Evidence map›Paper›PMID 22087303›Full record

ArticlePloS one2011

Identifying temporal codes in spontaneously active sensory neurons.

Alexander B Neiman, David F Russell, Michael H Rowe

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.1field-weighted citation impact, top 49% 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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
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.

Alexander B NeimanNeuroscience Program, Ohio University, Athens, Ohio, United States of America.
David F Russell
Michael H Rowe
Ohio University · US

Funding

Mechanisms of signaling in otoconial organsR01DC005063 · NIDCD · OHIO UNIVERSITY ATHENS · PI PETERSON, ELLENGENE H · 2001 to 2011
$5.4M
Stochastic Nonlinear Dynamics of Sensory Nervous SystemsR01DC004922 · NIDCD · UNIVERSITY OF MISSOURI-ST. LOUIS · PI RUSSELL, DAVID FRANK · 2002 to 2004
$869k
NIDCD NIH HHS DC 04922NIDCD NIH HHS DC 05063NIDCD NIH HHS R01 DC004922NIDCD NIH HHS R01 DC005063
6 · The paper itself

Abstract

The manner in which information is encoded in neural signals is a major issue in Neuroscience. A common distinction is between rate codes, where information in neural responses is encoded as the number of spikes within a specified time frame (encoding window), and temporal codes, where the position of spikes within the encoding window carries some or all of the information about the stimulus. One test for the existence of a temporal code in neural responses is to add artificial time jitter to each spike in the response, and then assess whether or not information in the response has been degraded. If so, temporal encoding might be inferred, on the assumption that the jitter is small enough to alter the position, but not the number, of spikes within the encoding window. Here, the effects of artificial jitter on various spike train and information metrics were derived analytically, and this theory was validated using data from afferent neurons of the turtle vestibular and paddlefish electrosensory systems, and from model neurons. We demonstrate that the jitter procedure will degrade information content even when coding is known to be entirely by rate. For this and additional reasons, we conclude that the jitter procedure by itself is not sufficient to establish the presence of a temporal code.

Indexed as

Action PotentialsAnimalsFishesInformation TheorySensory Receptor CellsTime PerceptionTurtles

Identifiers

PMID22087303
PMCPMC3210806
OpenAlexW2064567490

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.