Evidence map›Paper›PMID 36246524›Full record

ArticleFrontiers in cellular neuroscience2022

Response properties of spiking and non-spiking brain neurons mirror pulse interval selectivity.

Xinyang Zhang, Berthold Hedwig

Open access · goldAbstract read
In one paragraph

Article in Frontiers in cellular neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 46% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. 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 1 institution in 1 country.

Xinyang ZhangDepartment of Zoology, University of Cambridge, Cambridge, United Kingdom.
Berthold HedwigDepartment of Zoology, University of Cambridge, Cambridge, United Kingdom.
University of Cambridge · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the bispotted field cricket auditory pulse pattern recognition of the species-specific calling song is based on a delay-line and coincidence detection network, established by the activity and synaptic connections of only 5 auditory neurons in the brain. To obtain a more detailed understanding of the network and the dynamic of the neural activity over time we analyzed the response properties of these neurons to test patterns, in which the pulse duration was kept constant while the duration of specific pulse intervals was systematically altered. We confirm that the ascending interneuron AN1 and the local interneuron LN2 copy the structure of the pulse pattern, however with limited resolution at short pulse intervals, further evident in downstream neural responses. In the non-spiking delay-line interneuron LN5 during long pulse intervals full-blown rebound potentials develop over a time course of 35-70 ms. LN5 also reveals an overall increase in its membrane potential tuned to chirps of the calling song pulse pattern. This may contribute to the pattern recognition process by driving the activity of the coincidence-detector LN3 and may indicate a further function of the delay-line neuron LN5. The activity of LN3 and of the feature detector LN4 match the tuning of the phonotactic behavior and demonstrate an increasingly sparse coding of the calling song pulse patterns as evident in the response of the feature detector LN4. The circuitry reveals a fundamental mechanism of auditory pattern recognition and demonstrates a principle of neuronal coding.

Indexed as

auditory processingbrain neurondelay-linepattern recognitiontemplate matching

Identifiers

PMID36246524
PMCPMC9559836
OpenAlexW4298004433

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.