| Title |
The Five Myths of MMN: Redefining How to Use MMN in Basic and Clinical Research
|
|---|---|
| Published in |
Brain Topography, October 2013
|
| DOI | 10.1007/s10548-013-0326-6 |
| Pubmed ID | |
| Authors |
E. S. Sussman, S. Chen, J. Sussman-Fort, E. Dinces |
| Abstract |
The goal of this review article is to redefine what the mismatch negativity (MMN) component of event-related potentials reflects in auditory scene analysis, and to provide an overview of how the MMN serves as a valuable tool in Cognitive Neuroscience research. In doing so, some of the old beliefs (five common 'myths') about MMN will be dispelled, such as the notion that MMN is a simple feature discriminator and that attention itself modulates MMN elicitation. A revised description of what MMN truly reflects will be provided, which includes a principal focus onto the highly context-dependent nature of MMN elicitation and new terminology to discuss MMN and attention. This revised framework will help clarify what has been a long line of seemingly contradictory results from studies in which behavioral ability to hear differences between sounds and passive elicitation of MMN have been inconsistent. Understanding what MMN is will also benefit clinical research efforts by providing a new picture of how to design appropriate paradigms suited to various clinical populations. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 1 | 50% |
| Uruguay | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 207 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 3% |
| Germany | 1 | <1% |
| France | 1 | <1% |
| Australia | 1 | <1% |
| Hungary | 1 | <1% |
| Israel | 1 | <1% |
| Sweden | 1 | <1% |
| Spain | 1 | <1% |
| United Kingdom | 1 | <1% |
| Other | 0 | 0% |
| Unknown | 193 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 59 | 29% |
| Student > Master | 32 | 15% |
| Researcher | 19 | 9% |
| Student > Doctoral Student | 15 | 7% |
| Student > Bachelor | 15 | 7% |
| Other | 49 | 24% |
| Unknown | 18 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 64 | 31% |
| Neuroscience | 32 | 15% |
| Linguistics | 14 | 7% |
| Agricultural and Biological Sciences | 13 | 6% |
| Medicine and Dentistry | 13 | 6% |
| Other | 30 | 14% |
| Unknown | 41 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 October 2013.
All research outputs
#17,137,417
of 25,182,110 outputs
Outputs from Brain Topography
#331
of 516 outputs
Outputs of similar age
#137,347
of 219,332 outputs
Outputs of similar age from Brain Topography
#10
of 15 outputs
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