語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Functional Connectivity Analysis in ...
~
Cummings, Jennifer Anne,
FindBook
Google Book
Amazon
博客來
Functional Connectivity Analysis in Magnetic Resonance Imaging of Chronic Pain /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Functional Connectivity Analysis in Magnetic Resonance Imaging of Chronic Pain // Jennifer Anne Cummings.
作者:
Cummings, Jennifer Anne,
面頁冊數:
1 electronic resource (218 pages)
附註:
Source: Dissertations Abstracts International, Volume: 86-09, Section: B.
Contained By:
Dissertations Abstracts International86-09B.
標題:
Biomedical engineering. -
電子資源:
https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31843073
ISBN:
9798310156258
Functional Connectivity Analysis in Magnetic Resonance Imaging of Chronic Pain /
Cummings, Jennifer Anne,
Functional Connectivity Analysis in Magnetic Resonance Imaging of Chronic Pain /
Jennifer Anne Cummings. - 1 electronic resource (218 pages)
Source: Dissertations Abstracts International, Volume: 86-09, Section: B.
Chronic pain disorders are among the top causes of global disability, presenting unique therapeutic challenges due to their complex pathophysiology and inherently subjective nature. Recent advances in non-invasive imaging, particularly magnetic resonance imaging (MRI), offer unprecedented opportunities to investigate the mechanisms underlying chronic pain conditions. This dissertation advances our understanding through three interconnected studies employing functional connectivity approaches: First, we develop a novel graph- theoretical model that predicts brain functional connectivity patterns from white matter structural architecture, providing insights into both healthy and diseased brain function. Second, using cross-decomposition analysis, we reveal previously uncharacterized relationships between distributed somatosensory patterns extracted from body map data and resting-state functional brain networks in chronic lower back pain patients. Finally, we extend functional connectivity principles to the knee, identifying distinct patterns of cartilage thickness change over 8 years that correlate with osteoarthritis progression and risk factors. Together, these works demonstrate the utility of connectivity-based approaches in understanding chronic pain across multiple biological scales.
English
ISBN: 9798310156258Subjects--Topical Terms:
535387
Biomedical engineering.
Subjects--Index Terms:
Connectome
Functional Connectivity Analysis in Magnetic Resonance Imaging of Chronic Pain /
LDR
:02729nmm a22004093i 4500
001
2434812
005
20251001062530.5
006
m o d
007
cr|nu||||||||
008
261011s2025 miu||||||m |||||||eng d
020
$a
9798310156258
035
$a
(MiAaPQD)AAI31843073
035
$a
AAI31843073
040
$a
MiAaPQD
$b
eng
$c
MiAaPQD
$e
rda
100
1
$a
Cummings, Jennifer Anne,
$e
author.
$0
(orcid)0000-0002-0848-4009
$3
3824926
245
1 0
$a
Functional Connectivity Analysis in Magnetic Resonance Imaging of Chronic Pain /
$c
Jennifer Anne Cummings.
264
1
$a
Ann Arbor :
$b
ProQuest Dissertations & Theses,
$c
2025
300
$a
1 electronic resource (218 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: Dissertations Abstracts International, Volume: 86-09, Section: B.
500
$a
Advisors: Majumdar, Sharmila Committee members: Lotz, Jeffrey; Raj, Ashish; O'Connell, Grace.
502
$b
Ph.D.
$c
University of California, San Francisco
$d
2025.
520
$a
Chronic pain disorders are among the top causes of global disability, presenting unique therapeutic challenges due to their complex pathophysiology and inherently subjective nature. Recent advances in non-invasive imaging, particularly magnetic resonance imaging (MRI), offer unprecedented opportunities to investigate the mechanisms underlying chronic pain conditions. This dissertation advances our understanding through three interconnected studies employing functional connectivity approaches: First, we develop a novel graph- theoretical model that predicts brain functional connectivity patterns from white matter structural architecture, providing insights into both healthy and diseased brain function. Second, using cross-decomposition analysis, we reveal previously uncharacterized relationships between distributed somatosensory patterns extracted from body map data and resting-state functional brain networks in chronic lower back pain patients. Finally, we extend functional connectivity principles to the knee, identifying distinct patterns of cartilage thickness change over 8 years that correlate with osteoarthritis progression and risk factors. Together, these works demonstrate the utility of connectivity-based approaches in understanding chronic pain across multiple biological scales.
546
$a
English
590
$a
School code: 0034
650
4
$a
Biomedical engineering.
$3
535387
650
4
$a
Medical imaging.
$3
3172799
653
$a
Connectome
653
$a
Low back pain
653
$a
Global disability
653
$a
Magnetic resonance imaging
690
$a
0541
690
$a
0574
710
2
$a
University of California, San Francisco.
$b
Bioengineering.
$e
degree granting institution.
$3
3824563
720
1
$a
Majumdar, Sharmila
$e
degree supervisor.
773
0
$t
Dissertations Abstracts International
$g
86-09B.
790
$a
0034
791
$a
Ph.D.
792
$a
2025
856
4 0
$u
https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31843073
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9530507
電子資源
11.線上閱覽_V
電子書
EB
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入