Evidence map›Paper›PMID 23727451›Full record

ArticleNeuroscience2013

A spontaneous state of weakly correlated synaptic excitation and inhibition in visual cortex.

A Y Y Tan, S Andoni, N J Priebe

Abstract read
In one paragraph

Article in Neuroscience, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
0.8field-weighted citation impact, top 29% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 22 citations in OpenAlex.

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  11. Efficient codes and balanced networks.Nature neuroscience · 2016
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

A Y Y TanCenter for Perceptual Systems, Section of Neurobiology, School of Biological Sciences, College of Natural Sciences, The University of Texas at Austin, 2400 Speedway, Austin, TX 78705, USA. atyy@alum.mit.edu
S Andoni
N J Priebe
The University of Texas at Austin · US

Funding

Cortical Integration of Binocular InputR01EY019288 · NEI · UNIVERSITY OF TEXAS AT AUSTIN · PI PRIEBE, NICHOLAS J · 2009 to 2012
$1.5M
NEI NIH HHS EY-019288NEI NIH HHS R01 EY019288
6 · The paper itself

Abstract

Cortical spontaneous activity reflects an animal's behavioral state and affects neural responses to sensory stimuli. The correlation between excitatory and inhibitory synaptic input to single neurons is a key parameter in models of cortical circuitry. Recent measurements demonstrated highly correlated synaptic excitation and inhibition during spontaneous "up-and-down" states, during which excitation accounted for approximately 80% of inhibitory variance (Shu et al., 2003; Haider et al., 2006). Here we report in vivo whole-cell estimates of the correlation between excitation and inhibition in the rat visual cortex under pentobarbital anesthesia, during which up-and-down states are absent. Excitation and inhibition are weakly correlated, relative to the up-and-down state: excitation accounts for less than 40% of inhibitory variance. Although these correlations are lower than when the circuit cycles between up-and-down states, both behaviors may arise from the same circuitry. Our observations provide evidence that different correlational patterns of excitation and inhibition underlie different cortical states.

Indexed as

AnimalsExcitatory Postsynaptic PotentialsFemaleInhibitory Postsynaptic PotentialsNeural InhibitionRatsRats, Long-EvansSynaptic TransmissionVisual Cortex4-(2-hydroxyethyl)-1-piperazineethanesulfonic acidCIconfidence intervalcorrelationexcitationHEPESinhibitionin vivoprimary visual cortexspontaneous activity

Identifiers

PMID23727451
PMCPMC3778667
OpenAlexW2029106090

What OpenQuestion holds

Textmetadata
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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.