Tonotopic organization of the human auditory cortex: N100 topography and multiple dipole model analysis
The tonotopic organization of the human auditory cortex has been investigated by means of scalp potential mapping and dipole modelling of the evoked response occurring around 100 msec after the stimulus onset. The major characteristics of the topographical changes observed with increasing stimulus f...
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Published in | Electroencephalography and clinical neurophysiology Vol. 96; no. 2; pp. 143 - 156 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Shannon
Elsevier Ireland Ltd
01.03.1995
Amsterdam Elsevier |
Subjects | |
Online Access | Get full text |
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Summary: | The tonotopic organization of the human auditory cortex has been investigated by means of scalp potential mapping and dipole modelling of the evoked response occurring around 100 msec after the stimulus onset. The major characteristics of the topographical changes observed with increasing stimulus frequency were statistically demonstrated. Using a 3-concentric sphere head model, the scalp potential distributions can be explained in first approximation by two equivalent current dipoles, located in the supratemporal plane and mimicking the activity of both auditory cortices. To take into account the temporal aspects of the brain activities, 3 time-varying dipole strategies were tested. Frequency dependence of the dipole orientation has been evidenced in both hemispheres with the 3 models, whereas no significant change in dipole position was found. The tilt in dipole orientation could be related to the folding geometry of Heschl's gyrus, which varies with depth. In agreement with previous MEG findings, this brings new evidence for a tonotopic organization of the auditory cortical area involved in the N100 wave generation. Moreover, distinct frequency dependences of the equivalent current dipoles were observed in the early and the late parts of the N100. This study demonstrates that simple dipolar models, applied on electrical data, make it possible to reveal functionally distinct cortical areas. |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 ObjectType-Article-1 ObjectType-Feature-2 |
ISSN: | 0168-5597 0013-4694 |
DOI: | 10.1016/0168-5597(94)00242-7 |