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Record W2484635892 · doi:10.1385/0-89603-115-2:545

Electrophysiological Methods for Studying Ionic Currents in Brain Slices and Cell Cultures

2003· book-chapter· en· W2484635892 on OpenAlexafffund
Brian A. MacVicar, Maeve O’Beirne

Bibliographic record

VenueHumana Press eBooks · 2003
Typebook-chapter
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsUniversity of Calgary
FundersAlberta Heritage Foundation for Medical Research
KeywordsElectrophysiologyNeuroscienceExtracellularIntracellularSlice preparationCentral nervous systemIon channelBiologyBiophysicsChemistryCell biologyBiochemistry

Abstract

fetched live from OpenAlex

The last two decades have seen a tremendous explosion in our knowledge concerning the properties of neurons of the central nervous system (CNS). The basis of this explosion is twofold: one is the development of the methodology to maintain isolated slices of brain tissue alive, and the second is the discovery of pharmacological tools to alter specific ionic channels of neurons. Some pioneering work describing neuronal electrophysiology has also been done on neurons cultured in slice preparations or after dissociation. The purpose of this chapter is to briefly describe the methodologies involved in maintaining isolated brain slices and cultures of both slices and dissociated cells and to describe the experimental paradigms that have been developed in the last few years to determine the ionic currents underlying the electrophysiological properties of the mammalian CNS. Also, another important area of research will be discussed: the measurement of extracellular ion concentrations in the CNS and the dynamic changes that occur during neuronal activity. Much of this work has been done in vivo, but extracellular and intracellular ion measurements have also been made in brain slice preparations, Because of the complexity of the intact CNS, there are few experiments correlating extracellular ionic changes with intracellular ionic currents.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.575
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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 integrity0.0000.001
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 head0.161
GPT teacher head0.378
Teacher spread0.217 · 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
GenreOther

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

Citations2
Published2003
Admission routes2
Has abstractyes

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