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Record W2123748006 · doi:10.1002/hipo.10198

Ionic mechanisms in the generation of subthreshold oscillations and action potential clustering in entorhinal layer II stellate neurons

2004· article· en· W2123748006 on OpenAlexaff
Erik Fransén, Angel A. Alonso, Clayton T. Dickson, Jacopo Magistretti, Michael E. Hasselmo

Bibliographic record

VenueHippocampus · 2004
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsUniversity of AlbertaMcGill UniversityMontreal Neurological Institute and Hospital
FundersNational Institutes of HealthVetenskapsrådetNational Institute of Mental HealthSvenska Forskningsrådet FormasSwedish Foundation for International Cooperation in Research and Higher Education
KeywordsChemistryMembrane potentialNeuroscienceHyperpolarization (physics)Subthreshold conductionElectrophysiologyBiophysicsEntorhinal cortexHippocampal formationPhysicsVoltagePsychologyBiologyBiochemistry

Abstract

fetched live from OpenAlex

A multicompartmental biophysical model of entorhinal cortex layer II stellate cells was developed to analyze the ionic basis of physiological properties, such as subthreshold membrane potential oscillations, action potential clustering, and the medium afterhyperpolarization. In particular, the simulation illustrates the interaction of the persistent sodium current (I(Nap)) and the hyperpolarization activated inward current (Ih) in the generation of subthreshold membrane potential oscillations. The potential role of Ih in contributing to the medium hyperpolarization (mAHP) and rebound spiking was studied. The role of Ih and the slow calcium-activated potassium current Ikappa(AHP) in action potential clustering was also studied. Representations of Ih and I(Nap) were developed with parameters based on voltage-clamp data from whole-cell patch and single channel recordings of stellate cells (Dickson et al., J Neurophysiol 83:2562-2579, 2000; Magistretti and Alonso, J Gen Physiol 114:491-509, 1999; Magistretti et al., J Physiol 521:629-636, 1999a; J Neurosci 19:7334-7341, 1999b). These currents interacted to generate robust subthreshold membrane potentials with amplitude and frequency corresponding to data observed in the whole cell patch recordings. The model was also able to account for effects of pharmacological manipulations, including blockade of Ih with ZD7288, partial blockade with cesium, and the influence of barium on oscillations. In a model with a wider range of currents, the transition from oscillations to single spiking, to spike clustering, and finally tonic firing could be replicated. In agreement with experiment, blockade of calcium channels in the model strongly reduced clustering. In the voltage interval during which no data are available, the model predicts that the slow component of Ih does not follow the fast component down to very short time constants. The model also predicts that the fast component of Ih is responsible for the involvement in the generation of subthreshold oscillations, and the slow component dominates in the generation of spike clusters.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.105
GPT teacher head0.340
Teacher spread0.235 · 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".

Quick stats

Citations141
Published2004
Admission routes1
Has abstractyes

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