Evidence map›Paper›PMID 23871744›Full record

ReviewNeurobiology of learning and memory2013

Learning to learn - intrinsic plasticity as a metaplasticity mechanism for memory formation.

Megha Sehgal, Chenghui Song, Vanessa L Ehlers, James R Moyer

Open access · greenAbstract readReview
In one paragraph

Review in Neurobiology of learning and memory, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 86 papers.

0numbers the graph read from it
0cells of the map it votes in
86citing papers in PubMed
5.1field-weighted citation impact, top 3% 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

86 citing papers in PubMed, 159 citations in OpenAlex.

  1. Trial
  2. CaInternational journal of molecular sciences · 2026
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  9. Intrinsic Plasticity Mechanisms of Repetitive Transcranial Magnetic Stimulation.The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry · 2024
    Review
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  14. Progressive Excitability Changes in the Medial Entorhinal Cortex in the 3xTg Mouse Model of Alzheimer's Disease Pathology.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023
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  20. Adaptive control of synaptic plasticity integrates micro- and macroscopic network function.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2023
    Review

26 more citing papers are in PubMed but not listed here.

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 at 1 institution in 1 country.

Megha SehgalDepartment of Psychology, University of Wisconsin-Milwaukee, Milwaukee, WI 53201, USA.
Chenghui Song
Vanessa L Ehlers
James R Moyer
University of Wisconsin–Milwaukee · US

Funding

Mechanisms of aging-related extinction deficitsR03AG042814 · NIA · UNIVERSITY OF WISCONSIN MILWAUKEE · PI MOYER, JAMES R · 2013 to 2014
$150k
NIA NIH HHS R03 AG042814NIA NIH HHS R03-AG042814
6 · The paper itself

Abstract

"Use it or lose it" is a popular adage often associated with use-dependent enhancement of cognitive abilities. Much research has focused on understanding exactly how the brain changes as a function of experience. Such experience-dependent plasticity involves both structural and functional alterations that contribute to adaptive behaviors, such as learning and memory, as well as maladaptive behaviors, including anxiety disorders, phobias, and posttraumatic stress disorder. With the advancing age of our population, understanding how use-dependent plasticity changes across the lifespan may also help to promote healthy brain aging. A common misconception is that such experience-dependent plasticity (e.g., associative learning) is synonymous with synaptic plasticity. Other forms of plasticity also play a critical role in shaping adaptive changes within the nervous system, including intrinsic plasticity - a change in the intrinsic excitability of a neuron. Intrinsic plasticity can result from a change in the number, distribution or activity of various ion channels located throughout the neuron. Here, we review evidence that intrinsic plasticity is an important and evolutionarily conserved neural correlate of learning. Intrinsic plasticity acts as a metaplasticity mechanism by lowering the threshold for synaptic changes. Thus, learning-related intrinsic changes can facilitate future synaptic plasticity and learning. Such intrinsic changes can impact the allocation of a memory trace within a brain structure, and when compromised, can contribute to cognitive decline during the aging process. This unique role of intrinsic excitability can provide insight into how memories are formed and, more interestingly, how neurons that participate in a memory trace are selected. Most importantly, modulation of intrinsic excitability can allow for regulation of learning ability - this can prevent or provide treatment for cognitive decline not only in patients with clinical disorders but also in the aging population.

Indexed as

AgingNeuronal PlasticityAnimalsAplysiaHumansLearningMemoryMiceNeuronsRatsAgingIntrinsic excitabilityLearningMemoryMemory allocationMemory modulationMetaplasticity

Identifiers

PMID23871744
PMCPMC3855019
OpenAlexW2137350641

What OpenQuestion holds

Textmetadata
LicenceTDM
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.