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Memory-Related Synaptic Plasticity Is Sexually Dimorphic in Rodent Hippocampus

2018· article· en· W2886946556 on OpenAlexaff
Weisheng Wang, Aliza A. Le, Bowen Hou, Julie C. Lauterborn, Conor D. Cox, Ellis R. Levin, Gary Lynch, Christine M. Gall

Bibliographic record

VenueJournal of Neuroscience · 2018
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsImmunovaccine (Canada)
FundersNational Institute of Neurological Disorders and StrokeNational Institute of Mental HealthUniversity of California, IrvineU.S. Department of Veterans Affairs
KeywordsLong-term potentiationSynaptic plasticityHippocampal formationPostsynaptic potentialNeuroscienceEstrogen receptorExcitatory postsynaptic potentialHippocampusBiologyEstrogenEndocrinologyInternal medicineReceptorInhibitory postsynaptic potentialMedicine

Abstract

fetched live from OpenAlex

Men are generally superior to women in remembering spatial relationships, whereas the reverse holds for semantic information, but the neurobiological bases for these differences are not understood. Here we describe striking sexual dimorphism in synaptic mechanisms of memory encoding in hippocampal field CA1, a region critical for spatial learning. Studies of acute hippocampal slices from adult rats and mice show that for excitatory Schaffer–commissural projections, the memory-related long-term potentiation (LTP) effect depends upon endogenous estrogen and membrane estrogen receptor α (ERα) in females but not in males; there was no evident involvement of nuclear ERα in females, or of ERβ or GPER1 (G-protein-coupled estrogen receptor 1) in either sex. Quantitative immunofluorescence showed that stimulation-induced activation of two LTP-related kinases (Src, ERK1/2), and of postsynaptic TrkB, required ERα in females only, and that postsynaptic ERα levels are higher in females than in males. Several downstream signaling events involved in LTP were comparable between the sexes. In contrast to endogenous estrogen effects, infused estradiol facilitated LTP and synaptic signaling in females via both ERα and ERβ. The estrogen dependence of LTP in females was associated with a higher threshold for both inducing potentiation and acquiring spatial information. These results indicate that the observed sexual dimorphism in hippocampal LTP reflects differences in synaptic kinase activation, including both a weaker association with NMDA receptors and a greater ERα-mediated kinase activation in response to locally produced estrogen in females. We propose that male/female differences in mechanisms and threshold for field CA1 LTP contribute to differences in encoding specific types of memories. <b>SIGNIFICANCE STATEMENT</b> There is good evidence for male/female differences in memory-related cognitive function, but the neurobiological basis for this sexual dimorphism is not understood. Here we describe sex differences in synaptic function in a brain area that is critical for learning spatial cues. Our results show that female rodents have higher synaptic levels of estrogen receptor α (ERα) and, in contrast to males, require membrane ERα for the activation of signaling kinases that support long-term potentiation (LTP), a form of synaptic plasticity thought to underlie learning. The additional requirement of estrogen signaling in females resulted in a higher threshold for both LTP and hippocampal field CA1-dependent spatial learning. These results describe a synaptic basis for sexual dimorphism in encoding spatial information.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.071
GPT teacher head0.308
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations123
Published2018
Admission routes1
Has abstractyes

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