語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Feasibility of Multi-Component Spati...
~
ProQuest Information and Learning Co.
Feasibility of Multi-Component Spatio-Temporal Modeling of Cognitively Generated EEG Data and its Potential Application to Research in Functional Anatomy and Clinical Neuropathology.
紀錄類型:
書目-語言資料,手稿 : Monograph/item
正題名/作者:
Feasibility of Multi-Component Spatio-Temporal Modeling of Cognitively Generated EEG Data and its Potential Application to Research in Functional Anatomy and Clinical Neuropathology./
作者:
Zeman, Philip Michael.
面頁冊數:
1 online resource (458 pages)
附註:
Source: Dissertation Abstracts International, Volume: 75-07(E), Section: B.
標題:
Experimental psychology. -
電子資源:
click for full text (PQDT)
ISBN:
9780499284440
Feasibility of Multi-Component Spatio-Temporal Modeling of Cognitively Generated EEG Data and its Potential Application to Research in Functional Anatomy and Clinical Neuropathology.
Zeman, Philip Michael.
Feasibility of Multi-Component Spatio-Temporal Modeling of Cognitively Generated EEG Data and its Potential Application to Research in Functional Anatomy and Clinical Neuropathology.
- 1 online resource (458 pages)
Source: Dissertation Abstracts International, Volume: 75-07(E), Section: B.
Thesis (Ph.D.)--University of Victoria (Canada), 2013.
Includes bibliographical references
This dissertation is a compendium of multiple research papers that, together, address two main objectives. The first objective and primary research question is to determine whether or not, through a procedure of independent component analysis (ICA)-based data mining, volume-domain validation, and source volume estimation, it is possible to construct a meaningful, objective, and informative model of brain activity from scalpacquired EEG data. Given that a methodology to construct such a model can be created, the secondary objective and research question investigated is whether or not the sources derived from the EEG data can be used to construct a model of complex brain function associated with the spatial navigation and the virtual Morris Water Task (vMWT).
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018
Mode of access: World Wide Web
ISBN: 9780499284440Subjects--Topical Terms:
1180476
Experimental psychology.
Index Terms--Genre/Form:
554714
Electronic books.
Feasibility of Multi-Component Spatio-Temporal Modeling of Cognitively Generated EEG Data and its Potential Application to Research in Functional Anatomy and Clinical Neuropathology.
LDR
:05030ntm a2200397K 4500
001
913811
005
20180622095238.5
006
m o u
007
cr mn||||a|a||
008
190606s2013 xx obm 000 0 eng d
020
$a
9780499284440
035
$a
(MiAaPQ)AAINS28444
035
$a
(MiAaPQ)5010
035
$a
AAINS28444
040
$a
MiAaPQ
$b
eng
$c
MiAaPQ
100
1
$a
Zeman, Philip Michael.
$3
1186805
245
1 0
$a
Feasibility of Multi-Component Spatio-Temporal Modeling of Cognitively Generated EEG Data and its Potential Application to Research in Functional Anatomy and Clinical Neuropathology.
264
0
$c
2013
300
$a
1 online resource (458 pages)
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
500
$a
Source: Dissertation Abstracts International, Volume: 75-07(E), Section: B.
500
$a
Adviser: Ronald William Skelton.
502
$a
Thesis (Ph.D.)--University of Victoria (Canada), 2013.
504
$a
Includes bibliographical references
520
$a
This dissertation is a compendium of multiple research papers that, together, address two main objectives. The first objective and primary research question is to determine whether or not, through a procedure of independent component analysis (ICA)-based data mining, volume-domain validation, and source volume estimation, it is possible to construct a meaningful, objective, and informative model of brain activity from scalpacquired EEG data. Given that a methodology to construct such a model can be created, the secondary objective and research question investigated is whether or not the sources derived from the EEG data can be used to construct a model of complex brain function associated with the spatial navigation and the virtual Morris Water Task (vMWT).
520
$a
The assumptions of the signal and noise characteristics of scalp-acquired EEG data were discussed in the context of what is currently known about functional brain activity to identify appropriate characteristics by which to separate the activities comprising EEG data into parts. A new EEG analysis methodology was developed using both synthetic and real EEG data that encompasses novel algorithms for (1) data-mining of the EEG to obtain the activities of individual areas of the brain, (2) anatomical modeling of brain sources that provides information about the 3-dimensional volumes from which each of the activities separated from the EEG originates, and (3) validation of data mining results to determine if a source activity found via the data-mining step originates from a distinct modular unit inside the head or if it is an artefact. The methodology incorporating the algorithms developed was demonstrated for EEG data collected from study participants while they navigated a computer-based virtual maze environment. The brain activities of participants were meaningfully depicted via brain source volume estimation and representation of the activity relationships of multiple areas of the brain. A case study was used to demonstrate the analysis methodology as applied to the EEG of an individual person. In a second study, a group EEG dataset was investigated and activity relationships between areas of the brain for participants of the group study were individually depicted to show how brain activities of individuals can be compared to the group.
520
$a
The results presented in this dissertation support the conclusion that it is feasible to use ICA-based data mining to construct a physiological model of coordinated parts of the brain related to the vMWT from scalp-recorded EEG data. The methodology was successful in creating an objective and informative model of brain activity from EEG data. Furthermore, the evidence presented indicates that this methodology can be used to provide meaningful evaluation of the brain activities of individual persons and to make comparisons of individual persons against a group.
520
$a
In sum, the main contributions of this body of work are 5 fold. The technical contributions are: (1) a new data mining algorithm tailored for EEG, (2) an EEG component validation algorithm that identifies noise components via their poor representation in a head model, (3) a volume estimation algorithm that estimates the region in the brain from which each source waveform found via data mining originates, (4) a new procedure to study brain activities associated with spatial navigation. The main contribution of this work to the understanding of brain function is (5) evidence of specific functional systems within the brain that are used while persons participate in the vMWT paradigm (Livingstone and Skelton, 2007) examining spatial navigation.
533
$a
Electronic reproduction.
$b
Ann Arbor, Mich. :
$c
ProQuest,
$d
2018
538
$a
Mode of access: World Wide Web
650
4
$a
Experimental psychology.
$3
1180476
650
4
$a
Clinical psychology.
$3
649607
650
4
$a
Cognitive psychology.
$3
556029
650
4
$a
Neurosciences.
$3
593561
650
4
$a
Biomedical engineering.
$3
588770
655
7
$a
Electronic books.
$2
local
$3
554714
690
$a
0623
690
$a
0622
690
$a
0633
690
$a
0317
690
$a
0541
710
2
$a
ProQuest Information and Learning Co.
$3
1178819
710
2
$a
University of Victoria (Canada).
$b
Electrical Engineering, Biology, and Psychology.
$3
1186806
856
4 0
$u
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=NS28444
$z
click for full text (PQDT)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入