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Disambiguating electrical activity i...

Ales, Justin Michael.

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Disambiguating electrical activity in early visual cortex by combining multifocal evoked potentials and functional magnetic resonance imaging .

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Disambiguating electrical activity in early visual cortex by combining multifocal evoked potentials and functional magnetic resonance imaging ./
Author:	Ales, Justin Michael.
Description:	92 p.
Notes:	Adviser: Stanley A. Klein.
Contained By:	Dissertation Abstracts International69-03B.
Subject:	Biology, Neuroscience. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3306045
ISBN:	9780549529798

Disambiguating electrical activity in early visual cortex by combining multifocal evoked potentials and functional magnetic resonance imaging .
Ales, Justin Michael.

Disambiguating electrical activity in early visual cortex by combining multifocal evoked potentials and functional magnetic resonance imaging . - 92 p.

Adviser: Stanley A. Klein.

Thesis (Ph.D.)--University of California, Berkeley, 2007.

The low spatial resolution provided by EEG has made it impossible to accurately separate activity from different early visual areas. However, fMRI has been able to provide the high spatial resolution required to separate early visual areas. Through a combination of EEG with fMRI it is possible to take advantage of the strengths of both techniques. By using multifocal Visual Evoked Potentials (mfVEPs) one can extract retinotopically specific information from EEG data. In addition, standard fMRI expanding wedge and rotating ring retinotopic mappings provide detailed retinotopic maps for each individual subject. The mfVEP stimulus activates many independent sources in the visual cortex that span a large portion of the visual field. The many different independent sources allow the transformation of the nonlinear source localization problem into a linear regression. In order to accomplish this, the EEG sources were constrained to be within a few millimeters of the locations specified by the fMRI retinotopy, as well as with the orientation specified by the surface normal estimated from the MRI. Because of the constraints the problem changes from estimating the location, orientation and temporal modulation parameters of an EEG source, into just an estimation of the temporal modulation from each area. And by having a high density multifocal VEP stimulus there is a robust way to use a linear regression to extract the responses from different retinopically organized cortical areas This method disambiguates the contribution from V1 and V2 to the VEP, and demonstrates that EEG in combination with fMRI can be used to extract fast temporal information from early visual areas.

ISBN: 9780549529798Subjects--Topical Terms:

1017680
Biology, Neuroscience.

Disambiguating electrical activity in early visual cortex by combining multifocal evoked potentials and functional magnetic resonance imaging .
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020 $a 9780549529798
035 $a (UMI)AAI3306045
035 $a AAI3306045
040 $a UMI $c UMI
100 1 $a Ales, Justin Michael. $3 1272088
245 1 0 $a Disambiguating electrical activity in early visual cortex by combining multifocal evoked potentials and functional magnetic resonance imaging .
300 $a 92 p.
500 $a Adviser: Stanley A. Klein.
500 $a Source: Dissertation Abstracts International, Volume: 69-03, Section: B, page: 1479.
502 $a Thesis (Ph.D.)--University of California, Berkeley, 2007.
520 $a The low spatial resolution provided by EEG has made it impossible to accurately separate activity from different early visual areas. However, fMRI has been able to provide the high spatial resolution required to separate early visual areas. Through a combination of EEG with fMRI it is possible to take advantage of the strengths of both techniques. By using multifocal Visual Evoked Potentials (mfVEPs) one can extract retinotopically specific information from EEG data. In addition, standard fMRI expanding wedge and rotating ring retinotopic mappings provide detailed retinotopic maps for each individual subject. The mfVEP stimulus activates many independent sources in the visual cortex that span a large portion of the visual field. The many different independent sources allow the transformation of the nonlinear source localization problem into a linear regression. In order to accomplish this, the EEG sources were constrained to be within a few millimeters of the locations specified by the fMRI retinotopy, as well as with the orientation specified by the surface normal estimated from the MRI. Because of the constraints the problem changes from estimating the location, orientation and temporal modulation parameters of an EEG source, into just an estimation of the temporal modulation from each area. And by having a high density multifocal VEP stimulus there is a robust way to use a linear regression to extract the responses from different retinopically organized cortical areas This method disambiguates the contribution from V1 and V2 to the VEP, and demonstrates that EEG in combination with fMRI can be used to extract fast temporal information from early visual areas.
520 $a Finally, in order to eliminate one of the disadvantages of the m-sequence white noise stimulation approach a new method, State Triggered Kernel Estimation (STKE), was implemented. STKE allows for extracting non-stationary kernels from an m-sequence stimulus. The viability of this method is demonstrated with an experiment in which contrast was modulated. The results show how STKE can reveal the dynamics of the response kernels to a non-stationary stimulus. This extension allows a wider range of stimuli to be used in conjunction with m-sequence stimuli.
590 $a School code: 0028.
650 4 $a Biology, Neuroscience. $3 1017680
650 4 $a Health Sciences, Ophthalmology. $3 1019445
690 $a 0317
690 $a 0381
710 2 $a University of California, Berkeley. $3 687832
773 0 $t Dissertation Abstracts International $g 69-03B.
790 $a 0028
790 1 0 $a Klein, Stanley A., $e advisor
791 $a Ph.D.
792 $a 2007
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3306045