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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Attention deficits revealed by passive auditory change detection for pure tones and lexical tones in ADHD children
|
|---|---|
| Published in |
Frontiers in Human Neuroscience, August 2015
|
| DOI | 10.3389/fnhum.2015.00470 |
| Pubmed ID | |
| Authors |
Ming-Tao Yang, Chun-Hsien Hsu, Pei-Wen Yeh, Wang-Tso Lee, Jao-Shwann Liang, Wen-Mei Fu, Chia-Ying Lee |
| Abstract |
Inattention (IA) has been a major problem in children with attention deficit/hyperactivity disorder (ADHD), accounting for their behavioral and cognitive dysfunctions. However, there are at least three processing steps underlying attentional control for auditory change detection, namely pre-attentive change detection, involuntary attention orienting, and attention reorienting for further evaluation. This study aimed to examine whether children with ADHD would show deficits in any of these subcomponents by using mismatch negativity (MMN), P3a, and late discriminative negativity (LDN) as event-related potential (ERP) markers, under the passive auditory oddball paradigm. Two types of stimuli-pure tones and Mandarin lexical tones-were used to examine if the deficits were general across linguistic and non-linguistic domains. Participants included 15 native Mandarin-speaking children with ADHD and 16 age-matched controls (across groups, age ranged between 6 and 15 years). Two passive auditory oddball paradigms (lexical tones and pure tones) were applied. The pure tone oddball paradigm included a standard stimulus (1000 Hz, 80%) and two deviant stimuli (1015 and 1090 Hz, 10% each). The Mandarin lexical tone oddball paradigm's standard stimulus was /yi3/ (80%) and two deviant stimuli were /yi1/ and /yi2/ (10% each). The results showed no MMN difference, but did show attenuated P3a and enhanced LDN to the large deviants for both pure and lexical tone changes in the ADHD group. Correlation analysis showed that children with higher ADHD tendency, as indexed by parents' and teachers' ratings on ADHD symptoms, showed less positive P3a amplitudes when responding to large lexical tone deviants. Thus, children with ADHD showed impaired auditory change detection for both pure tones and lexical tones in both involuntary attention switching, and attention reorienting for further evaluation. These ERP markers may therefore be used for the evaluation of anti-ADHD drugs that aim to alleviate these dysfunctions. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Hong Kong | 1 | 1% |
| Unknown | 75 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 18 | 24% |
| Researcher | 11 | 14% |
| Student > Master | 10 | 13% |
| Student > Bachelor | 6 | 8% |
| Student > Doctoral Student | 3 | 4% |
| Other | 6 | 8% |
| Unknown | 22 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 20 | 26% |
| Neuroscience | 8 | 11% |
| Medicine and Dentistry | 7 | 9% |
| Linguistics | 6 | 8% |
| Agricultural and Biological Sciences | 2 | 3% |
| Other | 7 | 9% |
| Unknown | 26 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 November 2020.
All research outputs
#3,235,633
of 22,824,164 outputs
Outputs from Frontiers in Human Neuroscience
#1,605
of 7,150 outputs
Outputs of similar age
#44,131
of 267,563 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#26
of 142 outputs
Altmetric has tracked 22,824,164 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,150 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.6. This one has done well, scoring higher than 77% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 267,563 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 142 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.