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Record W2109957027 · doi:10.1093/cercor/bhh071

Selective Amplification of Neocortical Neuronal Output by Fast Prepotentials InVivo

2004· article· en· W2109957027 on OpenAlexaff
Sylvain Crochet

Bibliographic record

VenueCerebral Cortex · 2004
Typearticle
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsUniversité Laval
FundersNational Institute of Neurological Disorders and Stroke
KeywordsNeuroscienceSomaBurstingCortical neuronsOptogeneticsPostsynaptic potentialMechanism (biology)NeocortexElectrophysiologyBiologyPhysics

Abstract

fetched live from OpenAlex

Neocortical cells integrate inputs from thousands of presynaptic neurons distributed along their dendritic arbors. Propagation of postsynaptic potentials to the soma is crucial in determining neuronal output. Using intracellular recordings in anesthetized and non-anesthetized, naturally awake and sleeping cats, we found evidence for generation of fast, all-or-none events recorded at the soma in about 20% of regular-spiking and intrinsically-bursting neurons. These events, termed fast prepotentials (FPPs), were suppressed by hyperpolarizing the neurons or by inhibiting synaptic transmission with perfusion of Ca2+-free artificial cerebrospinal fluid. FPPs could be evoked by activation of specific cortical inputs and allowed neurons to fire at more hyperpolarized levels of membrane potentials. Thus, FPPs represent a powerful mechanism to boost the output of neocortical neurons in response to given inputs. We further found evidence for modulation of FPPs generation across the waking-sleep cycle, indicating important changes in the integrative properties of neocortical neurons in different states of vigilance. We suggest that FPPs represent attenuated spikes generated in hot spots of the dendritic arbor and constitute a powerful mechanism to reinforce the functional connections between specific elements of the cortical networks.

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 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 score0.133
Threshold uncertainty score0.547

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 integrity0.0000.000
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 head0.021
GPT teacher head0.246
Teacher spread0.225 · 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

Citations55
Published2004
Admission routes1
Has abstractyes

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