NICHD NIH HHS R37 HD094623NIMH NIH HHS R01 MH121069
6 · The paper itself

Abstract

Efficient memory-based problem-solving strategies are a cardinal feature of expertise across a wide range of cognitive domains in childhood. However, little is known about the neurocognitive mechanisms that underlie the acquisition of efficient memory-based problem-solving strategies. Here we develop, to the best of our knowledge, a novel neurocognitive process model of latent memory processes to investigate how cognitive training designed to improve children's problem-solving skills alters brain network organization and leads to increased use and efficiency of memory retrieval-based strategies. We found that training increased both the use and efficiency of memory retrieval. Functional brain network analysis revealed training-induced changes in modular network organization, characterized by increase in network modules and reorganization of hippocampal-cortical circuits. Critically, training-related changes in modular network organization predicted performance gains, with emergent hippocampal, rather than parietal cortex, circuitry driving gains in efficiency of memory retrieval. Our findings elucidate a neurocognitive process model of brain network mechanisms that drive learning and gains in children's efficient problem-solving strategies.

Indexed as

ChildCognitionFemaleHippocampusHumansLearningMaleMemoryMental RecallMental Status and Dementia TestsModels, PsychologicalParietal LobeProblem Solving

Identifiers

PMID33767350
PMCPMC7994581
OpenAlexW3137294325

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.