Evidence map›Paper›PMID 22754503›Full record

ArticleFrontiers in neural circuits2012

Mechanisms and benefits of granule cell latency coding in the mouse olfactory bulb.

Sonya Giridhar, Nathaniel N Urban

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neural circuits, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.7field-weighted citation impact, top 36% 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

8 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
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  5. Rapid Feedforward Inhibition and Asynchronous Excitation Regulate Granule Cell Activity in the Mammalian Main Olfactory Bulb.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2015
    Article
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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

2 authors at 2 institutions in 1 country.

Sonya GiridharCenter for Neuroscience, University of Pittsburgh, Pittsburgh PA, USA.
Nathaniel N Urban
Center for the Neural Basis of Cognition · USUniversity of Pittsburgh · US

Funding

Intraglomerular Lateral Inhibition in the Olfactory BulbR01DC005798 · NIDCD · CARNEGIE-MELLON UNIVERSITY · PI URBAN, NATHAN NEAL · 2002 to 2012
$2.9M
INTERDISCIPLINARY TRAINING IN COMPUTATIONAL NEUROSCIENCET90DA022762 · NIDA · CARNEGIE-MELLON UNIVERSITY · PI KASS, ROBERT E, RUBIN, JONATHAN E. · 2006 to 2020
$2.0M
NIDA NIH HHS T90 DA022762NIDCD NIH HHS R01 DC005798
6 · The paper itself

Abstract

Inhibitory circuits are critical for shaping odor representations in the olfactory bulb. There, individual granule cells can respond to brief stimulation with extremely long (up to 1000 ms), input-specific latencies that are highly reliable. However, the mechanism and function of this long timescale activity remain unknown. We sought to elucidate the mechanism responsible for long-latency activity, and to understand the impact of widely distributed interneuron latencies on olfactory coding. We used a combination of electrophysiological, optical, and pharmacological techniques to show that long-latency inhibition is driven by late onset synaptic excitation to granule cells. This late excitation originates from tufted cells, which have intrinsic properties that favor longer latency spiking than mitral cells. Using computational modeling, we show that widely distributed interneuron latency increases the discriminability of similar stimuli. Thus, long-latency inhibition in the olfactory bulb requires a combination of circuit- and cellular-level mechanisms that function to improve stimulus representations.

Indexed as

codinginhibitionlatencyolfactory bulb

Identifiers

PMID22754503
PMCPMC3385563
OpenAlexW1991597146

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.