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Record W2506363189 · doi:10.1007/978-1-60327-202-5_10

An Intact Septo-Hippocampal Preparation for Investigating the Mechanisms of Hippocampal Oscillation

2010· book-chapter· en· W2506363189 on OpenAlexaff
Romain Goutagny, Jesse Jackson, Sylvain Williams

Bibliographic record

VenueNeuromethods · 2010
Typebook-chapter
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsHippocampal formationNeuroscienceHippocampusRhythmTheta rhythmOscillation (cell signaling)StimulationPsychologyChemistryMedicineInternal medicine

Abstract

fetched live from OpenAlex

The medial septum (MS) is a structure best known for its role in theta rhythm generation in the ­hippocampus. Theta rhythm is a relatively slow brain oscillation of 3–12 Hz that is important for memory formation and synaptic plasticity. Despite that the role of the MS in theta generation has been investigated for more than half a century, very little is known about how MS neurons contribute to this ­phenomenon. In addition, exactly how hippocampal neurons participate in rhythmic activity in the MS remains relatively unexplored. Our poor understanding of theta generation is due in part to the challenging conditions offered by in vivo experimentation. To circumvent these obstacles, this chapter describes how to obtain a complete septo-hippocampal preparation in vitro to investigate theta generation. This method allows the study of theta rhythm with whole-cell and multiple field recordings in combination with precise pharmacology in vitro. We show that the preparation displays rhythmic oscillations in the hippocampus upon activation of the septum and, conversely, exhibits rhythmic activity in the septum following hippocampal stimulation. These results suggest that the septo-hippocampal preparation is a potentially powerful tool to investigate the cellular mechanism implicated in theta generation in vitro.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.095
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.121
GPT teacher head0.419
Teacher spread0.298 · 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.

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

Citations0
Published2010
Admission routes1
Has abstractyes

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