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Record W2156444203 · doi:10.1186/1471-2202-15-s1-p43

Non-uniform dendritic distributions of Ihchannels in experimentally-derived multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons

2014· article· en· W2156444203 on OpenAlexafffund
Vladislav Sekulić, Tse-Chiang Chen, John J. Lawrence, Frances K. Skinner

Bibliographic record

VenueBMC Neuroscience · 2014
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersNatural Sciences and Engineering Research Council of CanadaNational Institutes of HealthUniversity of Toronto
KeywordsHippocampal formationNeuroscienceExcitatory postsynaptic potentialPyramidal cellEntorhinal cortexInhibitory postsynaptic potentialInterneuronHippocampusCompartment (ship)Computer scienceBiologyChemistry

Abstract

fetched live from OpenAlex

Inhibitory interneurons are crucial for generating prominent network rhythms and coordinating information flow in hippocampal microcircuits. The oriens-lacunosum/moleculare (O-LM) cell is an interneuron type in the hippocampal CA1 region that synapses onto distal dendrites of pyramidal cells [1]. O-LM cells mediate feedback inhibition onto pyramidal cells and gate information flow between sensory input from entorhinal cortex and previously stored associations from the CA3 area. Despite the distal location of inhibitory synapses from O-LM cells onto the excitatory populations, their control of pyramidal cell output has been clearly shown [2]. Thus, how the dynamic firing properties of O-LM cells in its network circuit environment is generated needs to be understood. Furthermore, it is clear that the presence and distribution of voltage-gated channels on the dendrites of O-LM cells would affect its integrative properties in response to synaptic input. However, given the highly challenging aspects to experimentally determine whether and what sort of distributions of voltage-gated channels are present on dendrites, we take advantage of computational modeling studies to consider different possibilities. In this work, we focus on Ih channels. While the existence of Ih channels in O-LM cells has long been known [3], it is at present unknown whether these channels are present on O-LM cell dendrites. In previous work, we used ensemble modeling techniques in conjunction with experimental data to show that physiologically realistic multi-compartment O-LM cell models may possess dendritic Ih, but only uniform distributions across the dendritic tree were examined. In the work here, we turned our focus to how the kinetics of Ih and non-uniform distributions would affect our models’ output. In tuning our models, we found that different Ih kinetics as well as non-uniform distributions were better able to reproduce experimental O-LM cell responses. Interestingly, this occurred only when there were decreasing conductance densities away from the soma. This is in contrast to pyramidal cells which have higher Ih conductance densities in more distal dendrites [4]. Non-uniform distributions of Ih would indicate that there are particular synaptic input distributions that affect the firing properties of O-LM cells and thus their ability to affect information flow.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.096
GPT teacher head0.359
Teacher spread0.263 · 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 designSimulation or modeling
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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Citations0
Published2014
Admission routes2
Has abstractyes

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