Evidence map›Paper›PMID 29311778›Full record

ArticleFrontiers in neuroscience2017

Improved Transient Response Estimations in Predicting 40 Hz Auditory Steady-State Response Using Deconvolution Methods.

Xiaodan Tan, Qiuyang Fu, Han Yuan, Lei Ding, Tao Wang

Abstract read
In one paragraph

Article in Frontiers in neuroscience, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Neural auditory contrast enhancement in humans.Proceedings of the National Academy of Sciences of the United States of America · 2021
    Article
  3. 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

5 authors.

Xiaodan TanSchool of Biomedical Engineering, Southern Medical University, Guangzhou, China.
Qiuyang FuDepartment of Otolaryngology, Guangdong Second Provincial General Hospital, Guangzhou, China.
Han YuanStephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States.
Lei DingStephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States.
Tao WangCollege of Big Data and Internet, Shenzhen Technology University, Shenzhen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The auditory steady-state response (ASSR) is one of the main approaches in clinic for health screening and frequency-specific hearing assessment. However, its generation mechanism is still of much controversy. In the present study, the linear superposition hypothesis for the generation of ASSRs was investigated by comparing the relationships between the classical 40 Hz ASSR and three synthetic ASSRs obtained from three different templates for transient auditory evoked potential (AEP). These three AEPs are the traditional AEP at 5 Hz and two 40 Hz AEPs derived from two deconvolution algorithms using stimulus sequences, i.e., continuous loop averaging deconvolution (CLAD) and multi-rate steady-state average deconvolution (MSAD). CLAD requires irregular inter-stimulus intervals (ISIs) in the sequence while MSAD uses the same ISIs but evenly-spaced stimulus sequences which mimics the classical 40 Hz ASSR. It has been reported that these reconstructed templates show similar patterns but significant difference in morphology and distinct frequency characteristics in synthetic ASSRs. The prediction accuracies of ASSR using these templates show significant differences (

Indexed as

auditory steady-state responsecontinuous loop averaging deconvolutionlinear superposition hypothesismulti-rate steady-state average deconvolutionstimulus sequencing scheme

Identifiers

PMID29311778
PMCPMC5732975

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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.