Abstract
The ability to measure the intrinsic functional architecture of the brain has grown exponentially over the last 2 decades. Measures of intrinsic connectivity within the brain, typically measured using resting-state functional magnetic resonance imaging (MRI), have evolved from primarily “static” approaches, to include dynamic measures of functional connectivity. Measures of dynamic functional connectivity expand the assumptions to allow brain regions to have temporally different patterns of communication between different regions. That is, connections within the brain can differentially fire between different regions at different times, and these differences can be quantified. Applying approaches that measure the dynamic characteristics of functional brain connectivity have been fruitful in identifying differences during brain development and psychopathology. We provide a brief overview of static and dynamic measures of functional connectivity and illustrate the synergy in applying these approaches to identify both age-related differences in children and differences between typically developing children and children with autistic symptoms.
| Original language | English (US) |
|---|---|
| Journal | Journal of Experimental Neuroscience |
| Volume | 13 |
| DOIs |
|
| State | Published - May 1 2019 |
| Externally published | Yes |
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Keywords
- autism spectrum disorders
- children
- development
- neurodevelopment
- Resting-state functional magnetic resonance imaging
ASJC Scopus subject areas
- Neuroscience(all)
Cite this
Dissecting Static and Dynamic Functional Connectivity : Example From the Autism Spectrum. / White, Tonya; Calhoun, Vince D.
In: Journal of Experimental Neuroscience, Vol. 13, 01.05.2019.Research output: Contribution to journal › Comment/debate
}
TY - JOUR
T1 - Dissecting Static and Dynamic Functional Connectivity
T2 - Example From the Autism Spectrum
AU - White, Tonya
AU - Calhoun, Vince D.
PY - 2019/5/1
Y1 - 2019/5/1
N2 - The ability to measure the intrinsic functional architecture of the brain has grown exponentially over the last 2 decades. Measures of intrinsic connectivity within the brain, typically measured using resting-state functional magnetic resonance imaging (MRI), have evolved from primarily “static” approaches, to include dynamic measures of functional connectivity. Measures of dynamic functional connectivity expand the assumptions to allow brain regions to have temporally different patterns of communication between different regions. That is, connections within the brain can differentially fire between different regions at different times, and these differences can be quantified. Applying approaches that measure the dynamic characteristics of functional brain connectivity have been fruitful in identifying differences during brain development and psychopathology. We provide a brief overview of static and dynamic measures of functional connectivity and illustrate the synergy in applying these approaches to identify both age-related differences in children and differences between typically developing children and children with autistic symptoms.
AB - The ability to measure the intrinsic functional architecture of the brain has grown exponentially over the last 2 decades. Measures of intrinsic connectivity within the brain, typically measured using resting-state functional magnetic resonance imaging (MRI), have evolved from primarily “static” approaches, to include dynamic measures of functional connectivity. Measures of dynamic functional connectivity expand the assumptions to allow brain regions to have temporally different patterns of communication between different regions. That is, connections within the brain can differentially fire between different regions at different times, and these differences can be quantified. Applying approaches that measure the dynamic characteristics of functional brain connectivity have been fruitful in identifying differences during brain development and psychopathology. We provide a brief overview of static and dynamic measures of functional connectivity and illustrate the synergy in applying these approaches to identify both age-related differences in children and differences between typically developing children and children with autistic symptoms.
KW - autism spectrum disorders
KW - children
KW - development
KW - neurodevelopment
KW - Resting-state functional magnetic resonance imaging
UR - http://www.scopus.com/inward/record.url?scp=85071289142&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85071289142&partnerID=8YFLogxK
U2 - 10.1177/1179069519851809
DO - 10.1177/1179069519851809
M3 - Comment/debate
C2 - 31210734
AN - SCOPUS:85071289142
VL - 13
JO - Journal of Experimental Neuroscience
JF - Journal of Experimental Neuroscience
SN - 1179-0695
ER -