Evidence map›Paper›PMID 24465391›Full record

ArticlePloS one2014

Temporal features of spike trains in the moth antennal lobe revealed by a comparative time-frequency analysis.

Alberto Capurro, Fabiano Baroni, Linda S Kuebler, Zsolt Kárpáti, Teun Dekker, Hong Lei, Bill S Hansson, Timothy C Pearce, Shannon B Olsson

Erratum issuedAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Neuron synchronization analyzed through spatial-temporal attention.Frontiers in computational neuroscience · 2025
    Article
4 · The record

Corrections and comments

  • Erratum issued
5 · Who and what money

Authors and funding

9 authors.

Alberto CapurroDepartment of Engineering, University of Leicester, Leicester, United Kingdom.
Fabiano BaroniSchool of Psychology and Psychiatry, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, Victoria, Australia ; NeuroEngineering Laboratory, Department of Electrical & Electronic Engineering, University of Melbourne, Melbourne, Victoria, Australia ; Centre for Neural Engineering, University of Melbourne, Melbourne, Victoria, Australia.
Linda S KueblerDepartment of Evolutionary Neuroethology, Max Planck Institute for Chemical Ecology, Jena, Germany.
Zsolt KárpátiDepartment of Zoology, Plant Protection Institute, Centre for Agricultural Research, Hungarian Academy of Sciences, Budapest, Hungary.
Teun DekkerDivision of Chemical Ecology, Swedish University of Agricultural Sciences, Alnarp, Sweden.
Hong LeiDepartment of Neuroscience, School of Mind, Brain and Behavior, University of Arizona, Tucson, Arizona, United States of America.
Bill S HanssonDepartment of Evolutionary Neuroethology, Max Planck Institute for Chemical Ecology, Jena, Germany.
Timothy C PearceDepartment of Engineering, University of Leicester, Leicester, United Kingdom.
Shannon B OlssonDepartment of Evolutionary Neuroethology, Max Planck Institute for Chemical Ecology, Jena, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The discrimination of complex sensory stimuli in a noisy environment is an immense computational task. Sensory systems often encode stimulus features in a spatiotemporal fashion through the complex firing patterns of individual neurons. To identify these temporal features, we have developed an analysis that allows the comparison of statistically significant features of spike trains localized over multiple scales of time-frequency resolution. Our approach provides an original way to utilize the discrete wavelet transform to process instantaneous rate functions derived from spike trains, and select relevant wavelet coefficients through statistical analysis. Our method uncovered localized features within olfactory projection neuron (PN) responses in the moth antennal lobe coding for the presence of an odor mixture and the concentration of single component odorants, but not for compound identities. We found that odor mixtures evoked earlier responses in biphasic response type PNs compared to single components, which led to differences in the instantaneous firing rate functions with their signal power spread across multiple frequency bands (ranging from 0 to 45.71 Hz) during a time window immediately preceding behavioral response latencies observed in insects. Odor concentrations were coded in excited response type PNs both in low frequency band differences (2.86 to 5.71 Hz) during the stimulus and in the odor trace after stimulus offset in low (0 to 2.86 Hz) and high (22.86 to 45.71 Hz) frequency bands. These high frequency differences in both types of PNs could have particular relevance for recruiting cellular activity in higher brain centers such as mushroom body Kenyon cells. In contrast, neurons in the specialized pheromone-responsive area of the moth antennal lobe exhibited few stimulus-dependent differences in temporal response features. These results provide interesting insights on early insect olfactory processing and introduce a novel comparative approach for spike train analysis applicable to a variety of neuronal data sets.

Indexed as

AnimalsArthropod AntennaeMothsNeuronsOdorantsOlfactory PathwaysSmell

Identifiers

PMID24465391
PMCPMC3896344

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.