Brain connectivity differences between typically developed and ADHD subjects using Energy Landscape Analysis of resting-state fMRI data
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2022-07-18
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Abstract
Functional magnetic resonance imaging (fMRI) is an
effective tool used to study neural systems and functional
connectivity patterns within brain networks. Using resting-state
fMRI data, we can uncover the functional connectivity differences
in people with typically developed brains and brains of people with
attention deficit hyperactivity disorder (ADHD). Segmenting the
human brain into networks and analyzing the internetwork
connectivity can help us identify which brain network regions are
engaged and if they are working together. In this study, we used
energy landscape analysis, a method that calculates and interprets
multivariate time series data, such as resting-state fMRI, to
investigate brain activity differences in typically developed,
ADHD-Hyperactive/Impulsive, ADHD-Inattentive, and ADHDCombined subjects. The functional connectivity differences
between the subgroups, analyzed separately, could be attributed
to internetwork activity, and can possibly help identify biomarkers
of ADHD. The internetwork connections consisted of the auditory
network (AUD), attention network (ATN), default-mode network
(DMN), frontoparietal network (FPN), salience network (SAN),
sensorimotor network (SSM), and visual network (VIS). The
activity patterns and disconnectivity graphs are obtained for each
subject and the differences between groups are compared. Results
suggest that DMN and VIS are strongly coupled for females with
ADHD, whereas FPN and SAN are strongly coupled for males with
ADHD. These cognitive differences may attribute to neural deficits
and cognitive dysfunction in ADHD, such as trouble paying
attention and inability to control behavior. The energy landscape
analysis technique is a powerful tool for identifying differences
between typically developed and ADHD subjects, which could help
validate and encourage treatment options.