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Record W2737369184 · doi:10.1177/1744806917719847

Characterization of postsynaptic calcium signals in the pyramidal neurons of anterior cingulate cortex

2017· article· en· W2737369184 on OpenAlexafffund
Xu‐Hui Li, Qian Song, Tao Chen, Min Zhuo

Bibliographic record

VenueMolecular Pain · 2017
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsAnterior cingulate cortexNeurosciencePostsynaptic potentialCingulate cortexPsychologyMedicineReceptorInternal medicineCognitionCentral nervous system

Abstract

fetched live from OpenAlex

Calcium signaling is critical for synaptic transmission and plasticity. N-methyl-D-aspartic acid (NMDA) receptors play a key role in synaptic potentiation in the anterior cingulate cortex. Most previous studies of calcium signaling focus on hippocampal neurons, little is known about the activity-induced calcium signals in the anterior cingulate cortex. In the present study, we show that NMDA receptor-mediated postsynaptic calcium signals induced by different synaptic stimulation in anterior cingulate cortex pyramidal neurons. Single and multi-action potentials evoked significant suprathreshold Ca 2+ increases in somas and spines. Both NMDA receptors and voltage-gated calcium channels contributed to this increase. Postsynaptic Ca 2+ signals were induced by puff-application of glutamate, and a NMDA receptor antagonist AP5 blocked these signals in both somas and spines. Finally, long-term potentiation inducing protocols triggered postsynaptic Ca 2+ influx, and these influx were NMDA receptor dependent. Our results provide the first study of calcium signals in the anterior cingulate cortex and demonstrate that NMDA receptors play important roles in postsynaptic calcium signals in anterior cingulate cortex pyramidal neurons.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.093
Threshold uncertainty score0.367

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.042
GPT teacher head0.341
Teacher spread0.299 · 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 teacher head, 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".

Quick stats

Citations17
Published2017
Admission routes2
Has abstractyes

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